Simon Mardle
email: simon.mardle@talk21.com

Sebastien Metz
email: s_metz@sakana-consultants.com

Impacts of current EU regulation on the UK whitefish value

Keywords: value chain analysis, competitiveness, sustainability, bioeconomic modelling, whitefish value chain analysis, competitiveness, sustainability, bioeconomic modelling, whitefish value chain analysis, competitiveness, sustainability, bioeconomic modelling, whitefish

Cod and haddock are two of the "big 5" UK supermarket fish species and intrinsic to fish and chip shops nationwide. UK whitefish fleets produce a significant amount, however there is a reliance on imports to maintain supply. The UK is in a strong position to compete for raw material from Iceland and Norway given high prices paid for imports and investment by Icelandic and Norwegian companies in the UK. Regarding UK production of whitefish, the European Common Fisheries Policy landing obligation has introduced significant uncertainty. To avoid discarding of any quota stock, fishing may be stopped before all target stocks quota is reached. For demersal fleets, there is a transition period between 2016-18 where target stocks are introduced according to Advisory Council and EU agreement and Article 15, with all quota stocks from 2019. As the capacity of the fleets balance to the new regulations, supply will likely return and if maximum sustainable yield (MSY) is reached in 2020 then an increase in TACs from current levels is likely too. However, markets and industries can change in a short period. Particularly, most processing companies are small to medium size enterprises and those that concentrate on cod and haddock may have to adjust their business. Fleets could be resilient to such short term reductions in landings however this cannot be assumed. The competitiveness of producers will surely be affected in the short to medium term as a result.

Impacts of current EU regulation on the UK whitefish value chain

Simon Mardle* and Sebastien Metz**

Introduction

Cod and haddock are by far the largest marine species on the UK seafood market behind salmon, tuna and prawns. Seafish Factsheet [START_REF]Seafood Industry Factsheet[END_REF] reports that sales of cod and haddock in the UK account for over half a billion pounds sterling each year, one fifth of the UK seafood retail market, with the fish and chip foodservice sector worth over one billion pounds sterling per year largely providing cod and haddock [START_REF]Seafood Industry Factsheet[END_REF]. Furthermore, cod and haddock are for the most part sourced from North East Atlantic waters and have significant importance to UK producers, both fleets and processors.

The last European Common Fisheries Policy 1 has introduced some significant challenges to UK fishing fleets to maintain supply of key species in the short term. The two key policies in this regulation are the objective to reach maximum sustainable yield (MSY) for all quota stocks by 2020, and the implement of a landing obligation, essentially a discard ban, for all quota stocks by 2019. A transition period between 2016 and 2019 is being managed to drive fisheries to these positions by the stated years. MSY is calculated at a single species level but the landing obligation operates in a multi-species context. Hence, in 2019, this could mean that fleet's must stop fishing as soon as the quota of a single stock is met. The resulting effort level may be considerably less than fishing at MSY for some stocks. The binding policy is therefore likely to be the landing obligation, even though fishing below MSY, at levels potentially much lower than those resulting in maximum yield, will have a positive impact on the status of fish stocks. This could however have a severely negative impact on supply. Given this, it is an important statement made by the European PECH Committee which states, "Considering the unclear linkages between MSY and the landing obligation, … achieving exploitation rates able to produce maximum sustainable yield is likely the most important objective and should be prioritised" (North Sea p.67 of [START_REF]The discard ban and its impact on the Maximum Sustainable Yield objective on fisheries[END_REF]).

Recent studies have indicated that choke species could reduce catching opportunities for fleets if species for which there is low quota held cannot be avoided [START_REF] Russel | Economic Impact Assessment of the Landing Obligation Economic Impact Assessment[END_REF]. Extra-EU imports, which are considerable, will likely remain unaffected by the changes to the CFP. There is however a competition amongst several EU countries for a limited supply of extra-EU sourced whitefish: cod in particular but also haddock. The processing, retail and foodservice sectors will be most affected should the supply of cod and haddock reduce, putting added pressure on margins but also on the need to offer alternative products to satisfy demand for seafood products.

In addition to highlighting potentially conflicting objectives of policy, this paper aims to investigate how supplies and markets for cod and haddock are likely to be affected in the UK in the short to medium term. This could impact the competitiveness of UK producers and processors significantly. Competition in international markets is both an opportunity and a threat, as there is limited international supply of cod and haddock, even so it could be expected to have a positive impact in the supply chain for producers. Fleet adjustment, and the need to balance resource availability with the size and composition of the fleet, continues to happen in UK and other EU fleets. This reduces pressure on stocks (i.e. conservation objective) thus enabling the drive towards MSY and subsequently improves the economic performance of fleets (i.e. economic objective) but at the direct expense of reductions in numbers of vessels (i.e. social objective) and the social cost that brings. The objectives highlighted are of course simplified, but demonstrate the social objective pulling in a different direction to conservation and economy [START_REF] Mardle | The objectives of fisheries management: case studies from the UK, France, Spain and Denmark[END_REF][START_REF] Gallic | Les objectifs d'une politique publique vus par les acteurs: Une analyse multicritères de la politique commune de la pêche[END_REF][START_REF] Wattage | Evaluation of the importance of fisheries management objectives using choice-experiments[END_REF]. This is important with the introduction of the landing obligation as the total demand for fish continues to grow even though average consumption in the UK has decreased slightly in recent years and with that changing prices of fish maintain a healthy market for seafood.

This paper estimates the potential impact of changing regulation to the supply of cod and haddock on UK producers and UK markets. A modelling approach is taken to estimate how the landing obligation might impact fleets. Patterns of trade are analysed to understand the flexibility and complexity of cod and haddock markets. The structure of this paper provides an overview of the whitefish production in the UK and other EU countries, followed by an evaluation of the whitefish value chain, with results from modelled scenarios considering potential impacts on the UK whitefish market, concluding with a discussion and final comments.

Material and methods

UK Whitefish production

The UK whitefish fleet is for the most part concentrated in the Scottish ports of Peterhead and Fraserburgh, although there are whitefish vessels registered in other ports in England, Wales and Northern Ireland. For the purpose of this study, the following evaluation focuses on vessels using demersal trawl/seine to target cod, haddock, whiting and saithe predominantly, with revenue from these four species representing more than 50% of these vessels' total fishing income. The vessels selected are split into two length classes: 12 to 24m, and over 24m (Figure 1). There are many other vessels that catch whitefish in addition to other species, for example anglerfish, megrim, plaice, lemon sole etc, however these are not included in this analysis.

{FIGURE 1}

The number of vessels for the over 24m segment have remained stable at between 55-60 vessels across the period. The number of vessels for the 12-24m segment have fluctuated strongly mostly as a result of quota availability and the need to target other stocks to a greater extent for a time. This was evident in 2011-12 as the fishing opportunities for cod and haddock, as well as whiting and saithe, worsened. This is notably due to increasing fuel prices (approximately 34p in 2010 to 46p in 2011) and decreasing TAC particularly for North Sea cod from 40,000 tonnes in 2010 to 32,000 tonnes in 2011. From a level of around 50 vessels in 2008-10, the 12-24m fleet segment has reduced to around 37 vessels in 2014.

Cod, haddock, whiting and saithe contribute over 70% to both fleets total landing value (Figure 2). The remaining 30% of landings value is made up from anglerfish and flatfish and small amounts of hake, cephalopods, ling, plaice and pollack (included in "Others". Income in the most recent two year (i.e. 2013-14) are at their highest by a considerable margin. This indicates that fishing opportunities have increased with greater TACs, particularly North Sea haddock, but also that prices have improved. For example the North Sea and West Coast haddock TAC(IV, IIIa and VIa) increased from an average of 39,413 tonnes in 2011-12 to an average of 49,566 tonnes in 2013-14. Haddock prices rose from an average of £1.14 per kg to £1.26 per kg over the same two periods.

Both fleets have seen increases in income (Figure 2) and profit (Figure 3) in recent years. Income for the 12-24m fleet segment has increased by 50% between 2008 and 2014 and for the over 24m fleet segment by 33% from its lowest in 2009 compared to 2014. In addition, other income reflecting quota trade has increased by approximately 10% over the period for both fleet segments.

{FIGURE 2}

Average vessel profit is estimated to have increased sharply since 2009 and even more so since 2012. For the 12-24m fleet segment, this could be explained partly by less vessels getting a greater share. For the over 24m, number of vessels has however remained relatively constant. The increase in profitability is likely due to a mix of increased prices, increased TACs and stable costs (mainly energy/fuel costs). These latter costs have on average reduced from £299,000 in 2012 to £269,000 in 2014 for the larger vessels (over 24m). Conversely, all other costs appear to have increased by 10% year-on-year from 2012 to 2014. Smaller vessels (12-24m) have seen costs increasing significantly, with revenues increasing at a greater rate on average.

{FIGURE 3}

Overall, it is apparent that the amount of revenue required to breakeven for the over 24m whitefish fleet has reduced in recent years, mostly as a consequence of reduced costs and lower fuel prices (Figure 4). For the 12-24m whitefish fleet breakeven revenue has remained fairly stable increasing to a small degree in recent years. For both fleet segments, income per day has steadily increased. Similarly for both fleet segments, the number of days required to breakeven has decreased as income has increased at a greater rate than costs (Figure 4). In 2014, the 12-24m whitefish fleet segment is estimated to have broken even in 50% of the days fished and the over 24m fleet segment in approximately 43% of days.

{FIGURE 4}

2.2 UK Whitefish value chain UK whitefish production is important to the UK fishing industry, with cod, haddock, whiting and saithe contributing 14.3% to the total UK landings value (at £122.9 million) [START_REF]UK Sea Fisheries Annual Statistics[END_REF]. Even so, the strong demand for cod and haddock by UK consumers means that imports of these species are considerable and a magnitude higher than UK production. Total imports for cod and haddock represent in 2014 close to 152,000 tonnes for a value of £649 million, with Iceland, Norway, China and Denmark representing over 75% of the volume of imports (Figure 5). Iceland and Norway supplied 48% of the imports of cod in 2014 and 44% of haddock. China, Denmark, Germany and the Faroe Islands are also large suppliers (41% cod and 35% haddock). Most imports coming from China are processed products, companies taking advantage of Chinese lower costs to process raw material before shipping it back to the UK.

{FIGURE 5}

Data on nine whitefish value chains were collected for 2014 (Table 1). The majority of whitefish landings by UK registered vessels are at UK ports. The exceptions to this are cod, where 9,500 tonnes were landed in Norway in 2014 and 4,800 tonnes in Germany, and plaice where most landings by UK vessels took place in the Netherlands. This appears mostly due to closeness to port, market and processing requirements. The imports of cod are significant at 116,400 tonnes and a value of over half a billion euros. This is far more than the UK production and is originated mostly from Icelandic waters, the North Sea and the Barents Sea. There are also sizeable imports of haddock at 35,900 tonnes which is slightly less than the UK production, again from the same areas.

{TABLE 1}

Apparent consumption of whitefish is significant in the UK. Cod and haddock lead but other species contribute quite strongly in the market. The seven other species make up approximately 106,000 tonnes, one third of which is pollack (Table 1). Cod and haddock are part of the "big 5" supermarket fish species along with salmon, tuna and prawns. Accroding to data compiled by Seafish , retail sales for cod in 2014 were approximately 20% of the retail market (see Introduction) [START_REF]Seafood Industry Factsheet[END_REF]. However, with the demand for cod and haddock through fish and chip shops and other fast food outlets, estimated to exceed one billion GBP per year, cod and haddock are the most important wild marine fish on the UK market. Any significant change in supply could therefore affect significantly the UK market and UK fish producers.

EU Whitefish production

The UK is the largest EU producer of cod and haddock from the North Sea and Norwegian waters (Figure 6), equally for cod in these areas but mostly the North Sea for haddock. Cod is also produced in relatively large quantity by other EU countries, including Denmark, Poland, Spain, Germany and France from the North Sea, Norwegian waters and the Baltic. Haddock is mostly landed by the UK.

{FIGURE 6}

Modelling and analysis approach

A two stage modelling and analysis approach has been undertaken. The first stage comprises a typical bioeconomic model for scenario analysis that models the fleet and stock interactions of the UK fisheries (i.e. production). The second stage provides an analysis of the downstream impacts by including the results from stage one plus an assessment of imports in the coming years.

The stage one bioeconomic model is based on Fishrent and has been used in a successful study of the economic impact of the landing obligation on UK fisheries [START_REF] Salz | Study on the remuneration of spawning stock biomass[END_REF][START_REF] Russell | Landing Obligation Economic Impact Assessment (EIA): Interim Report Two: Scenario Analysis[END_REF]. The model comprises four key boxes: production, policy, economy and biology (Figure 7). As indicated, the model operates at the fleet and stock level, for all UK fleets, on a yearly level. For those stocks where stock assessments are available (http://www.ices.dk/marinedata/tools/Pages/stock-assessment-graphs.aspx ), a simple stock biomass approach is taken in the biology box where the next year's (t+1) stock available is calculated from the this year's (t) stock plus stock growth (G) minus the catch taken. Stock growth is estimated from: G t = α + biomass β t . with parameters α and β estimated using published stock assessment data. The policy box implements a harvest control rule that adjusts total allowable catch (TAC) from the previous year by up to +/-15%. The production box then estimates catch in time t (C t ), landings and discards based on constant catchabilities (q), effort in days fished (E) and level of biomass (B t ), i.e. C t = qE t B t . And, from catch and effort indicators, the economy box calculates the performance of each fleet in terms of revenue/income, costs and profit.

{FIGURE 7}

The stage two value chain analysis takes the results from the bioeconomic model indicating UK supply of whitefish and calculates the impact on the value chain incorporating supply of whitefish from other countries (e.g. EU and Iceland/Norway). A 'status quo' situation is assumed for imports from the rest of the world. However, in addition lower and upper bounds are identified to indicate an area of uncertainty in the results.

Calculation

Supply of whitefish to the UK market is dependent on UK production and imports. The biggest policy change in recent history in Europe has been the introduction of the landing obligation under the latest CFP reform. This effectively implements a discard ban for all stocks managed under the EU TAC system and has the potential to disrupt significantly the supply of key marine species. A key foundation of the CFP, relative stability was introduced in its current form in the early 1980s [START_REF] Hoefnagel | Quota swapping, relative stability, and transparency[END_REF]. This was before the need to ensure quota available to fleets matched catch composition, even though the latter changes according to stock abundance and tactical fishing practices (i.e. where, when and how fishing is undertaken) on a regular basis.

The landing obligation for demersal stocks is being implemented from 2016 through a transition period to 2019 from when all demersal TAC stocks are subject to the landing obligation. The transition period is designed to introduce only key target stocks to fleets' catch, so there is likely to be a small effect for most fleets. However, if the landing obligation is introduced with full compliance in 2019 then quota in the UK, based on current rules of allocation, will not necessarily be optimised to enable fleets to fish as many days as possible to maximise the use of that quota. Therefore supply of key stocks may be compromised, especially in the short term, as fleets adjust to quota for "choke" stocks not being readily available. If fleets don't receive assistance, perhaps through quota adjustment or subsidies, then vessels may quickly go out of business if they cannot attain a level of income that enables them to covers essential costs, a so-called break-even level [START_REF] Russel | Economic Impact Assessment of the Landing Obligation Economic Impact Assessment[END_REF][START_REF] Russell | Landing Obligation Economic Impact Assessment (EIA): Interim Report Two: Scenario Analysis[END_REF].

In this paper, two simulations are tested for the landing obligation for UK fleets: the first (AS-IS) is a baseline which simulates the implementation of the landing obligation and is designed to allow for quota top-up to account for total catch and also allows for small limits of zero-TAC stocks; and the second (TO-BE) builds on this by also considering key mitigation tools (or policy levers) that are documented in the regulation (i.e. Article 15). The policy levers of the latter simulation include the simulation of,

• de minimis -an additional 5% of UK quota is available to alleviate the impact of choke stocks only where any catch identified as de minimis must be discarded, • interspecies flexibility -unused quota of a fleet segment from any stock may be transferred to a "choke" stock if that "choke" stock is under safe biological limits up to a limit of 9%, and • survivability -skate is assumed to have a good chance of surviving being discarded and is therefore exempt from the landing obligation.

A key assumption is that quota allocations to fleet segments remain as in 2013 without further quota trade. The results presented for UK production can be considered to be the worst case scenario. Rest of the world imports are assumed to continue as in the base year under 'status quo', 2013. Bounds on status quo are provided by best and worst case estimations on rest of the world imports. This percentage bound is estimated based on imports from recent years for cod and haddock (Table 2). Confidence intervals of +/-10% for imports of cod are taken to be [105k, 127k] and of haddock [33k, 39k] from 2014 levels.

{TABLE 2}

Note also that exports are modelled to follow changes in UK production. For cod, given exports are at a similar level to UK production, any changes in UK production are likely offset by changes in exports so as to have a minimal net effect on supply.

Results

Simulation results for the UK production of whitefish, in particular cod and haddock, under the landing obligation are presented in Figure 8. During the transition period, between 2016 and 2018, as more stocks come under the landing obligation the total landings of cod and haddock are not affected considerably. In fact, with quota top-up, fleets are estimated to have more quota to access in the transition period. In 2019 however, as all quota stocks come under the landing obligation, the fleets are choked relatively early by the quota they are simulated to have available. In the As-Is simulation (Figure 8), this is estimated to result in cod and haddock quota utilisation of less than 40% of base year levels with a significant reduction in supply of cod and haddock versus 2013 levels.

{FIGURE 8}

In the To-Be simulation (Figure 8), the situation is marginally better with policy levers implemented (namely de minimis, quota flexibility and survivability). It is simulated that cod and haddock quota utilisation could be up to 50% of base year levels in 2022. However, this is still a significant reduction in supply of UK produced cod and haddock versus 2013 levels.

As discussed in section 2.1, it is apparent that the amount of revenue required to breakeven for the over 24m whitefish fleet has reduced in recent years where the 12-24m whitefish fleet breakeven revenue has remained fairly stable, but with income per day for both fleet segments steadily increasing. In 2014, the 12-24m whitefish fleet segment is estimated to have broken even in 50% of the days fished and the over 24m fleet segment in approximately 43% of days (Figure 4). Results from scenarios presented above indicate that fleet segments may reduce to 35-50% of base year levels of effort, which brings the whitefish fleet segments considered down to breakeven levels. This suggests that these fleets could continue to operate with profits in the short term with quota trade even though some individual vessels may struggle with a much reduced financial position. However, it is supply from UK production that is likely to be affected as fleets adjust under the landing obligation.

Considering the effects that these changes could have on total supply of cod and haddock to UK markets, the simulation results are combined with imports of cod haddock to the UK in 2013-14 and potential total supply projected to 2022. These results are presented in balance sheets in Figure 9.

{FIGURE 9}

It is estimated that 115,000 tonnes of cod and 90,000 tonnes of haddock were available to the UK market in 2013. In 2019 it is estimated that between 104,000 to 127,000 tonnes of cod and 51,000 to 59,000 tonnes of haddock could be available (As-Is and To-Be simulations respectively). As proportionally more haddock is supplied from UK production, this is the species likely to be impacted the most. It suggests that cod available to UK markets could be relatively similar to that in 2013, but for haddock 27%-40% less in market supply (i.e. lowest to highest simulated result in Figure 9). A drop of 20% in haddock imports between 2013 and 2014 indicates the level of volatility seen (Table 2).

The UK has the largest and most competitive seafood processing industry in the EU, "the highest GVA in absolute terms in 2012 (27% of the EU total)" and "the highest net profit in absolute terms in 2012 (66% of the estimated total)" [START_REF]The Economic Performance Report on the EU Fish Processing (STECF-14-21)[END_REF][START_REF] Yordanova | Seafish Processing[END_REF]. Compared to Iceland and Norway with 4,200 workers [START_REF] Popescu | Icelandic fisheries: A review[END_REF] and 9,600 FTEs [START_REF] Richardsen | Employment in EU Fish Processing Industry based on Norwegian Seafood Export[END_REF] respectively, UK fish processing is reported to have 17,855 FTEs in fish processing (Spain with 17,399) in 2012 [START_REF]The Economic Performance Report on the EU Fish Processing (STECF-14-21)[END_REF] and 19,511 FTE jobs in 2014 [START_REF] Yordanova | Seafish Processing[END_REF]. With 403 fish processing units (i.e. company locations) reported, an average of 48 FTE per unit even though 57% of units have greater than 100 FTEs, 83% of which specialise in sea fish and 15% salmon [START_REF] Yordanova | Seafish Processing[END_REF]. With regard to whitefish, the wholesale and processing sectors supply fish and chip shops that typically rely on cod and haddock. Total value to this part of the value chain is reported to amount to over £1 billion per year 2 . This implies that the processing/wholesale sectors will likely seek to make up any short fall from UK production in imports.

Discussion

It is reported that around 70% of all seafood sold in the UK are the "big 5" species, i.e. salmon, cod, haddock, tuna, prawns [START_REF]Seafood Industry Factsheet[END_REF]. Of these salmon is mostly farmed in Europe, prawns and tuna are mostly imported from outside Europe with only cod and haddock originating mostly from

European and neighbouring seas. The UK's share of North Sea cod EU TAC amounted to approximately 40% in 2015 and for North Sea haddock approximately 70% in 2015. In addition, quota was available to UK fleets fishing in Norwegian waters (ICES area II). Supply of cod and haddock from UK fleets is limited and with the introduction of the landing obligation Uk production will likely be reduced in the short term placing more reliance on imports, particularly from Iceland and Norway. If exports reduce as a result of UK landings decreasing then there'll be additional competition from other countries, possibly also increased by the landing obligation in those countries also.

From the analysis undertaken here, cod appears to be relatively secure especially as imports have increased by 15% in the three year period from 2012 to 2014. Haddock on the other hand is likely to see decreasing supply on the UK market in the short term as imports have decreased by 41% over the same period, with the landing obligation also potentially resulting in decreased supply.

The UK competes with Spain and other parts of Europe for cod and haddock supplies from Iceland [START_REF] Lawrence | Fleet Economic Performance: Dataset 2005-14[END_REF], particularly Spain's demand for expensive Icelandic salt cod. Cod and haddock TACs in Iceland have been increasing in recent years3 [START_REF] Seafish | Outlook for supplies of Icelandic cod and haddock to the UK[END_REF]. The UK is historically a strong market for exporting unprocessed cod and haddock to. Conversely, in 2015, ICES published recommendations to reduce the TAC of Barents Sea cod in 2016 by 10%. However, Norway and Russia kept 2016 TAC the same as in 2015. Even so, TAC for Barents Sea cod has reduced from 1m tonnes in 2013 to 894 thousand tonnes in 2015 and 2016, with a further decrease to 805 thousand tonnes advised by ICES for 2017 [START_REF] Anon | ICES Advice on fishing opportunities, catch, and effort, Barents Sea and Norwegian Sea Ecoregions. Cod (Gadus morhua) in subareas 1 and 2 (Northeast Arctic)[END_REF]. Haddock on the other hand was recommended to increase by 25%. Thus imports of cod, with such competition and reducing supplies may not be able to increase significantly in the short term. One website reported "Barents Sea cod quota cut will cause a fight for raw material" between the various processing sectors [START_REF] Seaman | Barents Sea cod quota cut will cause fight for raw material[END_REF]. In their analysis, increases in fresh cod with higher prices, given recent increases in demand, appeared to be the conclusion.

Retail is apparently becoming more demanding on the need to provide sustainable fish products. This has resulted in the Marine Stewardship Council (MSC) label becoming the most commonly used. As a result for example, Icelandic cod and haddock has been certified under the MSC scheme. It is estimated that approximately half of UK cod supply is MSC and the majority of haddock. Supermarkets vary hugely with MSC labelled product lines with MSC.org reporting that Sainsbury's have 76% seafood products labelled MSC with Waitrose and LIDL approximately 50% and other supermarkets from 2% to 37%. Policy that could impact such labelling is the EU's objective to ensure that all quota stocks are fished at maximum sustainable yield (MSY) by 2020. This would imply that stocks at this level are sustainable and may not necessarily require a label to indicate sustainability. In addition, the EC has recently completed a study considering the demand for a public sustainable label [START_REF] Dgmare | Summary of the public consultation on an EU ecolabel for fishery and aquaculture products[END_REF]. It is often surmised that a price premium is attached to sustainably certified seafood, however there appears little general evidence to support this. Such labelling is less clearly used (or apparently required) in the fish and chips sector that has annual sales of fish and chips in the UK of around £1.2 billion (see footnote 2).

There are several risks that could impact the competitiveness of producers in the short term. These include the landing obligation, fishing to levels of MSY and fuel prices. The first two issues could have a direct impact on supply, particularly reduced supply in the short term as quotas reduce to achieve MSY and the landing obligation (potentially) hinders the ability of fleets to land all of the quota allocated. Fuel prices will impact profit as costs in what is a high energy use business increase. In the medium term of course, as stocks reach MSY, quotas increase and quota trade enables more effective use of quota under the landing obligation fleets will be more resilient and likely to supply the markets with cod and haddock at current amounts or even greater. Sustainability and traceability are important issues and will like add to the competitiveness of producers, even though at present much of the cost of certification falls on producers and not on other parts of the value chain. Balancing fleet capacity and catch composition with quota available is particularly important and may take time.

Conclusion

The UK has traditionally been a significant market for cod and haddock and as such has in recent years seen significant investment by Icelandic and Norwegian companies in the marketing, wholesale and processing sectors (e.g. Icelandic Seachill, Seagold (Samherji), Carisma UK and links with UK Fisheries Ltd). Important quantities of cod caught in Iceland and Norway are reaching the UK domestic market, either by direct landings or by export of fresh and frozen fish that is mostly filleted. The UK is the destination of more than half of the fresh cod exports from Iceland (57% of the value in 2015) and of close to a third of the cod fillet exports from Iceland (31% of the value in 2015).

The demand for cod and haddock in the UK is strong and is likely to remain so given the importance of the retail market and fish and chip shop market for these species. Supply of cod is estimated to be relatively stable, however haddock has been declining and unless haddock can be sourced in the short term there will likely be a gap in supply as UK fleets adjust to the landing obligation. The UK imports more fresh / frozen cod and haddock than any other EU country, estimated 27% cod and 55% haddock in 2016 (EUMOFA trade data). The next largest importers, Netherlands (24%) and Denmark (15%), appear to import fresh / frozen cod in particular for re-export to Spain, Portugal and France, which also appears from trade data to be a similar phenomonen in the value chain for salted cod.

Of the main importing countries for fresh / frozen cod and haddock in the EU , the UK is estimated to pay the highest prices. On average prices were 35% higher than Netherlands and 29% higher than Denmark between 2015-17. Therefore, the UK is in a strong position to compete for raw material from Iceland and Norway. It may be possible that increased imports for these species will be able to fill the gap but also other substitutes could appear. Pangasius and salmon appears to compete on the retail market with fresh/frozen cod and haddock fillets and pollack competes strongly with cod and haddock in processed seafood (e.g. fish fingers and other battered/breaded fish).

In the medium to long term, as the capacity of the fleets balance to the new regulations supply will likely return and if MSY is reached in 2020 then an increase in TACs from current levels is likely too. However, markets and industries can change in a 5-10 year period. Particularly, most processing companies are small to medium size enterprises (SMEs)4 [START_REF] Yordanova | Seafish Processing[END_REF] and some that concentrate on cod and haddock processing may not survive a shock to their supply or at least may have to adjust how they operate. It appears that fleets could be resilient to such short term reductions in landings however this cannot be assumed. The competitiveness of Figure 9. Balance sheets for cod and haddock, including lower and upper bounds on to-be scenarios

Figure 1 .Figure 2 .Figure 3 .Figure 4 .Figure 5 .Figure 6 .Figure 7 .Figure 8 .

 12345678 Figure 1. Whitefish fleet segments 12-24m and over 24m vessels (source: estimated from [20])Figure2. Whitefish fleet segments 12-24m and >24m landings in value, GBP (source: estimated from[START_REF] Lawrence | Fleet Economic Performance: Dataset 2005-14[END_REF] and[START_REF]UK Sea Fisheries Annual Statistics[END_REF]) Figure3. Whitefish fleet segments 12-24m and > 24m profit, GBP (source: estimated from[START_REF] Lawrence | Fleet Economic Performance: Dataset 2005-14[END_REF] and[START_REF]UK Sea Fisheries Annual Statistics[END_REF]) Figure4. Breakeven revenue and days fished for whitefish fleet segments Figure5. Countries from which cod and haddock (in total) are imported to the UK in 2014[START_REF] Hmrc | UK Trade data[END_REF] Figure6. Production of cod and haddock by EU countries in 2013 by main sea area[START_REF]The 2015 Annual Economic Report on the EU Fishing Fleet (STECF-15-07)[END_REF] Figure7. Model process based on yearly time-step to simulate production in UK fisheries Figure 8. As-Is (left) and To-Be (right) simulation results for cod and haddock production from 2013-22.

Table 1 .

 1 Whitefish value chain in the UK in 2014, quantity and value[START_REF]UK Sea Fisheries Annual Statistics[END_REF]

	2014	Landings outside UK by UK vessels	Landings in UK by UK vessels	Imports	Exports	Apparent consumption*
	Cod	14.9 kt (M€25.1)	14.0 kt (M€34.7)	116.4 kt (M€510.8)	15.5 kt (M€65.4)	115.7 kt
	Haddock	0.7 kt (M€1.3)	35.4 kt (M€61.5)	35.9 kt (M€138.4)	1.0 kt (M€3.2)	72.1 kt
	Hake	2.8 kt (M€7.8)	8.5 kt (M€24.6)	4.7 kt (M€13.8)	3.9 kt (M€16.3)	16.4 kt
	Ling	0.4 kt (M€0.7)	4.4 kt (M€6.7)	1.2 kt (M€1.5)	2.3 kt (M€5.9)	5.0 kt
	Anglerfish	4.5 kt (M€17.9)	11.4 kt (M€39.2)	1.7 kt (M€7.8)	2.8 kt (M€17.6)	11.6 kt
	Plaice	15.6 kt (M€21.3)	3.5 kt (M€4.4)	4.2 kt (M€16.0)	0.3 kt (M€0.6)	8.1 kt
	Pollack	0.6 kt (M€0.8)	1.9 kt (M€4.3)	38.3 kt (M€89.5)	3.9 kt (M€12.9)	36.4 kt
	Saithe	1.6 kt (M€2.5)	11.1 kt (M€12.7)	3.2 kt (M€11.9)	4.7 kt (M€10.7)	15.9 kt
	Whiting	0.7 kt (M€0.8)	11.1 kt (M€14.8)	3.3 kt (M€3.2)	1.6 kt (M€1.5)	13.4 kt

*Apparent consumption = [(total catches -industrial catches) + aquaculture + imports] -exports

Table 2 .

 2 Changes in rest of world imports to UK for supply of cod and haddock, 2012-14[START_REF]UK Sea Fisheries Annual Statistics[END_REF][START_REF]UK Sea Fisheries Annual Statistics[END_REF]

			Cod imports		Change	Haddock imports	Change
		2012	2013	2014 (2012-14)	2012	2013	2014	(2012-14)
	Iceland	28,722	36,211	32,747	+14%	10,936	9,289	6,710	-39%
	Norway	17,111	20,036	23,757	+39%	23,675 11,386	9,115	-61%
	China	14,780	20,339	24,761	+68%	7,946	6,550	5,226	-34%
	Denmark	10,255	12,342	9,386	-8%	6,030	6,058	4,016	-33%
	Faroe Islands	6,592	7,226	6,353	-4%	2,504	3,110	2,861	+14%
	Germany	8,879	7,599	6,802	-23%	1,912	657	439	-77%
	Others	15,194	12,591	12,595	-17%	7,708	7,857	7,515	-3%
	TOTAL	101,53 3	116,343 116,401	+15%	60,711 44,907 35,882	-41%

Regulation (EU) No 1380/2013 on the Common Fisheries Policy

http://www.federationoffishfriers.co.uk/pages/facts-and-figures-603.htm

see http://www.fiskistofa.is/

Medium <250 employees and <€50m turnover; Small <50 employees and <€10m turnover; Micro <10 employees and <€2m turnover. Note balance sheet limits are also used. (See EU recommendation 2003/361)

Acknowledgments

This research was undertaken under the SUCCESS project which has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 635188. (http://www.success-h2020.eu/ )

producers will surely be affected in the short to medium term as a result as fleets adapt to supply the market.


Daniel Crespin
email: nnbcrespin@gmail.com

This note provides links and references for the mathematical framework of the NNB algorithm, and to download the NNB Demo Software as well as videos. Advantages of the NNB algorithm can be appreciated solving your own deep learning problems by running the Demo and comparing against backpropagation. §1 The NNB Algorithm NNB stands for Neural Network Builder this phrase referring to an algorithm for the direct calculation of deep neural networks and to the related software.

The neural networks are functions that recognize training data, these being n-dimensional numerical vectors with designated outputs equal to 1 (the 1-vecs) and 0 (the 0-vecs). There can be strips parameters -introduced by the NNB-that specify a user designated proportional separation between 1-vecs and 0-vecs. Using the data and strips the NNB algorithm calculates the architecture and weights of a three layer, feed forward, single binary output, discontinuous threshold perceptron neural network, called classical perceptron network, here shortened to network. The network calculated with the NNB exactly recognizes the training data, that is, has a 100% success rate. Furthermore the network maintains specified proportional distances to the decisory hypersurfaces according to set strips parameters.

Networks with outputs that are binary m-vectors are set theortical products of several single output networks and can be reduced in theory and in practice to the single output case. The venerable but slow, time consuming, energy wasting, unreliable and unpredictable backpropagation algorithm will be no longer necessary thanks to the NNB.

Using the NNB algorithm you avoid:

• Divination of the number of layers (3?, 10s?, 100s?) • Speculation on the quantity of neural units per layer The machine learning network problem consists in using the n-dimensional data vectors to calculate a network N that correctly recognizes the data. Preliminary theoretical work has established that the functional problem of calculating N is equivalent to the geometric problem of calculating certain polyhedron K in n-dimensional space. The polyhedron contains the 1-vecs and excludes the 0-vecs while respecting the strip values. The NNB proceeds to calculate such polyhedron and converts it into a three layer network N that perfectly recognizes the data vectors.

NNB Demo is freely available software. The AI community is invited to run the Demo and check the advantages of the algorithm. Use the link below to download NNB Demo, the videos, and test for yourself. Documentation is available within the GUI. §2 NNB Demo links Link to the Demo software:

The NNB Demo software runs under Windows and has a GUI. To download the Demo just click here, download the .rar file, unzip and run the install.

Links to videos:

Click here to download videos: DEEP LEARNING WITH NNB.mp4 DEEP LEARNING WITHOUT BACKPROPAGATION.mp4 This last video is also available in YouTube §3 Articles There are currently four platforms containing some of our work on neural networks: HAL Academia Researchgate ArXiv Below are links to specific articles. Note the redundancies: most articles appear in more than one platform.

Articles in HAL

Matrix Formulas for Semilinear Backpropagation Theory and Formulas for Backpropagation in Hilbert Spaces

•

  Random tossing numerical values for the initial weights • Guessing values for learning rate parameters • Conjecturing how many iterations each epoch requires • Repeating the epochs • Frustration from poor results


Abdelkarim Ammar

Aissa Kheldoun

Brahim Metidji

Billel Talbi

Tarek Ameid

Younes Azzoug

An Experimental Assessment of Direct Torque Control and Model Predictive Control Methods for Induction Machine Drive

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.


Abdelkarim Ammar

Tarek Ameid

Younes Azzoug

Aissa Kheldoun

Brahim Metidji

Implementation of Sliding Mode Based-Direct Flux and Torque Control for Induction Motor Drive with Efficiency Optimization

published or not. The documents may come   L'archive ouverte pluridisciplinaire


Mohan Michel Bitbol

Reply to: The Principles of Beginning, by Shaj

otherbeginning/reply-to-the-principles-of-beginning-by-shajmohan

The quest for another beginning of philosophy is conditioned by a regressive path towards its first beginning. This path is to be traveled backwards with a scrupulous attention to the critical moment when an unnoticed twist, an unseen bias, was introduced by the founders of philosophy. And this path must then be traveled forward again, to highlight the possibilities of thought that have been hidden and sometimes made impossible by these options. Such procedure is well-known. It has been used repeatedly during the two last centuries, from Hegel to Derrida, with special mentions for Husserl (in his First Philosophy), and then Heidegger, Schrödinger, or Wittgenstein. But it is fruitful to rehearse such archeological procedure, whenever a new historical situation opens up the space of an unprecedented sensitivity to what was special, or arbitrary, in the choices that were made almost unconsciously at the times of the first beginning of philosophy.

Our historical situation is arguably exceptional in this respect, for it combines at least two highly uncommon features.

The first feature is that human technology is not only accelerating its pace; it is creating the conditions of its selfreproduction and self-amplification through Deep Learning artificial intelligence plus robotics and transhumanistic projects. This "self-making" capacity of AI technologies is already having a destabilizing, may be inhibiting, effect on

human thought; indeed, to borrow a scathing sentence from Marc Richir, by promoting artificial intelligence, "Human beings think, in order never to think again".

The second uncommon feature of our time is to be confronted to the unlivable possibility that the conditions for life fail us on Earth. This is one of the ways for us (perhaps the most concrete way) to understand Shaj's reference to the "obscure experience" of being unable to anticipate the withdrawal of our world, when this world is the condition of possibility for living ahead of oneself, namely in permanent anticipation towards an open future.

Our sensitivity is then also exceptional, and I feel many signs of its sharpness in Shaj's rich reflection about the first and the new beginning of philosophy.

So, what are the unseen biases of the first beginning? The most glaring, and probably most decisive, of these biases is shortly evoked by Shaj, but I'd like to expand on it. It's nothing else and nothing less than the use of language, Logos, as the exclusive medium of expression and transmission. It sounds strange, almost shocking, to call this a "bias" of philosophy as a whole; and it sounds even more strange to think that there was a deliberation about such apparently obvious option. Yet, the early history of philosophy is buzzing of a vibrant debate about the primacy of Logos in philosophy. In his fragment 2, Heraclitus thus prescribes one to follow the common Logos, and to avoid remaining enclosed in singular rumination. He would not have done this prescription if it had been obvious. It was indeed a momentous decision, which did not remain unchallenged in the Greek area. It was especially criticized by Pyrrho, who advocated the Epochè, or suspension of judgment, in order to reach the practical purpose of philosophy which, according to him, was Ataraxia, a silent state of being. Aristotle was also well aware that the hegemonic position of language, judgment, and truth, was a burning issue in philosophy. In the book Gamma of his Metaphysics, he famously invited the heracliteans, sophists, and skeptics to uphold whatever proposition, and then showed that this was enough to trap them immediately in a self-contradiction of their thesis. Or else he invited them to remain silent, may be just moving their finger as Cratylus did, thus banning them from the Agora of discursive debate. This is what Michel Narcy and Barbara Cassin called "the decision of meaning", which has set the whole history of philosophy on a very particular path.

But how particular is it? Shaj makes the remark, borrowed from Plato, that there is the risk of emphasizing the components of language, such as words or propositions, to the detriment of the living whole of speech. Pondering on substances by focusing attention on substantives (as Wittgenstein warned us) is one form of this original mistake. Transforming philosophy into a logic of propositions, together with their combinations and inferential connection, as analytic philosophy tends to do, is another form of the same mistake. Instead, one should broaden the field of attention to the living whole of speech, which includes its background unformulated presuppositions, and even its own boundaries that open up to the speakers' life of which it is just an aspect. This is what Merleau-Ponty tried to convey, in the following quote:

"Each partial act of expression, as a common act of the whole of language (makes us verify) the power that speaking subjects have of going beyond signs towards meaning. The signs do not only evoke for us other signs and this without end; language is not like a prison in which we are locked up, or like a guide that we should follow blindly, since, at the intersection of all these linguistic gestures, finally appears what they mean" 1 .

By contrast with signs, that follow one another according to a logical grammar, meanings are lived through, they are expressions of an embodied life, they count as steps of lived life, and they can then sometimes break the rules of the logical grammar. Indeed, despite the rules, they bear the mark 1 "Chaque acte partiel d'expression, comme acte commun du tout de la langue, ne se borne pas à dépenser un pouvoir expressif accumulé en elle, mais le recrée et la recrée, en nous faisant vérifier, dans l'évidence du sens donné et reçu, le pouvoir qu'ont les sujets parlants de dépasser les signes vers le sens. Les signes n'évoquent pas seulement pour nous d'autres signes et cela sans fin, le langage n'est pas comme une prison où nous soyons enfermés, ou comme un guide qu'il faudrait suivre aveuglément, puisque, à l'intersection de tous ces gestes linguistiques, apparaît enfin ce qu'ils veulent dire". Merleau-Ponty, Signes, p. 101 of the teeming 2 anticipations of the embodied life. According to Merleau-Ponty, "The significant intention in me … is only … a determined void, to be filled by words. The meanings of discourse are thus ideas in the Kantian sense" 3 . Just as Kantian ideas, the meanings of discourse are aiming towards future developments, future embodied experiences, beyond the present vocal vibration of their sound. This "going beyond" is the very principle of operation of language, but it is also its major weakness, or at least its unrecognized incompleteness, as we shall now see.

This unrecognized incompleteness of the operation of language was forcefully brought about in Wittgenstein's Tractatus. According to its well-known section 6.522, "There are, indeed, things that cannot be put into words. They make themselves manifest". What cannot be put into words according to Wittgenstein is not only "The Mystical", but the very meaning of one's words (unless one is satisfied with the infinite regress of dictionaries); it is also the limits of empirical reality (5.5561), and, last but not least, the partial truth of solipsism (5.62). Let me concentrate on the latter unspeakable truth. Wittgenstein summarizes it by declaring that "The subject does not belong to the world: rather, it is a limit of the world" (5.632). When one speaks, one speaks of elements of the manifest world. Trying to overcome this obstacle, trying to speak of what does not belong to the manifest world, immediately triggers misunderstandings. For, what does not belong to the manifest world here means the very limit of this world, namely the manifestation itself as a whole, Such misunderstandings are glaring in the contemporary debate about the "hard problem" of the physical origin of 2 foisonnantes 3 "L'intention significative en moi (comme aussi chez l'auditeur qui la retrouve en m'entendant) n'est sur le moment, et même si elle doit ensuite fructifier en « pensées » -qu'un vide déterminé, à combler par des mots, -l'excès de ce que je veux dire sur ce qui est ou ce qui a été déjà dit. Ceci signifie : a) que les significations de la parole sont toujours des idées au sens kantien, les pôles d'un certain nombre d'actes d'expression convergents qui aiman-tent le discours sans être proprement donnés pour leur compte". Merleau-Ponty, Signes, p. 112 consciousness4 . In this debate, many actors behave as flies in a bottle because they don't realize that their problem is generated by the inherent narrowness of language. Why? Because language means and discriminates. And because both meaning and discrimination are arts to establish boundaries, even when what is tentatively meant is the horizon within which such boundaries are established.

Meaning is tantamount to displacing attention. It displaces attention from the sound of a word to what it signifies, from the pointed finger to what it aims at showing. Meaning thereby pushes us outwards, towards the future, towards something that is not close at hand. When we use a word for "consciousness", we are then automatically led astray, because conscious experience is not something over there to be meant in any way. Instead, consciousness is plainly here; this "here" that submerges us; this "here" that is presupposed by any location in space. Trying to mean consciousness is self-defeating, since what is allegedly meant is not beyond the very act of meaning it.

The same holds for the discriminative power of language. How can we discriminate present conscious experience from anything else? At this precise moment of consciousness that contains in it every possible intentional object, as well as the memories of the past and the projects for the future, there is nothing that can be contrasted with conscious experience and discriminated from it.

That present conscious experience is thus unspeakable does not mean that it should be banned from philosophy. Rather the contrary. Philosophy is haunted by it, at every step of its quest. This "unspeakable" pops out like the omnipresent reverse side and precondition of the philosophical Logos.

For instance, in my recent debate with speculative realism, I have insisted that one must broaden the range of arguments to include not only locutionary but also perlocutionary acts of language in them. My claim is that philosophical arguments address themselves to lived states, to the lived states of those who participate in the argumentative exchanges, beyond the abstract criteria of validity of the arguments. Indeed, philosophers have an additional resource compared to scientists: that of being able to directly modulate the judgment of validity that their interlocutors make on any argument. While the last word of a formal inference process consists of a string of characters, the last word of a philosophical argument is the recipient's approval; it is her propensity to say "yes", it is her experience of persuasion, it is her free consent to transform her vision of the world to make it conform to her new conviction. This supposes to shed light on the lived pre-conditions of the arguments, and to fully acknowledge this tacit background which alone gives them meaning and relevance.

Another example is the status of metaphysics. As Shaj cogently summarizes, "Metaphysics is the style of thinking where a component of the system is taken to be the comprehending law of the whole system". In the standard onto-theological determination of metaphysics, some supreme thing is supposed to hold the position of a principle of all things. This being granted, the stasis of metaphysics is not surprising: it goes round in circles within the domain of speakable things, without even visiting its immensely fruitful but unspeakable lived matrix. Even worse, metaphysics contents itself with mimicking a proper handling of speakable things by claiming being for its supreme thing; whereas this supreme thing, the thing-in-itself, the so-called absolute foundation, is nothing more than a reification of some regulative ideal of reason, as Kant rightly pointed out. This is why Henri Bergson proposed his own new beginning in 1903, by way of a radical redefinition of metaphysics, that clearly alludes to the unspeakable lived matrix of discourse. "Metaphysics, he wrote, is the science that claims to do without symbols. There is at least one reality that we all grasp from within, by intuition and not by simple analysis and symbols. It is our own person in its flow through time. It is our lasting self" 5 . But then, what can be the function of the language and symbols used in this very quoted sentence? Just a perlocutionary function, as in the case of elenctic arguments. Just the function of inviting the readers to experience the unspeakable origin of language for themselves; namely the function of inviting them to drop their ordinary clinging to identity by letting duration unfold.

So, Bergson's acceptation of metaphysics sounds like it is no longer underpinned by the law of identity as a fundamental principle. For, by substituting intuition for understanding, Bergson is moving away the very faculty which relies on identity. Let's hear his criticism of understanding: "One of the functions (of human understanding is precisely to conceal duration. (...) Nothing could be more natural, since our understanding is intended above all to prepare and enlighten our action on things. Our action is conveniently exercised only on fixed points; it is therefore fixity that our understanding seeks" 6 . Now, the principle of identity is the most concise expression one can give of fixity; but to realize this, one must examine it carefully, and reflectively. Formulated by Leibniz, the principle of identity is "the statement that a thing is what it is" 7 ; written shortly, this is symbolized by A=A. This looks like an innocent static, repetitive, tautology, with no relevance on time and duration. But let's now dig into its manifold presuppositions, even the most elementary, the most trivial so to speak; and let's go beyond the written to the reading. A, to begin with. A is a letter, a symbol. But is any A symbolically tantamount to any other A? Is the shape of A to count as symbolically the same when it is read under different angles, at different moments? Claiming that it is so is the founding act of written language. And the founding act of written language is to shelter its components from variety and change. Then, by supposing that A is the name of something, this sheltering from change 6 "C'est bien ce que nous crûmes apercevoir en étudiant la structure de l'entendement humain. Il nous apparut qu'une de ses fonctions était justement de masquer la durée. (...) Rien de plus naturel, si l'intelligence est destinée surtout à préparer et à éclairer notre action sur les choses. Notre action ne s'exerce commodément que sur des points fixes ; c'est donc la fixité que notre intelligence recherche". Bergson, La pensée et le mouvant, introduction 7 Leibniz, Nouveaux Essais, IV, 7, § 9 is transferred to the things named, despite their visible alteration. A would be enough to ensure fixity; just its stubborn presence of which nothing more is to be said. Just its stubborn presence that is said to stand for the alleged stubborn presence of the thing whose name it is. Just a stubborn presence, whereas both the thing and its name constantly fluctuate in the attention paid to them. But that's not all. The principle of identity says A=A. Let's read it from left to right. A … equals… A. 'A' fades away, 'equals' comes to the fore. 'Equals' fades away, and another shape, recognized as the symbol 'A', emerges. Disappearance and re-cognition. Fading away and emergence. And across this flux, we are asked to accept, against any evidence, that the same is to be seen where there looks to be another. Here, the temporal deployment of the principle of identity as it is read operates as the model, or the archetype, of any negation of duration by our understanding.

If, on the contrary, metaphysics strays from the task of identifying and naming a principle, a supreme thing forever identical among temporarily identical things, if, on the contrary, metaphysics finds itself assigned the task of expressing manifestation in its unfolding, it becomes phenomenology. It looks like this is just old stuff; but it seems to me that, despite the stunning corpus of writing that constitutes the present phenomenological tradition, spreading the phenomenological stance, and agreeing on its consequences for philosophy is still work in progress.

The following reflections about consciousness are derived from: M. Bitbol, La conscience a-t-elle une origine? Flammarion, 2014

H. Bergson, Introduction à la métaphysique, chapitre VI de La pensée et le mouvant.


Tarek Ameid

Arezki Menacer

Hicham Talhaoui

Youness Azzoug

Discrete wavelet transform and energy eigen value for rotor bars fault detection in variable speed field-oriented control of induction motor drive

Keywords:

published or not. The documents may come

Discrete wavelet transform and energy eigen value for rotor bars fault detection in variable speed field-oriented control of induction motor drive

Introduction

In industry, drive applications require high performances, the squirrel-cage induction motor (IM) takes an important place due to its rigidity, and works more efficiently compared to the wounded rotor. In addition, it adjusts to several service applications, where the speed should closely follow a trajectory specified reference that is independent of any external load disturbance. The operation modes of the IM are vulnerable to a variety of unwanted conditions, which make it susceptible to different types of defaults. In this respect, these faults in the machine can be classified into two categories: on the one hand, External, such as: overload, poor mounting, the voltage and the environmental phenomena. On the other hand, Internal, such as: interturn short circuit [START_REF] Bachir | Diagnosis by parameter estimation of stator and rotor faults occurring in induction machines[END_REF][START_REF] Guezmil | Detecting interturn short-circuit fault in induction machine using high-order sliding mode observer: simulation and experimental verification[END_REF], eccentricity of the rotor [START_REF] Samaga | Comprehensive study of mixed eccentricity fault diagnosis in induction motors using signature analysis[END_REF][START_REF] Talhaoui | Mixed eccentricity fault diagnosis in the sensorless field oriented control induction motor using DWT technique[END_REF] and broken rotor bars [START_REF] Moussa | A detection method for induction motor bar fault using sidelobes leakage phenomenon of the sliding DFT[END_REF][START_REF] Bessam | Detection of broken rotor bar faults in induction motor at low load using neural network[END_REF]. The broken rotor bars fault causes fluctuation and decreases torque's amplitude; therefore, more fluctuation and mechanical vibrations can be produced, and then these problems can lead to the damage of the machine. Ultimately, the rotor bars fault effect becomes more obvious by the increase of the broken bars number, especially, in the open-loop drives [START_REF] Menacer | Effect of the position and the number of broken bars on asynchronous motor stator current spectrum[END_REF]. To avoid such problems, the fault diagnosis and detection process become highly necessary step to protect this type of electrical components [START_REF] Nandi | Condition monitoring and fault diagnosis of electrical machines-a review[END_REF].

The purpose of the field-oriented control is to have good performance flux and torque decoupled control, this technique has led to a radical change in control of the IM [START_REF] Casadei | FOC and DTC: two viable schemes for induction motors torque control[END_REF]. The recommended machine model for closed-loop FOC design takes into account the effective geometry of the rotor based on multi-winding model for diagnosis purpose considering the broken rotor bars fault [START_REF] Ameid | Broken rotor bar fault diagnosis using fast Fourier transform applied to field-oriented control induction machine: simulation and experimental study[END_REF].

In recent years, several techniques for the fault detection have been proposed in the literature; they focused on the diversity of the encountered problems, and have made it a challenging topic for many researchers. Furthermore, it is usually known that the developed techniques for IMs diagnosis in open-loop drives are not so effective when the motor's control structure becomes more complex, particularly, the closed-loop vector controlled motors [START_REF] Hachemi Benbouzid | A review of induction motors signature analysis as a medium for faults detection[END_REF][START_REF] Chen | Fault detection, classification and location for transmission lines and distribution systems: a review on the methods[END_REF][START_REF] Ramana | Diverse fault detection techniques of three-phase induction motora review[END_REF][START_REF] Talhaoui | Fast Fourier and discrete wavelet transforms applied to sensorless vector control induction motor for rotor bar faults diagnosis[END_REF].

The use of signals approach for diagnosis has a great importance for the broken rotor bars detection. It's necessary to employ different analysis to interpret the acquired signals for the detection process, such as stator voltage, current, speed, temperature, and vibration signals [START_REF] Ramana | Diverse fault detection techniques of three-phase induction motora review[END_REF][START_REF] Talhaoui | Fast Fourier and discrete wavelet transforms applied to sensorless vector control induction motor for rotor bar faults diagnosis[END_REF]. The monitoring and diagnosis based on motor current signature analysis (MCSA) are widespread used methods, whereas, they present many advantages like requiring only one current sensor per machine, and is based on straightforward signal processing such as Fast Fourier Transforms (FFT) [START_REF] Kechida | fault detection of broken rotor bars using stator current spectrum for the direct torque control induction motor[END_REF][START_REF] Saidi | Diagnosis of broken-bars fault in induction machines using higher order spectral analysis[END_REF]. The FFT analysis method has been proved to be a good technique for fixed frequency supply, such as the connected machines to the electrical grid (steady-state), where it is used to determine the spectral signatures by investigating components around the fundamental frequency [START_REF] Menacer | Application of the Fourier and the wavelet transform for the fault detection in induction motors at the startup electromagnetic torque[END_REF]. However, the effectiveness and accuracy of the FFT are affected by the amount of time domain data. In addition this can be more affective in cases of inconstant load or speed, since both of them make a variation on the motor slip or timefrequency. Therefore, this assumption may be considered as a limitation of this approach and the FFT analysis cannot be applied by consequence. For this reason, the wavelet decompositions becomes our main focus in this paper which will be proposed in order to overcome the aforementioned difficulties [START_REF] Bouzida | Fault diagnosis in industrial induction machines through discrete wavelet transform[END_REF][START_REF] Da Costa | Rotor failure detection of induction motors by wavelet transform and Fourier transform in non-stationary condition[END_REF][START_REF] Riera-Guasp | Detection of broken outer-cage bars for double-cage induction motors under the startup transient[END_REF][START_REF] Panigrahy | Broken bar fault detection using fused DWT-FFT in FPGA platform[END_REF].

The wavelet transform is a window technique with a variable size. It is used in order to improve the stator phase current analysis in steady and transient states. The wavelet transform is a new description of spectral decomposition via the scaling concept. Wavelet theory offers a unified framework for many techniques, which have been developed for different applications in the field of signal-processing. Moreover, it can provide information in both of time and frequency domains [START_REF] Briz | Broken rotor bar detection in line-fed induction machines using complex wavelet analysis of startup transients[END_REF][START_REF] Cherif | Stator inter turns fault detection using discrete wavelet transform[END_REF].

In Ref. [START_REF] Shi Pu | Broken bar fault diagnosis for induction machines under load variation condition using discrete wavelet transform[END_REF], the authors present a method for the broken rotor bar fault detection based on discrete wavelet coefficients, when the induction motor operates with load variation. Others [START_REF] Kia | Diagnosis of Broken-bar fault in induction machines using discrete wavelet transform without slip estimation[END_REF] use the DWT for the current space vector magnitude or the instantaneous magnitude of the stator phase current analysis, the energy associated to the rotor fault in the frequency bandwidth is computed, this energy allows to evaluate the fault severity without any slip estimation. The DWT is used in Refs. [START_REF] Bouzida | Fault diagnosis in industrial induction machines through discrete wavelet transform[END_REF][START_REF] Kechida | Approach signal for rotor fault detection in induction motors[END_REF] for the analysis of stator current to detect the rotor bars fault in steady and start-up transient states, the calculation of the energy Eigenvalue of the stator current signal proves its importance as a good fault severity indicator. In most cases, the diagnostic methods are used for open-loop machine operation. However, in closed-loop drives, the control-loop masks and compensates the fault effect [START_REF] Ameid | Broken rotor bar fault diagnosis using fast Fourier transform applied to field-oriented control induction machine: simulation and experimental study[END_REF]. As a consequence, they cause a difficulty in fault detection using stator current analysis. Some attempts can be found in literature which uses other quantities for fault analysis. For instance, in Refs. [START_REF] Bellini | Different procedures for the diagnosis of rotor fault in closed loop induction motors drives[END_REF][START_REF] Serna | detection of Rotor fault in field oriented controlled induction machines[END_REF], d (direct) and q (quadratic) current axis components have been used for broken rotor bars detection in closed-loop drive. Nevertheless in case of variable speed drive, the continuous speed variation between two reference values causes a non-stationary state in the signals and confusion in the DWT spectrum, consequently a more difficulties in the fault diagnosis process.

The main objectives of this paper are the diagnosis of the broken rotor bars fault and the evaluation of the fault severity when the IM operates in closed-loop drive with continuous speed change. The FOC control strategy is presented to preserve a high performance decoupled control. The used method for the fault detection is DWT analysis which will be applied to output signal of the speed regulator and stator phase current. The choice of this technique has been done to ensure a good diagnosis during the continual variation of speed. The evaluation of the stored energy in each level of the active power energy allows both, to evaluate the fault severity (break or fissure), and to distinguish between fault and normal variation.

The effectiveness of the control scheme with diagnosis method will be investigated in simulation and experimentation using the Matlab/ Simulink software and hardware implementation using Real-Time interface (RTI) environment based on dSpace 1104 board. The realization of the control strategy is done by Digital Signal Processor with graphical programming platform (Matlab/Simulink/Control Desk). The simulation and experimental validation has shown a good dynamic control under rotor bars fault, wherein, the same signatures of the fault are proved in both results.

This paper is structured as follows: Section 2 presents the dynamic modeling of the IM taking into account the rotor bars fault. Section 3 describes the vector controlled IM. In section 4, the discrete wavelet transforms method is proposed. Section 5 illustrates and discusses the simulation results of the proposed control technique with diagnosis method. Then, the experimental validation is presented in Section 6.

Modeling of the induction motor with taking into account the rotor bars fault

The development of the reduced model which is dedicated for closed-loop control is inspired by the multi-winding model of the induction machine. This proposed model takes into account the rotor geometry which is considered as a squirrel-cage. The modeling is based on the equivalent scheme of the rotor which is shown in Fig. 1. It can be noticed that each bar of the rotor cage is represented by a resistance R b , in series, with a leakage inductance L b . The short-circuit ring portion between the two bars, as well, is represented by a resistance R e in series with a leakage inductance L e . A mesh is composed of two bars and two portions, hence, the cage is modeled by q number of meshes where each mesh represents one of the two rings of the short circuit, which are located on the rotor periphery. Therefore, with N r number of bars, the cage contains 2N r nodes and 3N r branches based on the theory of electrical circuits. As a result, the number of independent currents in the cage is:

- -= + N N N 3 ( 2 1
) 1 r r r [START_REF] Singh | A review of induction motor fault modeling[END_REF][START_REF] Menacer | Stator current analysis of incipient fault into asynchronous motor rotor bars using fourier fast transform[END_REF]. The modeling steps are presented in details in Refs. [START_REF] Talhaoui | Fast Fourier and discrete wavelet transforms applied to sensorless vector control induction motor for rotor bar faults diagnosis[END_REF] and [START_REF] Kechida | fault detection of broken rotor bars using stator current spectrum for the direct torque control induction motor[END_REF] in order to highlight the effect of the broken rotor bar fault. This model presents a difficulty in the control implementation, due to the big number of equations. To transform the system in N r phases into (d, q) system, the extended Park's transformation of the rotor will be applied.

The system is put in canonical form:

= - L d I dt V R I [ ] [ ] [ ] [ ][ ] (1)
where: As:

= ⎡ ⎣ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ - - - - ⎤ ⎦ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ = ⎡ ⎣ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ - - ⎤ ⎦ ⎥ ⎥ ⎥ ⎥ ⎥ ⎥ L L M L M M L M L L R R ωL ωM ω L R ω M R R R R R [ ] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ; [ ] 0 0 0 0 0 0 [ ] 0 0 0 [ ] 0 0 0 0
The total cyclic inductance of a stator phase which is given by the following equation: . The total cyclic inductance of the rotor is calculated by:

= - + + - L L M L N L 2 2 ( 1 c o s α ) rr rc rp e r e (2)
where:

The rotor mesh inductance can be calculated by the following equation: The mutual inductance between non adjacent rotor meshes is defined by: = -M π r l 2 . . The electrical angle of two adjacent rotor meshes:

= - ( ) L πrl 2 . .
= p α π N 2 r
The four matrices, taking into account the broken rotor bars fault, can be expressed by:

⎧ ⎨ ⎩ = + - ∑ ± - = - - ∑ - R R R R R (1 cosα) .(1 cos(2k 1).α) (1 cosα) .sin(2k 1).α N N rdd,rqq r 2 k bfk rdq,rqd 2 k bfk r r (3)
In this expression, the summation is applied to all bars with fault. R bfk is the increased resistance of the bar index k from its initial value before the fault.

Vector control based on the reduced model of IM

The Field-oriented control of the IM has been developed to allow a speed variation over a wide range. It separates the stator currents of IM into flux torque components in the (d, q) coordinate reference frame. The model system Eq. ( 1) is a heavily coupled, multivariable and nonlinear system. Those properties complicate the control design of the IM. The rotor flux-oriented coordinate is applied in order to simplify the model of the IM, where the rotor flux and the electromagnetic torque are aligned to the direct axis (d) and quadratic axis (q) respectively. In this coordinate system the rotor flux is assumed as [START_REF] Ameid | Broken rotor bar fault diagnosis using fast Fourier transform applied to field-oriented control induction machine: simulation and experimental study[END_REF][START_REF] Ameid | Simulation and real-time implementation of sensorless field oriented control of induction motor at healthy state using rotor cage model and EKF[END_REF].

⎧ ⎨ ⎩ = = ϕ ϕ ϕ 0 dr r qr (4)
The electromagnetic torque of IM is defined by:

= - - T p N M L ϕ i ϕ i 3 4 .
( ) e r s r rc dr qs qr ds [START_REF] Moussa | A detection method for induction motor bar fault using sidelobes leakage phenomenon of the sliding DFT[END_REF] While the quadratic flux is: = ϕ 0 qr , the electromagnetic torque expression becomes:

= - = T p N M L ϕ i K ϕ i 3 4
. . e r s r rc dr qs dr qs [START_REF] Bessam | Detection of broken rotor bar faults in induction motor at low load using neural network[END_REF] where: The rotor flux components are expressed in the stator reference as: where:

⎧ ⎨ ⎪ ⎪ ⎩ ⎪ ⎪ = - = - = - + = - + ϕ L i M i ϕ L i M i ϕ M i L i ϕ M i L i . . . . . . . .
= T L R / r r c
r : Rotor time constant. From using Eq. ( 1) and Eq. ( 7), the model for vector control design of IM is shown in Eq. ( 9), with the stator current, rotor flux and ring current are taken as state variables:

⎧ ⎨ ⎩ = + = x t Ax t Bu t y t Cx t ˙( ) ( ) ( ) ( ) ( ) (9)
As. The application of conventional signal processing methods such as Fast Fourier Transform FFT in fault diagnosis, does not always give a good performance because of to the accuracy and the large sample size of signals, which requires a space memory. Furthermore, they have a fixed length of the window and they cannot be used in transient state The wavelet transform is a similar tool to the Fourier transform; the difference is that the former decomposes the signal into a set of scaled and translated versions of a mother wavelet instead of using sine waves of different frequencies as the Fourier transform. The main advantage of this method is that flexibility in descripting the non-stationary states signals. Wavelet transforms is considered as an important aspect in speed and/or variable load, in this context, it is quite comparable to the Fourier analysis. However, wavelets are largely oscillating functions that are rapidly damped, unlike the sinusoidal functions of Fourier analysis [START_REF] Zhu | Wavelet analysis of sensor signals for tool condition monitoring: a review and some new results[END_REF][START_REF] Vitor | Induction motor fault diagnosis using wavelets and coordinate transformations[END_REF].

= x i i ϕ ϕ i [ ] T ds qs dr qr e ; = u V V [ ] T ds qs ; = y i i [ ] T ds qs ; = ⎡ ⎣ ⎢ ⎢ ⎢ ⎢ ⎢ -- - - - - - - -- - - - - - - - - - - - ⎤ ⎦ ⎥ ⎥ ⎥ ⎥ ⎥ A a a R ω a R a R a ω a R ω a R a a R a ω a R a R a R a R a R a R a R a R a R a R a 0 0 0 0 0 0 0 0 ; rdd r
= ⎡ ⎣ ⎢ ⎤ ⎦ ⎥ = ⎡ ⎣ ⎢ ⎤ ⎦ ⎥ B a a C 0 0 0 0 0 0 0 0 ; 1 0 0 0 0 0 1 0 0 0 ; T 8 8 ⎜ ⎟ = = = = = = = = = -⎛ ⎝ ⎞ ⎠ a R σL a M N L L σ a M N L L σ a M N L L σ a M L a L a R L a σL σ M N L L , 3 . 4 . . , . 2 . . , . 2 . . , 3 2 , 1 , , 1 , 1 3 . 4 .
The wavelet is divided into two categories: continuous and discrete, designate as a mathematical tool. In Continuous Wavelets Transform (CWT), the signal is multiplied by a function with the wavelet and the transform is calculated separately for different segments of the timedomain signal. The Discrete Wavelet Transform (DWT) also has the same main idea as the (CWT), however, it is developed mainly for the processing of sampled signals. In addition, DWT calculation is close to the idea of quick filter bench and it is easy to be implemented. Still this does not prevent the application of the continuous wavelet transform for analyzing the sampled signals [START_REF] Bouzida | Fault diagnosis in industrial induction machines through discrete wavelet transform[END_REF][START_REF] Kechida | Approach signal for rotor fault detection in induction motors[END_REF].

The decomposition of the signal in multi-resolution is obtained by filters of different cut-off frequencies; they are used to analyze the signal at different scales. The signal is passed both, through a series of high-pass filters H (details) to analyze the high frequencies, and through a series of low-pass filters L (approximations) to analyze the low frequencies as shown in Fig. 2, where it can see the detail and approximation signals reflect the time evolution of the associated frequency components of the original signal S i , which are contained within their associated frequency band [START_REF] Yahia | Induction motors airgap-eccentricity detection through the discrete wavelet transform of the apparent power signal under non-stationary operating conditions[END_REF].

For decomposition process by the wavelet at level n (Fig. 2), the decomposition level of the first signal contains two coefficients, where a 1 is the approximate version and d 1 is the detailed representation. These coefficients can be calculated by the following expressions:

⎧ ⎨ ⎩ = ∑ - = ∑ - a Lk nS k d H k nS k ( 2 ) ( ) ( 2 ) ( ) k n i k n i 1 1 (10)
The next decomposition level is based on the a 1 coefficient. Therefore, the new coefficients can be expressed as:

⎧ ⎨ ⎩ = ∑ - = ∑ - a Lk na k d H k na k ( 2 ) ( ) ( 2 ) ( ) k n k n 2 1 2 1 (11)
The computing of higher-level decompositions is done in a similar ways. After the decomposition process, the original signal S i can be reconstructed again [START_REF] Talhaoui | Mixed eccentricity fault diagnosis in the sensorless field oriented control induction motor using DWT technique[END_REF] as shown in Fig. 3. This recursive process is given by:

When the rotor bars fault appears in the IM, the wavelet can give information on the presence of the default. Whereas, the diagnosis is based on the observation and comparison between decomposition levels that contain the fault information. By calculating the associated eigenvalue with each level or each decomposition node, a highly efficient diagnostic tool can be constructed to evaluate the faults severity. The energy eigenvalue for each frequency band is defined by: [START_REF] Kapoor | Bearing fault analysis by signal energy calculation based signal processing technique in Squirrel Cage Induction Motor[END_REF]

∑ = = = E D n ( ) j k k n j k 1 , 2 (13)
With j is the decomposition level, n is the DWT decomposition time, and D is the magnitude at each discrete point of the wavelet coefficient of the signal in the corresponding frequency band.

The energy eigenvalues of signals decomposition levels contain information which can be used for diagnosis process and the identification of fault's degree in the IM. The deviation of certain value indicates the severity of the failure.

Simulation results

The FOC control of the IM with rotor bars fault is simulated by using Matlab/Simulink software. The used motor in the simulation section is a 1.1 kW three phases squirrel cage with 16 rotor bars. The IM characteristics are given in the appendix. The global vector controlled IM based on the reduced model in healthy and faulty states are shown in Fig. 4.

The results of the vector controlled IM are given for healthy and faulty machines. When the speed is variable, the fault detection is considered by DWT analysis of the rotor speed, stator phase current and the output signal of the speed regulator. The fault severity is evaluated by the calculation of the stored energy in each level of the stator phase current, output signal of the speed regulator, and the active power. The used sampling frequency for the simulation section is 10 kHz.

Healthy state of the IM

Fig. 5 shows the simulation results of the electrical and mechanical quantities of the IM in healthy state. The test of the FOC will be achieved when the speed changes (the speed reference varies between 101 and 99 rad/s (≅ 964.478 and 945.380 rpm)) with rated load application during the launch of the IM.

For the variable speed operation in healthy state of the machine (Fig. 5), the rotor speed shows a good reference following and an accurate tracking without a static error. The electromagnetic torque and the stator phase currents show fast and good dynamics. Also, the direct and quadratic currents components are presented as an image of the rotor flux and electromagnetic torque respectively. The rotor flux components preserve a perfect decoupling between flux axes. Thereby, the results validate the proposed scheme.

Faulty state of the IM

In order to highlight the effect and the fault severity of the FOC control when the speed varies continuously, the broken rotor bars fault is simulated by increasing the bar resistance given in Eq. ( 3). In this case, the IM operates with nominal load and fault at the start-up.

By examining the results in Fig. 6, the broken rotor bars fault effect doesn't appear in the rotor speed and electromagnetic torque, due to the regulation of current and speed in the closed-loop which hides and compensates it. In contrast with a small oscillation appears in the stator phase current I a , direct current I ds and quadratic current I qs respectively. However, the decoupling between the flux axes is preserved, therefore, it is noted that the FOC control is maintained robust vis-a-vis the fault.

Discrete wavelet analysis

To extract the fault components by using DWT, it's required to select the type of mother wavelet and the number of decomposition levels. The Daubechies-40 is used as the mother wavelet for the DWT analysis. The calculation of the decomposition level n depends on the sampling rate f sa and the frequency net f s . It can be obtained by using the following equation [START_REF] Kechida | fault detection of broken rotor bars using stator current spectrum for the direct torque control induction motor[END_REF]:

> + n f f log( / ) log(2) 1 sa s ( 14
)
where:

The sampling rate was 10000 Hz and the supply frequency is 17.887 Hz.

Table 1 shows the frequency band for each level. The rotor bars fault diagnosis based on spectrum analysis of sinusoidal current detects the sidebands harmonics around the fundamental supply frequency given by:

= ± f n s f (1 2. . ) rbb s ( 15
)
where:

f s is the frequency training of the machine, sis the slip and = n 1,2,3, .....

In the case of analyzing the non-sinusoidal (continuous) component, the harmonic frequency is given by:

= f n s f 2. . . rbb s ( 16
)
Table 2 shows the calculation frequencies of the broken rotor bars fault in simulation results of the stator phase current spectrums and the A medium speed value is considered in order to determine the medium slip and localize approximately the bands of the fault frequency. The application of the wavelet analysis permits to evaluate the fault when the speed is continually variable.

In Fig. 7, the DWT analysis of electrical and mechanical quantities are represented, where the same levels of decompositions (the a 10 , d 10 , d 9 and d 8 signals) are accounted in both results. The rotor bars fault identification in the rotor speed spectrum is very delicate due to the PI controller which maintains the regulation of the speed and corrects the fault influence. However, the analysis of the stator phase current shows a particular low variation at the d 10 , d 9 and d 8 levels due to the fault, since they contain the frequency components f rbb = (1 ± 2.n.s)f s (Tables 1 and2) compared to the healthy state of IM (Fig. 7a). Furthermore, the approximation a 10 and the detailed d 10 coefficients of the output signal of the speed regulator can be used for the fault detection, and it is manifested by oscillation which varies with the evolution of the frequency (Table 1 andTable 2).

The conspicuous problem for the fault diagnosis is when the rotor speed/reference changes continuously. Therefore, an important difference between signals level cannot be found in wavelet decomposition. The calculation of the stored energy in each level of signals is necessary in order to evaluate the severity of the fault.

Fig. 8 shows the simulation results of the stored energy for different levels of the stator phase current, the output signal of the speed regulator and the active power for healthy and faulty states of the machine.

When the fault occurs in the IM, the energy levels slightly increase in the stator phase current and the output signal of the speed regulator results (Fig. 8a andb), which fit the aforementioned characteristic. To overcome this problem, the calculation of the stored energy in each level of the active power is proposed in order to distinguish the fault effect. Therefore, it's remarked clearly in (Fig. 8c) that the active power signal's energy has increased by the fault. This result can be considered as an indicator of the rotor bars fault.

Experimental validation

The proposed control scheme with the diagnosis method will be verified also in experimental tests. The experimental results below illustrate the same conducted steps and tests as the simulation section. The same sampling frequency in the simulation tests is used for the realtime control; this value has been chosen with regard to the control scheme complexity. The experimental test bench has been realized in the laboratory of electrical engineering of Biskra (LGEB) from Algeria. The control algorithm is implemented using dSpace DS1104 R&D controller board with control desk and Matlab/Simulink software package. Fig. 9 shows the experimental ground of IM drive which is essentially composed of 1.1 kW squirrel-cages IM (healthy and faulty states) driven by a SEMIKRON converter that is composed of a rectifier and IGBT inverter. A magnetic powder brake is used as load is coupled to the rotor of IM, and an incremental encoder used as a speed sensor and as well as position sensor. The currents and voltages, respectively, are sensed by current (Hall-type) and voltage sensors. Then, an autotransformer (0-450V) linked to the grid is used for power supply. Fig. 10 shows the descriptive diagram of experimental setup and software/hardware linkage. The execution of the program inside the DSP of dS1104 board converts it into a real-time system on the hardware (dSpace 1104 RTI) after it was in the software (Simulink). In addition, the Control Desk visual interface gives us the access to adjust all Simulink variables in real-time in order to obtain a satisfied control behavior. The PWM switching sequences are calculated in Matlab/Simulink with a commutation frequency equal to 5 kHz, then, they are generated by an analog digital converter using dSpace interface board. In order to control the IGBT grid and increase noise immunity, the control signals are maintained in the analog format with (0-5 V) voltage, and they are offset from one another. The delivered dSpace output signals (PWM) will be amplified to (0-15 V) by an adaptation carte which was carried out in the laboratory (Fig. 11). A supply voltage of (400 V) is filtered through the rectifier in order to fix the DC-bus of the converter. After that, the dS1104 receives another time the input signals by currents sensor from (ADC) ports and speed from encoder through (INC) ports. Finally, the IM has been controlled via Control Desk, where the results were obtained by a numerical oscilloscope (GW-INSTEK) which was plugged with the real-time interface through (DAC) ports.

Remark 1. The used induction machines in the experimental implementation have different characteristics with the used machine in simulation section, but they preserve the same power (1,1 kW). The reduced rotor cage model identification is more complex than the classical model and requires specified information about machine geometry in which, unfortunately, they can be offered only by the constructor; for this reason, we have used in this work another machine with an equivalent characteristic. It can be confirmed that this mismatch between two machines didn't confuse the studied phenomena which already have been analyzed by simulation tests.

1 Healthy state of the IM

The figures below show the experimental results of the vector controlled IM in healthy state. Several electrical and mechanical quantities of the IM at measured time of 10s with zoom effected at 1s are presented, in order to compare with simulation results. Fig. 12 illustrates the experimental results of the FOC control of the IM in healthy state, the load is applied at start-up. It is noted that the rotor speed response presents a full superposition without overshoot (1div = 500 rpm). This indicates to the good tracking as observed in ZOOM of rotor speed. The electromagnetic torque (1div = 5 N m) shows fast dynamic. The waveform of the stator phase currents is correctly sinusoidal (1div = 5 A). The direct current component (1div = 5A) is stabilized in the rated value, while the quadratic current component (1div = 5A) follows perfectly the torque evolution. The rotor flux components (1div = 0.5 Wb) show a good orientation with a perfect decoupling.

2 Faulty state of the IM

In experimental tests, the broken rotor bars fault has been realized by drilling a small hole of 3.1 mm diameter in all the rotor bar depth as shown in Fig. 13.

The FOC is carried out in faulty state of the operating machine with variable reference speed of 101 to 99 rad/s (≅ 964.478 to 945.380 rpm) and the load is applied at the start-up.

The analysis of the obtained results in faulty state (Fig. 14) by comparison to the healthy state (Fig. 12), shows that the rotor speed and electromagnetic torque are not affected by the broken rotor bars fault owing to closed-loop control. However, the amplitude of stator phase current isn't constant; a perturbation provoked by the fault is observed in the direct and quadratic current components.

Briefly, the experimental and the simulation results give the same phenomena in the faulty state of the machine when the speed varies continuously.

3 DWT signals analysis

The DWT has been used also for the rotor bars fault diagnosis of the IM in experimental tests. The decomposition levels n will be calculated by using Eq. ( 13), where, the sampling rate was 10000 Hz and the supply frequency is 36.042 Hz in the real-time implementation. 4 illustrates the calculation frequencies of the rotor bars fault in experimental results of the stator phase current aw well as in the output signal of the speed regulator.

Fig. 15 shows the DWT analysis in experimental results of the rotor speed, the stator phase current, and the output signal of the speed regulator in healthy and faulty states of the IM. The rotor speed analysis using DWT is very difficult to distinguish between the fault and the healthy state, since the same signal has appeared in the a 9 level. As we have mentioned before, the control-loop masks and compensates the fault effect. For this reason, the analysis of the output signal of the speed regulator is proposed to solve this problem.

However, the comparison between the results of DWT analysis of stator phase current and the output signal of the speed regulator in healthy state (Fig. 15a) and faulty state (Fig. 15b) can be summarized in the following points: ➢ An oscillation and small variation is shown in both results, ➢ The amplitude coefficient levels a 9 , d 9 , d 8 and d 7 for the stator current and a 9 , d 9 for the output signal of the speed regulator are increased. The DWT analysis obtained for the experimental results are similar with the simulation results. The direct analysis obtained by DWT is very difficult to view the severity of the fault in signals level. For this, the energy stored in each level of DWT is necessary (Fig. 16).

Fig. 16 shows the stored energy value for the experimental results of the stator phase current, the output signal of the speed regulator, and the active power respectively. In comparison to the faulty and the healthy states of the machine, a small increase of the energy value is observed for the stator current (Fig. 16a) and the output signal of the speed regulator (Fig. 16b). Contrariwise, a considerable increase of the proposed energy for the active power (Fig. 16c), this result can be used as a good indicator for the fault detection and for the fault severity.

Conclusion

In variable speed drives, the fault detection and diagnosis are very delicate. For this issue, a simulation and an experimental study are considered for the machine in closed-loop drives using a FOC technique. A reduced model for the rotor cage, with taking into account the rotor bars fault of the IM, has been used for the control design. The vector control is introduced as IM variable speed drive, particularly, when the speed varies continuously and the machine operates with rotor bars fault. The obtained simulation and experimental results give a high robustness against the fault effect and a good control performance like an accurate reference tracking and fast response.

For the diagnosis purpose, the DWT has been employed to analyze several electrical and mechanical control quantities when the machine operates with continuously variable speed.

The DWT analysis of the stator phase current and the output signal of the speed regulator don't show clearly the fault effect. The calculation of the stored energy in each decomposition levels gives information about the broken rotor bars fault, particularly for the active power energy. This information can be used for the determination and the severity of the fault when the machine operates with variable speed. The result is evaluated in simulation and confirmed by the experimental results.

Nomenclature

Fig. 1 .

 1 Fig. 1. Rotor cage equivalent circuit of induction machine.

Fig. 2 .

 2 Fig. 2. DWT decomposition process at level n.

Fig. 3 .Fig. 4 .

 34 Fig. 3. Multi-level decomposition n.

  By applying the field orientation, the current components become:

Fig. 5 .

 5 Fig. 5. Electrical and mechanical characteristic of the vector controlled IM in healthy state.

4 .

 4 Fault diagnosis of IM using discrete wavelet transform (DWT)

Fig. 6 .

 6 Fig. 6. Electrical and mechanical characteristic of the vector controlled IM in faulty state.

Fig. 7 .

 7 Fig. 7. DWT of the rotor speed, the stator phase current and the output signal of the speed regulator.

Fig. 8 .

 8 Fig. 8. Energy value in the simulation results for various levels (a) stator phase current, (b) output signal of the speed regulator and (c) active power.

Fig. 9 .

 9 Fig. 9. Experimental test bench.

Fig. 10 .

 10 Fig. 10. Descriptive block diagram of the dSpace based experimental setup.

Fig. 11 .

 11 Fig. 11. PWM control signals.

Fig. 12 .

 12 Fig. 12. Electrical mechanical characteristic of the vector controlled IM in healthy state.

Fig. 13 .

 13 Fig. 13. Broken rotor bar of induction motor.

Fig. 14 .

 14 Fig. 14. Electrical and mechanical characteristic of the vector controlled IM in faulty state.

Fig. 15 .

 15 Fig. 15. DWT of the rotor speed, the stator phase current and the output signal of the speed regulator.

  interface Vdc Direct voltage V a , V b , V c Three phases reference voltages a, b, c S a , S b , S c Switching states of the inverter a, b, c V dsref , V qsref (d,q) axis reference voltages of the stator I a , I b , I c Three phases currents a, b, c of the stator I ds , I qs (d,q) axis current components of the stator

Fig. 16 .

 16 Fig. 16. Energy value for various levels:(a) Stator phase current, (b) Output signal of the speed regulator and (c) Active power.

Table 1

 1 Frequency Levels of Wavelet Coefficients in simulation tests.

	Level	Frequency band
	d 1	2500-5000 Hz
	d 2	1250-2500 Hz
	d 3	625-1250 Hz
	d 4	312.5-625 Hz
	d 5	156.25-312.5 Hz
	d 6	78.12-156.25 Hz
	d 7	39.06-78.12 Hz
	d 8	19.53-39.06 Hz
	d 9	9.76-19.53 Hz
	d 10	4.88-9.76 Hz
	a 10	0-4.88 Hz

phenomena like the IM operates in the closed-loop drive with speed variation.

Table 2

 2 Frequencies of the stator current and the output signal of the speed regulator with fault in simulation tests.stator phase current I a spectrum quadratic current I qs spectrum

	= s 0.1145	(1-2s)f s	(1-4s)f s	(1+2s)f s	(1+4s)f s	= s 0.1145	2sf	4sf
	f calculated (Hz)	13.790	9.694	21.983	26.079	f calculated (Hz)	4.096	8.192

Table 3

 3 Frequency Levels of Wavelet Coefficients in experimental tests.

	Level	Frequency band
	d 1	2500-5000 Hz
	d 2	1250-2500 Hz
	d 3	625-1250 Hz
	d 4	312.5-625 Hz
	d 5	156.25-312.5 Hz
	d 6	78.12-156.25 Hz
	d 7	39.06-78.12 Hz
	d 8	19.53-39.06 Hz
	d 9	9.76-19.53 Hz
	a 9	0-9.76 Hz

Table 3

 3 presents the frequency band for each decomposition level. Table

Table 4

 4 Frequencies of the stator current and the output signal of the speed regulator with fault in experimental tests.

	stator phase current I a spectrum

Ie

Short circuit ring current [I] Current vector [L] Inductance matrix [R] Resistance matrix [