Longqin Xu

Shuangyin Liu

Daoliang Li

Key Technology of South Sea Pearl Industry Management Information Service Platform Based on the Internet of Things

Keywords: Internet of things, Pearl industry, WSN, RFID, EPC, PML, Cloud computing platform Introductions

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all levels governments, pearl industry in Zhanjiang has been rapidly developed in recent years. However, in the huge production and consumption of the pearl industry, there are still problems [START_REF] Zhang | Economical analysis of dilemma of chinese pearl industry and outlet[END_REF][START_REF] Yi | Development strategies of "south pearl" industry in Zhanjiang[END_REF] as follows: 1) The model of current Sea water pearl farming descended traditionally, which consumes a lot of resources and extensively cultivated. New products and technologies cannot be fast promoted, which produces low value-added products; 2) Low level of information collection and control in sea water pearl process of production and in short of water management system for the whole process of pearl production, thus resulted in low level of industrialization; 3) With substandard and unreasonable feeding, spraying, fertilizing, resulted in higher cost as well as risks of investment for formers; 4) Over farming with high-density caused environmental pollution and deterioration of sea water as well. The experience is far enough to clearly get to know the pearl growth environment, which is impossibly assisted by current techniques and disease resistant warning mechanism of sea water pearl poorly works; 5) Lacking of information, irrational expansion of the scale, and unsmooth channel in sales and cyclical fluctuations in market conditions, which hurt the enthusiasm of farmers; 6) without a set of pearl industrial management system to cover the whole process of production, the current information systems in this field is only suits for a single enterprise system and a single custom developed, which resulted in diversified description of pear introduction and the waste of resources and the development of modern management is blocked. In this paper, for the existing problems in the management of the whole process of sea water pearl production in Guangdong areas, we has built the pearl industrial management information services platform based on the Internet of Things which combines pearl cultivation and processing techniques, networking technology and intelligent information processing technologies, to achieve the automatic production process control product traceability and scientific management of sea water pearls. Then high yield, efficient, safe, and healthy farming and sustainable development water pearl could be possible. The research on morphological characteristics of corn seed had got good identification results while much less study of corn purity identification and much more application about corn side features. This paper proposed that the color features of crown core area had significant function on corn purity after the study on three commonly used maize varieties. The DBSCAN was optimized by farthest first traversal algorithm for the purity identification. The experimental result indicated this method had high classification rate and the higher precision and offered a reference for building accurate purity identification system.

Internet of things and working principle 1.The concept of Internet of things

Internet of things is a network which combines information sensing devices such as the smart sensors, radio frequency identification (RFID), laser scanners, global positioning system (GPS), in accordance with the agreed protocol, to connect Internet with anything, to exchange information and communication in order to achieve intelligent identification, positioning, tracking, monitoring and management [START_REF] Wen | 2010 the government work report[END_REF][START_REF] Sun | Internet of things: summarize on concepts, architecture and key technology problem[END_REF] .

Internet of things in the current development home and abroad

Currently, in Japan, the United States, South Korea, EU and other countries corresponding policy has been introduced in support of the development of internet of things, and has made a lot of basic research and application development.

In the United States and Europe, internet of things have greatly developed in intelligent power, intelligent home, intelligent transportation, intelligent logistics, ecological monitoring, e-health and other fields [START_REF]Commission of the European communities[END_REF] . IBM proposed the concept that "wisdom of the Earth, internet of things and cloud computing" which leads the new round of IT technology revolution in 2009 [START_REF]South Korea plans to 2012 networking infrastructure building internet of things[END_REF] . The starting and development in internet of things in our country has not lagged behind other countries, and a long-term planning "next-generation broadband mobile wireless communications network" has been made, which specially focuses on the research and development of "sensor and its network." Premier Wen Jiabao proposed "Feel China" when visiting Wuxi on August 7, 2009. The concept of internet of things in China has attached great importance and become a new wave core areas after the computer, Internet, mobile communications information industry. Some provinces have a large number of domestic uses of sensor networks to solve the power, agriculture, fisheries and transport in the "M2M" and other information and communication services [START_REF]Commission of the European communities[END_REF][START_REF]South Korea plans to 2012 networking infrastructure building internet of things[END_REF][START_REF]European Research Projects on the Internet of Things (CERP-IoT) Strategic Research Agenda(SRA).Internet of things-strategic research roadmap[END_REF][START_REF] Zhu | The Design of the Remote Water Quality Monitoring System based on WSN[END_REF] . In the future things will not only penetrate into the smart city, smart transportation, smart homes, public safety, environmental protection and other fields, but also greatly promote the economic development, which is seen as a new emerging industries.

Workflow of internet of things

The basic work flow of internet of things is composed by the entity markup language Information Server (Physical Markup Language Information Server, PML-IS), information collection system, the object name server (Object Name Service, ONS) and information management system [START_REF]Commission of the European communities[END_REF] . The function of each is as follows: 1) Information collection system. The system includes wireless water sensors, weather sensors, RFID tags, wireless sensor network (WSN), readers (reader)\GPRS wireless communication, data exchanging, monitoring and management software, mainly to complete the collection of the water environmental factors, transmission and storage, in order to achieve automatic information collection for farming environment. The information is transferred by wireless sensors and GPRS connection to the central server which handles the processor installed in information processing software, such as the collected data conversion, analysis, comb, integrity checking, data recovery and other operations, the processed data to the appropriate database management software for individual use.

2) The object name server (Object Name Service, ONS) [START_REF]Commission of the European communities[END_REF] . The ONS server main function is achieving correlation between the various sensor points and PML-IS server and established the maps with ecological information on pearl breeding, pearl Electronic Product Code EPC tag and the PML description of pearl product.

3) Physical Markup Language Information Server, PML-IS. [START_REF]Commission of the European communities[END_REF] . The user can first create and maintain data, define the rules, and then the user can product a code in accordance with predetermined rules of pearl, and then use the XML information on the items described in detail in order to facilitate access to other servers. 4) Information management system. The system with the help of hardware and software to obtain environment, processing and production management information in the whole process of pearl production management, products information is provided through the mapping between the object name server information and the PML-IS server retrieving the detailed description about the product in the PML-IS Information Server for pearl farmers and consumers, such as information search, product traceability and other functions in the form of the Web, also users can master all process of pearl production status by phone or wireless PDA.

The application model of internet of things in the pearl industry management network information service platform

The application of the internet of things in pearl industrial management information service platform, whose advantage has been taken to reach seamless in monitoring and management containing sea water pearl production, processing and product traceability. The diagram is shown in Figure 1. As shows in Figure 1, Internet of things has achieved environment information collection, pearl product identification and monitoring by smart sensors and RFID and completed the mapping among pearl environmental information, the Electronic Product Code EPC tags and the PML-IS server by The ONS server which has achieved correlation between the various sensor points and PML-IS server in the processing of products such as the nursery, nucleus inserted, rest, picking. All information can be optimized through the pearl industrial information service platform transferred by a wireless or wired network. That can make the existing internal management system to be compatible with the maximum and became integral part of internet of things. RFID, WSN and electronic product code (EPC) are integral essential factors in the pearl industry. It will effectively monitor and convert data each other in all aspects of the process in sea water pearls farming, product processing and product distribution, to establish a landmark product and quality of traceability; the standardization and unified of data collection, transmission and seamless in sectors of production in the pearl industry will also be achieved.

E P C
2 Pearl industrial management information service platform

System Goals

For the realization of intelligent processing and digitization process in south sea pearl production, the pearl industrial management information service platform has been established with key technology of the Internet of Things, artificial intelligence and expert systems theory and computer-assisted decision-making strategies development.

On this account, it will improve the standard of management and production process of water pearl enterprises and farming on the level of pearl, thus the intensive pearl industry development and scientific management is secured.

System Architecture Design

The system is divided into data acquisition layer, transport layer, data servers, business logic (functional layer) and the presentation layer with the use of the N-tier B/S structure mode; Development platform uses NET Framework which effectively reduces the system client requirements, and the distribution of the client applications and version control problems will be avoided. System architecture is shown in Figure 2.

In architecture, the presentation layer has completed the function of interface interaction with the end-user, and the applications layer has .aspx page and related code; Business logic layer is used to encapsulate business rules and business logic, which is packaged as. NET components in the application layer. Data server layer has adopted the layer style persistence (CMP) design pattern with container, in which pattern the business object data does not consider where the original data is from and how to store it, as long as the data access components interact with data server (or servers ), all data is manipulated through stored procedures.

Real time information processing and information management

System features module design

According to actual needs of the majority of pearl farmers and management staff of enterprises and institutions, in addition to problems of existing software systems are badly in need of upgrading, as well as independence of pearl farming industry model and complexity of culturing in the process of breeding, feeding, disease prevention and control management, such as insertion of nuclear, fishery drugs, disinfection, rest, oxygen, microscopic examination, testing, painting, drilling, water quality control and so on, these large number of knowledge is classified through theoretical guidance such as information intelligent perception, artificial intelligence, expert systems and knowledge engineering, to sort out their internal relations, and optimize the combination of knowledge based on expression of a variety of methods. With research of the knowledge of high effective south sea pearl production model to built pearl databases, production and processing information database, disease diagnosis prevention and treatment knowledge database, then shared south sea pearl management information service platform is set up and rebuilt for the pearl industry to provide assisted strategic supplementary decision for south sea pearl enterprises and units.

The functions of this platform includes: environmental data collection and management, prediction and warning, water quality control management, production management, quality and traceability management, expert systems, supply and demand information, farming techniques information, processing technology information, technical services, expert consultation, decision analysis, system maintenance. So users can easily use this system in multi-angle multi-channel. The system function structure is shown in Fig. 3 Through the pearl industrial management information services platform, pearl farming information services in prenatal and postnatal and science information, aquaculture management and remote intelligent decision-making services in products are provided; effectively achieve a smooth channel for the transformation of pearl culture technology, significantly enhance the quality of sea water pearls, greatly improve production and promote sea water pearl industry's enthusiasm for aquaculture and create the northern Gulf region "pearl" industry. While the research institutes of the new technology, new achievements and new products in the marine pearl culture in the promotion of the use can increase the stocking density, shorten the breeding cycle, reduce farming risk, reduce production costs and improve the level of aquaculture technology and quality control, reduce labor intensity, expand production scale, advance the automation of production management, putting forward pearl culture toward equipment engineering, digital culture, information-oriented, which has great scientific significance and practical value in the healthy development of pearl industry.

Analysis of key technology and its applications in internet of things 3.1 Wireless sensor network (WSN)

WSN is the key information technology in the pearl culture industry, the management environment monitoring and collection, which use wireless sensor node (Node) to collect and perceive farming environment information, and timely send or receive information with aggregation node (Sink). [START_REF] Zhu | The Design of the Remote Water Quality Monitoring System based on WSN[END_REF] Connected the DNS cloud server, on-site monitoring center with aggregation node (Sink) of wireless sensor network through the RS-232 serial cable or GPRS , forming on-site real-time information collection system(Figure 4) While monitoring seawater pearl environmental information on-site with the wireless sensor networks, we deploy a certain number randomly sensor information collection nodes in the pearl farming region, each node can form wireless sensor network by self-organizing. The data monitored by sensor nodes can be transmitted and processed through multi-hop route between other sensor node and the sink node (base station) [10], and then transmitted via the GPRS or Internet monitoring center to the scene, server or terminal device. The pearl industrial management information service platform based on internet of things is in use of the wireless sensor nodes which have integrated solar panels, lowpower and the 433MHz communication frequency based on the thought that pearl farms has larger areas for information collection, so nodes is distributed, and cable power supply is not convenient and monitoring and collection for eco-environmental factors and other characteristics is dynamic. Communication distance between nodes is 500m, and communication speed can reach 76.8kbps, thus achieve the real-time dynamic acquisition and transmission for water quality and climate pearl farming environment factors.

Wireless water quality data acquisition node

RFID

RFID is encoding vector in the process of pearl production, processing and product distribution, which transform environment information collected by the WSN, production, processing chain to the corresponding coding and record in the RFID chip, the application model is shown in Figure 5. RFID tags of pearl products are scanned by the sensor, then the code analysis is transmitted to the local coding system for data processing; ONS is responsible for queries and mapping management with processing Electronic Product Code EPC and the corresponding PML-IS server address; Information through the network will be transferred to DNS cloud computing services platform for the information management with other aspects of pearl culture [11] . RFID has the advantages of automatic sensing, transmission information content, Mass and dynamic storage, and can record with multi-dimensional pearl industryrelated information; also coding hidden to prevent malicious copy, safe and reliable without human intervention and so on.

Electronic product code (EPC)

EPC code (electronic product code) is the Auto-ID Center which is assigned to each physical target with only sign of the query code, it includes a string information on behalf of pearl and production categories and its ID, the date of the various stages of cultivation, production dates of purchase, production date, manufacturer, expiration date, pearl processing date [START_REF] Li | Zhu.Research on middleware of EPC system[END_REF] . Meanwhile, with the whole process of pearl farming in the various aspects of changing, the production management data can be updated in real time. Typically, EPC code can be made of silicon into electronic tag and attached to kernel of pearl to be identified, transferred and checked by information-processing software. When the pearl products through the data collection authorized points, it is not only correctly read the code of the unique pearl products but also read out of production with other inter-relate through the ONS system and PML system, so as to achieve the seamless of all aspects and improve management efficiency pearl industry. Pearl industry standard EPC code and coding rules need to be encoded by the national standards and industry research institutions and departments jointly developed, comprehensive, unambiguous, practical, scalable and open, etc., are common pearl culture industry compliance with coding standards and rules, which can effectively eliminate all aspects of pearl production and processing of fault information management, enhance the management efficiency of pearl farming.

PML entity's markup language

PML is a standardized language, which helps user to define rules and maintain the data, can be coded with information about the name of pearl products, categories, attributes of the breeding, production and processing status, production and other aspects of information according to the rules in advance and use XML to descript the product information [START_REF] He | The Key Technologies of IOT with Development & Applications[END_REF][START_REF] Tim | Transforming agriculture through pervasive wireless sensor networks[END_REF][15] . It solves problem of the limited capacity of electronic tag storage without saving a lot of physical information. Concerning the Internet of Things, PML server is mainly used to provide a common mode of the original information items defined in the rules, to facilitate the access to other servers.

Technology Integration

According to the demand of south sea pearl industry management and technique expansion, integrated technology services concept is adopted, sensor networks, distributed technology, artificial intelligence, forecasting and decision-making, gray theory, artificial neural networks, hybrid intelligent diagnostic reasoning, fuzzy reasoning, database technology, MIS Technology, Rich Internet, WebGIS technology and disaster monitoring and early warning technology etc. is integrated. This platform with integrated hardware and software, large-grained, loosely coupled, dynamic binding characteristics, overcomes differences in shielding characteristics of a heterogeneous network. Pearl industry management information service platform that contains pearl and pearl products processing and marketing enterprise business applications, including local, covering pearl breeding, processing, distribution and the whole process, before, during and post-natal and other various links on the River platform, according to a unified transport protocol, EPC encoding, ONS system via a wired or wireless networks, relying on the local computing and cloud computing to support distributed on the basis of the built; pearl cultivation and processing in accordance with the upper, middle and lower reaches various aspects of water quality and meteorological sensors transfer the state property, state property of production, processing, deployment of personnel, operating environment, complete the quantity, quality control and direction of information flow and feedback intelligent deployment, from "farm to the sales counter." The seamless link for the pearl quality control, production information management, creating brand offers reliable protection.

Conclusions

We explore the technology of on internet of things in the pearl industrial management information services application platform focusing on the current pearl industrial management problems. It combines the Internet with pearl industry, and restricts the Pearl environmental information, various aspects of production factors, product processing and marketing of pearl. It has become a modern information technology to drive the fisheries modernization. Considering characteristics of cultured pearl industry and culture of enterprise information progress, the application of things is not so easily to realize, it is the integration of multiple technologies and integration of multiple applications in a systematic works, some key technology such as transfer protocol, integrated and embedded technology and information security and so on still need further improvement. In the future, the gradual integration of networking technology into pearl culture industry management will push forward the healthy and sustainable aquaculture industry development.

Fig. 1 .

 1 Fig. 1. Internet of things based pearl industrial information service platform structure diagram

Fig. 2 .

 2 Fig. 2. Architecture diagram of Internet of things based pearl industrial information service platform

Fig. 3 .

 3 Fig. 3. Function structure of management information service platform based on Internet of things

Fig. 4 .

 4 Fig.4. Application of WSN technology in pearl industry management

Fig. 5 .

 5 Fig.5. RFID application model

  :

					Pearl industry management information service platform
	Ecological environmental data acquisition management	Water quality control management	Product data management	Trade leads	Pearl expert system	R e a r i n g technique	Technical service	Decision analysis	System maintenance management
	Predict early warning management	Product data management	Quality tracking management	Scientific breeding	disease diagnosis	Economic Analysis	Process technology	Consultations

Acknowledgements

This research is financially supported by the China Spark Program Project (2007EA780068), Guangdong Science And Technology Program Project (2010B020315025) and Zhanjiang Science And Technology Program Project (2010C3113011).


Xingye Zhang

Jianqin Wang

Jianye Cui

Jie Zheng

Jing Pan

Manlin Chen

Design of Distributed Traceability System for Wheat Products Quality

Keywords: wheat products traceability system, EPC coding scheme, ONS

The circulation of wheat products involves a number of different types of food-related enterprises, including planting bases, grain trading companies, warehousing enterprises, food processing plants, sales companies and so on. The centralized traceability architecture cannot meet the requirements such as transaction data security. While, the distributed traceability architecture faces the difficulty and complexity of information processing for the traceability data stored and managed by different enterprises. In order to meet the requirements imposed on distributed data management and diversity of deployment requirements, an EPC (Electronic Product Code) coding scheme is proposed, in addition, based on which we design and implement a distributed wheat products quality traceability system in this paper. The test indicates that the distributed quality traceability system can track the wheat products quality information in the whole supply chain of wheat products effectively.

Introduction

China's wheat production and consumption is huge. Wheat products safety is a serious matter for consumers as well as for companies involved in the food chain. Because of the complexity and diversity of the wheat products circulation chain, it is extremely difficult to track the details of the wheat products information in each circulating step. Hence, it is urgent for business to build a traceability system for wheat products supply chain which is suitable to China's situation. EPC (Electronic Product Code) is designed to give each product a unique identification number in order to effectively improve supply chain management. It can be used to track the movement of physical products throughout an entire supply network based on RFID (Radio-Frequency Identification) technology and the associated computer networks [START_REF] Barchetti | RFID, EPC and B2B convergence towards an item-level traceability in the pharmaceutical supply chain[END_REF]. RFID is a non-contact and multi-objective automatic identification technology, widely used in traceability from farm to consumer [START_REF] Zangroniz | RFIDbased traceability system for architectural concrete[END_REF]. The EPCIS (EPC Information Service) provides storage and query services for the EPC-related data of physical products, using EPC as index key [START_REF] Tribowski | EPCIS-Based Supply Chain Event Management: A Quantitative Comparison of Candidate System Architectures:International Conference on Complex, Intelligent and Software Intensive Systems[END_REF]. ONS (Object Name Service) is a global query service, using the existing DNS (Domain Name System), used to help to locate the EPCIS when retrieving the EPCrelated information from EPCIS which are hosted at each supply chain participant through the traceability system, by converting the EPC to a URL (Universal Resource Locater) [START_REF]Object Naming Service (ONS) Version 1.0[END_REF]. Up to now, many traceability systems have been proposed based on EPC and RFID, such as aquatic product traceability system [START_REF] Zhiqiang | An aquatic product traceability system based on RFID technology[END_REF], meat product traceability system [START_REF] Ren | Research on RFID-based meat product track and traceability system[END_REF], agricultural products traceability system [START_REF] Li | Design and implementation of traceability information system for agriculture product quality:2010 2nd International Conference on Advanced Computer Control (ICACC)[END_REF], cattle breeding traceability system [START_REF] Zaiqiong | A RFID-based traceability system for cattle breeding in China:2010 International Conference on Computer Application and System Modeling (ICCASM)[END_REF].

Bello proposed a general model of traceability system in the field of food manufacturing chain [START_REF] Bello | A general approach to model traceability systems in food manufacturing chains:10[END_REF]. However, most of the existing traceability systems are owned by one or several enterprises and require a central server to store the trace information in the whole supply chain. Considering the diversity and complexity of the wheat products supply chain and the granular or powdered property of the wheat products itself, we develop a distributed traceability system for wheat products to meet the requirements imposed on distributed EPC-related data management and diversity of deployment requirements. With the help of ONS, each EPCIS server can exchange data of the products details, so as to track the wheat products quality information in the whole supply chain of wheat products effectively.

Wheat Products Supply Chain Model

Taking into account the reality in China, the wheat products supply chain is illustrated by Figure 1. The circulation includes wheat production, wheat trade and processing and wheat products sales. The wheat may come from an individual farmer or a planting base. Before sales company, the wheat or wheat products may go pass several grain trading companies, warehousing enterprises and food processing plants. Similarly, the wheat products may go pass several sales companies before a certain consumer. In each transaction, an EPC is generated for a batch of wheat products and the detail information of the products is stored and associated with it as well as in every process inside these enterprises. For a certain batch of wheat products, its raw materials may come from several enterprises. We show a batch of flour chain as an example represented in Figure 2. In this case, food processing plant F which produces the batch of flour, buys the raw materials (wheat) from warehousing enterprise D and warehousing enterprise E. The batch of raw materials from warehousing enterprise D comes from farmer G and planting base B. Besides, the batch of raw materials from warehousing enterprise E comes from grain trading company C and grain trading company C buy it from planting base A. And, the batch of flour is sold to food processing plant H. In order to trace out all the supply chain nodes and the detail information of the wheat products, each business entity in the wheat products supply chain should record the necessary information related to quality and security and so on, which provides the basis for the traceability system.

(1) Each business entity should record the production data for each batch of wheat products. For example, planting base and farmer should record the seed information and the details of the use of chemical fertilizers and pesticides, warehousing enterprise should record the rate of mildew, food processing plant should record the rate of water and so on.

(2) Each business entity should record the information of the flow of products. For a certain batch of wheat products, the information of the correspondence between container or vehicle and itself, the details about where it comes from and where it goes to, the details of the raw materials and so on should be recorded.

(3) Each business entity should generate a unique serial number for each batch of wheat products within it. All the information related to the batch of wheat products should be established links with the unique number. The unique serial number can be an EPC. When a transaction occurs, an EPC should be generated and the EPC is associated with all the related information of the certain batch of wheat products. The EPC will be used to trace the records of all the movements within the supply chain.

Wheat Products Distributed Traceability System Architecture

The wheat products supply chain in China is complicated and diverse. Not every business entity has ability to maintain a traceability system service. However, in order to trace the whole information of the supply chain, all the business entities in the supply chain should have the ability to use the traceability system. Taking into consideration the factors such as the diversity and complexity of the wheat products supply chain and the granular or powdered property of the wheat products, we design a distributed traceability system for wheat products to meet the requirements imposed on distributed EPC-related data management and diversity of deployment requirements. The architecture of the distributed traceability system is represented in Figure 3.

ONS

Fig. 3. Architecture of distributed traceability system

As is shown in Figure 3, this distributed traceability system is divided into two levels. The platforms in level 1 form the backbone of the system, while the platforms in level 2 are essential parts of the whole system. In this distributed traceability system, each business entity in the wheat products supply chain has its own company prefix in EPC, while not every business entity has its own EPCIS servers. The business entity in level 1 must has an EPCIS server and has got its own company prefix from the registration center. In other words, if a business entity owns an EPCIS server and has got its own company prefix from the registration center, its EPCIS server is a member of platforms in level 1. The business entity in level 2 has to register its own company prefix in the entity which is in level 1 and it can store its EPC-related data in its own EPCIS server as well as in the EPCIS server in level 1 which is owned by the business entity who gives the company prefix to it. On the condition that the EPC-related data is stored in the servers in level 2,the parent server in level 1 serves as a proxy when Design of Distributed Traceability System for Wheat Products Quality 5 data query occurs which will transmit the requests from the servers in level 2 to other servers and send back the responses as well.

The EPCIS servers in this system are independent, equal in status with each other and connect with each other through the ONS. Each EPCIS server has complete software system to support the storage and query service, including middleware software, business support system, web services system, the local ONS service system and so on. Each local client needs to equip RFID Reader & Writer, middleware system in order to read data from and write data to RFID tags.

EPC Coding Scheme for Distributed Traceability System

EPC coding is a coding standard which is compatible with EAN/UCC coding system. EPC is a unique number used to identify a specific item in the supply chain. The general structure of EPC consisting of a fixed length (8-bits) header followed by a series of numeric fields whose overall length, structure, and function are completely determined by the header value [START_REF] Zhang | Automatic Identify Technology[END_REF]. EPC can indicate different type of encoding, such as SGTIN, SSCC, SGLN, GRAI, GIAI, and so on.

Considering the various coding schemes, we choose SGTIN-96 to identify a batch of wheat products. SGTIN (Serialized Global Trade Identification Number) is a kind of new coding schemes, based on GTIN (Global Trade Item Number) which from the general specification EAN/UCC. A single GTIN can only mark a particular object class, not to identify a specific physical object. In order to give a single object a unique symbol, a serial number is appended to GTIN. GTIN and the unique serial number are called serial GTIN (SGTIN) [START_REF]Study on Traceability Coding of Wheat Quality and Distributed Object Name Service[END_REF]. SGTIN-96 has ninety six bits, and consists of six fields: header, filter value, partition, company prefix, item reference and serial number. Each SGTIN shares the same Header 00110000 [START_REF][END_REF]. The filter value is used to distinguish the business type of the enterprise and the partition number is used to define the count of bits that the item reference and the company prefix can take up. The company prefix is used to distinguish business entities. Each business entity must register its own company prefix in the registration center and it can assign the item reference and serial number by itself. For example, after a planting base gets its company prefix, it can assign four decimal digits (fourteen bits) in the item reference to their subsidiaries to identify them as is shown in Table 1.

Details of Distributed Traceability System Process

Data Flow Within A Business Entity

When a bath of wheat products is passing through a RFID reader equipped on one place or a transaction occurs or some information which needs to be recorded of a batch of wheat products is generated, a series of automatic or manual operations will be done to handle and store the information. The general data flow within a business entity is represented in Figure 4.

As is shown in Figure 4, EPCIS is the core node for the data flow within a business entity. Several signals such as an EPC number from a RFID reader, a query message from the business system will trigger a data flow. For example, when a bath of wheat products is passing through a RFID reader equipped on a gateway of a warehouse, the RFID reader will read all the RFID tags adhere to containers and vehicles and all the data from the reader will be transferred to a savant, then a report about the data from the savant will be "pushed" to EPCIS. After that, EPCIS will store the data and invoke the business system to deal with the data, then a set of data from the business system will be returned to EPCIS and EPCIS will store the set of data. Besides, when the business system handles the data, it may call EPCIS to do other things.

Data Flow Between EPCIS Servers

To track a supply chain, a series of data will be exchanged between EPCIS servers. The communication between any two EPCIS servers is private and they should agree on communication protocols and data formats before they exchange private data. In general, two EPCIS servers exchange data via the Internet and using HTTP or HTTPS provided by web services. For each EPC query, an EPCIS server will answer a series of record related to the EPC, including rate of mildew, rate of water and so on. Sometimes the server also answers a list of EPCs and the EPCs include where it comes from or the source of raw materials or where it goes to. By querying all the EPCs which come from the answer of each query, the detailed information of a supply chain is tracked. Taking the chain shown in Figure 2 as an example, the data flow is represented in Figure 6. As is shown in Figure 6, a track process of an EPC includes as many times of requests as the number of the nodes involved in the supply chain. In this case, a user queries the EPC 6901003.1000.

RFID

EPCIS

Conclusion

In this paper, we presented a distributed traceability system for wheat products based on EPC and ONS. The system allows a user to track the detailed information of the whole supply chain. The architecture of the system has been described from several points of view and it has shown to have the ability to meet the requirements imposed on distributed EPC-related data management and diversity of deployment requirements.

In the architecture described above, each node of the supply chain involved in retrieving traceability information can be queried for detailed information. Therefore, the system's availability depends on each node's response time and the reliability of each node.

For this reason, our future work will cover the study of dynamic storage query and RQC (Reliability and Quality Control).

Fig. 1 .

 1 Fig. 1. Wheat products supply chain

Fig. 2 .

 2 Fig. 2. A batch of flour chain

Fig. 5 .Fig. 6 .

 56 Fig. 5. The general ONS query process

Table 1 .

 1 EPC coding scheme based on SGTIN-96According to the EPC coding scheme shown in Table1, a business entity's company prefix takes up eleven decimal digits. For example, a sequence of 96-bit binary data -00110000 011 101 1100100011011000011101101101001010001 0000 01 00000000000000000000000000001111101001 can be converted to a standard URI: urn:epc:tag:sgtin-96:6901001.0000.1.1001, 6901001, in which, 6901001 is a company prefix got from the register center, 0 is a company prefix from a business entity in level 1, 1 is an item reference and 1001 is a batch number of wheat products.

		Header	Filter Value	Partition	Company Prefix	Item Reference	Serial Number
	Coding
	Segment Bit	8	3	3	24	14	4	38
	Count
	planting base A0	00110000	3	5	6901001	0000	--	--
	planting base A1	00110000	3	5	6901001	1000	--	--
	grain trading company A0	00110000	3	5	6901002	0000	--	--

  1.2 from D to track the information of the circulation of the EPC. Firstly, D finds out three EPCs 6901003.1000.1.1, 6901001.2000.1.1 and 6901001.1000.1.1 which are associated with 6901003.1000.1.2 in itself. Then, D sends the first request 1 using EPC 6901003.1000.1.1 to F and gets the reply 2 withthe information related to EPC stored in server F and one EPC 6901004.1000.1.1 which is from H. Then D sends one request 3 using EPC 6901004.1000.1.1 to H and gets the reply 4 with the information related to EPC stored in H from H. In this way, D sends one request using EPC 6901001.1000.1.1 to G and one request using EPC 6901001.2000.1.1 to B, and gets one reply with information related to the requested EPC from each server. Finally, the detailed information of the circulation related to EPC 6901001.1000.1.2 is tracked.

Xingye Zhang1, Jianqin Wang1,2,*, Jianye Cui1, Jie Zheng2, Jing Pan2 , Manlin Chen2


Hong Luo

Hui Xue
email: xue_huicn@yahoo.com.cn

Least-Squares Approach for harmonic and interharmonic analysis in power system

Keywords: Least square, linear prediction, interharmonic, harmonic

A new algorithm based on least-squares method for harmonic and interharmonic analysis is proposed. The approach employs least-squares method and is based on a linear prediction relation for multiple sinusoidal signals. It is shown that the method allows for accurate harmonic and interharmonic estimation with high frequency resolution. The approach is compared with that of DFT method and prony method.

Introduction

Harmonic/interharmonic measurement is an important function of a power quality analyzer widely used in monitoring the quality of power. The use of power electronic devices which increases the harmonic pollution in power system on the one hand and the widespread use of sensitive loads such as computers and microprocessor-based industrial controllers on the other hand signify the ever-increasing need for harmonic/interharmonic measurement devices. To monitor and maintain the power quality, there has been an increasing interest in devising harmonic/interharmonic measurement methods and devices over the last decade [START_REF] Joorabian | Harmonic estimation in a power system using a novel hybrid least squares-adaline method[END_REF]- [START_REF] Lu | Optimal harmonic estimation using a particle swarm optimizer[END_REF].

Discrete Fourier transform(DFT) has been widely used for spectral analysis of harmonics, however, DFT suffers from leakage and picket fence effect and suffers from the major problem of resolution because of some invalid assumptions(zero data or repetitive data outside the duration of observations) make in this method [START_REF] Girgis | A Quantitative Study of Pitfalls in the FFT[END_REF]- [START_REF] Kay | Modern Spectral Estimation: Theory and Application[END_REF]. It is very important to develop better tools of interharmonic and harmonic estimation to avoid possible damages due to its influence.

This paper proposed a least square approach for harmonic and interharmonic analysis in power system. Least square is time-domain approach which has to do with the criterion for selecting a solution to the overdefined equations produced when more measurements than states are represented in the estimation problems [START_REF] Phadke | Synchronized phasor measurements and their applications[END_REF], and has been widely used in power quality analysis. Tests show that this proposed approach can give an accurate harmonic and interharmonic estimation with high frequency resolution, the test results are compared with DFT and Prony method.

2

The proposed algorithm

Suppose the power signal is represented

) cos( 1 i k i i L i k t A x       (1)
In [START_REF] Chan | Aparameter estimation approach to estimation of frequencies of sinusoidals[END_REF], It has been shown that k x can be uniquely expressed as a linear combination of its previous 2L samples as follow.

     L i i k i k x a x 1 (2) Where i L i a a   2 (i=1, 2..L); Then (2) can be expressed as follows        L i i k i k i k x x a x 1 ] [ (3) Since ) cos( cos 2 ) cos( cos 2 1 1 1 1 i k i i L i i L k L k i k i i L i i k k t A t L x x t A t x x                        (4)
From ( 1), ( 3) and ( 4) we obtain

1 cos 2 1      L i i i t i a  (5)
Equation ( 5) can be expressed as follows

1 ) ( 1         L i t i j t i j i i i e e a   (6)
Equation ( 6) can be expressed as follows

0 2 0     L i t i i e b  (7) Where i L i L i a b b     2 , (i=0,1,..L-1) and 1  L b
. Then the positive phase angles of the roots of (7) are the frequencies of the sinusoidal. The parameter of i a can be obtained as follows. Since (3) can be expressed as following

S X X k k 1 0  (8)
Where

           M k k k x x X  0 ,   T L a a S ,..... 1  and                            L M k L M k M k M k L k L k L k k k x x x x x x x x X 1 1 1 1 
, where the value of M is bigger than L, Then S can be solved using the least mean square method, that is

0 1 k k X X S   , (9)
where

T k k T k k X X X X 1 1 1 1 1 ) (   
After the parameter i a obtained, the frequencies can be obtained using (7), and we can construct a matrix, denoted as E. Then the amplitude and phase angle can be calculated again using the least mean square method again as

Y E E E A ' ) ' ( 1   (12)

SIMULATION RESULS

We investigate the performance of the proposed approach. Matlab is used to perform the simulations. The sample frequency is 3840Hz. And the data window length is 64 points, which is (1/60) second. The DFT, Prony and proposed method are compared for two cases.

Case 1: Suppose the test signal is as : \ )

t f t f t f t x       Where 2 . 60 1  f Hz, 3 . 90 2  f Hz, 6 . 180 3  f Hz. 2 cos( 2 . 0 ) 2 cos( 2 . 0 ) 2 cos( ) ( 3 2 1
There is a 0.2Hz frequency deviation of fundamental components, and the signal contains an 20% interharmonic with a frequency of 72Hz and a 20% 3 rd harmonic component with a frequency of 180.6Hz. The measurement results using DFT, Prony and LMS are given in Fig. 1. Fig. 1 shows that DFT cannot separate the three components, Prony can separate the different frequency components but the amplitude estimation is mistaken, LMS can not only separate the different components, but also can give an accurate estimation of the amplitude as shown in Fig. 1. In fact the frequency resolution of LMS can be very high, another experiment is given as follows.

Case 2: The test signal is

) 2 cos( 5 . 0 ) 2 cos( ) ( 2 1 t f t f t x     Where 2 . 60 1  f Hz, 64 2  f Hz .
There is a 0.2Hz frequency deviation in the fundamental frequency, and a 50% 64Hz interharmonic exists in the signal. The frequencies of the fundamental component and interharmonic frequency are near to each other which make it hard to separate them. The measurement results are given in Fig. 2. Fig. 2 shows that DFT and Prony cannot separate the two components because their frequencies are so near to each other, while the proposed LMS method can give an accurate estimation of these two components.

Conclusion

A new algorithm based on Least-squares method for harmonic and interharmonic analysis in power system was proposed in this paper. The algorithm uses the linear prediction model of the sinusoidal. Theoretical analysis and simulation experiments validate the proposed algorithm have high frequency resolution in harmonic and interharmonic analysis

Fig. 1

 1 Fig.1 Spectra obtained. (a) DFT (b) Prony (c) LMS


Lifeng Shen

Xiaoqing Yuan

Daoliang Li

A Research of Agricultural Informationalization Evaluation and Decision Support System

Keywords: Agricultural Informationalization, Evaluation, Decision Support System

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

of China, developed a series of documents and policies, and implemented a number of informationalization projects. As a result, the construction of basic facilities in China's agricultural informationalization, the ability to develop and use information resources, and the system of information services are continuously improved, so that the information technology has been better adopted during agricultural affairs. The envi-ronment for informationalization development has been gradually enhanced, and the agricultural informationalization progress of China has been obviously accelerated.

Despite those achievements that China has made, some problems have been emerged during the agricultural informationalization development. For example, from the country level to the local level, the agricultural informationalization development lacks of a scientific and appropriate agricultural informationalization evaluation index system. Under this circumstance, a practical agricultural informationalization evaluation index system has been established for the urgent need of guiding the development of agricultural informationalization in various regions. This should be the guidelines of the agricultural informationalization in different regions, and the basis for the examination of the agricultural informationalization progress. Therefore, the establishment of a scientific agricultural informationalization evaluation index system means the motivation for guiding the agricultural informationalization work nationwide.

Taking the above analysis into consideration, the establishment of a scientific agricultural informationalization evaluation index system for the promotion of agricultural informationalization evaluation work is of particular necessary. Using a sur- set up an evaluation and decision support system for eco-cities, and presented the eco-city multilevel fuzzy comprehensive evaluation model and an evaluation support system.

Based on the need of the establishment of agricultural informationalization evaluation index system, this paper presents a study on the design of a an agricultural informationalization evaluation and decision support system. The system incorporates the analytic hierarchy process and aggregative index number in supporting the evaluation processes.

System Analysis

1 Analysis of System Users

There are mainly three groups of users of this system, including system administrators, provincial administrators, and experts. System administrators use the system, mainly for the purpose of division and management of system users and their limits of authority, and for the maintenance of the stable operation of the evaluation and decision support system, who, at the same time, have to be equipped with considerable system maintaining knowledge to re-adjust relative parameters of the evaluation index system in accordance with the evaluation requirements in necessity. What provincial administrators mainly do is to collect and update the data of local agricultural informationalization; therefore, a certain amount of system maintaining knowledge is needed. As for experts, some web application skills are required to be grasped, so that they are able to grade on the website and submit the grading result.

Analysis of Functional Requirements

According to surveys, it is concluded that there are mainly five perspectives of functional requirements of the system as follows:

(1)User information management. This system, with three groups of users involved, is in a prerequisite need of settings of the user management function.

(2)Setting of the index system. The evaluation index put forward in this article is in need of the criterion of practices, and it has to be modified appropriately according to the actual situation during the application period. Accordingly, the setting function of the index system has to be reserved.

(3)Setting of index weights. Experts have to grade via the analytic hierarchy process, and the system will process the grading result and finally figure out the weight values of all indexes.

(4)The collection and process of index data. The stability of this system and the regularity of the efficient functioning have to depend on the reliability of the data, which is the basis of the entire evaluation process. Due to the fact that most of the index data collected in the research are quantified, the collection of data is one of the major function of the system.

(5)The calculation of agricultural informationalization indexes and the display of the evaluation result. The core of the system is the scientific and reasonable evaluation for agricultural informationalization levels in various provinces. Therefore, on the basis of the confirmation of index weights and index database, the code design is wanted for the realization of the calculation of agricultural informationalization indexes, whose result has to be displayed in tables or histograms via an efficient MSMMI.

System Design

System Structural Design

The agricultural informationalization evaluation and decision support system adopts layered structure, involving data layer, application layer, and presentation layer, shown in Figure 1. The database of this system has to save the data information as follows: 1) user information; 2) information of index system setting; 3) index weight information; 4) index normalized value; 5) the data input by provincial administrators and the database after data integration. For the reliability of the system, the backup database was kept on this layer, and all data will be saved as backups all the time.

(2) Application layer The application layer, which has been regarded as the core of the system, calls relative data in the database for the realization of agricultural informationalization evaluation and analysis, and adopts the needs during the evaluation to achieve further system management, including the setting of indexes and the modification of index weights.

(3) User layer The client for human machine interface is various commonly used internet explorers, where users are allowed to enter the interface of the agricultural informationalization evaluation and decision support system, e.g. experts are able to grade, system administrators are capable of system maintenance, and the provincial administrators can have a visualized understanding of the evaluation results.

Design of System Function

According to the demand analysis of system function, the function of agricultural informationalization evaluation and decision support system can be figured out as what Figure 2 demonstrates, including following functional module: (2) Weight calculation module With this module, experts are able to grade via the analytic hierarchy process based on the index weights, during when judgment matrix establishment, single-level sort with its consistency check, and multilevel sort with its consistency check are needed to figure out the index weight. At the same time, system administrators are able to have the system weight further adjusted.

(3) Data processing module Provincial administrators are able to input original data of indexes through this module, which leads to the realization of storage management of collected data. At the same time, this module is used to normalize all data, when system administrators can get all input data automatically for further calculation of agricultural informationalization indexes.

(4) Index calculation module This module can be applied for the calculation of the total indexes of agricultural informationalization of various provinces, and the calculation of the sub-indexes of different indexes of agricultural informationalization of various provinces, which can be displayed in tabular forms. When the agricultural informationalization levels of various provinces are evaluated, the evaluation results of various provinces can be ranked and displayed intuitively in histograms.

(

5) User module

The module contributes to the appropriate distribution and management of the authority limits of three groups of users including system administrators, provincial administrators, and experts.

Design of System Workflow

The agricultural informationalization evaluation and decision support system has integrated functions including index setting, information collection, analysis display, etc.

After the indexes are set, index information will be collected. Then, the system, based on the setting of indexes and the collected data, will select an applicable evaluation method for the realization of evaluation, whose results will later be displayed on the stage page for reading and reference. The workflow of the system is shown in Figure 3.

Fig. 3. The workflow of the system 3.4 Database Design

The database of the agricultural informationalization evaluation and decision support system embodies a considerable number of data sheet, including the data sheet of administration regions, a relative sheet of index system structural information, relative sheet of index data collection information, and a relative sheet of index data summarization. On account of the limited length of the article, merely some representative sheets will be listed as examples.

Sheet 1 Administration Regions Information

Field Name Name Data

The realization of MVC Design Mode

The MVC mode embodies 3 categories of components: 1) the model object is the core of the entire application software, in charge of packaging the structure of software data and the operation as well as the work flow of processing services; 2) the view object is the connector between the application software and the outside, by forwarding the input of its user to the controller, consulting the business situation, and synchronizing the relative date to the user via visualization; 3) the controller object is the link between models and the view. On the one hand, it provides the user input with analysis into the order for model implementation; on the other hand, it, in accordance with the user input, calls relevant models and the view to satisfy the demand data visualization for the user.

With the application of MVC mode, the data processing, the control of system input and output are both separated with data presentation, making the system structure clear and flexible, so that it leads to the avoidance of entanglement and confusion of the data processing, program function, and show code when early developers are using the method starting from the interface and then code. The design of Struts MVC mode is demonstrated as follows.

HTML

HTML, short for Hypertext Markup Language, as a common language in the internet and a simple and universal explanatory markup language, is a descriptive text consists of HTML orders. The HTML order is able to explain languages, images, movies, sounds, figures and interlinkages. The structure of HTML can be divided into the head part and the body part, in which, the former one is used for the description of the information demanded by the explorer, and the latter one is the detailed and specific content of the page.

Javascript

Javascript is a scripting language developed from LiveScript by Netscape. As a script, it is able to write Javascript code into HTML files, and it can be compiled and executed while the internet explorer reads it. Javascript can effectively save the download time on the client page by increase the interactivity of webpage and simplify some regularly repeating HTML files. Furthermore, Javascript is capable of transferring some operations such as user authentification on the client side and reduce the burden of servers.

JSP

JSP, similar to the ASP technology, is a technology realizing mixed code of regular static HTML and dynamic HTML. It inserts Java program segment and JSP label into traditional webpage HTML files. The JSP is of the ability to realize the separation between web logics, design and presentation, for the design based on the reusable components, resulting in rapidity and simplicity of the application software development based on Web.

Servlet

Servlet, namely the server applet, is Java application software independent from both the system operation platform and the network and transport protocols server, for the extension of server functions and the generation of dynamic Web pages. It is the Java application software at the server side inside the Web server, which differs from the Java application software that is started from the traditional order line. Servlet is loaded by Web server, which has to embody the Java virtual machine for Servlet support. Servlet, in the MVC mode, is capable of the matching of models and views and the accomplishment of the user request.

Struts

Struts is an open source project organized by Apache organization, based on the Web application in MVC mode, which provides the MVC system development with bottom support. It, adopting Servlet as the main technology, is able to reduce the time to develop Web application with the application of MVC design model. Struts frameworks such as JSP, user custom tags or so are helpful for the improvement of developing efficiency and for development of system maintainability and extendibility.

Conclusion

Addressing the need of the agricultural informationalization evaluation and decision support system,a agricultural informationalization evaluation and decision support system is developed based on MVC development mode in the environment of Windows XP+Tomcat 5.0+SQL Server2000. This article provided information on the system design, functions, database and work flows. The research has achieved its objectives by developing a tool which can support the agricultural informationalization evaluation effectively and efficiently.

1

 1 Introduction 14 indexes. Liu Shihong(2007) argued that there need to be 6 factors and a total of 25 indexes included in the rural i In recent years, both the Party Central Committee and the State Council have paid considerable attention to agricultural informationalization

  vey, BaiWanping(2008)has succeeded in the establishment of a rural informationalization construction effect evaluation index system in western regions. Huang Zhiwen(2009), for the evaluation of rural informationalization level in various regions throughout China, has designed 5 index numbers and nformationalization evaluation index system. Zhang Xicai, Qin Xiangyang, Zhang Xingxiao (2008)applied the industry chain theory of agricultural informationalization, and developed a series of Beijing rural informationalization evaluation index system including 6 first-class indexes and a total of 23 second-class indexes. Gao Ya and Gan Guohui(2009) have selected 24 indexes from 6 perspectives for the establishment of agricultural informationalization evaluation index system.There seems no attempt to develop the agricultural informationalization evaluation and decision support system so far. Based on the technology of Geographical Information System, an evaluation and decision support system developed by Zhao Yongpeng(2007), combining data storage, managing, analysis, and decision support, used to evaluate the effect of the vegetation recovery on dumps, has been a decision support system related to evaluation. Xia Yuanyong, Yan Dongmei, Shen Hong and Zhou Qiangxin (2006)contributed a evaluation and decision support system based on Web to the stability of side slopes around the Three Gorges reservoir areas, and took the actual situation of side slopes around the Three Gorges reservoir areas into considera-tion during the analysis of the demand, function, and operation process of the system, so that the operation modules are divided, and the frame graph of the entire system is finally figured out. Based on the characteristics of systematicness, diversity, spatiality, dynamicness during the urban sustainable development, Wang Guixin and Chen Ping(2006) have established a evaluation and decision support system for the future sustainability of urban development from the perspectives including architecture, functional module, integration methods, etc. In order to solve the problem of the fuzzy comprehensive evaluation of the eco-cities, Hu Jianyuan and HuangKun(2006)

Fig. 1 .

 1 Fig. 1. System Structure

Fig. 2 .( 1 )

 21 Fig. 2. The figure of system function

  development tool of the agricultural informationalization evaluation and decision support system, has been developed, compiled and debugged in the environment of Windows XP+ JDK 1.5.0+Tomcat 5.0+SQL Server 200, seen in the figure as follows. The development mode of MVC, based on Struts, was adopted for the establishment of the agricultural informationalization evaluation and decision support system, in the B/S systematic structure based on WEB. Struts is the framework of considerable popularity based on MVC in nowadays, which has led to the general realization of the separation between the business logic layer, the presentation layer, and the control layer, and at the same time contributes to the promotion of extendability and circulativity of the application software.

Fig. 4 .

 4 Fig. 4. The Software Environment of System Development

Fig. 5 .

 5 Fig. 5. The Design of Struts MVC Mode

Acknowledgements This research has been substantially supported by the program of National Agricultural Informationalization Evaluation Index System Research carried out by Market and Economic Department in the Ministry of Agricultural.


Qiucheng Li

Daoliang Li

Zhenbo Li

Design of expert system for fault diagnosis of water quality monitoring devices

Keywords: Automatic, On-line, Fault diagnosis, Aquaculture, Water quality monitoring

A new system for automatic detect fault of water quality monitoring devices used in aquaculture is proposed in this paper. The proposed system can detect the whole system which includes platform、gateway、WSN、sensor、 actuator. China is the world's largest freshwater culture nation which provides 80% of the freshwater culture fish. The water quality is essential to freshwater culture, and the environment is controllable. In this paper, water quality sensors are used to detect the water quality of culture ponds. By the use of wireless sensor networks, the data can be sent to remote server. So farmers can check the state of the culture ponds where the internet is available. This paper is proposed to detect the state of the monitoring system, if the monitoring system falls, the system will alarm to the user.

Introduction

China is the world's largest freshwater culture nation which provides 80% of the freshwater culture fish. The water quality is essential to freshwater culture, and the environment is controllable. In this paper, water quality sensors are used to detect the water quality of culture ponds. By the use of wireless sensor networks, the data can be sent to remote server. So farmers can check the state of the culture ponds where internet is available. Water quality is very important in aquaculture. We use WSN technology to monitoring the water quality to ensure the circumstance is suitable for the fish to grow. In this way, human has been released from hard working. The water quality monitoring system is essential for the aquaculture. If the monitoring system fails, and the water quality become bad, a lot of fish will die, farmer will lost a lot. So a new system for automatic detect fault of water quality monitoring devices used in aquaculture is proposed in this paper [START_REF] Avci | An expert system based on fuzzy entropy for automatic threshold selection in image processing[END_REF].

Water quality monitoring model

The water quality monitoring system proposed in this paper is used in outdoor aquaculture. The most important attributes of the water quality are dissolved oxygen and water temperature. If the dissolved oxygen is lower than 3mg/l, the growing of fish will be constrained. If the dissolved oxygen is lower than 1mg/l, the fish will die. Both the water temperature is too high or too low will constrain the growing of fish. The water quality monitoring model is illustrated by Figure 1. The first part is sensor which can detect both dissolved oxygen and water temperature. The second part is a transformer which is powered by solar battery and sends out the data collected by sensors wirelessly according to H 15.4 communication protocol. The third part is gateway which receives the data send from transformer and sends them out to the remote server. In this system, the sensor has three channels, includes dissolved oxygen, water temperature, and dissolved oxygen engineering value. The transformer has three channels, include device information, device voltage, and signal strength [START_REF] Avci | An expert diagnosis system for classification of human parasite eggs based on multi-class SVM[END_REF]. The gateway has seven channels, includes city power supply, current one, current two, switch signal, analog signal one, analog signal two, and device voltage. That information is the source of the fault diagnosis system [START_REF] Du | Detection and diagnosis for sensor fault in HVAC systems[END_REF].

Design of fault information database table

After three months observation of the current water quality monitoring system, fault object can be divided into five categories: software platform, gateway, transformer, sensor, and actuator. Fault grade can be divided into three categories: mild, moderate, serious [START_REF] Reza | Designing a hierarchical neural network based on fuzzy clustering for fault diagnosis of the Tennessee-Eastman process[END_REF]

Design of fault diagnosis rule database

The fault diagnosis rule database is illustrated by Figure 3.Rules is made on the base of careful observation of the water quality monitoring system. Each fault object has the expert to give the suggestion of the rule-making. Each fault object has four attributes, communication state, device state, data continuation state, data rationality [START_REF] Lee | Fault detection of wireless sensor networks[END_REF]. Fault level has been divided into three levels. Serious means that the fault is fatal to the operation of the water quality system. Moderate means that the fault is not fatal to the operation of the water quality monitoring system, but the fault will be fatal to the operation of the water quality monitoring system. Mild means that the fault is not fatal to the operation of the water quality monitoring system, but the fault has the possibility to be fatal to the operation of the water quality monitoring system [START_REF] Tsai | Fault diagnosis for magnetic bearing systems[END_REF].

Fault object

System interface

Fault information management is illustrated by Figure 5. The result of fault diagnosis is stored in the database. For the purpose of being friendly to the users, a web-based system interface has been developed. Users can search the device Id, fault level, fault type, fault state, fault occurring time [START_REF] Al-Kasassbeh | Network fault detection with Wiener filter-based agent[END_REF].

Fig. 5. Fault information management

Fault report is illustrated by Figure 6.The report can statistic the fault information.

From this report, we can see the amount of each kind of fault happened in a specified period.

Fig. 6. Fault report

Conclusion

In this paper, we presented an expert system for fault diagnosis of water quality monitoring devices based on rule database. The system allows a user to track the detailed information of the whole monitoring system. The architecture of the system has been described from several points of view and it has shown to have the ability to meet the requirements imposed on early warming of the water quality and monitoring devices and fault diagnosis of the monitoring system In the architecture described above, each fault of the water quality monitoring system can be tracked for detailed information. Therefore, the system's stability can be enhanced. The profit of the aquaculture farmers can be ensured. For this reason, our future work will cover the study of artificial intelligence to make the system smarter [START_REF] Barco | Knowledge acquisition for diagnosis model in wireless networks[END_REF].

Fig. 1 .

 1 Fig. 1. Water quality monitoring model

Fig. 3 .

 3 Fig. 3. Fault diagnosis rule database

  . Mild means that operation and maintenance staffs should know that. Moderate means that if operation and maintenance staffs have time, they should deal with the problem. Serious means that the fault is fatal, operation and maintenance staffs should deal with the problem as soon as possible. The fault information database table is illustrated by Figure2. The fault diagnosis system stores the fault occurring time, and records fault reason and deal method which is added by operation and maintenance staffs. In this way, if the same kind of fault occurs again, we can check the database to check the previous records[START_REF] Keleş | Expert system based on neuro-fuzzy rules for diagnosis breast cancer[END_REF].

	Field meaning	Field name	Data type
	ID	def_id	varchar
	Smart device ID	dev_id	varchar
	Fault type	def_type	int
	Fault grade	def_grade	int
	Fault occur reason	def_occurReason	Varchar
	Fault occur time	def_occurTime	Datetime
	Fault solved time	def_dealTime	Datetime
	Deal method	def_dealMethod	Varchar
	Channel ID	ch_id	Varchar
	Fault description	def_desc	Varchar
	Fig. 2. Fault information table(smart device)

Start


Yanbo Su

Hongwen Li

, Yarong

Jin He

Qingjie Wang

, Hui Li

Rabi G Rasaily

Study of Automatic Test System of Surface Flatness in No-Till Field Based on the PLC Technology 

Keywords: No-till, automatic test system, surface flatness,PLC, MCGS

In this paper, automatic test system of surface flatness was designed according to the characteristics of the no-till field by combining the PLC (Programmable Logic Controller), laser sensor and stepping motor automatic control technologies. Monitor and Control Generated System (MCGS) configuration software was used to form the interaction interface. Real-time data report and the trend line could be created by accessing PC machine to this system, and then the surface roughness detection was realized automatically.

Compared with the traditional test methods, results of the automatic test system showed that the measured value is accordance with the artificial measured value, and the correlation coefficient between them was above 0.95; and the detection efficiency had been improved by 2.3 times. These results proved the effectiveness of the automatic test system in detecting the surface flatness of the no-till field.

Introduction

Conservation tillage is an advanced agricultural tillage technology, which advocates no tillage or reduced tillage, covering surface with straw, in order to reduce the wind erosion, water erosion and improve drought resistance [START_REF] Jinyao | Conservation tillage in China[END_REF][START_REF] Zhi | Characteristics of drifting sand flux over conservation tillage filed[END_REF] . Surface flatness is one of the significant indexes evaluating the quality of no tillage operations. Currently, the main method to measure the surface flatness is by manually pulling the rope from its ends on the soil surface. Its results are precise, but its efficiency is low and labor intensity is high. Therefore, It is necessary to carry out the research on rapid measurement of the surface flatness to improve the detect efficiency. At present, certain progress has been made in detecting the surface flatness rapidly through automatic detection by domestic and foreign researchers. For example, J. Lee, et al. studied the measurement method of surface height using infrared sensor and ultrasonic sensor [START_REF] Lee | Non contract sensors for distance from ground surface[END_REF] . A. M. Mouazen, et al. analyzed the difference of detection performance between the ultrasonic sensor and the linear variable displacement transducer under the field covered with corn straw [START_REF] Mouazen | An automatic depth control system for online measurement of spatial variation in soil compaction, Part 1: Sensor design for measurement of frame height variation from soil surface[END_REF] . Cai Guohua made the comparative study by ultrasonic sensor, infrared sensor and linear variable displacement transducer under the three conditions of wheat broken stalks, residue, both broken stalks and residue respectively [START_REF] Guahua | Study on automatic opener depth control system for no-till seeder[END_REF] . However, infrared sensor and ultrasonic sensor used by these methods can be influenced easily by the moisture content and temperature of soil, and the sensitivity of linear variable displacement transducer to surface deformation is affected. In addition, this method exits a certain delay [START_REF] Guahua | Study on automatic opener depth control system for no-till seeder[END_REF] . In short, the precision and efficiency of surface flatness detection need to be improved.

In this paper, the rapid automatic detection under no tillage surface is realized by the principle of laser ranging, combining the PLC and MCGS configuration software.

Laser sensor has high precision and less external influence [START_REF] Yuanyuan | Parameter optimization of laser triangulation sensor based on PSD[END_REF] , can meet the requirements of precision and speed in detecting the surface flatness. The testing part is composed of LRFS-0040-1 laser sensors and matching circuit.

Main structure and working principle

Before testing, first test plots on the grid has to be divided, using laser sensor driven by stepping motor to scan detection line listed by the grid intersection.

While in operations, adjust the height of outrigger, and ensure that the detection system must be in reliable level and in stable state. The surface roughness automatic test system through own structure form the initial space coordinates, and through the manual reset and system in the software of reset control function, ensure the initial operating point for the X-axis, Y-axis intersection. At the same time, according to detection accuracy and time requirements, set the laser scanning area, X-axis, Y-axis stepper motor stepping distance and speed. After start, the X-axis stepping motor move step by step. When the Y-axis reaches the setting position, PLC receives signal, and then control the stepping motor of X-axis from moving, and drive the Y-axis rail screw rotation through initiating the Y-axis direction movement of stepping motor, thereby stimulating laser sensor stepping a grid distance. After this movement, the alternate detection of flatness scanning is completed. After the scan is complete, through the system reset function can realize reset; adjust the position of the laser sensor. When the Y-axis touches travel switch on the X-axis,PLC control X-axis stepping motor stop the movement. At the same time when laser sensor touches the limit switch of the Y-axis, PLC controls the motor to stop from Y-axis stepping movement, which completes laser sensor reset.

3

The design of Automatic detection system

The design of hardware part

The hardware part of automatic detection system is mainly made by the control system, the data acquisition system and the test bench. Figure 2 shows the hardware structure of system, noting the wring mean of PLC's each pin that the system used. The control system. The control system consists of PC, slave computer and control devices. PC uses the software of the automatic detection system for surface flatness that developed by MCGS for on-site monitoring. The control of slave computer puts to use Mitsubishi programmable logic. The control system uses PLC as host machine, gathering six electrical signal of reset, start, stop, X-axis limit switch, Y-axis limit switch and laser sensors, and output four electrical signals of stop-start and move for X-axis, Y-axis, to complete position control and detection of surface height in the X-axis and Y axis using the laser sensor.

The data acquisition system. Data acquisition system uses laser sensors, transmitters, A / D converter through the RS-422 interface to send data to the principal computer, using the software of the automatic detection system for surface flatness monitoring test real-time results.

The system uses LRFS-0040-1-type laser sensors, its main technical parameters shown in Table 1. Surface flatness testing for No-till generally be carried out in the field, the solar radiation has a certain influence on detection of the laser [START_REF] Xingfu | Laser receiver used for laser-controlled land leveling system[END_REF] . In order to eliminate the deviation caused by sunlight, the paper was calibrated laser range sensor, the methods are as follow:

(1) Install the automatic detection system for surface flatness in the no-till land, and adjust the laser sensor to the level of the state, making the ray of the laser parallel to the X-axis;

(2) Fixed a baffle opposite the laser sensor at 200mm, so that the ray of the laser after reflection by the baffle can be received by the sensor;

(3) Record the initial distance of the sensor to the baffle and the output current of the sensor;

(4) Set stepping distance of X-axis to 10mm, the moving range is 1000mm in MCGS;

(5) Start the system, record the sensor current value when it moves backward 1mm, so you can get 100 groups of distances and corresponding values. The test bench and hardware. The test bench mainly includes X-axis guidway, Y-axis guidway, stands leg and land wheel. The distance of X-axis guidway is 2680mm, width is 240mmh and thickness is 85mm. The way of transmission is the ball screw. Because only one end of the Y-axis guidway fixed to the X-axis guidway, in order to ensure Y-axis to maintain the level in the detection process, so determined Y-axis's length is 1000mm, the way of transmission is the lead screw. Test bench leg height adjustable stand, easy to detect in a test station before transfer to the state level.

The distance of stands leg on the test bench can adjust, in order to facilitate the test bench to level before the test. Meanwhile, there has a land wheel on each stand leg which is conducive to the movement.

According to the features of no-till surface flatness testing, combined with the need of the detection system, the system employs FX1S-10MT-type PLC made by the Japanese Mitsubishi, which output type is transistor output [START_REF] Junxu | Design and implementation of portable testing instrument for PLC[END_REF] , used 6 inputs and 4 outputs, among them Y0 and Yl port can simultaneously output 100 KHz pulse.

Select linear motion unit type WG206 in X-axis direction, stepper motor drives uses SH-2H042MB which is two-phase hybrid stepping motor driver; select 17HS111 type stepper motor in Y-axis, the type of stepper motor drives is 3ND883.

The design of software system

The software of this system mainly includes measurement system, data-collection This system sets up the parameters such as serial port number, signal baud rate, data bits, stop bits, data check mode and data acquisition mode by driving software.

y = 3E-05x + 3.9933 R 2 =

PC.

When driving slave computer communication test is normal, the PC configuration is developed in the MCGS configuration software environment [START_REF] Weidong | The development and application of configurable software MCGS[END_REF] , such as building monitoring system project, and producing user application system which made up of main control windows, device windows, user windows, real-time databank windows and operation strategy. The main control windows sets up collection range, step distance, step speed of the surface flatness automatic test system X-axis and Y-axis and menu command et al. Device windows, the key of normal equipment operation, is the connection media of the surface flatness automatic test system based on MCGS configuration software and PLC [START_REF] Yang | High-voltage motor test system based on PLC and MCGS configuration software[END_REF][START_REF] Shao Limin | Design and experiment on PLC control system of variable rate fertilizer[END_REF][START_REF] Shouyong | Design and implementation of fuzzy control for irrigation system with PLC[END_REF] . The real-time surface flatness data collected by slave computer sends to the database by building data connection, and the data is output by Excel and reserved permanently in the user windows. The monitoring system could operate real-time database in according to the setting order and condition, control the open and close of user windows, and detect the working state of the device by the definition of operation strategy, so that it will accurately control X-axis, Y-axis and laser sensor working process.

4

Experiment results and discussion

Experiment design

The experiment was conducted at the National precision agricultural research station of Xiao Tangshan, Beijing in Sep. 2011. The experimental steps are as follow: (2) The stepping distance and measuring range in the X axis direction was set as 50 mm and 1000 mm in the MCGS software, respectively; while in the Y axis direction, the stepping distance and measuring range was set as 100 mm and 300 mm in the MCGS software, respectively. Each value of the marked junctions projected on the field will be measured.

(3) Fix two piles on the field when detecting each junction on the line, and a piece of string should be tied on the two piles and adjusted for lever.

(4) Measure the distance from the marked projecting junctions on the surface of the field to the string.

(5) Conducted 3 groups of the experiment, and record the data of the surface roughness and detecting time measured by the system and manpower, respectively.

Results and discussion

As shown in table 2, the linear regression between the results detected by the surface flatness automatic test system and manpower was obtained for the 3 groups of results, respectively. The relationship between the two measured values was also shown in The average time of detecting the surface flatness in the same line was 18min and 43min, respectively by using the corresponding surface flatness automatically detecting system and manpower. Therefore, the efficiency of the surface flatness automatically detecting system has been improved by 2.3 times compared with the manual measuring method.

Fig. 1

 1 Fig.1 Automatic test system of surface flatness in no-till field 1. Stepping motor of X-axis 2. Limit switch of X-axis 3. Guidway of X-axis 4. laser sensor 5. Limit switch of Y-axis 6. Guidway of Y-axis 7. Bench 8. Wheel 9. PC 10. Control box 11. outrigger No-till surface flatness inspection system mainly composed by control part, the operative part, and the testing part as shown in figure 1. Control part mainly composed by the control box and some of the major PC. The operative part is composed of the test bench, X-axis guidway, Y-axis guidway and the stepping motor.

Figure 2

 2 Figure 2 Hardware structure of the system

( 6 ) 3

 63 Have a regression analysis for these 100 sets of data, obtain the relation curves between distance and the current, shown in Figure Where x is distance (mm), y is current (mA) The variance Analysis results show that when the equation of the regression coefficient R> 0.95, linear detection system shows good linearity and a high level of detection accuracy.

Figure 3 Figure 4

 34 Figure 3 Relation curves between distance and current

Fig. 5

 5 Fig.5 Field experiment (1) Divide the field into 50 mm x 100 mm grids and install the automatic detection systems on the no-till field. Ensure that the starting point is the junction of the X-axis and Y-axis, and the X, Y axis is adjusted for level.

Figs. 6

 6 Figs. 6(a), 6(c) and 6(e). It was shown obviously in the Figs. that a positive correlation was existed between the surface flatness automatic test system and the artificial measured value in the 3 groups, respectively. Furthermore, the related correlation value for the 3 groups was 0.983, 0.976 and 0.988, respectively, which indicated that the differences between the values detected by the surface flatness automatic test system and manpower were negative.Tab. 2 Result of linear regressionCoefficient of Regression Equation R 2 F k b First 1.0247 567.69 0.983 2.24E-35 Second 0.9699 604.14 0.976 1.92E-31 Third 0.8032 654.77 0.988 4.56E-38 After the regression equation was obtained, we put the artificial measured value into the equation, than the trend of the real flatness of the field was acquired. Figs 6 (b), 6 (d) and 6 (f) showed the curves of the trends of the surface flatness in the same line detected by the automatic test system and manpower. The value differences (less than 2mm) between the two measured methods for these 3 groups of experiment were 80%, 80% and 95% respectively of the total measuring point. The differences, especially those more than 2mm, were caused by the existed gap between the straw/blocks with the field surface, such as the differences appeared in the points of 5th, 8th, 12th, 13th in Figs 6 (b), 3rd , 8th, 12th, 20th in Figs 6 (d) and 16th in Figs 6(f).

Table 1

 1 Technical parameters of the laser sensor

	Variable	Parameters	Variable	Parameters
	Measurement Range	0.2-50m	Measurement Accuracy	±3mm
	Output Range	4-20mA	Testing Rate	5Hz
	Resolution	0.1mm	Radial Dispersion	0.6mrad
	Supply Voltage	10-30VDC	Wavelength	650nm

  Result of linear regression between system measurements and manual measurements

			system(mm)
			by
			Detected
			system(mm)
			by
			Detected
	885 890 895 900 905 910 888 290 890 892 894 896 898 900 902 904 292 Fig.6 (c) The second Regression Curve 295 300 305 310 Detected by manpower(mm) 315 294 296 298 300 302 304 306 308 310 Detected by manpower(mm) (e) The third Regression Curve	875 880 885 890 895 900 905 910 880 885 890 895 900 905	1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Detected by the manpower Detected by the system (d) The second Correlation Curve 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Detected by the manpower Detected by the system (f) The third Correlation Curve

 This work was encouraged by National Natural Science Foundation of China (Grant No. 51175499), the Australian Centre for International Agricultural Research (ACIAR), Beijing Natural Science Foundation (Grant No. 6112015) and the Special Fund for Agro-scientific Research in the Public Interest (Grant No. 200903009).

Conclusions

(1) This test system realized the detection of surface flatness based on laser ranging principle by using common PLC technology as the platform and MCGS as a means.

(2) The result of the analysis of the tests showed that the tow lines fit linear correlation and all of their correlation coefficients were over 0.95, which means the regression line fit well with the data points. Using the regression model to predict values, means comparing the predictive value and the measured values of the system, and the points where the error is less than 2mm meet 80% and less than 3mm meet 95%, then we can say that the measured values of the system and the predictive value fit better.

(3) Comparing with traditional manual measurements, this system can improve the test rate more than 2.3 times. So this system can be the better alternative to test Surface Flatness instead of traditional manual measurements in No-Till Field precisely.