Heying Wu
email: heyingwu@163.com

Haiyan Zhu

RESEARCH ON THE COMMON CAUSES OF DEFECTS AND THEIR PREVENTION MEASURES FOR RCF-TYPE PCB MILLS PRODUCTION

Keywords: PCB mills, Blade-type errors, Edge collapse, Missing angle, Micro missing

Blade-type error, edge collapse cutaway, micro missing, four kinds of defect for RCF-type PCB mill production are deeply analyzed and their preventions measures are given detailed according to the author's many year's practice. These measures have been practiced and achieved good results. The research results can increase pass rate of such tools in the production and reduce production costs obviously, and owns with a special important using values and widely promoted significance.

Introduction

Printed Circuit Board(PCB)is an important part of electronic component. PCB mills are used to process various products of printed circuit board for notebook computers and mobile phone plants. With the current rapid development of CNC machine tool technology, the production and the process technologies of PCB milling are also making progress. Through investigation, most domestic and foreign enterprises have adopted the high cost of CNC grinder to produce PCB milling. However, in spite of the performance of advanced CNC grinding machine, the production process of PCB mills will inevitably lead to a variety of defects because of its production technology, poor management and CNC machine tool comprehensive factors of failure and so on. In order to improve the rate of qualified products and reduce production costs, it is necessary to further study the causes of defects and effective measures of the PCB mills in its production process.

Type of PCB Mills

The following describes the common of four major categories PCB mills all over the world, they have accounted for above 90% of all the printed circuit board tools, and will have huge potential market and development prospects [START_REF] Yanxieli | Circuit board machining technology[END_REF]. All the pictures in this paper are filmed by author himself during the production research process.

RCF Mill (diamond mesh type mills)

This kind of mill is the most common type of cutting for milling printed circuit board outside, with diamond-shaped blade, chip up along the trench discharge, effective chip removal with a large cutting force and the characteristics of higher life expectancy. Its front-end tools will be designed to various structures and parameters according to the productive required, however, the shape of a swallowtail is the main designed structure to facilitate cutting materials.

SC Mill (spiral mills with broken bits slot)

SC Mill is called spiral mills with broken bits slot, its right spiral cutter blade as the main body, with multiple right-spiral grooves and the thin edge cutting edge grooves, and the spiral grooves with a good chip removal performance, especially suitable for processing of paper substrates and CEM-3 products.

SR Mill (consecutive mills with multi-edges)

SR Mill is called consecutive mills with multi-edges, has multi-right spiral cutting edges without chip-breaker grooves, which is mainly used for PCB terminal notch processing. If the high accuracy is required, it can be designed to the right spiral and the left spiral types, which is mainly based on the process precision and the product categories.

RS Mill (consecutive milling with two edges under cut)

RS Mill is called consecutive milling with two edges under cut. This kind of mill has two left helical cutting edges and large junk slots, and suitable for precision milling. With excellent functions of machining surface precision and preventing flash. This under-cut mill is required to pay special attention to its downward chip removal direction.

Common Causes of Defect and Their Preventive Measures for Producing RCF-Type PCB Mills

In the above described the types of PCB mills, not only is the RCF-type milling cutter the most commonly used in processing printed circuit board, but also is the largest number of production in the enterprises. But the defects produced in the production process would decline the rate of finished products, which can lead to an increased production costs, and to market competition pressure of enterprises [START_REF] Xudawei | Operation technique and examples of machining production line[END_REF]. Therefore, it is necessary to further study and analysis the causes of defects and their preventive measures during the produce milling cutters in enterprises. The author has years' enterprise's production line experience of RCF type PCB milling. The following will analyze the common defect types, causes and preventive measures in the process of milling cutter production.

Defects 、Causes and Measures of Blade-Type Errors

Blade-Type Errors

Blade-type error refers to the milling edge geometry and the geometric shape of drawings required exist one or several differences [START_REF] Park | Evaluation of mach inability in the micro end milling of printed circuit boards[END_REF]. As shown in Figure 2 (a), the difference between the milling cutter and the drawing is that the former is less a Ledge, the drawings require RCF milling cutter has six Left-edges, but only has five Left-edges in the actual process of production, which must cause the milling cutter to waste product. Similarly, there exists such phenomena that the milling cutters are less one or several Right-edges, or while both on the left and right edges are less one or several edges in the milling cutters production, or vice versa. As shown in Figure 2 (b), the milling cutter has no fish tail, which would also cause it to waste product.

Causes of Blade-Type Errors

The main reasons for this defect are as follows: First, the operators are not strictly implemented the technological process of production, for example the technology workers look at drawings with mistakes cause to count the wrong edges, and then lead to set the wrong edges parameters of programs. Second, the machine operators have not checked the products, the milling cutters, carefully by themselves. Besides, the quality inspection workers have not timely feedback the defects to production sites, which lead a lot of such defect to occur. Finally, the technical personnel who did not perform their duties at the production site, they did not comply with the related requirements of production process, not strictly random in proportion to the production machine products, leading to these defects are ignored. However, the milling cutter has not the fish tail because of programmers forgot to compile the fish tail program, which causes CNC machine does not carry out the production process.

Preventive Measures

First, all the programmers, the technical personnel and the production operators must master the production drawings thoroughly and review them carefully, especially should rigorous review and check each parameter of the trial products. If there were parameters not comfort to the drawings, then the corresponding correction should to be done immediately, and eliminate such defects in the bud state effectively. Second, the machine operators and production technology workers should check the some proportion products made by machines randomly in accordance with of the production process. If any parameter surpasses the tolerance range, an immediate correction to the processing program parameter, to eliminate the edge flaws of products.

Causes of Edge Collapse

Edge collapse means a edge gap is greater than or equal to1/2 values of the edge depth or edge width, or the fish tail has the phenomena of serious damage and many edges missing.

Through analyzing, we know that the carbide is a common tool material, and its major shortcoming of mechanical property is brittle, if there is little impact or vibration, it would prone to cause the destruction phenomena of break off, flaking and collapse [START_REF] Hinds | Drilling of printed circuit boards: factors limiting the use of smaller drill sizes[END_REF]. Therefore, the edge collapse defect is produced mainly by the following several reasons:

(1).Due to the unloading robot and the yard lumber holes beyond the tolerance range in the horizontal direction during the robots of CNC grinding unload mills to the yard lumber, resulting in a collision causes mills produce edge collapse defect.

(2).It is very easily leads to serious collision among mills, or with other objects while workers are taking, attiring or checking mills during all the production processes.

(3).The cutting grinding wheel edge has bumps lacks, which causes mills load uneven forces and thus produces edge collapse in machining the spiral grooves process.

(4).The grinding wheel surface is blocked by chips, which can increase friction force between the grinding wheel and the mills. [START_REF] Yanxieli | Circuit board machining technology[END_REF]. Adjust the tolerance level accuracy between the unloading robot and the yard lumber holes in the horizontal movement direction to ensure that the both at work can not interference with each other.

Preventive Measures

(2).Mills can not be collided in all aspects of the production.

(3). In order to prevent collapse defect occurs in grinding wheel's edge, it is necessary regularly to test grinding wheel's working status and processing geometric parameters, which can ensure the wheel meets machining requirements.

Missing Angle

Missing angle means a edge gap is more than 1/4 and less than 1/2 values of the edge depth or edge width. The extent of this defect is much slither than the edge collapse defect. However, its causes are identical with the edge collapse. Therefore, its preventive measures are consistent with the edge collapse.

Micro Missing

Micro missing refers to a row of micro saw teeth are presented on edges. And it can be discovered by eyes observed carefully in compare with the edge collapse and the micro missing [START_REF] Chae | Investigation of micro-cutting operations[END_REF]. However, this defect is quite easy to be discovered if it is placed under the 20 or 30 times microscopes. So the defect judgment standards main rely on its appearance.

The main cause of micro missing is the surface of grinding wheel is too rough, resulting in a series of continuous micro saw teeth are generated on the milling edges by the grinding wheel's abrasives during the cutting process; another main cause is the initial speed of grinding wheel is too fast after finishing the wheel [START_REF] Yang | Study for increasing micro-mill reliability by vibrating milling[END_REF]. This defect can cause the result is that a serials of ripple type of cutting edges will present on products' surface, which can undoubtedly affect the quality of the PCB processing.

Preventive measures: First, The just repaired wheel should be slight grinded again by the whetstone wheel with micro size abrasives to further increase the grinding wheel surface's finish. Second, set the wheel with low-speed to grind in the beginning, and then gradually increase the speed to prevent the micro-missing of mill edges. Third, change the grinding wheel's rotation can reduce such defect according to certain rules in processing. Fish tail is the most critical part to determine mill to process, and its geometric size and shape can directly affect the quality of PCB products and the life of itself. The judgment standards include the fish-tail's shape asymmetry and the moon surface arc and so on.

The main cause of this defect as follows: First, the aperture grinding wheel has not located in the fish-tail axis center while processing, which can make the fish-tail edge points exist a height difference and the geometry size is asymmetrical [START_REF] Jun | Investigation of the dynamics of micro end milling -Part II:model validation and interpretation[END_REF]. This paper at first introduced the most common types of PCB mills that produced by domestic and foreign enterprises. And then combined with the author's many years' front-line production practice learned in enterprise, in-depth study various definitions and types of defects of the RCF-type PCB mills, and shows with the corresponding defective photographs to explain the meaning of various defects clearly. Besides, this paper has also studied the common causes of each defect and proposed the practical and feasible preventive measures. These measures have been practiced and achieved good results, which has advantage of improving the rate of finished products and reducing productive costs, and owns with a very important applicable value and widely promoted significance.

Fig. 1 .

 1 Fig. 1. Four types of PCB mills

Fig. 2 .

 2 Fig. 2. Blade-type errors with (a) Less a left spiral edge and (b) Without fish tail

Fig. 3 .

 3 Fig. 3. Edge collapse with (a) Front end edge collapse and (b) Fish tail edge collapse

Fig. 4 .

 4 Fig. 4. Missing angle with (a) Middle edge missing angle and (b) Fish tail edge missing angle

Fig. 5 .

 5 Fig. 5. Irregular fish tails with (a) Fish tail is asymmetry and (b) Moon surface arc


Xiaobin Qiu

Nan Zhou

Xin Wang

Design of Labour Agency Platform Based on Agent Technology of JADE

Keywords: labour agency, multi-agent, JADE 1、Introduction

Ordinary labour agency system provides services for clients with a data center which comprises single or multi servers according to the scale. And each server provides service of regular function. Therefore problems in security, load balance and extendibility may be involved. In this paper, a labour agency platform using an agent technology called JADE was designed, which effectively solved the problem of normal systems.

2、Agent and JADE

Agent refers to an entity which stays in specific environment with independent behavior and can interact with other agent at high-level. Agent technology supports analyzing, modeling, structuring and deploying the system by abstract concept and design concept of agent. As it provides high-level abstractions and natural modeling method to simplify the system development and control complexity, and especially

3、System Framework

Ordinary labour agency system usually includes a recruitment management subsystem, a job management subsystem and an information release subsystem. All functions which every labour service agency uses are completely the same. When using agent, each system can provide personalized functions in the main function consistent circumstance according to the agent requirements. For instance several labor agency systems can be deployed in a platform, namely, system 1, system 2, etc. All these systems may have the same functions or some personalized functions, but all interfaces must be completely consistent in order to provide a uniform service. These systems are equal between statuses. A system can work with other systems, or work alone while not suffered from any other system's influence. Platform structure is shown as Fig. 2. The function of each system platform is complete. All systems unite each other by agency communication channels. For users, it appears like one system. Consequently, not only every system on the platform has complete function, but also there is not any coupling between systems. Safety and extendibility of platform can be improved effectively.

In the design of labour agency platform, each system mainly includes a system management agent, a recruitment agent, a job agent, a recruitment broker agent and a job broker agent. System function structure is shown as Fig. 3.

Fig. 1

 1 Fig. 1 Agent platform architecture

Fig. 2

 2 Fig. 2 Labour agency platform architecture

Fund project:"The 11th five-year plan" National science and technology support projects (2006BAJ07B07) Author:Qiu Xiaobin(1977-),Male, Engineer, The main research direction for network technology and application.

Fig. 3 functions of the system platform

System management agent is responsible for managing the entire system agents.

When a job seeker arrives, system management agent will start the job agent and the job broker agent to serve it. Job agent manages the basic information of job seeker.

Job broker agent is primarily responsible for job seekers offering the right candidates.

In the same way, when an interviewer comes, system management agent will start the recruitment agent and the recruitment broker agent to serve it. Job broker agent and recruitment broker agent is in the many-to-many relationships. When a job broker agent inquires a recruitment position, multiple recruitment broker agents can provide recruitment posts for it. And it chooses the most suitable one for its recruitment broker agent.

4、System Implementation

The

Fig. 4 system realization model

Agent management platform is responsible for creating agent and managing the agent pool. JobInfoAgent and JobSeekerAgent are responsible for receiving the needs of users and paying the broker agent. Broker agent performs match and returns results according to the strategy library. To demonstrate the working process of the system implementation, an example of seeking a job launched by a job seeker is given below.

The recruitment process is similar.

When JobSeekerAgent obtains demand, it sends messages to all actived.recruitment agents, with the message type CFP.The content is job intension including salary requirement, site requirement, position requirement, etc. The purpose is to let recruitment agent send their recruitment information. Recruitment agent detects CFP message, inquires, starts recruitment broker agent and sends PROPOSE message to recruitment agent, if there is information matching the requirements. The content of message is recruitment information. When job agent detects PROPOSE message, job agent will start the job broker agent, create a list of job agents and send the list as a parameter to the job broker agent. Job broker agent performs matching with recruitment broker agents according to related conditions. If matched, job broker agent will send an ACCEPT message to the recruitment broker agent, or send a REJECT message to it. The agent which detects the ACCEPT message is the recruitment agent selected by job broker agent. The recruitment agent sends an OK message whose content is the information of matching successfully. Job agent detects the OK message, confirms the success of the employment and notifies users. If match fails, the process will start again.

5、Conclusions

Labour agency system is implemented by multi-agent with JADE. It can effectively improve the platform for safety and expansibility, and can implement load balance better than other systems. Not only can JADE implement multi-agent in one machine, but also in multi machines and can be deployed distributedly. Currently the implementation is in only two machines due to the actual platform situation. The improvement of the system can mainly be in the efficiency of system strategy and the further promotion in the future.


Yan Xue
email: xueyan@mail.caas.net.cn

Yeping Zhu

GIS-based Regional Agricultural Economic Information Query and Analysis System

Keywords: GIS-based "Regional Agricultural Economic GIS, Agricultural Economic, Information Query

Information Query and

Analysis System" built on spatial attribute characteristics of statistical information implements dynamic information query, dynamic generation of statistical charts and tables, and dynamic generation of spatial distribution map with geographic attributes and specialized charts, and provides a solid basis for researching geographic distribution of agricultural economic information, analyzing issues concerning the agriculture, countryside and farmers from micro and macro perspective, and making macro decisions scientifically and rationally. This paper provides the system architecture design and related function demonstration, and discusses further development direction of the system.

Introduction

Fast growth of the information age poses higher requirements on statistical data informatization -requiring the integration of statistical data and spatial information resources to provide comprehensive and deep statistical analysis, as well as more timely and complete information services. Hence, with the fast development of social informatization and geographic space technology, the integration of statistical information and geographic space information resources has become an important part in the construction of statistical data system. [START_REF] Li | Application of Geospatial Information and Technology in E-Government[END_REF][START_REF] Zhang | Technology of Rural Socio-Economic Statistical System Based on GIS[END_REF] Geographic Information System (GIS) is a computer system capable of collecting, storing, managing, analyzing, displaying and applying the data related to spatial geographic distribution on entire or part of the earth surface, and it is a universal technology for analyzing and handling massive geographic data. [3][4] GIS is an emerging frontier discipline incorporating the computer science, geography, surveying and telemetry, environmental science, urban science, spatial science, information science and management science. GIS has experienced amazing progress over the past 30 years with improving functions, increasingly showing its powerful vitality and bright prospect. At present, GIS has been widely applied in many areas including city planning, transportation, agricultural production, natural resource investigation, ecologic environment assessment, facilities management, etc.. [START_REF] Sun | Application and Advance of Geographic Information System in Agriculture [J[END_REF][6] Since 1980s, "Rural Economic Information Database" that focuses on agricultural and rural economic statistical information has covered agricultural economic information with spatial implication in Chinese counties involving the population, farmland, crop production, etc. Since then, it has been primarily used in government agencies and research institutions, while "Regional Agricultural Economic Information Query and Analysis System" built on data resources closely related to this geographic information implements dynamic information query, dynamic generation of statistical charts and tables, and dynamic generation of spatial distribution map with geographic attributes and specialized charts by utilizing the database technology and GIS technology, and provides a solid basis for researching geographic distribution of agricultural economic information, analyzing issues concerning the agriculture, countryside and farmers from micro and macro perspective, and making macro decisions scientifically and rationally.

System Design Objective

To research, analyze, design and develop functions of "Regional Agricultural Economic Information Query and Analysis System" based on the database and GIS technologies, the system should realize the following main objectives:

1

To research visualized query and management of statistical information; provide such functions as information display, query and retrieval.

2

To implement statistical information analysis by utilizing spatial information analysis technology, so as to provide the analysis of agricultural economic information with spatial attributes for agricultural managers and decision makers.

3

To encapsulate system functions as GIS component objects and business logic component objects by utilizing the component technology, and implement the system integration by connecting the component objects to make the system scalable.

As critical information resource of the country, the confidentiality and security of rural economic statistical data are of very importance. Strict encryption management mechanism shall be established for the system to guarantee the database security.

System Function Structure

County economy overview

Analysis and Statistics Ranking modules provide nationwide province and county information query, statistics and analysis in the form of spatial distribution map and chart. In Specialized Data module, the system is preconfigured with advantageous industry zone of agricultural products, regional layout of unique agricultural products and nationwide agricultural product trading market through which specialized distribution map can be created by means of the query. At the same time, self-defined topic is designed, allowing the user to create the specialized item and form the specialized item distribution map as needed. Related information displayed in above modules can be saved, printed or output in file.

Realization and Presentation of System Function

The system can run on WinddowXP/2000 or higher. In order to ensure the system operation and background data security, the encryption lock shall be used during the software operation.

This system takes full advantages of powerful graphic presentation capability of GIS platform to provide numerous view presentation means and present the information queried and analyzed on geographic map by means of "What You See Is What You Get", allowing the user to have a visualized perception and operation platform.

Region Introduction

This module presents agricultural and rural economic information of each province or county. In general, there are two options for selecting the information to be displayed: by clicking on related icon in the window, for example: clicking on the location of the region on the map to display related information of this region, or by inputting the name of the region to be displayed in relative window, then the system will search automatically and display all information of this icon in the database. Currently, there are 31 provinces, municipalities and autonomous regions, as well as over 2800 cities and counties in China, hence, this system displays related information of each province by clicking on the location of each province (see Figure 2), and displays the information of each county through the county search function by inputting the county name (see Figure 3).

Information Query & Analysis

For users, it is especially important to capture, seize and analyze related information anytime as needed. This module provides the province or county query result in the form of the map and table quickly by clicking the year and region easily and quickly (see Figures 4 and5), and displays the data change in the form of the chart for the purpose of analyzing agricultural and rural economic information (see Figure 5).

Statistics Ranking

This module is designed to meet conventional demand of users for the utilization of agricultural economic information. Through this platform, the users can view statistics ranking of hot regions or important agricultural economic indicators they concern (see Figure 6).

Specialized Data

This module is mainly used by decision making department of the government and macro researchers. In this module, the system has provided the information of agricultural production and agricultural product market distribution in the country, and can display, search, locate on the map and output relative specialized information easily as needed (see Figure 7). In addition, the system is designed to provide self-defined topic function, enabling the user to design different specialized data at will and create the specialized data distribution chart to respond to instant or urgent event, and understand related agricultural and rural economic information of different regions in real time. Of course, the system function needs further enrichment and improvement, for example, further researching and realizing and deep mining of basic data by utilizing the modeling technique, GIS route analysis and buffer analysis.

Conclusion and Discussion

Fig. 1 .

 1 Fig. 1. System Function Structure.

Fig. 2 .

 2 Fig. 2. Displays information of each province.

Fig. 4 .Fig. 5 .

 45 Fig. 4. The province query result.

Fig. 6 .

 6 Fig. 6. Statistics Ranking.

Fig. 7 .

 7 Fig. 7. Specialized Data.

"

  Regional Agricultural Economic Information Query and Analysis System" takes full advantages of spatial data organization capability and spatial analysis capability of GIS technology. It can not only provide scientific and accurate basic agricultural economic data timely, accurately and comprehensively, but also lay a solid foundation for drilling down and analyzing the data of different years and different indicators, improving the data management, development and utilization level, driving the systematic management and sharing of basic data, and realizing the resource management informatization. The system has been used by related government agencies and agricultural statisticians. The result shows that the system function design accords with the work characteristics of users, and provides scientific and effective means and methods for improving the productivity and realizing the value of the data.


Mingli Ding
email: dingmingli2006@gmail.com

Dongmei Yang

Jindong Zhao

Lili Zhuang

Research on Static Decoupling Method of Non-gyro Micro Inertial Measurement Unit

Keywords: Non-gyro micro measurement unit (NGMIMU), decoupling, total least squares (TLS)

In a non-gyro micro inertial measurement unit (NGMIMU), the coupling error reduces the system measurement precision obviously. Based on the definition of the coupling error, a new static decoupling method applied total least squares (TLS) algorithm is proposed. TLS considers not only the error of accelerometer output, but also the calibrating error of the input signal arising from the couple factor. Based on TLS, the solution of the coupling coefficient equation has the characteristic of minimum norm to the input and output values. In the navigation parameter estimation, according to the relationship of the accelerometer input and output value, the accurate estimated input value can be acquired through fitting the couple coefficient matrix using TLS and reconstructing the input value using Moore-Penrose generalized inverse matrix. A simulation case for estimating angle rate is investigated by this approach. The results show that the ratio of decoupling error is less than 8% and verify the feasibility of the static decoupling method.

Introduction

Most current micro inertial measurement units (MIMU) use linear accelerometers and gyroscopes to sense linear the acceleration and angular rate of a moving body respectively. In a non-gyro micro inertial measurement unit (NGMIMU) [START_REF] Schuler | Measuring Rotational Motion with Linear Accelerometers[END_REF][START_REF] Shmuel | A Nongyroscopic Inertial Measurement Unit[END_REF][START_REF] Tan | Design of Gyroscope-free Navigation Systems[END_REF][START_REF] Lee | Innovative Estimation Method with Measurement Likelihood for All-accelerometer Type Inertial Navigation System[END_REF][START_REF] Kao | Design and Analysis of an Orientation Estimation System Using Coplanar Gyro-free Inertial Measurement Unit and Magnetic Sensors[END_REF][START_REF] Jinsong | Optimum technology for non-gyro micro inertial measuring unit[END_REF] , accelerometers are not only used to acquire the linear acceleration, but also replace gyroscopes to compute the angular rate according to their positions in three-dimension space. NGMIMU has the advantages of anti-high g value shock, low power consumption, small volume and low cost. It can be applied to some specific occasions such as tactic missiles, intelligent bombs and so on.

A generalized definition of couple is that the response of an actuation includes the additional information about the other actuation which would not affect the response. In a NGMIMU system, the couple defines that the output of a single-axis accelerometer contains the additional information of the other accelerometer in other direction. The static couple indicates that the coupling degree is fixed whether the measuring time and measuring conditions change or not. We use the coupling coefficient to denote the coupling degree. The static couple mainly arises from the following reasons: a. the sensing axis of the accelerometer produces a deviation due to the low precision of the accelerometer itself; b. the low machining precision of the rigid body which bears the weigh of the accelerometer; c. the low mounting precision of the accelerometer; d. it is difficult to realize in physics that all the accelerometers mount at one point on the rigid body when some algorithms are expected. When the accelerometer coupling error is small, the measurement value of the angular rate will distort seriously. So the study of the decoupling method is expected urgently. The key problem of the static decoupling method is to estimate the coupling coefficient. The traditional least squares algorithm could not acquire the ideal estimation precision for it considers only the output error of the accelerometer.

In this paper, Total Least Squares algorithm-TLS [START_REF] Valaee | Localization of Wideband Signals Using Least-Squaress and Total Least-Squaress Approaches[END_REF][START_REF] Kubus | On-line estimation of inertial parameters using a recursive total least-squares approach[END_REF][START_REF] Yang | Constrained Total Least-Squares Location Algorithm Using Time-Difference-of-Arrival Measurements[END_REF] is applied in the novel static decoupling method. This method reconstructs the linear calibrating input signal under the condition that there exist errors not only in the input signal but also in the output signal. The signal reconstructing has two steps: step 1. fitting the couple coefficient matrix by using TLS, step 2. reconstructing the calibrating signal by using Moore-Penrose generalized inverse matrix.

Accelerometer Output Equation

As all know, the precession of gyroscopes can be used to measure the angular rate. Based on this principle, MIMU measures the angular rate of a moving body. The angle value can be obtained by integrating the angular rate with given initial conditions. With this angle value and the linear acceleration values in three directions, the current posture of the moving body can be estimated.

NGMIMU uses linear accelerometers to measure the angular acceleration of the body, and the relationship between the linear acceleration a and the angular accelera- tion  is

    r a . ( 1
)
The angular rate in a certain direction can be calculated by using the linear acceleration between two points. To obtain the linear and angular motion parameters of a moving body in three-dimension space, the accelerometers need to be appropriately distributed on the moving body and the analysis of the accelerometer outputs is needed.

An inertial frame and a rotating moving body frame are exhibited in Fig. 1, where b represents the moving body frame and I the inertial frame. An inertial frame and a rotating moving body frame are exhibited in Fig. 1, where b represents the moving body frame and I the inertial frame. The acceleration of point M is given by

) ( 2 r r r r R a b b I                    , (2)
) ( r r R a I             . ( 3
)
Thus the accelerometers rigidly mounted at location i r on the body with sensing direc- tion i  produce i A as outputs.

) ,...,

[ N i r r R A i i i I i            , 2 , 1 ( ]
where

               0 0 0 x y x z y z       ,            Iz Iy Ix I R R R R         . (5)
In ( 5),

                                                       0 0 0 . (6)
Using ( 4) and    , we have

  i T i I T i T i i i T i T i i I T i i i i I i r R r r r R r r R A 2 2 ) ( ) ( ) (                                        . ( 7
)
3 Analysis of Static Couple of NGMIMU

Nine-accelerometer Configuration

The study of the decoupling method is based on the nine-accelerometer configuration of NGMIMU in [6]. The locations and the sensing directions of the nine accelerometers in the body frame are shown in Fig. 2. Each arrow in Fig. 2 points to the sensing direction of each accelerometer.

X Y Z A 1 A 2 A 3 A 4 A 5 A 6 A 7 A 8 A 9

Fig. 2. Nine-accelerometer NGMIMU configuration

The locations of the nine accelerometers are

             0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 , , 9 1 l r r  , ( 8
)
where l is the distance between the accelerometer and the origin of the body frame. The sensing directions are

             1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 , , 9 1    . ( 9
)
It is easy to obtain

                  0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 , , 1 1 1 1 l r r    . ( 10
)
Using (7), the accelerometer output equation can be acquired as

                                                                                                     y x z x z y z y x Iz Iy Ix z y x i l l l l l l R R R l l l l l l A             2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0          . ( 11
)
With (11), the linear expressions are

) ( 2 1 7 6 9 4 A A A A l x       , ( 12a
)

) ( 2 1 8 1 7 3 A A A A l y       , ( 12b
)

) ( 2 1 4 2 5 1 A A A A l z       , ( 12c
)

Analysis of Static Coupling Error

In (12), the angular accelerations are all expressed as the linear combinations of the accelerometer outputs. The conventional algorithm computes the angular rate as the time integration of the equations in (12), and gets the rotation matrix of the body frame with respect to earth frame by using a numerical solution, then calculates the posture parameters of the moving body by using the relationship of the elements in the rotation matrix.

According to the definition of the couple and the reasons for the static coupling error, the static couple of the accelerometer can be regarded as the situation that there is a small angle between the sensing direction of the accelerometer and the body coordinate axis as shown in Fig. 3.

X Y Z A 1 α 1 β 1

Fig. 3. Real location of accelerometer

For being simple and convenient, the cross coupling problem of 1 A , 4 A and

7

A is specially discussed here. In an idea case, Obviously the computed angular rate has the coupling error and will bring the posture error to the navigation parameters. Assume that the angles between The real accelerometers outputs are

1 1 1 1 1 1 1 sin cos sin cos cos C A A A A z y x          , ( 13a
) 2 2 2 2 2 2 4 cos sin cos cos sin C A A A A z y x          , ( 13b
)
3 3 3 3 3 3 7 cos cos sin cos sin C A A A A z y x          . ( 13c
) where x A , y A , z
A are the real accelerations in three directions. In the course of decou- pling, we replace them by the setting input signal calibrated, which all include the calibrating errors. In (13),

1 C , 2 C , 3
C are the static zero drift errors of the accel- erometers respectively. From (13a), we arrive that 1 A includes two real output compo- nents of the two accelerometers which are perpendicular with x axial, and A have the similar outputs. Based above, it is found that there exists errors not only in the calibrating values of the accelerometers A . In order to increase the estimation precision of the NGMIMU system, the decoupling method to the corresponding coupling error should be carried on.

Static Decoupling Method

where

n m R A   , n R x  , m R b  , n m  .
b Ax    . ( 15
)
But in fact, A is often formed by the input signal and the output signal of the system which inevitably have errors. So the best prediction method is to consider the deviations both in A and b . This is the key point of the TLS. Assume A and b have the deviation errors E and e at the same time, ( 14) can be rewritten as

e b x E A    ) ( . ( 16
)
Now we calculate (16) by using TLS. Change (16) into

0 ) (   z D B , (17)
where

  A b B :   ,   E e D :   ,        x z 1
. So the solution of (17) can be express as to find a vector z such that

min 2  D , ) ( ) ( E A range e b    , (18)
where

2 1 1 1 2 2             m i n j ij d D
. And to the given function ( 17), TLS can find a vector TLS x such as the following consistency equation Let singular value decomposition (SVD) of matrix B be

) ( ) ( E A range e b    , (19)
* USV B 
, whereU is an unitary matrix with size m m ,

V is an unitary matrix with size n n  ,  V is the associ- ate matrix of V , S is an diagonal matrix with size n m  and the elements in its leading diagonal is non-negative.

Analysis of the Decoupling Method

Basing the analysis in 3.2, (13) can be expressed by

out IN A A H   , ( 20
)
where H is the coupling coefficient matrix and its value is

          3 3 3 3 3 3 2 2 2 2 2 2 1 1 1 1 1 1 cos cos sin cos sin cos sin cos cos sin sin cos sin cos cos C C C                , IN A
  m k A A A A A A k k k zk yk xk , , 1 , , , , , , 7 4 1 
  from (20)
. First consider to fit the first row of H and substitute the measured data into (20), and we get

                                 1 1 1 1 1 1 1 1 1 1 11 sin cos sin cos cos 1 1 C A A A A A A A A zm ym xm z y x m           . ( 21
)
The solution of the linear equation is the first row of the coupling coefficient matrix. But for that both of the calibrating matrix IN A of the accelerometer input and the ac- celerometer output matrix out A have errors, we can not arrive the solution with high precision by using the traditional method. While using TLS, the solution to (21) has the minimum norm to

Simulation Results

After analyzing the static decoupling method to the accelerometer of the NGMIMU system mentioned above using TLS, simulations of the system with different coupling angles are performed respectively in this section. Table 1 and Table 2 illustrate the measured results and the output values of the angular rate after decoupling by using the method in this paper with different sampling numbers, respectively. In the simulation, the initial conditions in position, velocity, posture angle and angular rate are

0 ) 0 (  x m, 0 ) 0 (  y m, 0 ) 0 (  z m, 0 ) 0 (  x v m/s, 0 ) 0 (  y v m/s, 0 ) 0 (  z m/s, 0  x  rad, 0  y  rad, 3    z rad, 0 ) 0 (  x  rad/s, 0 ) 0 (  y  rad/s, 0 ) 0 (  z  rad/s
respectively. The accelerometer static bias is 10 -5 g. The sampling time is 10ms. Fig. 4 is curve of the decoupling error at different coupling error.

Fig. 4. Curves of decoupling error

From Table 1, Table 2 and Fig. 4, it is obvious that the value of the angular rate before decoupling distorts seriously no matter what the coupling angle is. Under the situation of the same coupling angle, with the increasing of the sampling numbers, the decoupling error ratio ( % 100   z z zh

  

) is smaller and smaller. The value of the decoupling error ratio is smaller than 8% and near to 0. The increasing estimating precision is due to the increasing sampling points which fit the coupling coefficient matrix correctly. Comparing Tab.1 and Tab.2, it is obvious that the decoupling error ratio in Tab.1 is less than that in Tab.2. The reason is that the larger the coupling angle is, the serious the distortion degree of the accelerometer is. The simulation results show that the static decoupling method can reconstruct the input signal with high precision effectively.

The static coupling error is one of the main system errors which seriously affect the estimating precision when the navigation calculation is being carrying on to a NGMIMU system. The decoupling problem can be transform into a problem of solving an equation by changing the system mathematics model with coupling error into a format like b AX  . In this paper, the decoupling method by using TLS and Moore- Penrose generalized inverse matrix considers not only the error of the accelerometer output but also the error of the input signal for calibrating the system. The method highly improves the estimating precision of the coupling coefficient and the reconstructing precision of the input signal. And it is necessary to be home in on the analysis of the dynamic coupling error with nonlinear characteristic in further research.

Fig. 1 .

 1 Fig. 1. Geometry of body frame (b) and inertial frame (I)



  acceleration of point M relative to body frame.  is the tangential acceleration owing to angular acceleration of the rotating frame. If M is fixed in the b frame, the terms b r  and b r  vanish. And (2) can be rewritten as



  represent the angular rate along x, y and z axis respectively;

1 A , 4 A and 7 A 1 A 4 A , 7 A

 147147 are the three accelerometer outputs which are perpendicular each other in the configuration. But due to the static coupling error, the outputs of the accelerometer includes the additional acceleration information from the other two accelerometer .

4 A and 7 A

 47 have the similar case.

1 A , 4 A , 7 A 1  , 4  , 7  1  , 4  , 7 

 147147147 and the horizontal direction of the coordinate axis where the corresponding accelerometer locates are , respectively, the altitude angles are , respectively.

4 A

 4 and

7

 7

7

 7

  Calculating (14) by using the Least Squares algorithm is equivalent to seek the solution obvious that the calculation is based on the assumption that the vector b has a deviation b  and the coefficient matrix A has no deviation, (14) becomes b

  obvious that the TLS solution has the minimum norm with respect to A and b simultaneously.

A.

  simultaneously by using TLS. We also can find the TLS solution of the second and third row of H by using the same method. Now we reconstruct the input signal  For that the coupling coefficient matrix TLS H is acquired, there exists an input signal with respect to the measured output signal fulfill (20), namely of the Moore-Penrose generalized inverse matrix , we get get the angular acceleration without coupling error.

  is the calibrating matrix of the

	accelerometer input and is express by  A x		A	y	z A	 T 1 ,	out A is the accelerometer
	output matrix and is express by 	1 A	4 A	7 A	 T	.
	If	we	measure	the		system	m	times,	we	get

Table 1 .

 1 Decoupling results when coupling error is 0.001rad.

	Sampling	Real value	Before decouping	After decoupling	Decoupling
	number N	ωz (rad/s)	ωz c(rad/s)	ωzdc (rad/s)	error (%)
	10	0.000499	0.000815	0.000548	9.82
	50	0.002397	0.003683	0.002550	6.38
	100	0.004207	0.006736	0.004452	5.82
	150	0.004987	0.008811	0.005243	5.13
	200	0.004564	0.009722	0.004769	4.49
	300	0.000756	0.034278	0.000801	5.95
	400	-0.003784	0.039546	-0.003626	3.25
	500	-0.004794	0.048781	-0.004648	3.05

Table 2 .

 2 Decoupling results when coupling error is 0.005rad.

	Sampling	Real value	Before decouping	After decoupling	Decoupling
	number N	ωz (rad/s)	ωz c(rad/s)	ωzdc (rad/s)	error (%)
	10	0.000499	0.001879	0.000574	15.03
	50	0.002397	0.008616	0.002605	8.67
	100	0.004207	0.016490	0.004549	8.13
	150	0.004987	0.022333	0.005385	7.98
	200	0.004564	0.028845	0.004921	7.82
	300	0.000756	0.036292	0.000825	9.12
	400	-0.003784	0.043270	-0.003563	5.84
	500	-0.004794	0.056988	-0.004577	4.53

Acknowledgments. This work is supported by "the National Natural Science Foundation of China" (Grant No. 60901042 and No. 61171189) and "the Fundamental Research Funds for Central Universities" (Grant No. HIT. NSRIF. 2010105).


Yong Wang

Xiaorong Zhu

Yongxing Jia

Changying Ji

Object Recognition on Cotton Harvesting Robot Using Human Visual System

Keywords: attention mechanisms, human visual system, cotton, object recognition

Object recognition is one of the hottest issues in the field of vision system for harvesting robot. How efficiently and accurately to remove the background and get the object in image is the key research. The attention mechanisms of human visual system (HVS) can be segmented an image into the region of interesting (ROI) which is considered important and the background which is less important, and recognized the object from ROI using the local information. In this paper, an algorithm based on the characteristic of HVS is proposed. In algorithm, the image was partitioned into many blocks of equal size. ROI was got through calculating the factor of weight of each sub-block image, and the object was extracted by segmenting the ROI. Experiment results show that the algorithm can be recognized the object efficiently and accurately.

A new method for vision system of harvesting robot is provided.

Introduction

Two main tasks of harvesting robot are to recognize and locate the object and to harvest the object without damaging. The first task recognize and locate the object is the key task. This task determined how the harvesting task can implement smoothly.

The principal objective in the first task is to extract the object which was interesting from the image, in order to prepare for subsequent image processing steps. Nowadays, there are many methods for object reorganization, such as using the color difference between object and background. Some researchers use color difference (R-G) and color difference ratio (R-G)/(G-B) to recognize the apples [START_REF] Yongsheng | Recognition and shape feature extraction of apples based on machine vision[END_REF][START_REF] Xining | Research on Lane Detection Based on Improved Hough Transform[END_REF][START_REF] Yong | Using Color Data and Shape properties for Cotton Fruit Recognition[END_REF]. The experiment results showed this method can eliminate the inferences of shade, backlighting and soil. The recognition rate reaches above 90%. Others use the spectral reflection ration of different parts of the crop [START_REF] Ting | Feature Acquisition of Cucumber Fruit in Unstructured Environment Using Machine Vision[END_REF][START_REF] Henten | An autonomous robot for harvesting cucumbers in greenhouse[END_REF]. These methods have a good effect for recognizing object. However, there is no considering the biological visual characteristics, especial the characteristics of human vision, to recognize the object. The human eyes were formed a unique visual characters in the long evolutionary history. The human eyes can recognize the target accurately and quickly in the complex environment. So many researchers are interesting in the biological vision. Liu Changqin [START_REF] Liu Changqin | A model of Motion Direction Detection based on Biological Vision[END_REF] present a model of motion direction detection based on the characteristics of sustained-transient cell of biological vision, and simulated on the computer. The experiment results show this model can recognize the motion direction of object. Song Nong [START_REF] Nong | Applications of human visual attention mechanisms in object detection[END_REF] developed an auto target recognition algorithm employing attention mechanisms with bottom-up and top-down control strategies. The experiment results show the objects for detection using the algorithm is effectively. Other researchers [START_REF] Mu | An Adaptive Image Enhancement Algorithm based on Human Visual properties[END_REF][START_REF] Mu | An Adaptive Color Image Enhancement Algorithm Based on Human Visual Properties[END_REF][START_REF] Libo | Application of human visual system in extraction of plant leaf image[END_REF][START_REF] Saghri | Image quality measure based on a human visual system model[END_REF][START_REF] Jian | Research on Target Recognition Technology based on Local Feature[END_REF][START_REF] Wei | Method of image quality assessment based on human visual system and structural similarity[END_REF] present their own algorithms for image process based on the research of biological vision. Therefore, the bionic vision will be a hottest field for the future research [START_REF] Wei | Study on Biological Vision[J][END_REF][START_REF] Xingzhong | Object Recognition Models Based on Primitive Visual Cortices: A Review[J][END_REF]. This paper developed an algorithm for cotton recognition using the characteristic of attention mechanisms of HVS.

The rest of the paper is organized as follows. In Section II we introduce the materials of experiment throughout the paper. In Section III an algorithm using four factors of attention mechanisms of HVS can be found. We present some experiment results in Section IV. Finally, we conclude the paper in Section V.

Materials

This subject is Suman-12 which was in mature period Jiangpu farm of Nanjing Agricultural University. The color images in the outside were acquired by a digital color CCD camera WAT-231S in October. The image acquisition card is Matrox Meter-II/Standards. The color signals from WAT-231s were transferred by the image acquisition card as a 24-bit RGB color image and processed using Lenovo X200

Computer, the CPU is Intel Core2 Duo 2.4GHz, the memory is 2GB, and OS is Windows XP. The color images were taken at the time from 10:00 AM to 4:00 PM. These images were taken under sunny and cloudy weather. So the machine vision system is composed of a color CCD camera to acquire the cotton image, the image acquired card to transferred the analog signal to digital signal, and the PC to process the acquired image. The machine vision is shown as Figure 1. To extract the ROI, the main factor affected human eyes are to be considered, such as the impact factor of brightness, contrast, sharpness and location. To calculate the effect of four factors mentioned above. First the image was blocked sub-image by equal space. Set the size of each block is m and n, and then calculated the impact factor of each block, obtained the weight factor  of each blocks through normalization. Finally, the background was removed and ROI was remained based on the value of weight factor of  .

Brightness Factor

Brightness factor describes the sensitivity level of human eyes to light. It is measured through Weber-Fechner law that is the relationship between the physical magnitude of stimuli and the percered intensity of the stimuli is the logarithm. This kind of relationship can be expressed as Equation (1):

0 I I lg k s  . ( 1
)
where k is the constant factor, I is the mean brightness of each block, I 0 is the absolute threshold, generally taken the maximum brightness value of each block.

Contrast Factor

Contrast factor describes the sensitivity level of human eyes to changed detail in image which can be expressed by variance. It can be expressed as Equation ( 2):

2 2 1 1 1 1 1 1 ( , ) ( , )
m n m n i j i j d f i j f i j m n m n                 . (2)
where ( , ) f i j is the gray value of pixel(i, j).

Sharpness Factor

Sharpness factor describes the resolution of human vision. It can be expressed through the gradient. It can be written as Equation (3):

2 2 1 1 ( , ) ( , ) mn H
V i j f i j f i j k mn         . (3)
where ( , )

H f i j and ( , )
V f i j is the horizontal and vertical gradient, respectively.

Combining the horizontal and vertical gradient yields the spatial gradient.

Location Factor

Location factor describes the degree of interest in the different parts of image. It can be express as Equation ( 4):

2 0 0 max ( ) ( ) 1 (1 ) i c i c x x y y r B r       . ( 4
)
where B is the basic weight value, the range value is [0, 0.5],

Weight Factor

The four factors of each sub-block were considered, i  was used to evaluate the importance of each sub-block. i  is expressed as Equation ( 5):

2 2 2 2 i s d k r      . ( 5
)
In order to decrease the influence of the absolute error of i  , the i  was progressed by normalized. The weight vector of  is expressed as Equation ( 6):

1 i N i i       . ( 6
)
where N is the number of block. Now, the importance of each block can be expressed by the vector of  . It is matched with the characteristic of human eyes. We call it as weight factor. If the value of  is smaller than threshold, then the gray value was become zero, otherwise, the gray value is no changed. Then ROI can be extract through all the vector  . The object of interesting can be got through segmenting ROI. The formula is expressed as Equation ( 7):

, 1, 2, 0, i I T I i N T          . ( 7
)
where T is the threshold, N is the number of blocks.

Figure 2 shows the cotton recognition algorithm which was mentioned above. The process starts with the factor functions for segmentation. After segmenting the image, a low pass filter was conducted to remove noise. Then the features of object were labeled, such as area, perimeter, etc, from the binary image. These features were used to locate the cotton in 3-dimension space. It can be seen that almost all the interesting object could be recognized by the proposed method. However, the number of sub-block images is changed by manually.

Under cloudy weather, the segmentation achieved good results when the number of sub-block images is 4×4. The object segmentation will be failure when the number of sub-block image is too many, for extraction of ROI is incomplete. Otherwise, the segmentation will be failure because too many background joining in ROI. Therefore, the number of sub-block will be changed interactive in order to achieve good results.

It can be seen from the experimental results. The segmentation results under cloudy weather are better than sunny weather. The brightness of leaves and ground closed to the cotton fruit under sunny weather that lead to mistake between leaves and fruit. There is spot noise after segmentation. It needs further process to remove the noise.

Conclusions

We proposed an algorithm to detect the object. The algorithm is based on the attention mechanism of human vision so that some experiments were conducted to investigate how effective and accurate it is. The experiment results show that the algorithm is effective and accurately at extracting the object present in complex scene. However, the accurate of detection is better under cloudy weather than sunny weather. Under the sunny weather, there is spot noise after the recognition of ROI. It needs further process to extract the object.

Fig. 1 .

 1 Fig. 1. composition of machine vision

  center coordinate of original image, 00 , cc xy is the center coordinate of each block image, respectively, and max r is the maximum distance from each point to the center coordinate of original image.

Fig. 2 .

 2 Fig. 2. cotton recognition algorithm

This work is supported by the Natural Science Foundation of China(No.61001078), China Postdoctoral Science Foundation(2010047065), the Postdoctoral Science Foundation of Jiangsu Province(0902005C), Youth Foundation of College of Science(QNDZ200905).


Weiming Cai

Songming Zhu

Huinong He

Zhangying Ye

Fang Zhu

Research on Decoupling Control in Temperature and Humidity Control Systems

Keywords: Dry-and-wet Bulb Method, Coupling Problems, Fuzzy Neural Network, Wavelet Basis, Temperature and Humidity

Temperature and humidity are two highly coupled variables in a control system, which need to be decoupled for effective control. Moreover, the coupling problem may get more severe and the two control loops may produce a strong interference to each other that can cause system instability when the humidity is measured by dry-and-wet bulb method. In this study, a control method based on fuzzy-neural-network was studied for solving the coupling problem. The shape of membership function can be adjusted in time by using a wavelet basis as the fuzzy membership function. An effective real-time decoupling control system for temperature and humidity could be realized by neural network fuzzy inference. Decoupling control tests were conducted in a control room with 1.6 m × 1.0 m × 4.0 m. The results show that the performance of the control system on dynamic response speed, stability, and anti-jamming have been improved after decoupling.

Introduction

Coupling problems widely exist in nonlinear time-varying systems with multiple inputs and outputs. One of the major technical difficulties in designing a measurement and control system is to control the coupling objects effectively [START_REF] Tan | Online relay automatic tuning of multi-loop PI controllers[END_REF]. The objects need to be decoupled for effective control. Most of traditional method of decoupling control is built on the basis of a mathematical model, however, it is hard to establish accurate mathematical model for many production process [START_REF] Kim | Independent joint adaptive fuzzy control of robot manipulator[END_REF]. As a kind of multivariable nonlinear system, control systems of temperature and humidity are widely embedded in many products such as temperature and humidity environmental chambers, drying box of agricultural products, food processing ovens, etc [START_REF] Putranto | Application of the reaction engineering approach (REA) for modeling intermittent drying under time-varying humidity and temperature[END_REF][START_REF] Jin | modelling evaporation-boiling phenomena during vacuum cooling of cooked meat[END_REF][START_REF] Varela | Design and implementation of a strategy of predictive control of paddy rice drying[END_REF]. The performance of those products mainly depends on the control veracity of temperature and humidity, however, there is coupling between the two variables, and it is very difficult to improve the accuracy for the needs of high quality products by using traditional control methods [START_REF] Schoen | A new empirical model of the temperature-humidity index[END_REF]. Decoupling Control has been already proved to be a *Corresponding author. E-mail: nnhe@mail.hz.zj.cn key technique for building temperature and humidity control systems for high quality products.

In recent years, fuzzy neural network provides a new way to solve problems that can't be done by traditional methods in the field of control [START_REF] Lin | Adaptive hybrid type-2 intelligent sliding mode control for uncertain nonlinear multivariable dynamical systems[END_REF]. Fuzzy control does not require precise mathematical description of the control object in achieving good control of the system, however, factors such as nonlinear, time-varying and random interference of the system may result in inappropriate or incomplete fuzzy control rules which will affect control performance [START_REF] Ren | Classified real-time flood forecasting by coupling fuzzy clustering and neural network[END_REF][START_REF] Soyguder | Fuzzy adaptive control for the actuators position control and modeling of an expert system[END_REF]. Neural network has good capacities in nonlinear processing, self-learning, self-organizing, and adaptability although it needs long training time and its dynamic characteristics are not ideal [START_REF] Mahdavi | A New Set of Sufficient Conditions Based on Coupling Parameters for Synchronization of Hopfield like Chaotic Neural Networks[END_REF]. Fuzzy neural network is the combination of fuzzy control and neural network, and it can not only integrate the merits of both fuzzy control and neural network, but also can overcome their shortcomings. Therefore, this new method makes it possible to build higher precision control systems in products with coupling problems.

Nowadays, products with core of temperature and humidity control system such as environmental chambers are widely used in agriculture, aerospace, military, electronics, and other fields. It is the objective of many scientists and engineers to improve the performance of those products and to meet the requirements for higher accuracy in control process. In order to look for a new way in designing high quality temperature and humidity control systems, a novel method was proposed to improve the decoupling effects in a temperature and humidity control system in the paper.

Coupling in Temperature and Humidity Control Systems

The temperature and humidity will have effect on each other in an environment; changes from temperature will result in humidity fluctuating, and the temperature will also get a certain influence from humidity variety. Relative humidity (RH) is usually measured by dry-and-wet bulb method: To detect air temperature by a thermal resistance sensor, namely the dry-bulb temperature; and to detect the temperature of the veil kit soaked in distilled water by a same thermal resistance sensor, namely the wet-bulb temperature. The mathematical formula can be derived through the heat transfer theory and thermodynamic theory as follows:

  100     g s g s h E T T NP E X (1)
Where: X h is the relative humidity %; E s is the saturated water pressure under wetbulb temperature; E g is the saturated vapor pressure under dry bulb temperature; N is a constant related with wind speed; P is atmospheric pressure; T g is the dry-bulb temperature ; T s is the wet-bulb temperature.

The control of temperature and humidity is generally based on the principle of balances on temperature and humidity. Customarily, temperature homeostasis is realized through heating by a heater and refrigerating by a cooler or adding cold air; simultaneously, the humidifier (usually produced by heating steam) is work together with a dehumidifier (Generally by cooling and dehumidification condensation through the heat exchanger) for achieving dynamic equilibrium of humidity.

Fig. 1. Schematic diagram of measurement and control for room temperature and humidity

However, this kind of method for temperature and humidity monitoring and control may produce coupling problem. As Fig. 1 show, the temperature of dry bulb will decrease quicker than the wet bulb when the temperature in the regulation room drops for some reason; consequently, by formula (1), the measurement value of relative humidity will increase although the actual humidity in the room has not changed. Then, the humidity control loop will start to work for adjusting the humidity falsely. It might be called systematic error which is brought by the measured value of the relative humidity [START_REF] Singh | Calibration of special relative humidity and temperature (RHT) sensors and evaluation and expression of uncertainty in the measurement[END_REF], and will exacerbate the coupling effect between the temperature and humidity in the room. Therefore, coupling problems may get more severe and the two control loops may produce a stronger interference to each other that can cause system instability when the humidity variable parameter is measured by dry-and-wet bulb method although it is the most popular way in humidity measurement.

3

Principles and Methods

Control Systems of Temperature and Humidity

Input and output control systems for temperature and humidity can be described as follows:

             , 1 , , 1 ,          k X k X k X k X P k Y k Y h h t t h t                   k T k T k Y k Y h t h t 1 , 1 (2)
Where: Y t is the output of temperature, Y h is the output of humidity; X t is the input of temperature, X h is the input of humidity; T t is the system disturbance and measurement noise of temperature, T h is the system disturbance and measurement noise of humidity.

The method of Wavelet

A wavelet is a mathematical function used to divide a given function or continuoustime signal into different scale components [START_REF] Jin | Wavelet basis function neural networks for sequential learning[END_REF]. Usually, one can assign a frequency range to each scale component. Each scale component can then be studied with a resolution that matches its scale. A wavelet transform is the representation of a function by wavelets. The wavelets are scaled and translated copies (known as "daughter wavelets") of a finite-length or fast-decaying oscillating waveform (known as the "mother wavelet"). Wavelet transforms have advantages over traditional Fourier transforms for representing functions that have discontinuities and sharp peaks, and for accurately deconstructing and reconstructing finite, non-periodic or non-stationary signals. Information can be effectively extracted from signals by wavelet transform, which is a good way for local analysis [START_REF] Yilmaz | Fuzzy Wavelet Neural Network Models for Prediction and Identification of Dynamical Systems[END_REF]. Continuous wavelet transform is a waveform transform that obtain continuous values through scaling parameter a and translating parameter b. In practical applications, a and b will be discretized and all the discrete wavelet form a function group which can be used as a base function.

For the advantages of wavelet described above, Wavelet basis [START_REF] Li | The Performance Analysis of Several Wavelet Bases in Applications(I)[END_REF][START_REF] Li | The Performance Analysis of Several Wavelet Bases in Applications (Ⅱ)[END_REF] was used as the membership function of fuzzy neural network in our study, and it can be expressed as follows:

    b a x H H b a   , (3)
Where: a is the expansion factor; b is the translation factor. The base expression of mother wavelet H (•) is as follows:

      2 2 2 x cos e x H x    (4)

Decoupling Control Based on Fuzzy Neural Network

The decoupling control structure of temperature and humidity based on fuzzy neural network (shown in Fig. 2) is consists of four layers, which includes an input layer, a fuzzy layer, a fuzzy rules layer and an output layer.

(a) Input layer: Changes of temperature and humidity (X t , X h ) will be put into the neural network, and the input value of each neuron will be converted to the fuzzy domain [-1, 1].

Fig. 2.

Control structure of temperature and humidity based on fuzzy neural network (b) Fuzzy layer: Fuzzy variables will be obtained from the inputs; and wavelets are used as the fuzzy membership function in our study. The affiliation between the inputs and the fuzzy linguistic variables is as follows:

        ij ij a ij b i x a ij i i ij b x e x H 2 cos 2 2 2              (5)
Where: i = 1, 2; j = 1, 2 ... N; a ij , b ij are the corresponding dilation factor and translation factor.

(c) Fuzzy rules layer: each neuron represents a fuzzy rule, which will export the corresponding fitness of rules.

Xt

Results and discussion

In order to see the validity of the control method in our study, test works were done in a control box with the dimensions of 1.6m × 1.0m × 4.0m, and the total power of the control box is about 16.5kw; as shown in Fig. 1, the control box is made up of heater, evaporator, compressor, circulating, and Temp.&Humi. Controller. Fig. 3 shows a response curve of temperature and relative humidity before and after decoupling when the set value of temperature is changed from 37 ℃ to 28 ℃ and humidity is changed from 60% to 82% in our test work; Fig. 3a and Fig. 3b are the response curves before and after decoupling respectively. From Fig. 3a, it can be observed the temperature reached the predetermined value (28 ℃) after about 14 minutes but the humidity still not reached a steady state half an hour later, and the overshoot is more than 7%RH; The change of temperature and humidity has brought more serious coupling to the humidity control. From Fig. 3b, we can find the temperature and humidity reached the predetermined value after about 11 minutes; the overshoot of humidity is less than 1%, and the overshoot of temperature is less than 1 ℃. This shows that the decoupling control is successful by the way of fuzzy neural network in the changed process. In addition, from Fig. 3a and Fig. 3b, it can also be found that the time needed for reaching the setting value is 1 minute shorter after decoupling, which suggesting that the changes of humidity can also have effect on temperature control. Fig. 4 shows another response curve of temperature and relative humidity before and after decoupling when the humidity is not changed(60%RH) but the set value of temperature is changed from 50 ℃ to 40 ℃; Fig. 4a and Fig. 4b are the response curves before and after decoupling respectively. From Fig. 4, It can be found that the temperature reached the set value(40℃) after about 6 minutes under decoupling control (see Fig. 4b) and the change of humidity caused by temperature also returned to the original(60% RH); However, without decoupling, it took more than 15 minutes for the humidity returning its original value as the measured value of humidity rose because of temperature dropped. This further shows that the system achieved a good control effect by the way of fuzzy neural network and the response speed has also been improved a lot. In addition, from Fig. 4a, at about the 6 th minute, we can notice that there is a short time interval in which the measured value of humidity is lower than its set value from the; it is because that the control loop of humidity took effect falsely as the drop of temperature resulted in the measured value of humidity increased (detail reason is included in the second part of this paper); however, the coupling problems does not exit any more when decoupling control was used according to Fig. 4b. Fig. 5 shows variations of temperature and relative humidity when the measured temperature value fell because of disturbance from the outside world; Fig. 5a and Fig. 5b are the variations of temperature and relative humidity before and after decoupling respectively. From Fig. 5a, it can be found that the measured value of the temperature was suddenly decreased about 14℃ at the 2 nd minute(From 60℃ to 46℃) for outside interference; it took more than 7 minutes for the humidity return to steady state although the temperature recovered to 60 ℃ about 1.5 minutes later as the temperature control loop took effect. From Fig. 5b, the measured value of the temperature was suddenly decreased about 18℃ (From 60℃ to 42℃) at the first minute for outside interference; It only spent about 2 minutes for the humidity recover from the interference and recover time of the temperature is less than 1 minute although the interference is more serious compare to Fig. 5a. Comparing Fig. 5a and Fig. 5b, It can be indicated that changes in temperature had brought a greater impact on humidity control; therefore, for achieving a humidity control loop with high antijamming capability, we should find good ways to decrease the coupling effect from temperature changes, which is a most important factor that should be considered in designing control systems of temperature and humidity. Usually, there is coupling in measurement and control systems of temperature and humidity; the change of temperature and humidity can take effect on each other's control loop. Systematic error caused by the coupling described in the second part of this paper is one of the main factors in the performance of control systems, which can reduce the anti-interference ability. Therefore, it is very important to find a way to solve the coupling problem. The fuzzy neural network was used for its good performance of local anomaly identification. Fig. 3, Fig. 4, and Fig. 5 show that the method tried in this paper has achieved good decoupling effect; the decoupling control systems has a strong anti-interference ability, fast response, smaller overshoot, and high stability.

Conclusions

Systematic error brought by the measured value of relative humidity is unavoidable, which will exacerbate the coupling effect in measurement and control systems for temperature and humidity. Fortunately, there are some decoupling ways to reduce the effect of errors and improve control precise. Most of traditional method of decoupling control is built on the basis of mathematical models; coupling from measured value errors could be reduced by mathematical compensation, however, the humidity and the temperature themselves are a pair of coupled variables, which also need to be decoupled. Moreover, it is hard to establish accurate mathematical model for many production process. Whereas fuzzy neural network can provide new ways in decoupling control, which does not require precise mathematical description of control objects. The membership function is a generalization of the indicator function in classical sets, which were introduced by Zadeh in the first paper on fuzzy sets (1965). In fuzzy logic, it represents the degree of truth as an extension of valuation. One of the most important factors on the effect of the fuzzy neural network is the membership function we chose. Our primarily study shows that it is a good choice to put wavelet basis as the membership function of fuzzy neural network for decoupling control.

This study provided scientific analysis on coupling problems of measurement and control systems for temperature and humidity, which is important for better understanding coupling problems in control process for this kind of system, and thus improving decoupling ways for control loops. Although more experiments should be done in different type of environment to further confirm our decoupling way, the research offered a novel try in designing high quality temperature and humidity control systems on technical theory and engineering design. Following this work, further verification experiment and scientific evaluation will be done in the future.

  Output layer: Defuzzfication will be achieved, and the output will be normalized in this layer.

Fig. 3 .Fig. 4 .

 34 Response curves of temperature and relative humidity before and after decoupling(1) Response curves of temperature and relative humidity before and after decoupling[START_REF] Kim | Independent joint adaptive fuzzy control of robot manipulator[END_REF]

Fig. 5 .

 5 Variations of temperature and relative humidity before and after decoupling when measured values of temperature fall

Acknowledgments

Research grant support from the Key Laboratory of Eco-Agricultural Environmental Engineering and Intelligent Equipment of China Agricultural Ministry (Grant Number: 588040*172210214 [2]) is acknowledged.


Benhai Xiong

Qingyao Luo

, Liang Yang

, Jiayi Pan

Traceability System of Pig-raising Process and Quality Safety on 3G

Keywords: :Intelligent PDA, 3G, Live pigs, Feeding files, Quality traceability 1

Abstract:In view of existed not flexibility and low efficiency in establishing feeding file of large-scale farms or farmer farms of pigs, by adopting intelligent PDA or mobile phone as application platform, combining with .Net 2005 language and SQL Server 2005 CE database as well as TD-SCDMA wireless wide band communication linking Internet as data transmission method,this study suggested data criterions on feeding process information collection of pigs, and developed a mobile PDA or phone system to track swine feeding process data, such as operators and main inputs, and to trace pork quality safety. The running of the system shows that it realized all kinds of data collecting and wireless submission including ear tag wearing and movements, immunity events, feeds and veterinary drugs used as well as casual inspection data,and also achieved remote data maintaining for pig′s feeding files and deepness inquiry to pork quality. The system not only makes up a deficiency from table data recording system for feeding file setting of a large-scale swine farm, but also is a kind of effective solution for farmer farm to set up swine feeding files. Furthermore, the system is a kind of mobile and convenient supervising tool to service official veterinarian to carry out their work. Finally, with the TD-SCDMA technology prevalence and communication fee decrease, the system will take part in a important role in constructing Chinese pork quality safety traceability system.

Introduction

Since a case of the Bovine spongiform encephalopathy(BSE) occurred in Britain in 1986, zoonoses such as BSE , highly pathogenic avian influenza (HPAI) and food quality safety problems such as Sudan red powder, melamine milk and Clenbuterol pork happened occasionally and so have been paid wide attention [START_REF] Lu | Animals and their Products Identification Technologies as well as Traceability Management[END_REF] . The case of Shuanghui Clenbuterol pork [START_REF] Cctv | Special View: Clenbuterol pork into Shuanghui[END_REF] , reported by the CCTV on March 15,2010,showed again great potential problems for the food safety and the importance of supervision and traceability of animal product quality. Early in this century, some developed countries and regions set up trade barriers such as technical regulations, standards and conformity assessment procedures on the advantage of science and technology, management and environmental protection and established new threshold for Chinese export, especially for animal product export. From 1 January 2002, the European Union (EU) legislation ((EC) No 178/2002) require that all products sold in shops must have traceability labels, including the country of birth, fattening, slaughter, slaughterhouse ID, segmentation packaging country , segmentation grant No, whether European Union membership is and so on. Canada began to construct traceability system for individual identification, move and premises identification about cattle, sheep and swine as the earliest as 2001, developed the first traceability system in 2003, respectively published the first edition (Can-Trance standard) in 2003, and second edition of the agricultural traceability standard based on EAN.UCC information identification and bar code traceability system in 2006. These standards for all the food in Canada are not mandatory. U.S. introduced the biological invasion movement framework in 2002 and all foods sold in the United States, including US and other country food, must been registered in the U.S. food and drug administration (FDA). Importers and processors have the obligation to record information about their middle suppliers and buyers for 2 years at least, and must copy the records in order to accept the FDA investigation.

Subsequently in 2007, FDA also announced food protection plan (FPP) to improve food security and strengthen traceability in the food processing and distribution processes [3,[START_REF]FDA Food Protection Plan six-month summary[END_REF][START_REF]National Animal Identification System (NAIS)-Technical Supplement to Draft Program Standards[END_REF] .

In China, animal product quality traceability system began with animal epidemic prevention system led by the ministry of agriculture in 2002 [3] . After the animal husbandry and law enacted in 2005, "the Administrative Rules on identification and rearing files for animal and poultry" was issued by the Ministry of Agriculture [START_REF]The administrative rule on identification and farming files of livestock and poultry[END_REF] and put in effect on July 1,2006. The rules proposed specific norms for identification and rearing files in pig-rearing link. Then, State council of China issued "the administrative regulations on pig slaughter" [7] on May 1, 2008 and took effect on August 1, 2008, which mainly provides legal base for supervising pig-slaughtering link by commerce departments according to law.

3G is able to provide high-speed data business and is the new generation mobile communication combining with wireless communication, multimedia communication technologies. TD-SCDMA is a 3G technology standard proposed by China based on international cooperation [START_REF] Fan | Development study for wide wireless communication technology: Chinese high technology enterprises[END_REF] . The technology convergence of wireless 3G network data transmission and international Internet system provide new technology means for expanding safety supervision and quality traceability for pig and products.

By the means of 3G technologies and PDA or mobile intelligent system, this study attempts to develop the mobile data collection and transmit system for main inputs in pig-producing link, and mobile terminal for government supervision and traceability enquiry, and provide technical reserves for exploring whole tracking and traceability solution in different pig-rearing models and network environments

2

Materials and Methods

Research Object

This study takes commercial pig-raising farms or household farmers as the research model, pig individual and pork end-product as the research object in order to study data collection solution in pig-raising link and traceability inquires on end product.

Individual Code and Ear Tag for Pig

According to the administrative rule, a pig must have a unique logo code, which consists of 15 digit code. The first digit represents the category of animal, for example, 1 represents pig; Then the subsequent 6 digits represent administrative district code in where pig farms are located, corresponding with GB T2260-1999 [START_REF]Administrative districts code for the People's Republic of China[END_REF] ; the next eight digits from the 8th to the 15th is pig individual No in the same district.

Data Standards for Pig-raising Process

In the pig-raising link, the required collection information includes responsible body information including pig-raising farm or

Development Environment

System development adopts Microsoft Visual Studio, Windows mobile 6.0 SDK, SQL mobile 2005, Visual c #, Microsoft ActiveSync 4.5 [START_REF] Fu | Windows Mobile telephone application and development[END_REF][START_REF] Luan | the design and study of the embedded internet based on GPRS[END_REF] . A PDA or smart phone collect, submit the collected data to the Tianjin pork quality traceability central database constructed by XiongBenHai (2009) [START_REF] Xiong | A Solution on Pork Quality Safety Production Traceability from Farm to Dining Table-Taking Tianjin City as an Example[END_REF] , or modify and query uploaded data remotely.

Technical Route of System Development

As shown in Fig 3

Results and Analysis

According to pig identification code, data collection standards, hardware and software development environments and technology framework of system function design suggested from 2.1 to 2.5, mobile construction of pig-raising files and traceability inquiry system based on intelligent PDA or phone is developed. Main results are as follows: Collecting data can save in the mobile client or IC card in .txt file format in order to subsequent data treatment, also synchronize to PC or directly submit to remote pork quality traceability center database by GPRS (2G) or TD-SCDMA(3G).

Collection of Pig Individual Identification

Fig. 1 Function structure of embed system on pig feeding process data collection and final product quality inquiry

Inquiry

Raising files and quality trace based on 3G not present until one or one batch ear tag code is inputted. Furthermore, the device system date on the mobile client is also uploaded as the sampling inspection date when the data is saved or uploaded. More detail information also includes different inputs information.

Discussion

China is a big pig producing country, the number of pigs for sale reaches up to 640 million in 2009, pork production up to 48 890 thousand tons, both rank the first in the world [START_REF] Gao | Animal almanac of China[END_REF] . But for pig production mode, both large sized commercial production and small scale backyard production will exist in a rather long period. How to build effect pork quality traceability system from pig production to consumer dinning-table is heavy responsibility for consumers' right and food safety despite of a difficult task. Therefore, exploring different modes of tracking and tracing technology solution of pork production for different requirement environments should prepare for a rainy day.

Normally, because producing number in large-scale commercial farms is big, their production and management are also standard, hardware and software in the information technology application is better than small-size farms and backyard farmers, pig-raising files data in raising process is collected by computer record and internet transmit system, batch data treatment is able to be accomplished [START_REF] Xiong | A Solution on Pork Quality Safety Production Traceability from Farm to Dining Table-Taking Tianjin City as an Example[END_REF] . Nevertheless, if there is the communication signal of GPRS or 3G within farm, the mobile data collection system is able to be used for recording part key data and modifying data in the center database by farmer technician or area official vet, especially fro sampling inspection information for pigs raised or for sale. In fact, the raising files for commercial farmers is conducted by farmer technicians and supervised by area official vet at present. The mobile system provides a mobile supervision means for supervisors.

Next, for free-range pig-raising farmers, constructing computer data recording and internet transmit system is not practical, so the mobile data collection solution is improved from that of 2009 based on GPRS technology [START_REF] Xiong | Identification of Swine Individuals and Construction of Traceability System under Free-range Pig-rearing System[END_REF] . Free-range farmer raising files on the remote server can be established for certain quality farmers with proper training and area official vet's help.

Obviously, establishing pig-raising electronic files by this system is simpler than that based on computer, without warning function for feed additives and veterinary drugs' withdrawal period. But, it can meet general traceability requirement of consumers.

For the end product traceability, traceability inquiry based on 3G has obvious advantages comparing to that on GPRS technology developed by Xiong (2009)

Conclusion

Tracking and traceability for the whole production process of pig and pork products is a focused issue widely concerned by governments at all levels and consumers at present and in a quite long time period and is also a test of government ability for people. This study showed that using smart PDA or phone, 3G wireless wide band network communication technology as well with internet, provide a solution of Chinese pig-raising information in the process of pig production, which includes mobile collection and transmit solution for farm manager and pig individual ID, main inputs in pig production, multimedia traceability solution such as that of image and text based on 3G. The developed system has been applied in Tianjin pork quality traceability network platform and application effects achieve the systematic design goal. The study is supplement for constructing pig-raising electronic files in commercial farms and may be a whole solution for free-range pig-raising farmers and can meet for high level consumers' right. As the rapid development of TD-SCDMA network service and decrease of service fee, data tracking and quality traceability in the whole pig production based on 3G technologies will be vast potential for future development.

Fig 2

 2 Fig 2 showed the running interface for fixing ear-tag, 15-digit code can be not only manually typed in and also scanned by PDA in batches. Considering PDA's memory capacity, the max number of reading or inputting ear-tag is 20 every operation.

Fig. 2

 2 Fig. 2 Tag wearing, data collection and submission for pig

Fig. 3

 3 Fig.3 immunity events and data collecting for pigs

Fig. 4

 4 Fig.4 Sampling inspection data collecting and submission for pigs

Fig. 5

 5 Fig. 5 Output of traceability inquiry results based on 3G system

  1, system models contain user management model solving user extent to different data use, raising files model including collection and transmission of data, supervision and inspection model for official vet to treat test results for hormone, sulfonamides and heavy metal residues for marketing pigs and for government easily to know sampling supervision results, tracing inquiry model to provide different levels of query service for government supervision department and consumers.

  , this study introduces image's inquiry and view(Fig 4). At present, although just trying to display supervisor and sale scene pictures, as supervision ticketing in deferent traceability points are put into effect in the future, they are directly viewed in relative links, especially for ticketing of illegal drugs in order to meet traceability right for high-grade consumers. Obviously, all these need 3G technology. With the rapid development of 3G technology, continuously increasing effective area and deducing charges, 3G technology application of the mobile traceability inquires will be more and more.

Acknowledgements

Funding were provided by the national high technology research and development program of China (863 Program) (2006AA10Z266), Tianjin municipal science & technology Innovation fund (06FZZDNC0100) and the national science & technology program (2009ZX03001-019).