Mingfei Zhang

Daoliang Li
email: dliangli@cau.edu.cn

Wang Lianzhi

M A Daokun

Ding Qisheng

Design and Development of Water Quality Monitoring System based on Wireless Sensor Network in Aquaculture

Keywords: WSN, Water quality monitor, Zigbee, Control, System integration 

This paper presents a system framework taking the advantages of the WSN for the real-time monitoring on the water quality in aquaculture. We design the structure of the wireless sensor network to collect and continuously transmit data to the monitoring software. Then we accomplish the configuration model in the software that enhances the reuse and facility of the monitoring project. Moreover, the monitoring software developed to represent the monitoring hardware and data visualization, and analyze the data with expert knowledge to implement the auto control. The monitoring system has been realization of the digital, intelligent, and effectively ensures the quality of aquaculture water. Practical deployment results are to show the system reliability and real-time characteristics, and to display good effect on environmental monitoring of water quality.

Introduction

China as a huge fishery country produces a great quantity of aquaculture every year in the world. As all known, water quality is very important in aquaculture, so the real-time monitoring and early warning studies on the water environment have been an essential part of aquaculture. At present, most domestic water quality monitoring are still using manual methods. The detection process involved in sampling, sample transportation and preservation, laboratory data measured etc., is a complex but associated system. Any error of the steps will affect the results of the final data. The traditional artificial method as regular or irregular sampling and monitoring is waste of time, inefficient, and difficult to objectively reflect variation rules and facts. It has been unable to meet current water quality monitoring needs. Along with the quickly development in communication technology and sensor technology, it accelerates the remote monitoring and automatic water quality monitoring process. The real-time water quality monitoring system based on wireless sensor network due to its convenience, real-time, accurate characters, has been get researchers more and more attentions [START_REF] Wang Pengxiang | Introduction and developing trends of online water quality monitoring system in cultivation[END_REF][START_REF] Du Zhiguo | Design of water quality monitoring wireless sensor network system based on wireless sensor[END_REF][START_REF] Wang Zhu | Remote water quality mentoring system based on WSN and GPRS[END_REF][START_REF] Zhao Jing | Research and application of wireless sensor networks in water quality monitor[END_REF][START_REF] Ye Xiangbin | Application of wireless sensor net works in environment monitor[END_REF][START_REF] Song Dejing | Study on water quality monitoring system of multi-points online for seawater industrial fish culturing[END_REF][START_REF] Han Antai | Design of acoustic signal acquisition system of stored grain pests based on wireless sensor networks[END_REF] .

Introduction to WSN

WSN (Wireless sensor network) is composed of data acquisition node, wireless transmission network and information processing center. Data acquisition nodes integrate sensors, data processing module and communication module. Through the communication protocol, the nodes form a distributed network. Then the network transmits the optimization data to information processing center. The system adopts Zigbee based on IEEE 802.15.4 communication protocol. Zigbee is a wireless intercommunication technique that has low transmitting rate and low cost advantages. It can be embed in devices, is particularly suitable for industrial control, aquaculture water quality monitoring, wireless sensor networks and smart devices such as the widely distributed applications [START_REF] Cao | Development of an integrated wireless sensor network micro-environmental monitoring system[END_REF][START_REF] Mainwaring | Wireless sensor networks for habitat monitoring[END_REF][START_REF] Steere | Research challenges in environmental observation and forecasting systems[END_REF][START_REF] Chen Dan | Survey on wireless sensor networks[END_REF] . Wireless Wireless sensor networks are widely used throughout intelligent transportation, environmental protection, public safety, peace at home, smart fire alarm, industrial monitoring, elderly care, personal health, floriculture, food traceability, enemy detection and intelligence gathering, and other fields [START_REF] Ren Fengyuan | Wireless sensor networks[END_REF] . Particularly in the areas of agriculture and rural information, WSN can be more widely available, such as: precision agriculture-the precise application of sensor technology, intelligent expert management system, remote monitoring and remote sensing systems, bioinformatics and diagnostic systems, food safety traceability system.

Water quality monitoring system architecture applied WSN

Based on WSN, the water quality monitoring system uses three-layer structure: data acquisition layer, data transport layer and application layer to establish its architecture. The architecture as figure 1 shows:

Fig. 1. System architecture based on WSN

In the data acquisition layer, the water quality monitoring system uses WSN which is formed by a large number of tiny sensor nodes through wireless self-organizing way. The sensors obtain data in the network include PH, water level, water temperature, DO (dissolved oxygen) sensor. WSN integrates sensor, MEMS and wireless communication technologies, can real-time perception and handle object's data information in network range, then send to the users. It has many excellent characters, such as large cover range, remote monitor, high monitoring precision, quick deployment and low cost. Through using WSN technology, the system can effectively monitor transport data and ensure the real-time data to be transported to the water quality monitoring software for analyzing and providing later control decisions.

In the data transport layer, there are two types of transmission methods: long-distance and short-distance data transmission. The system uses the GPRS to transport long-distance data, and uses the Zigbee to obtain the sensors' monitoring data, and then utilizes application software to manage the data and to make decisions to control devices. The real-time data through the sensors by Zigbee stored in the database to ensure users can query any time any sensor monitoring data information to analyze.

In the application layer, the water quality monitoring software is the main part. Through the soft ware, users can monitor the quality of the water all the time from the real-time data to ensure the water quality of the aquaculture. Water quality monitoring software utilizes the expert knowledge stored in the data and knowledge database together with the pretreatment data transported from sensors to make the decisions. Then the system decides whether to open or close the valve on relation device to increase or decrease the oxygen, water with the decisions. On-site users can receive early warning information from smart handheld device and depend on the decisions to operate. In order to facilitate user management, and data on water quality issues can occur in time to respond, the software also uses SMS early warning function. Off-site users can receive early warning information from PDA and other smart phones, and can send commands by SMS to control the valve on device. The users can not only get the current water quality environmental data, but also analyze the data in period to get the water environment trends to overall manage water quality.

The system collects temperature, PH, dissolved oxygen sensor signals by sensor module, via wireless transport module transmit data, and combines with system software to achieve real-time monitoring and control. The system based on users demand, can monitor the water quality data at any time. It provides scientific evidences to automatic monitoring of water quality information, automatic control and intelligent management. Water quality monitoring system software can pre-process, display and analyze the data from wireless sensor network, then make the corresponding decisions. Software system architecture and functional modules show as follows.

Software architecture

The functions of water quality monitoring software in application layer are mainly the water quality data analysis and decision-making. The software development tool is Visual studio 2005, and develops, compile, debug in Windows XP. The software architecture based on .NET framework, using MVC structure, implements the separation of logic layer, display layer and data layer, which improved application scalability and reusability. The software architecture shows as the figure3. In this architecture, the software hierarchical structure has three-layers: display layer, logic layer and data layer. Data acquisition and device control layer is related to the wireless sensor network hardware of the system architecture. The whole workflow process of the software is: firstly each sensor node in the wireless sensor network sends the water quality monitoring data to the water quality monitoring software; secondly in the design project, the users can see the real-time data by double-click the corresponding graphical device, and get the network topology. The user also can get the trends of one sensor data in a period or compare several sensors data in one comparison chart; thirdly according to the water quality data and device status, the users can add/delete device information, change the parameters of the device channel and set the sleeping status to the device for saving the battery power through the device configure module; fourthly through data analysis module, the software calls the knowledge from the knowledge database in the data layer to analyze the water quality data and decides to whether send control commands to the associated devices. The users can real-time monitor and manage aquatic water quality conveniently and efficiently by the various monitoring and control functions that the entire software modules work together to achieve.

Software function modules

The software main function modules include project design module, device configure module and data query/store/analyze module. Project design module through the user interface can display real-time data of water quality parameters in the monitoring region, over-limit alarm and historical data records; Device configure module uses communication protocol to communicate with the routing node, in order to achieve data transmission and device configuration aims, and in this module sensor network topology can be displayed to users; Data module uses database to implement the storage of the history monitoring data, and provides query and analysis operations to the users. Water quality monitoring software functions structure shows as figure 4.

Fig. 4. Software functions structure

Project design module. The functions in this module are mainly related to water quality monitoring on-site equipment graphical deployment and configuration. The user can present the equipment deployment in a project in a graphical method. It is easy for users to the project management, and users can design several projects for different demands. Each project can not only be reused, but also convenient and highly interactive to user operation. Friendly user interfaces provide the ability that the users can fully control the state of engineering equipment. Module functions include: 1) Drag the graphical devices to the project to implement the deployment; 2) Configure the graphical devices and associate with the actual physical devices address;

3)The graphical devices in the project allow users to drag and drop, double-click to configure properties, view real-time water quality data in the relation device.

Current popular model of monitoring software is configuration software. The configuration software which has outstanding specialty such as rich user-defined properties, using flexible, and functions powerful, is a software platform tool for data acquisition and control. Its main contents include good man-machine graphical interface, real-time database, real-time control, communications and networking, open data interface, wide support to I/O devices.

As a water quality monitoring software, the configuration of the used devices would help users design and management of the project, so the module uses configuration model on the graphical devices in the development. The graphical devices configuration in the water quality monitoring software include ponds, access node, routing node, collection node, control valves, switches. Users can design the project by dragging and dropping the graphical device from the graphical devices configuration toolbar. All graphical devices in the project can be moved, added relations, and viewed the real-time data by clicking in the main project interface. For the collection node and routing node, because they communicate with the software by protocol, the communication state maybe not stabilization in the project. The corresponding graphical device has two states, one green color expresses the good communication state, and the other red color expresses the bad state. Because the communication state refresh in time, the users can manage the device communication state from the project main interface. Also the control device has two state, green expresses the valve open, red expresses close. The control device can be set auto control to implement the operations depend on the monitoring data of the sensor. Users can re-design new projects, and user-designed project can be saved to reuse that implement different management in different projects for the user. properties, channel parameters, sub-device parameters, system parameters and sleep settings. The device configure main interface shown in Figure 6.

Fig. 6. Device configure interface

Through this module, users can carry out the parameters of the corresponding device configuration management, and water quality monitoring data and device status data will be stored for use. The changes of hardware devices configuration in the wireless sensor network can be completed by the operations that the device properties add, delete, modify in the project. It makes water quality monitoring software to keep devices properties update and have accurate information in time. In the design project module, graphical device associated with the actual hardware device is through adding the device address to the graphical device. In the device configuration module, the device properties and device channel attributes are need to configure fields as shown in Table 1,2 The software can configure the system parameter such as device storage parameters, including the storage of cycles, the begin record time and the end recorded time to adjust the device stored setting. Since sensor devices in the wireless sensor network rely mainly on battery power energy, in order to ensure the device continued work time, device configure module provides a sleep set. Through the sleep setting, users can control the sensor device periodically stop working, and can wake up when needed in a time. Through the setting, it greatly enhances the device working time. In this module, users can also understand the WSN topology of the network, and can get the current device CPU voltage and battery voltage by double-click the graphics device in the topology that facilitates the management of the current device.

Data query/store/analysis module. The module is mainly related to query/store/analysis the monitoring data on the configured device. The functions include: 1) Query and preserve the basic properties of the devices; 2) Query and preserve the basic properties of the device-channel; 3) Query and preserve water quality sensor real-time data; 4)Analyze the graphical device real-time data and make the control command. HisSts_x_x int N Channel Date Through combined the knowledge in knowledge database with the sensor data in water quality database, the module judged the data whether below the lower limit or higher than the upper limit. If it's true, the graphical device in the project will be twinkled to alarm the user. And the software if judged the device state was auto state, it will auto send commands to the control device. Analysis flow chart is shown in Figure 8.

Application

The wireless sensor network hardware monitoring equipments deployed in the crab ponds of the local famers in Yixing Jiangsu province. Water quality monitoring software deployed in the control room of PengYao ecological park. The application has received good results in practice. Devices deployment shows as figure 9.

Fig. 9. On-site devices deployment

The steps of monitoring process to the instance of the application are as follows:

(1) Wireless acquisition nodes installed in local farmers' crab ponds, and they are directly connected with the water quality sensors including temperature, water level, PH, DO (dissolved oxygen) sensor to implement the water quality data collection, storage and distribution. Each acquisition node has four sensor interface, can connect up to four sensors to detect five water quality parameters. Acquisition nodes and sensors connected by RS485 communication interface.

(2) Routing nodes installed between the crab ponds and monitoring system center receive data from acquisition node and send to the monitoring system center. Use the routing node can extend the communication distance, and ensure the smooth communication.

(3) The system using ZigBee protocol transmits data to the water quality monitoring system for the related decision-making.

(4) The monitoring system receives the data including water quality data and the node voltage data. Through the water quality data, monitoring system can manage the water quality environment and decision-making. Through the node voltage data, water quality monitoring system can grasp the current energy situation and communication conditions, facilitate equipment maintenance and management.

(5) Send control commands to the control device, and send messages to the user PDA to notify the user, the user can remote control valve by SMS.

Conclusions

In this paper, a system capable of water quality monitoring based on WSN is presented. The system has made several achievements in: (1) Unlike some simulators, this system is a practical monitoring application where sensor nodes periodically send the information they got to the software for decision making and analysis. (2)Wireless sensor network ensures the real-time and reliability of the monitoring data, and sleeping setting make the sensor devices work longer. (3)Configuration software model enhances the reuse and facility of the monitoring project, and provides user-friendly management to the users. (4) The monitoring software can represent the monitoring hardware and data visualization, and analyze the data with expert knowledge to implement the auto control. Furthermore, it can send warning (Via SMS or graphical device twinkle) messages to relevant users when undesirable events are detected.

Future work will deploy more nodes to provide long-term monitoring. Besides, as the water quality parameters correlation between each other, adding data fusion functions and fuzzy control model, which will greatly improve the accuracy of the system monitoring, it will be the next step in the direction of system development.

1 )

 1 Wireless communication technology-2.4GHz short range communication and GPRS communication, wireless signals cover 3km range; (2)Embed control technology-intelligent information acquisition and control; (3)Wireless network technology-network routing layer, communication caching, self-diagnosis and maintenance technology; (4)Energy manage technology-low power consumption and energy management.

Fig. 2 .

 2 Fig. 2. System structure in application

Fig. 3 .

 3 Fig. 3. Software architecture

Fig. 5 .

 5 Fig. 5. Project configure interface Device configure module. The module is mainly related to the physical device information properties, including the address and type of physical device, channel address and type. The functions include: 1) The device attributes configuration; 2) Device-channel attributes configuration; 3) Device parameters configuration, including reading the current configuration and reset the parameters of the device; 4) Device dormant state configuration, including reading the current configuration and reset the device parameters. Device configuration relates to device properties, channel

Fig. 7 .

 7 Fig. 7. History data analysis interfaceThrough the preservation of historical water quality data, the users can analyze the water quality monitoring data, view data trends, and grasp the overall trend of water quality. The data preservation include water quality monitoring data and device status data, and the corresponding data fields shown inTable 3,4.

  ,4.

Fig. 8 .

 8 Fig. 8. Analysis flow chart

Table 1 . Device attributes configure data sheet

 1 .

	Primary key	Field Name	Field Type	NULL	Description
	PK	DevAddr	int	N	Device Address
		DevName	varchar	N	Device Name
		DevType	int	N	Device Type
		DevRole	int	N	Device Role

Table 2 . Channel attributes configure data sheet

 2

	Primary Key	Field Name	Field Type	NULL	Description
	PK	ChlMark	int	N	Channel Mark
		ChlName	varchar	N	Channel Name
		ChlDev Addr	int	N	Relation Device Address
		ChlDevNum	int	N	Relation Device Channel Number
		ChlType	varchar	N	Channel Type
		ChlUnit	varchar	N	Channel Unit
		ChlAltitude	int	N	Channel Altitude
		ChlDotNum	int	N	Decimal Digits
		ChlLowerLi mit	int	N	Channel Lower limit
		ChlUpperLim it	int	N	Channel Upper limit
		ChlFieldPara	int	N	Calibration

Table 3 . Water quality data sheet

 3

	Primary key	Field Name	Field Type	NULL	Description
	PK	HisData_Index	int	N	Data Index
		RecordTime	Date	N	Record Time
		HisData_ChlSum	int	N	Channel Sum
		HisData_x_x	int	N	Channel Date

Table 4 . Device state data sheet

 4

	Primary key	Field Name	Field Type	NULL	Description
	PK	HisSts_Index	int	N	Data Index
		RecordTime	Date	N	Record Time
		HisSts_ChlSum	int	N	Channel Sum

System architecture based on WSN (wireless sensor network)The process to monitor water quality environment includes data acquisition, data transmission, data preservation and decision-making, which is involved with software and hardware comprehensive integration, so the excellent architecture becomes the top priority to the water quality monitoring system as a composite system.

Acknowledgements

. This research was financially supported by the National High Technology Research and Development Program of China (2007AA10Z238), Beijing Natural Science Foundation (4092024), National Major Science and Technology Project of China (2010ZX03006-006) and 948 Project of China Agriculture Ministry (2010-Z13).


Hui Chen
email: chenhui@ecjtu.jx.cn

Research of Intelligent Gas Detecting System for Coal Mine

Keywords: Coal mine, Gas Detecting System, SCM

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

Introduction

As the most important source of energy in China, Coal consumption is about 70% of all the energy consumption [START_REF] Yan | Analysis on relationship between economic growth and coal consumption[END_REF][START_REF] Zhenfu | Optimum utilization of coal resources in western region of China[END_REF] . However, coal mine accident happened frequently in China and lots of people suffered from these disasters. Among all the accident, gas leakage leads to gas explosion is the main reason [START_REF] Bu | Handbook of Coal Mine Gas Disaster Prevention and Utilization[END_REF][START_REF] Zhou Jun | Causes for "1.25" Extremely Large Methane Explosion in Gengcun Coal Mine and the Preventive Measures[END_REF] . So, it's significantly important to develop gas monitoring safety system in coal production enterprises. In this paper, a gas detection and monitoring system is presented, its main functions including: Real-time monitoring gas concentration, transmitting dynamic safety operation parameters underground coal mine, automatic warning about danger before accident happens and providing useful information on rescuing and evacuating people or equipment to decision makers.

Overall Design of Gas Detecting System

Gas detecting system should meet some specific needs: it can monitoring combustible gas concentration underground coal mine, warning against over standard gas concentration and transmitting real time data to host computer above ground [START_REF] Kai | Conception of Coal Mine Safety Comprehensive Early Warning System[END_REF][START_REF] Yi | Design of Portable Methane Detection Alarm[END_REF] . The gas detecting system in this paper adopts single-chip microcomputer as control computer; the overall schematic diagram of system is shown in Figure 1. The reason for selecting single-chip microcomputer as a control core is that it possesses advantages of small size, high reliability, low price which made it very suitable to be used in industries of intelligent instrument and real time control field [START_REF] Yong | Applications of Single-Chip Microcomputer used in the Control System[END_REF] .

Hardware System Design of Gas Detecting System

The Hardware architecture of system mainly including main control unit, sensors and signal amplifier circuit, A/D converter module, sound-light alarming circuit, keyboard and display module, serial-communication module.

Main Control Unit

Featured by high integration level, small size and low prices, Single chip microcomputer has been widely used in a broad range of industrial applications including process controlling, data collection, electromechanical integration, intelligent instrument, household appliances and network technology, and significantly improved the degree of technology and automation.

Two factors are taken into account here in chip selecting, first one is anti-interference ability, the poor working conditions and complex operating situations in mine tunnel increase the interferences in SCM application systems, so the SCM must have high resistance to outside interference; second one is the performance-price ratio of the SCM. Considering the aforementioned factors, we adopted the AT89S52 developed by ATMEL as main control unit, and the final scheme of main control circuit consists of AT89S52, timer and reset circuit [START_REF] Yu Cai Etc | New Type AT89S52 Serial Single-Chip Microcomputer and Its Application[END_REF][START_REF] Xing | Theory of AT89 serials Single Chip Microcomputer and Interface Technology[END_REF] . As shown in figure 3.

Sensors and Signal Amplifying Circuit

Sensor Selection A crucial issue in gas detecting system design is how to select gas sensors. Common gas sensors are metal oxide semiconductor such as tin oxide, zin coxide, titanium oxide and aluminum oxide. Problems encountered with these sensors are lack of flexibility, poor response times and operated at elevated temperature [START_REF] Yasin | Room temperature multi gas detection using carbon nanotubes[END_REF] . A new method of ch4 detecting based on infrared techniques was presented in recent years, but it is still in progress and much work should be done before it can be applied to solve the practice problems [START_REF] Jiang | Detecting System of Methane Based on Infrared Technology[END_REF] . This system adopted catalytic combustion type gas sensor MC112 developed by SUNSTAR group to measure the gas (ch4) concentration. Figure 4 shows the outside view and internal circuit of MC112, table 1 lists the main technology parameters of MC112. MC112 gas detector exploits catalytic combustion principle; the two-arm bridge is comprised of measure and compensates components pairs. When it is exposed to combustible gases, measure components resistance RS increased and transmit output voltage parameter through measuring bridge, the voltage parameter is directly proportional to the gas concentration value. The compensate component works as temperature compensation and reference. Main features of MC112 include good repeatability; work stably, reliability, linear output voltage, and quick response.

The mine safety rules stated that if methane gas concentration exceeds 1%, safety system should make an alert, if gas concentration exceeds 2%, all people must evacuate immediately. Since the detecting range of MC112 for low concentration methane is 0%-2%, it is suitable for measuring low concentration methane in the coal mine.

A/D Converter Module

As shown in Figure 6, this module consists of multiplexer CD4051, sampling holder LF389, A/D converter AD574A [START_REF] Zhi | Application of AD574 in Data Acquisition[END_REF] and parallel I/O chip 8255A. As a core part, AD574A is a 12-bit successive-approximation A/D converter chip with three-state buffer; its conversion time is about 25μs. AD574A can directly connected to AT89S52 without additional interface logic circuit, with internal high accuracy reference power supply and clock circuit, AD574A can operate normally without external clock source and reference power supply. transfer rate, long distance transmission and Wide common-mode range, its maximum transfer rate reaches to 10Mbps, maximum cable distance reaches to 1200m [START_REF] Rui | Complete Collection of Serial Communication Technology[END_REF][START_REF] Castro | et a1.Well-known serial buses for distributed control of backup power plants RS-485 versus controller area network(CAN)solutions[END_REF] .

The sound-light alarming unit is shown at the right part in Figure 9. As shown in this figure, P21 and P10 of AT89S52 will take control of sound-light alarming unit when the test value of CH4 gas concentration exceeds the preset value. The primary functions of the software control system including system initializing, threshold value setting, methane gas concentration data collecting and displaying, serial communications etc. To achieve the above functions, we developed serial ENTER key to finish this step. When ENTER key is pressed, system start the operating of data collection and A/D conversion, then transmit the converted data into binary format by calling a subprogram of double-byte multiply. We need three storage units to hold these data because they are 24 bits data in binary format. Next, system will transmit these binary format data into binary-coded-decimal format by calling a subprogram of triple-byte to binary-coded-decimal. In the last step, comparing the value with pre-set threshold value to decide if the system should send an alarm signal.

In the meantime, these data will be sending to host computer above ground through RS-485 serial communications unit. Still, the system will send a positive pulse to reset the watchdog timer every 1.6 sec. the Crystal Oscillator frequency of the SCM adopted in this system is 12MHZ, with timer/counter TO, working in mode 1(16bit timer/counter), its maximal timing interval is about 66ms, so the system will send a feeding dog signal to watch dog circuit every 66ms.

Conclusions

In this study, an intelligent gas detecting system is presented. It can be used to real-time monitoring the methane gas concentration underground coal mine. The measuring scope of this system ranges from zero to 2 percent, the sensitivity of the sensor reach to 0.01 percent. It is equipped with the quick speed and high performance 12-bit A/D converter, the operating environment temperature ranged from -20℃~+70℃. Still this system features with high reliability, easy to operate, high performance-price ratio. In this paper, the total plan and software and hardware design of a gas detecting system are presented, by using Proteus to test hardware circuit and using software package Keil to test assemble language source program, the simulation test result shows this system is of high accuracy, quick response and is feasible.

Fig. 1 .

 1 Fig. 1. Schematic Diagram of Gas Detection System The operating interface of system is shown in Figure 2. Number at upper right corner shows the default or user-defined gas concentration value, number at upper left corner shows detected gas concentration value. One alarm lamp is equipped. All functions are controlled by keys arranged on the control panel, including POWER key, RESET key, DATA COLLECTION key. Other keys including ten number keys, ADJUST VALUE key and ENTER key are used to change threshold value.Basic operating procedures are as follows:  Firstly press POWER key, the system initialized.

Fig. 2 .

 2 Fig. 2. Operation Interface Diagram of System

Fig. 3 .

 3 Fig. 3. Main Control Unit

Fig. 4 .

 4 Fig. 4. Outside View and Internal Circuit of MC112

Table 1 .

 1 Main Technical Parameters of MC112 Rated voltage It is necessary to amplify the weak electrical signal detected by MC112 (1% gas concentration fluctuation will result in 16mv voltage change). The system adopted AD623 developed by AD Company as the high performance instrumentation amplifier. It has many merits: (1) rail-to-rail voltage output with 3-12v single supply (2) easy to modify signal gain though an external resistor, it will be act as a unit gain without external resistor and signal gain can reach to 1000 with an external resistor; (3)low power consumption, large-scale operation voltage, good linearity, good thermal stability and high reliability. The schematic diagram of signal amplifier circuit is shown in figure 5.

Fig. 5 .

 5 Fig. 5. Signal Amplifying Circuit

Fig. 6 .

 6 Fig. 6. A/D Converter Module

Fig. 7 .

 7 Fig. 7. Digital Displaying Circuit

Fig. 8 .

 8 Fig. 8. Keyboard Module Circuit

Fig. 9 .

 9 Fig. 9. Serial Communications and Sound-Light Alarming Units

Fig. 10 .

 10 Fig. 10. Flowchart of the Main Program


Longzhi Zhao
email: azhaolongzhi@163.com

Xiaolan Zhang
email: bzhang_xiaolan85022@163.com

Na Li

Mingjuan Zhao
email: dzhaomingjuan100@163.com

Jian Zhang

The Effects of Internal and External Factors on the Mechanical Behavior of the Foam Copper

Keywords: ANSYS, foam copper, porosity, strain rate

The study on the mechanical properties of foam copper has become increasingly important, for the potential market in the foam metal. The Kelvin model was supposed to be the suitable model to construct the ideal open-cell, continued and three-dimensional structure. The static tensile behavior on the foam copper was simulated by ANSYS and the effects of the porosity and strain rate on the foam copper were analyzed. The results show that there is a great influence of the porosity on the elastic modulus-the higher the porosity is, the smaller the elastic modulus, and though the larger the strain rate is, the smaller the elastic modulus, the effect on it is very small. The Kelvin model exhibit a characters of anisotropy, and the displacement and the stress of the node is different form its' location.

Introduction

The porous metal is a continued grid body which forms of strings or walls. The cavities is constructed by the three -dimensional polyhedron, and then called this kind of three-dimensional materials "foam materials". The composition of the foam solid is only by the cell edges (the cavities connected by the strings) called "open-cell", and called "closed-cell" for the walls of polyhedron is solid, and then the cavities is closed between its adjacent cavities [START_REF] Zhang | The Properties of Representative Units of Porous Materials[END_REF]. With the rapid development of the computer technology, more and more heating of the CPU make obviously the CPU heat sink more important. For the heat sink materials is not satisfied the increasingly need of the market [START_REF] Hao | Thermal design of electronic equipment[END_REF], zhang had invented a new heat sink material which called foam copper. So the mechanical properties of it are very significant and necessary.

Foam copper is a new functional material with three-dimensional pore structure, high porosity which can up to 60%~95%, light specific gravity-only 10%~50% of the same volume metal, high specific surface area can up to 10~40 cm2, cm3 is widely used as heat exchangers and heat sinks. With three-dimensional copper foam pore structure, higher porosity, 60% ~ 95%; proportion of light, with the volume of metal is only 10% to 50%; the larger surface area, up to 10 ~ 40cm2, cm3, can be used for heat exchangers, and heat sinks [START_REF] Cao | The Mechanical Property and Progress of Metal Foams[END_REF]. In this paper, the static tensile behavior on the foam copper was simulated by ANSYS.

The establishment of the model

The Kelvin model is the ideal model that is used to simulate the mechanical properties of the lower relative density foam materials which can more truly reflect the geometric features of foam materials, which can fully fill the entire space, and can better meet the some properties. The unit cell of the Kelvin model is shown in Figure 1. What can be from the figure: it consists of 8 regular hexagons and 6 squares, contains 24 vertices and 36 pillars of equal length. Three plane-symmetry axises pass through the center of figure and four line-symmetry axises pass through the pillars of 6 squares [START_REF] Shi | Finite Element Analysis for The Elastic Modulus of Open-cell Foams Based on a Tetrakaidecahedron Model[END_REF]. The pillars of foam materials are conceived as same cross-section beam [START_REF] Xie | Anisotropic Elastic Properties of Foam Metal with Open Cells[END_REF]. Kelvin multi-cell model is shown in Figure 2.Circle cross-section beam was established in this paper, and the load is imposed parallel to the direction of the extension of the cell. The Y axis is opposed to the direction, and the origin is showed at the bottom of the multi-cell model.

Discussion

The effects of the volume fraction

The volume fraction of the foam copper is changed by the porosity in this paper, and this means that the volume fraction is equal to the porosity in this paper. The porosity is one of the main characteristic parameters of the porous materials, which is referred to the volume of the solid compared to all of the volume. The porosity of foam is arranged between 85% and 95% in this paper. The mechanical properties and physical properties in the elastic area were studied in this paper. The volume fraction of the Kelvin model is shown in Eq.1.

( ) ( )( )

3 2 2 6 3 4 a R a R P + - = π (1)
Where P is porosity, R is the radius of cross section, a length of the pillar. The materials parameters are shown in Table 1. The time-displacement curves of three nodes are selected to analyze the mechanical properties of the foam copper based on the Kelvin model in this paper. The node 1156 located on the top surface, the node 3027 located on the middle of the model, and the node 11149 is closed to the bottom surface. The Y-axis time-displacement curves of three nodes are shown in the Figure 3. The results show that the increment in displacement is very small before the time of 0.1 second, the increment become large and increase linearly with the extend of the time. After stretching the model, the displacement of the node 1156 is larger than the node 3027, which is larger than the node 11149. These conclude that the more closed of the location to the force, the larger of the displacement is. This can owed to the time and space for the transmission of the force.

Figure 4 shows the time-displacement curves of the node 1156 under different porosity. It shows that in the elastic area, the greater the porosity, the smaller the displacement, which indirectly indicates that the greater the porosity, the elastic modulus. This manly result from that the smaller the porosity, the bigger the volume of entity, and the bigger load area, then the smaller the load of average area. The time-displacement curves of X, Y, Z axes are shown in Figure 5. What can be from the figure is that the time-displacement curves of three axes trend differently. Y, Z axes exhibit increasing trend, while X axis exhibit opposite. The increment of the Z axis is small than Y axis, for the Y axis is the direction of the force. So the Kelvin model has anisotropy character. This is accord with the LU's statement.

The effects of the strain rate

The porosity of the foam copper is set as 85%, and the model is the same to above.

The effect of the strain rate on the elastic modulus is shown in Figure 7. It can be seen from the figure that the elastic modulus doesn't exhibit linearly increase with the strain rate. The larger the strain rate, the smaller increment of the elastic modulus. The elastic modulus decrease, but it decreases small. Then can conclude that the effect of the strain rate on the elastic modulus is very small. It may be appearing a situation, the elastic modulus may be stable when the strain rate up to a limit. This is equal to the elastic modulus has a limit. This because that the strain rate would not neither change the internal structure and properties like the porosity and the aperture nor alter the external circumstance in order to change the internal properties like the temperature.

The Y-axis strain rate-displacement curves of three nodes located differently are shown in Figure 8. It shows apparently that the curves of the node 1156, 3027, and 11149 don't intersect, and different greatly. Especially in the situation of the small effect of the strain rate on the elastic modulus, the increment of the node's displacement depend on the location very largely. This indicates that the node distance from the force affect directly the stress and the displacement. This is because that though in static model, the more far to the load, the longer the time of the transmission, for the time and the space is necessary for the transmission of the load. And in the process of transmission, it is inevitable for the loss of the force. Then the displacement and stress is small with distant location. The Equivalent stress nephograms of the different location of the node are shown in Figure 9. The stress is increased gradual from blue to red. The same conclusion can be from the figure. What can be seen from the figure is that the stress is the biggest in the intersection. Although the angles between the pillars are not right angle, it is not beneficial to transfer the force especially in the intersection which is easy to concentrate the stress.

Fig. 1. The Kelvin model Fig . 2 .

 2 Fig. 1. The Kelvin model Fig .2. The multi-cell model

Fig. 3 .Fig. 4 .

 34 Fig. 3. Y-axis displacement

Fig. 5 . 6 .

 56 Fig. 5. Time-displacement curves of Fig. 6. Time-displacement curves of X, Y, Z-axes of the node 1156 X, Y, Z-axes of the node 3027

Fig. 7 .Fig. 9 .

 79 Fig. 7. Elastic modulus-strain rate curve Fig. 8. Displacement-strain rate curves of different location

Table : 1

 : the materials parameters.

	Porosity	Section radius /mm	elasticity modulus /Gpa	Poisson's ratio	shear modulus /Gpa	yield strength /Mpa
	85%	0.0550	16.50	0.343	6.00	1.60
	87%	0.0515	14.00	0.343	5.50	1.40
	89%	0.0480	12.00	0.343	5.00	1.22
	91%	0.0440	9.90	0.343	4.14	1.00
	93%	0.0375	7.70	0.343	3.20	0.78
	95%	0.0315	5.50	0.343	2.30	0.56


Guangyao Xiong
email: axiongguangyao@163.com

Meizhu Zheng
email: bzhengmeizhu@163.com

Deying Li

Longzhi Zhao
email: dzhaolongzhi@163.com

Yanlin Wang

Minghui Li
email: fliminghui@163.com

Study on the influence of non-electrical parameters on processing quality of WEDM-HS and improvement measures

Keywords: WEDM-HS, Non-electrical parameters, Processing quality, Improvement measure

The high-speed wire electrical discharge machining (WEDM-HS) machine has been more and more favoured by customers for the low manufacturing cost, the degree of automation and the advantages over the WEDM-LS in price performance ratio. However, the processing quality (the precision of form and position and the surface quality) of WEDM-HS is poorer than that of WEDM-LS, and the processing quality is one of the main technical indicators of WEDM. There are many factors on the processing quality of WEDM-HS, the effects of non-electrical parameters, including the machine precision, the wire-moving system and wire-moving way of the wire electrode and the working solution, on the processing quality of WEDM-HS are discussed, and the corresponding measures of improving the processing quality are put forward, which provide the sufficient basis for further improving the processing quality of WEDM-HS.

Introduction

The wire electrical discharge machining (WEDM) is the method of EDM that the metal wire is used as tool-electrode [START_REF] Li | Theoretical basis of EDM[END_REF]. In the processing, the anode of pulse power connects with the workpiece and the cathode connects with the electrode wire, the high-temperature generated by impulsive discharge between the workpiece and the wire electrode will make the workpiece melted and gasified to achieve processing, and the relative trajectory and velocity between them are controlled to cut out the workpiece with a certain shape and size. WEDM could be used to solve the processing problems of materials with special mechanical properties, such as high melting point, high hardness and ductility, and the parts will be with special structure and requirements, which are difficult or unsolvable for the traditional process.

Therefore, it has the utmost importance in mold, forming tool, unmanageable materials and complex precision parts.

According to the moving way of wire electrode, WEDM machine can be divided into high-speed and low-speed CNC ones, which have great difference in structure and processing property [START_REF] Li | The Research Status and Development Trend of Electric Discharge Wire-cutting Technology[END_REF][START_REF] Guo | Study on dynamic stability of multiple cut on machine tool in HS WEDM[END_REF]. Because the various schemes are taken in the high-speed and the low-speed WEDM, which leads to much difference in the structure of machines, the wire-moving systems and processing conditions, it may not be very appropriate to make a comparison between the processing performances of two machines one by one. Excluding the factor of cost, the accuracy, functionality, reliability, and processing stability of the domestic WEDM-HS machine have large gap comparing with foreign advanced WEDM-LS technology. In this paper, the ways of improving the processing surface quality of WEDM-HS will be discussed from the influence of main non-electric parameters on processing quality.

Main non-electrical parameters on processing quality of WEDM-HS and improvement measure

Influence of the precision of WEDM-HS on processing quality

The precision of WEDM-HS is the primary condition to ensure the processing quality, and the precision of worktable is primarily decided by the precision of transmission parts (screw mandrel, nut and gear), the fit clearance, the equipping precision, and the work environment of machine et al. The processing quality is poor for the poor transmission precision of worktable. Therefore, the manufacturing precision of WEDM-HS should be strictly controlled to improve processing precision.

Influence of the stability of wire-moving system on processing quality and control measures

The flexible metal wire is used as the electrode in WEDM, which is carried out by the role of impulsive discharge between the workpiece and wire electrode. The wire electrode will be pushed away from the discharge area, and bended backward with a certain flexivity when the wire electrode is discharging. As shown in Fig. 1, line 1 is the actual track of wire electrode, the processing direction of which is L1; line 2 is the theoretical track of wire electrode, and line 3 is the actual track of wire electrode, the processing direction of which is L3. Under the condition of limiting flexivity, the dynamic WEDM-HS process is always simplified to the static variation, and the bending section of the wire electrode is approximated as an arc, so the actual discharge point has deviated y cm from the theoretical cutting point, and the flexivity could be expressed as the following Eq.1 [START_REF] Li | Theoretical basis of EDM[END_REF][START_REF] Li | Study on the Variations of Form and Position of the Wire Electrode in WEDM-HS[END_REF].

F fH fL y 4 2 - = (1)
Where y is the flexivity (cm); L is the span length of wire electrode (cm); H is the thickness of work piece (cm); f is the discharge force and F is the tensile force of wire electrode.

The traditional wire cutting drives the wire electrode in V-groove of guide wheel to move back and forth through the rotation of guide wheel, the schematic diagram of guide wheel positioning as shown in Fig. 2. The bearing ball is easy to wear, and produce the radial traverse for the speed of guide wheel is 8000 n/s, which makes the vibration of wire electrode [START_REF] Xia | Electric Sparkle Cutting Bad Reasons for Product Quality and Prevention[END_REF]. The wire electrode moves generally back and forth with the speed of 10 m/s, as a result, the bottom of V-groove will be abraded, so the accurate positioning of wire electrode can not be guaranteed. When the cutting directions are changed, the direction of L1, L2, L3 and L4 as shown in Fig. 1, the position of tangent point and the tension between wire electrode and guiding wheel are variable, resulting in the change of flexivity between y1 and y3. It is obviously that y1 is larger than y3, and y2 equals with y4. As the form and position of wire electrode changes, it is difficult to improve precision. The flexivity of wire electrode cased by the discharge power has no influence on processing precision when the straight line is cut, and the flaw is produced called sunken corner for processing the corner to influence the processing precision, the formation of sunken corner as shown in Fig. 3, in addition, the vibration of wire electrode will inevitably produce the deviation of cylindricity when the cylinder is cut. Therefore, the form of spacial variations and the position of wire electrode should be steadied in order to reduce the accuracy error of wire electrode. In order to reduce the flexivity and steady on the variations of form and position of wire electrode, two guiders with wear properties are adopted to position the wire electrode up and down by Shanghai Mass Electronic Equipment Co., Ltd. The wire electrode passes through the guider as shown in Fig. 4, which is blocked by the small holes of guider. The aperture and diameter of wire electrode match reasonably, and the deviation cased by wire electrode is blocked by the small holes when the processing directions are changed, which is the four directions. As the guide device is installed, the actual distance L between two fulcrums up and down of wire electrode is decreased. According to the Eq.1, the flexivity is actually reduced. So the variations of form and position of wire electrode are inhibited and steadied, in order to further improve the stability of processing precision. The workpiece surface processed by WEDM-HS will generally produce obvious stripes, when there is almost no stripe for WEDM-LS, it is decided by the cooling method and wire-moving way of WEDM-HS [START_REF] Liu | Technology Research of WEDM Using Composite Cooling Liquid[END_REF]. In WEDM-LS, the workpiece is immersed in de-ionized water to cool, and the wire-moving way is wire-moving one-way with low speed, while the rushing fluid is adopted to cool in WEDM-HS, the working solution is emulsion, and the wire-moving is instability to produce stripes inevitably, for the wire-moving way is wire-moving back and forth with high speed. The stripes of workpiece surface processed by WEDM-HS can generally be divided into two kinds, the one is the stripes with color, whose black and white concentration in the entrance and exit of wire-moving are different, and sometimes the kerf of exit side is slightly wider. The basic reason is the detergency of working solution. It is generally acknowledged that the stripes are caused by the rushing fluid and the dirty degree of working solution in entrance and exit. The other is the convex-concave stripes. When the wire electrode moves from top to down, the working solution is taken from the top into kerf along the wire electrode, and the discharge products are taken out in the processing zone from the bottom along wire electrode to accumulate at the exit of kerf, blocking the new working solution to come into kerf. So the insulated state of working solution is not normal at the exit of wire electrode, resulting in the abnormal discharge, and the kerf width of exit is less than that of the entrance as shown in Fig. 5. When the wire electrode moves back and forth, the height of entrance and exit of wire electrode are different in the same surface, which will affect the processing precision and surface roughness of wire-cutting. The measures to reduce strips as follows:

(1) To remove the black and white stripes, the saponification solution with strong detergency should be used as the working solution of WEDM, and the detergent state of kerf should be improved by adding some detergency substance. The spiral nozzle is used to spray, and the guiders with high wear properties mentioned above have reasonable spraying structure, making the working solution even eject along the axis of wire electrode.

(2) The wire electrode of general WEDM-HS does not reverse until the entire wire go to end, in order to form the convex-concave stripes. The processing zone that the wire electrode passes through is longer, the convex-concave stripes are more obvious, whereas the stripes are few. When the electrode wire is short to a certain extent, the convex-concave stripes could be removed. In order to remove the convex-concave stripes, the key is to control the length of wire electrode in each direction and the repeated addition of cutting traces of wire electrode in processing zone, it's to remove the convex-concave stripes. The wire-moving method of ultra-short trip back and forth is adopted by Shanghai Mass Electronic Equipment Co., Ltd. In order to achieve the cutting without strip, the actual cutting distance of reversing direction each time is very short, it's about a quarter of the wire diameter, and the irregularities formed during the movement of wire electrode up and down are stacked with each other, so the black and white and convex-concave stripes will be difficult to find out. If the cutting path in reversing each time is shorter, the effect will be better.

The wire-cutting technology of ultra-short trip back and forth dose not use the short molybdenum wire, which will lead to the short section of wire electrode long-term concentrated to accelerate the loss of wire diameter and break of wire, and affect seriously the processing precision. Although the storing wire cylinder rotates and reverses frequently, the whole cutting process is still performed with the full-length molybdenum wire of storing wire cylinder, in order to avoid the loss of wire diameter after the concentrated discharge effectively. However, the high-frequency pulse power is cut off frequently to reverses frequently the storing wire cylinder, which will affect the average cutting speed.

Influence of residual stress inside the workpiece on processing quality

When the roughcast after heat treatment is processed by WEDM, due to the removal of much metal and interrupted cutting, the relative balance of residual stress inside the workpiece will be destroyed to reduce the processing precision of parts. Even the material will be suddenly cracked in the process of cutting, and the wire electrode is caught and pulled apart by kerfs in severe cases. Therefore, materials with excellent harden ability and small deformation of heat treatment should be chosen. In addition, the heat processing methods should be chosen correctly and the standards of heat treatment should be performed strictly.

Processing quality

The TP-25 WEDM machine produced by Shanghai Mass Electronic Equipment Co., Ltd. is used to process. The processing material is Cr12, which size is 10 mm×10 mm×40 mm. The processing condition and processing quality are shown in Table 1.

The research results show that compared to the guide wheel to position and adopting the wire-moving of whole trip back and forth, the surface roughness value can be reduced 0.8 μm, the maximum error of sunken corner can be reduced 10 μm, and there is no reversing stripe using the guider with high wearing resistance to position and the wire-moving of ultra-short trip back and forth. So the processing quality of workpiece is greatly improved in spite of the decline of cutting speed.

Conclusion

1) The manufacturing precision of WEDM has great influence on the processing quality, and should be strictly controlled to improve machining precision.

2) The variations of form and position of electrode wire, producing inevitably in the process of WEDM-HS, which could be effectively controlled by the guiding device with high wearing resistance to improve the processing quality, if the wire-moving cutting method of ultra-short trip back and forth is applied to cut with no strips, however, the cutting speed will decline.

3) The strips could be reduced to improve the surface quality by using the working solution with the strong detergency and the appropriate spray method.

Fig. 1 .Fig. 2 .

 12 Fig.1. Variations of form and position of wire electrode. (1-Processing track along L3; 2-Theoretical track; 3-Processing track along L1)

( 1 -

 1 Bearing; 2-Guide wheel; 3-Wire electrode; 4-Tangent point processing along L1; 5-Tangent point of theoretical track; 6-Tangent point processing along L3)

Fig. 3 .

 3 Fig.3. The formation of sunken corner. (1-Theoreti-cal track; 2-Actual track; 3-Wire electrode)

Fig. 4 . 3 Influence

 43 Fig.4. The positioning of guiders with wear properties.(1-Guiders; 2-Spray nozzle plate)

5 .

 5 (a) Moving from top to down (b) Moving from down to up Fig.Wire-cutting back and forth.

Table 1 .

 1 The comparison of processing quality with different parameters

	Sample	Position mode	Wire-moving way	Exist reversing strips or not	Surface roughness (μm)	Max-sunken corner (μm)	Processing time (s)
	01	By guide wheel	Whole trip forth back and	exist	2.4	17	3062
			Ultra-short
	02	By guider	trip back and	not	1.6	7	2125
			forth

Acknowledgment. Work was supported by the National Natural Science Foundation of China (Grant No. 10972030).


Qingwei Duan
email: duanqingwei@ires.cn

Xiaoping Xin

Guixia Yang

Baorui Chen

Hongbin Zhang

Yuchun Yan

Xu Wang

Baohui Zhang

Gang Li

Current situation and prospect of grassland management decision support systems in China

China, with wide grassland areas of the second rank throughout the world, is faced with a severe challenge on how to manage its vast and degenerating/degenerated grassland. Computer and network technologies are more and more widely applied in grassland production, research and education, which is just a greatly encouraging field. Tremendous achievements have been made in grassland management decision support system (GMDSS) research in developed countries at present, but there is still a long way to obtain a great development for developing countries, such as China. This paper reviewed the research progress and current situation in the GMDSS research and application in China. Concept models and empirical models are still hugely focused on the corresponding research fields in China, but the integrated GMDSS has not been well developed. Therefore, Chinese scientists must develop the integrated models from the existing models, and accordingly sinicize the GMDSS of models used in the developed countries for availably application. In the other hand, there is a same direction of research and development about the GMDSS not only for developed countries but also for China, which is going to be combined with internet, 3S (GIS, RS and GPS) and virtual technology.

Introduction

Information technology, digital agricultural technology and decision support systems (DSS) and other technologies have been put on a very important position in agriculture, but China is still relatively lagging behind in the field of grassland management DSS(GMDSS) especially when compared with the devoloped countries.In this serious international situation, we must catch up, otherwise we will not only lag behind in scientific research, but also prevents China to an inferior position in the international competition in the livestock industry.

The grazing system is a complex systems, including animals, plants, environment and peoples. About pasture growth, animal nutrition, the environment changes and the management of human behavior factors on grazing system interaction, a great deal of statistics models,

Remote sensing model grassland production

A

The Model construction and appliacation of mathematical methods in grassland management

Systems dynamics simulation of the grassland management

System dynamics is a discipline about the analysis of information feedback system, and also an integrated cross-discipline which to be used to understand system problems and resolve system problems.It is an integrated natural and social sciences disciplines based on systems theory,control theory, information theory,. Lv

Integrated application of 3s technology

4.Small decision support systems

Small DSS is relatively more than big one in the farm management,such as pig farm, cattle farm's small DSS.The small DSS can realize the industrialization and the automatic control, to be quite convenient with the market trail connection, compared with the huge grassland area livestock husbandry. And small DSS is manoeuvring, therefore develop rapidly.

5.Calibration and application of broad model

Although the overseas software's chinization is not a long-term plan, but is also an important direction.

Virtual reality technology

The virtual reality technology is a technology of reflecting the biological growth process with graphs and dynamic images.

Realizing the virtual reality in GMDSS will

7.Prospects of grassland decision -making system in China

Study of GMDSS has made some achievements, such as grassland productivity model and grassland system simulation, but there is still no practical GMDSS in China.

In future research, we should firstly combine the existing resources, including the remote sensing monitoring data, the ground datum and the meteorological data etc,and full use of IT

  mechanism models and simulation models have been set up in the past. Scientists established many computer DSS with the existing models, which improved the grassland management from a extensive management to a targeted intensive management. By simulating various production management strategy with the DSS, the simulation results can guide the production and management. Judging from the production level of GMDSS, it reducing the production management of blindness, reduce business risks; from the policy level, it helping the decision support for the government. With scientific and technological development and social needs increasing, grazing management simulation model have been made remarkable achievements in research and applications (Duan Qingwei, 2009). This paper reviews the recent studies of domestic progress about GMDSS, including the base model, small DSS, network technology, remote sensing, GIS technology ,WebGIS technology and virtual reality technology in DSS applications, and highlighted several ongoing large-scale domestic DSS research, and to outlook China's future trends in DSS research for reference of China GMDSS research and applications 。 2.Construction of basic model 2.1 Crop growth models Crop growth models can be used in pasture systems, hence the crop growth model would greatly facilitate pasture models study. Although the crop growth simulation research started very late,some basic researchs have been undertaken in China.Such as, "Rice population computer simulation model of material production"from Shanghai Institute of Plant Physiology of the CAS. "Rice growth calendar model (RICAM)" from Jiangxi Agricultural University;After 1990s, Institute of Agricultural Meteorology,Chinese Academy of Agricultural Sciences, finished CERES -Maize model Chinesization.In 1992,Jiangsu Academy of Agricultural Sciences finished"Rice cultivation Computer Simulation Optimization Decision System (RCSODS);Chinese Academy of Agricultural Sciences finished " Cotton Production Management Simulation System" (Zhang Wei, et al.). Liu Yilian, Chou Ziming(1994a) established populations of Leymus chinensis meadow Hulunbeier growth and yield simulation model based on the theory of crop growth simulation, combined with the growth characteristics of natural grass. The model consists of three sub-models: (1) photosynthesis and respiration; (2) assimilate distribution; (3) leaf area. The model can simulate aboveground biomass of Leymus chinensis populations with temporal dynamics by using the measured data validation of the model, and more objectively reflect the weather conditions on the grass growth and yield formation. Liu Yilian, Chou Ziming (1994b) carried on a certain numerical experimentation using the kinetic simulator model of Leymus chinensis.They discussed the influence of the meteorological factor-temperature, soil moisture, solar radiation not in the same year to change-to Leymus chinensis population output; The output calculates the dynamic "actual production", Which shows the statistical model simulation potential and the limitation. Pu erciren, Liu Naizhuang(1994) took the crops growth analog theory as a foundation, considered the multi-populations character of the steppe community, established the population biomass time dynamic synthesis influence's whole pattern for the high and cold Kobresia humilis meadow ,Which can reflect effect of the meteorological factor and the biotic factor to biomass production, including random population physiological process-photosynthesis, respiration, assimilation products assignmentquantity simulations and the leaf area index dynamics, the community structure kinetic simulator et.al, 6 kinds of subschemata,which can quantify the grassland community ground biomass and the underground biomass seasonal variation, and that is a good attempt of prairie vegetation photosynthesis output simulator study. Wei Yurong (2004) used the Xilingol typical grassland animal husbandry meteorology data, from the environment factor to the forage and domestic animal influence's angle embarking, from qualitative to the quantitative analysis external environment condition to the grassland animal husbandry production's influence and the revelation lawn animal husbandry production rule, established a set decision-making service system to be possible to used in instructing the animal husbandry production.

  Shengli use system dynamics to simulate grassland ecosystem very early 1990s in China. Lv Shengli , in Gansu Academy of Sciences, built a set of models in second production in micro and macro aspects of grassland.LvShengli (1991) studied " China grassland productivity simulation". He simulated the productivity of grassland for macro-and long-term dynamics by using system dynamics approach, system dynamics modeling and computer simulation tools。And he also made a scientific prediction and verification for the grassland productivity and the development trend of China.Outstanding features of this study compared with similar studies abroad are: 1), According to existing problems of grazing management in China, highlighting the breed of livestocks and livestock structure adjustment; 2), Focus on solving the contradiction between supply and demand cool-season forage,so that Grasssland Seasonal Livestock Manegement theory can reach the stage of dynamic simulation; 3), Suitable for medium and long term macro-policy research. Lv Xiaoying, LvShengli (2003) established a dynamic model of grassland animal husbandry sustainable development using principles and methods of System Dynamics.This study simulated the livestock husbandry prospects for the future development on the 2000-2020 period in the northern temperate zone and alpine grassland steppe grassland.Dynamic model of sustainable agriculture development takes cold season and warm season forage needs satisfaction rate as bonds, which make primary pasture production and secondary livestock production process a organic whole coupled with the dynamic and complex feedback structure. With this model we can achieved analysis and comparison of a variety of sustainable agriculture development simulation programs, from which to reveal the barriers in the development process, seek strategies to improve the status of a favorable way, show various scenarios of possible development trends, provide a basis for policy-makers. Aim at Gannan grassland animal husbandry practical situation, one of the major pastoral areas in Gansu Province, Duan Shunshan, Lv Shengli et.al (1995) analyzed the Gannan grassland animal husbandry development of power and constraints; predicted 30 years of pastoral animal husbandry in Gannan (1990-2020) the dynamic process of development and change; established long-term development of grassland animal husbandry in Gannan dynamic model by using system dynamics simulation technology, system dynamics flow diagram and spreadsheet functions.

3 .

 3 Construction of GMDSS 3.1Grass-livestock Digital Management DSS in Pastoral area Lanzhou University preside over "the pastoral area grass livestock digitization to manage DSS" the topic (2007AA10Z232) from the People's Republic of China Department of Technical Science, Which was authorized in 2007.It is a special topic--modern agriculture area of technology digit agricultural technology-in the project the national high-tech research development plan (863 plans).This beginning and end age limit of the topic is August, 2007 to October, 2010, Beijing Raising livestock Research institute of Chinese Agriculture Academy of science is the cooperation unit. This topic sets an experiment area of the Gannan pastoral area, through the investigation and the monitoring to the grassland and the livestock husbandry, with the help of network techonology, 3S technology, system model and optimized decision-making, the exploration research based on MODIS (Moderate Resolution Imaging Spectradiometer) grassland remote sensing monitoring and the evaluating indicator system, they established the grassland information fast gain model, the grass livestock dynamical equilibrium and the analysis diagnostic model and the pastoral area grassland animal husbandry integrated management decision model.They made a contrastive analysis for lately 30 year grass livestock spatial variation condition, optimized grass livestock production technology flow, constructed GMDSS based on the network technology. This project already applied for the pastoral area grass-livestock digitizatal management DSS1.owner (nationality): Lanzhou University: China. For the first time publication date: 2009-04-20, registration authorization date: 2009-09-28). Following research work is still in advance.

  Figure1 Grassland ecological environment monitoring &appraisal diagram under 3s technical support

Figure. 2

 2 Figure.2 Framework for the digital prataculture technique platform of China

  Xiong Benhai (2005) has constructed "the cow fine cultivation technology platform"using RFID, PDA and wireless local network technologies,which realized the comprehensive gathering cow's individual body situation information and through calculate gain cow's date nutrition required quantity using the nutrient forecast model and the cow secretes curve model,which directs the instruction date grain formula, achieves the cow individual the fine raising goal. Wang Zhonghua (2005) uses digital technique collecting cow milk production quantity, young ingredient, amount of exercise, body situation, body weight change information, as well as cow's foundation date grain picks the appetite, through the overall system automatically controls feed's supplement plan, which realized cow nutrition need, feed design, information acquisition, cow automatic diagnosis, automatic control et al various technological means. Expert system of the alfalfa planting management and pest control developed by Beijing Intelligence Valley Science and Technology Limited Company can be used to alfalfa planting management and pest control production. (National Copyright Administration registration number: 200210952; Software copyright registration number: 2002SR2425; Patent of invention number: 02121283.X) (Bai Fengshuang, 2003) Jiang Wenlan has set up a big sustainable production model of forage resources population protection using the biocybernetics method, and take the experiment as an example, she had determined the concrete protection target and the grazing management measures, studied the unicast artifiicial pasture optimum control model with herd the countermeasure; constructed the artifiicial pasture applying fertilizer model and the grazing system nutrient cycle mechanism model, and proposed "Integrated computer fertilizer recommendation expert system for artificial pasture".

  We should complete the forage adaption assessment and the ecology regional planning to direct macroscopic region forage production. Secondly, we must research and develop GMDSS of our own proprietary intellectual property rights and suit the Chinese grassland production management profitting developed countries, or adjusting overseas mature model is a convenient way.For example,the introduction of Australian GRAZPLAN system by IARRP-CAAS. Simultaneously we should realize combination between the remote sensing monitor data and DSS, and realize timeliness and effectiveness of GMDSS. China has approximately 4×10 8 hm 2 grassland, the area is no 2 in the world, we should develop our own GMDSS adapt to China grassland geography, climate and special grazing tactics, which is requested from the extensive economy to the intensive economy trend of development. We must realize the grazing management mathematically quantification and controllable; we must develop comprehensive GMDSS, as well as small grazing management decision-making calculator. Along with developement of computer network technology, small calculators may provide the online use. In brief, our country's grazing management is still the family pasture-like extensive management, There is still a very big disparity compared with the developed country. Our grazing management DSS research also just begin.Because the DSS research is time and expends-consuming work, usually,we need model research foundation, simultaneously need the massive data foundation and computer application ability, and the multi-disciplinary cooperation. We hope in the near future, we might realize dynamic grassland process management based on the knowledge library, the model base and the remote sensing database, and realize the virtual reality--the grassland management process and the effect present by the visual picture form in front of us.

Application of GIS and WebGIS technology

	the domestic DSS research to a certain extent.	seed selection for Gansu returning cropland back
	Institute of Agricultural Resources and	to grassland,that is offering decision support and
	regional	Planning,Chinese	Acedamy	of	basis for forage adaptation problem.
	Agricultural	Sciences	(IARRP-CAAS)
	introduced and improves the Australian
	GMDSS-GRAZPLAN	for	North	China
	grassland.They used long-term observation data
	of the temperate grassland, fitted and adjusted its
	first floor model parameter, based on which,
	they established a suite of domestic animal
	system's system simulation and the dynamic
	management system for Chinese temperate
	grassland, which could accurately simulate the
	ungrazing grassland production and the
	community structure dynamics and grassland
	production and the community structure under
	different stocking rates, defferent utilization
	pattern (rotational grazing or forbidden
	grazing)in grazing situation.which can provide
	references for the family pasture livestock
	production, ecology,economically optimized
	management and dynamically regulation (Tang
	Huajun, Xin Xiaoping, 2009).
	6.New technology application in
	grassland management
	6.1 The model and the network bond is a current
	international agriculture model study important
	tendency. Expert system ( ES) or DSS combine
	with GIS, whicn may cause ES or DSS
	decision-making process integrated with the
	geography information.Through useging GIS
	analysis result, we can enhance ES and DSS
	decision-making level.At the same time,
	decision-making result issuing through GIS may
	strengthen intuitive, and builds the foundation
	for the further localization implementation
	(Chen Liping, Zhao Chunjiang ,2002). Sun Juan
	(2004) established forage adaptation and
	returning cropland back to grassland DSS based	Through taking example by the
	on GIS,which acilitated Gansu Province forage	overseas advanced technology can also promote

Acknowledgment. Research was supported


Xiangbin Xu
email: champagnewq@yahoo.com.cn

HSFDONES: A Self-Leaning Ontology-based Fault Diagnosis Expert System Framework

Keywords: HSFDONES, Ontology, Fault Diagnosis, Self-learning, Data Mining

HSFDONES is an expert system fault diagnosis which makes the fault diagnosis working more intelligently, HSFDONES uses the ontologybased self-leaning theory and technology to build fault diagnosis expert system. The fault diagnosis knowledge structure is defined and the relevant structure ontology and core fault ontology is researched in HSFDONES; the fault diagnosis data warehouse is built, the decision tree and Apriori algorithm are used to acquire fault knowledge to realize HSFDONES' s ontology self-learning. HSFDONES offers system framework for building intelligent fault diagnosis system. Finally the agricultural machinery' s hydraulic fault diagnosis expert system was developed on the basis of the framework.

Introduction

HSFDONES (Hydraulic System Fault Diagnosis Ontology Expert System, hereinafter referred to as HSFDONES) is an ontology-based hydraulic system fault diagnosis expert system. The system architecture of HSFDONES is shown in Fig. 1. HSFDONES takes data warehouse technology to organize and manage heterogeneous system fault information, the ontology is used as HSFDONES' knowledge backbone. In order to realize ontology self-leaning, HSFDONES takes learning algorithm in the field of machine learning to realize diagnosis ontology self intelligent learning, and finally HSFDONES uses Jena and Topic Maps as its reference and presentation engine respectively. Fig. 1 The System Architecture of the HSFDONES

2

HSFDONES Data Warehouse

Data Warehouse Structure

Hydraulic system fault information is stored in the media such as database, Excel, TXT and other file formats, the different format data can not offer knowledge efficiently. Data warehouse technology is an effective solution to solve this problem [START_REF] Hong | OLAP and Data Warehouse Modeling Techniques[END_REF]; data warehouse technology can extract, handle and standardize large, varied data. The data in warehouse is organized in the form of the data cube, after data ' s standardization and consistency, the data can be loaded and imported into the data warehouse' s cubes, the hydraulic system fault data warehouse' s structure is shown in Fig. 2.

HSFDONES Knowledge Structure

Oontology-Based Knowledge

HSFDONES core ontology includes two parts: the hydraulic structure ontology and the hydraulic fault ontology. Hydraulic structure ontology describes the structure of hydraulic system and assembly relations; Hydraulic fault diagnosis ontology describes the hydraulic system' s critical fault information, which means hydraulic system failure and their relationship.

In order to design and build the HSFDONES core ontology, first we should define the domain area [START_REF] Jinfei | Skeleton of Boiler-Based Fault Detection System of the Domain Ontology Construction[END_REF] of hydraulic system' s fault diagnosis, which can be done by consulting domain experts, filed researching and statistics of historical data. After that, we can make abstraction to identify and define the ontology classes, class hierarchy, class property, restrictions, characteristics (such as symmetric, transitive, etc), finally build individual instances of ontology classes to get HSFDONES diagnosis ontology model.

HSFDONES Fault Knowledge Definition

The hydraulic system' s fault is described in three parts, which are fault phenomenon, fault causes and failure sources (the parts or component which causes the failure). Fault phenomenon is the presenting symptoms, fault source is parts or components where the fault raises, fault causes is information chain which can track from fault phenomena to fault source. HSFDONES fault knowledge can be described in fault triples:

<Fault phenomena, Fault causes, Fault source> HSFDONES fault knowledge should figure out the connection which links the fault phenomenon to the fault source through some logical analysis.

HSFDONES Fault Ontology Construction

HSFDONES hydraulic system fault ontology is built in the seven-step ontology way.

After consulting domain experts, we get the following fault diagnosis knowledge: 1) IF " the fuel tank can not change direction"AND " the valve can not return to the center position"THEN " the electromagnetic iron is damaged" ;

2) IF " the valve can not return to the center position"AND " the electromagnetic iron is good"THEN " the gap is too small"OR " the oil is polluted" ;

3) IF the electromagnetic iron is good"THEN " the coil is aging"OR " the switch is circuited" .

Let' s take the first diagnosis knowledge as an example to show the process of ontology constructing:

The fault knowledge triples are: < Fuel tank can not change direction, Valve can not return to the center position, Electromagnetic iron is damaged> According to the fault knowledge, we can define related ontology knowledge in the ontology knowledge base, namely: Fuel tank' s changing direction: Can not change -> fault phenomenon Valve resetting position: Can not reset -> fault cause Electromagnetic iron Status: Is damaged -> fault source The fault phenomena, fault causes and fault source described in HSFDONES fault knowledge triple can modeled as ontology' s class, their status (such as: "can not change direction ", "can not reset position", etc.) are modeled as class properties associated the corresponding ontology class.

Different from the hydraulic system structure ontology, we just build the fault diagnosis core ontology, and the fault diagnosis core ontology can self-learn new ontology once the hydraulic system new failure occurs, which means fault diagnosis core ontology can grow dynamically.

The fault diagnosis should be formalized so as to be understood by machine, we build the fault diagnosis ontology model in Proté gé IDE [START_REF]The Proté géproject[END_REF], after that we should transfer and formalize the fault diagnosis ontology model, HSFDONES use OWL as the ontology coding language to formalize and describe fault diagnosis ontology model [START_REF] Du | Ontology-Based Fault Diagnosis for Chemical Process[END_REF], OWL-based ontology can be shared between systems.

HSFDONES'Self-Learning Algorithms

Self-learning Algorithms

HSFDONES ontology self-learning algorithm can excavate fault knowledge from the hydraulic fault data warehouse, which can be transferred into ontology by referring to the hydraulic system structural ontology and core fault ontology, and the new-learned fault ontology are stored in the fault ontology library. Decision tree [START_REF] Wei | Data Mining Concepts and Techniques[END_REF] algorithm is efficient classification algorithm in data mining, it can extract decision-making knowledge from the training data, decision tree' s knowledge is described in the tree-style, which includes internal nodes, fork and leaf nodes, the internal nodes in decision tree represent a test property, the fork in decision tree represent classification, the leaf in decision tree nodes represent a diagnosis result, the decision tree can display knowledge in a graphical way, the decision tree uses ID3 and the C4.5 as learning algorithm, ID3 is mainly applied to discrete attributes, C4.5 classification can leaning from both discrete and continuous attributes, C4.5 builds decision tree based on information entropy theory, which calculate the information gain for each attribute recursively, select the highest information gain attributes as the split attribute, the information gain is calculated as following:

1) Compute the entropy of dataset:

)) / ) , ( ( log * ) / ) , ( (( ) ( 2 1 S S C freq S S C freq S Info i k i i    
2) Compute the Weighted entropy sum of property:

)) ( * ) / (( ) (    i i x T Info T T T Info 3) Compute the Info Gain of property: ) ( ) ( ) ( T Info T Info X Gain x  
The freq (Ci, S) represents the sample size belongs to class Ci in training set S, Gain (X) represents information gain of the property X. C4.5 learning algorithm finds max information gain property as the root of decision tree, and then call the algorithm recursively in the split data set, until a whole decision tree is constructed; once the decision tree is built, we should prune it to get a refined, non-redundant decision tree.

Knowledge Extraction

The knowledge leaned by decision tree is showed in a " IF ... ... Then ... ..." style, we can extract the knowledge rule from decision trees as follows:

1) The fault knowledge rule is paths which link the root to each leaf respectively;

2) The internal test nodes along the path represent the premise of the rule (IF) section and each leaf node at the end of the path represent conclusions (THEN).

HSFDONES Knowledge Inference and Presentation

Knowledge Inference

HSFDONES take Jena as it' s of inference engine, Jena is Java-based open source semantic web toolkit developed by HP, it offers a programming environment for parsing RDF, RDFS and OWL ontology, and Jena provides a rule-based inference engine. Jena' s inference engine can be used in OWL-based ontology, its inference is based on direct graph, if can offer forward reasoning, backward reasoning and reasoning mixed. The rule sets Jena get are bound to the data model, which can form a new reasoning input, so the query results returned by the Jena inference engine include both original data triples and the new knowledge rules inferred from the ontology library.

In HSFDONES system,once the hydraulic fault diagnosis ontology OWL ontology model is imported into Jena' s ModelFactory, the Jena inference engine can transform the OWL ontology into a an ontology inference graph, then the Jena inference engine can take the ModelFactory API to interact with the hydraulic fault diagnosis ontology, which means the end-user can query and get hydraulic fault diagnosis knowledge.

In the HSFDONES system, the Jena API is embedded into the JSP code, the diagnosis knowledge inferred by the Jena is transformed in a XTM-formatted style, which finally is showed in the end-user' s web browser.

Knowledge Presentation

HSFDONES take the Topic Maps to present the fault diagnosis knowledge, Topic Maps can organize and describe the ontology knowledge topics based on meta-data, and the ontology knowledge organized and described on the topic-based can be navigated and explored easily. The HSFDONES knowledge topic map includes three basic elements: topic, association and the occurrence. In the topic map, HSFDONES fault source organized can be located easily,and the fault correlation can be displayed directly, which means a easy way for the user to navigate, explore and trace the hydraulic fault, this is mostly helpful for the fault detection and prevention.

HSFDONES take the TM4J as it' s topic map engine, TM4J offer a user-friendly interface and a powerful a secondary development environment, which make it flexible and extensible, TM4J take a XML-based specification language-XTM to describe the ontology knowledge and its relation, so HSFDONES needs a data adapter, which bridge the gap between the OWL and XTM, the working processes of the adapter is showed in Fig. 3.

Fig. 2 .

 2 Fig. 2. HSFDONES Data Warehouse Structure

Fig. 3 .

 3 Fig.3. HSFDONES Knowledge Representation

Acknowledgements

This study was supported by JiangXi Natural Science Foundation(No.2009GZS0015), JiangXi Educational Committee Foundation(No.GJJ10467), National High-tech Research and Development Program of China(863 program) (No. 2009AA04Z106) and Jiangxi Key Laboratory of Ministry of Education for Conveyance and Equipment.