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1、DISTRIBUTED TEMPERATURE CONTROL SYSTEMBASED ON MULTI-SENSOR DATA FUSIONCai Yan, Yang Hailan ,Hua Xueming and Wu YixiongAbstract:Temperature control system has been widely used over the past decades. In this paper, a general architecture of distributed temperature control system is put forward based

2、on multi-sensor data fusion and CAN bus. A new method of multi-sensor data fusion based on parameter estimationisproposed for the distributed temperature control system. The major feature of the system is its generality, which is suitable for manyfields of large scale temperature control. Experiment

3、 shows that this system possesses higher accuracy, reliability, good realtime characteristicand wide application prospectKeywords:Distributed control system; CAN bus; intelligent CAN node; multi-sensor data fusion.1. IntroductionDistributed temperature control system has been widely used in our dail

4、y life and production, including intelligent building, greenhouse, constant temperature workshop, large and medium granary, depot, and so1on . This kind of system should ensure that the environment temperature can be kept between two predefined limits. In the conventional temperature measurement sys

5、tems we build a network through RS-485 Bus using a single-chip metering system based on temperature sensors. With the aid of the network, we can carry out centralized monitoring and controlling. However, whenthe monitoring area is muchmore widespread and transmission distance becomes farther, the di

6、sadvantages of RS-485 Bus become more obvious. In this situation, the transmission and response speed becomes lower, the anti-interference ability becomesworse. Therefore, we should seek out a new communication method to solve the problems produced by RS-485 Bus.During all the communication manners,

7、 the industrial control-oriented field bus technology can ensure that we can break through the limitation of traditional point to point communication mode and build up a real distributed control and centralized management system. As a serial communication protocol supporting distributed real-time co

8、ntrol, CANbus has much more merits than RS-485 Bus, such as better error correction ability, better real-time ability, lower cost and so on. Presently, ithas been extensivelyused in the implementationof distributedmeasureme nt and con trol doma ins.With the developme nt of sen sory tech no logy, mor

9、e and more systems beg in to adopt multi-se nsordata fusi ontech no logyto improve theirperformances.Multi-sensor data fusionis a kind of paradigm forintegratingthe data from multiple sources to synthesizethe new345information so that the whole is greater than the sum of its parts .And it is a criti

10、cal task both in the con temporary and future systems which have distributed n etworks of low-cost, resource-c on stra ined sen sors2. Distributed architecture of the temperature control systemThe distributed architecture of the temperature con trol system is depicted in the Figure 1. As can be see

11、n, the system con sists of two modulesseveral in tellige nt CAN no des and a mai n con troller. They are interconnectedwith each other through CANbus. Each module performs itspart into the distributed architecture. The following is a brief description of each module in the architecture.llmin Cofitro

12、lDeirl - I 1Cabling unitTdp 电iConvarfI Tender atur*IunitSrv AKDisplay 111 Mouae3. 1ma in con trollerAs the system s main con troller,the host PCca n com muni cate with thein tellige nt CAN no des. It is devoted to supervise and con trol the whole system, such as system configuration,displayingrunnin

13、g condition,parameter in itializatio nand harm onizing the relati on shipsbetwee n eachpart.What s more, we can print or store the system s historytemperature data, which is very useful for the an alysis of the system performa nee3.2. Intelligent CAN nodeEach intelligent CAN node of the temperature

14、control system includes five units: MCUa single chip, A/D conversion unit, temperature monitoring unit sensor group, digital display unit and actuators a cooling unit and a heating unit. The operating principleof theintelligent CAN node is described as follows.In the practical application, we divide

15、 the region of the control objective into many cells, and lay the intelligent CAN nodes in some of the typical cells. In each node, MCU collects temperature data from the temperature measurement sensor groups with the aid of the A/D conversion unit. Simultaneously, it performs basic data fusion algo

16、rithms to obtain a fusion value which is more close to the real one. And the digital display unit displays the fusingresult of the node timely, so we can understandthe environment temperature in every control cell separately.By comparing the fusion value with the set one by the main controller, the

17、intelligent CANnode can implement the degenerative feedback control of each cell through enabling the corresponding heating or cooling devices. If the fusion result is bigger than the set value in the special intelligent CANnode, the cooling unit will begin to work. Onthe contrary, if the fusion res

18、ult is less than the set value in the node the heating unit willbegin to work. By this means we can not only monitor theenvironment temperature, but also can make the corresponding actuator work so as to regulate the temperature automatically. At the same time every CANnode is able to send data fram

19、e to the CANbus which will notify the main controller the temperature value in the cell so that controller can conveniently makedecisions to modify the parameter or not. Since the CAN nodes can regulate the temperature of the cell where they are, the temperature in the whole room will be kept homoge

20、neous. Whats more, we can also control the intelligent node by modifying the temperaturessetting value on the host PC.Generally, the processors on the spot are not good at complex data processing and data fusing, so it becomes very critical how to choose a suitable data fusion algorithm for the syst

21、em. In the posterior section, we will introduce a data fusion method which is suitable for the intelligent CAN nodes 。4. Multi-sensor data fusionThe aim to use data fusion in the distributed temperature control system is to eliminate the uncertainty, gain a more precise and reliable value than the a

22、rithmetical meanof the measured data from finite sensors. Furthermore, when some of the sensors become invalid in the temperature sensor groups, the intelligent CAN node can still obtain the accurate temperature value by fusing the information from the other valid sensors.4.1. Con siste ncy verifica

23、ti on of the measured dataDuring the process of temperature measurement in our designed distributed temperature con trol system, measureme nt error comes into being in evitably because of the in flue nee of the paroxysmal disturb or the equipment fault. So we should eliminate the careless mistake be

24、fore data fusi on.We can elimi nate the measureme nt errors by using scatter diagram method in the system equipped with little amount of sen sors. Parameters to represe nt the data distributi on structure in clude media n Tm, upperquartilenu mbe Fv,lower quartilenu mbe FLand quartiledispers ion dF.I

25、t is supposed that each sen sor in the temperature con trol system proceeds temperature measurement independently.In the system, there areeight sensors in each temperature sensor group of the intelligentCANbode.So we can obta in eight temperature values in each CAN node at the same time. Wearrange t

26、he collected temperature data in a sequenee from small to large:T1, T 2, ,T 8In the seque nee, T 1 is the limit in ferior and T 8 is the limit superior.We defi ne the media n TM as:(1)The upper quartile Fv is the median of the intervalTm, TJ.The lower,T J.The dispersionquartile number FL is the medi

27、an of the intervalof the quartile is:We suppose that the data is an aberration one if the distance from the median is greater than adF, that is, the estimation interval of invalid data is:In the formula, a is a constant, which is dependent on the system measurement error, commonly its value is to be

28、 0.5, 1.0, 2.0 and so on.The rest values in the measurement column are considered as to be the valid ones with consistency. And the Single-Chip in the intelligent CAN nodewill fuse the con siste nt measureme nt value to obta in a fusi on result5. Temperature measureme nt data fusi on experime ntBy a

29、ppl ying the distributed temperature con trol system to a gree nhouse, we obtai n an array of eight temperature values from eight sen sors as followsS) 1S2Js5SsS728.132Q31 929,936.629328,0233The mea n value of the eight measureme nt temperature result isComparing the meanvalue (8)T with the true tem

30、perature value in the cell of the greenhouse, we can know that the measurement error is +0.5 C . After we eliminate the careless error from the fifth sensor using the method introduced before, we can obtain the mean value of the rest seven data (7)T=29.6 C , the measurement error is -0.4C .The seve

31、n rest con siste nt sen sor can be divided into two groups withsensor S1, S 3, S 7 in the first group and sensor S 2, S 4, S 6, S 8 in the second one. The arithmetical mean of the two groups of measured data and the standard deviation are as follows respectively:T(n = 29.3 flC 疔=2 22= 29.9 t=1.56Acc

32、ordi ng to formula (13), we can educe the temperature fusi on value with the seve n measured temperature value.The error of the fusion temperature result is -0.3C .It is obvious that the measurement result from data fusion is more close to the true value than that from arithmetical mean. In the prac

33、tical application, the measured temperature value maybe very dispersive as the monitoring area becomes bigger, data fusion will improve the measuring precisi on much more obviously.6. Con clusi onsThe distributed temperature con trol system based on multi-se nsor data fusion is constructed through C

34、AN bus. It takes full advantage of the characteristics of field bus con trol system-FDCS. Data acquisiti on, data fusi on and system con troll ingis carried out in the in tellige nt CAN node, and system management is implemented in the main controller (host PC). By using CAN bus and data fusion tech

35、nology the reliability and real-time ability of the system is greatly improved. We are sure that it will be widely used in the future.References1 D.SuandW.McFarland, “A2.5 -V,1-WmonolithicCMOSRFpoweramplifier, ”inProc.IEEECustomIntegratedCircuitsConf.,1997,pp.189- 192.2 D.K.SuandW.J. McFarland, “AnI

36、CforlinearizingRFpoweramplifiers usingenvelopeeliminationandrestoration,”IEEEJ.ofSolid -StateCircuits,vol.33,no.12,pp.2252- 2258,Dec.1998.3 B.Baliweber,R.Gupta,andD.J.Allstot,“Fully -integratedCMOSRFamplifier, ”inProc.IEEEInt.Solid-StateCircuitsConf.,1999,pp.72 - 73.4 A.Giry,J.-M.Fourniert,andM.Pons

37、, “A1.9GHzlowvoltageCMOSpoweramplifierformediumpowerRFapplications,”inProc.IEEERadioFreque ncyl ntegratedCircuits(RFIC)Symp.,2000,pp.121 - 124.5 C.FallesenandP.Asbeck, “A1W0.35 mCMOSpoweramplifier forGSM-1800with45%PAE”, inProc.IEEEInt.Solid -StateCircuitsCon仁2001,pp.158- 159.6 R.Gupta,B.M.Ballweber

38、,andD.J.Allstot,“DesignandoptimizationofCMOSRFpoweramplifiers, ”IEEEJ.Solid -StateCircuits,vol.36, no.2,pp.166 - 175,Feb.2001.基于多数据融合传感器的分布式温度控制系统蔡艳,杨海澜,许轲,吴毅雄摘要:在过去的几十年, 温度控制系统已经被广泛的应用。 对于温度控制提出了一 种基于多传感器数据融合和 CAN 总线控制的一般结构。一种新方法是基于多传 感器数据融合估计算法参数分布式温控系统。 该系统的重要特点是其共性, 其适 用于很多具体领域的大型的温度控制。实验结果表明该系统

39、具有较高的准确性、 可靠性,良好的实时性和广泛的应用前景。关键词:分布式控制系统; CAN 总线控制;智能 CAN 节点;多数据融合传感器。 1介绍分布式温度控制系统已经被广泛的应用在我们日常生活和生产,包括智能建筑、温室、恒温车间、大中型粮仓、仓库等。这种控制保证环境温度能被保持在 两个预先设定的温度间。 在传统的温度测量系统中, 我们用一个基于温度传感器 的单片机系统建立一个RS-485局域网控制器网络。借助网络,我们能实行集中监 控和控制 .然而 ,当监测区域分布更广泛和传输距离更远 ,RS-485 总线控制系统的 劣势更加突出。在这种情况下,传输和响应速度变得更低,抗干扰能力更差。因

40、此,我们应当寻找新的通信的方法来解决用RS-485总线控制系统而产生的问题。在所有的通讯方式中, 适用于工业控制系统的总线控制技术, 我们可以突破传统 点对点通信方式的限制、建立一个真正的分布式控制与集中管理系统, CAN 总 线控制比RS-485总线控制系统更有优势。比如更好的纠错能力、改善实时的能 力,低成本等。目前,它正被广泛的应用于实现分布式测量和范围控制。随着传感器技术的发展, 越来越多的系统开始采用多传感器数据融合技术来 提高他们的实现效果。多传感器数据融合是一种范式对多种来源整合数据 ,以综 合成新的信息, 比其他部分的总和更加强大。 无论在当代和未来, 系统的低成本, 节省资源

41、都是传感器中的一项重要指标。2 分布式架构的温度控制系统分布式架构温度控制系统如图中所示的图 1。可以看出,这系统由两个模块 两个智能 CAN 节点和一个主要的控制器组成。每个模块部分执行进入分布式架构。下面的是简短的描述下各模块。3.1 主要控制器作为系统的主要控制器,这主pc能和智能CAN节点通信。它致力于监督和 控制整个系统,系统配置、显示运行状况、参数初始化和协调各部分间的关系。 更重要的是, 我们能打印或储存系统的历史温度的数据, 这对分析系统性能是非 常有用的。3.2 智能 CAN 节点每一个温度控制系统的智能 CAN 节点有五个部分: MCU 一个单片机, A/D 转换单元, 温

42、度监测单元传感器群,数字显示器,激发器一个冷却单元 和供暖单元。接下来介绍智能 CAN 节点的工作原理。在实际操作中,我们划分控制的目标进入一些单元,储存智能 CAN 节点在 一些典型的单元。在每个节点,单片机借助 A / D 转换单位从温度测量传感器收 集温度数据。同时,它执行基本的数据融合运算获得运算的结果,更接近实际。数字显示器及时显示融合节点的结果, 所以我们能及时了解在每个控制单元所处 的环境温度。通过比较融合值用主控制器构建一个,这样智能 CAN 节点可以通过相应的 加热或冷却装置实现反馈控制各单元。如果在特别的智能 CAN 节点融合结果大 于设定值,冷却单位将开始工作。相反 ,如

43、果在节点融合的结果低于设定值加热 单位将开始工作。用这种方法 ,我们不仅能监控环境温度 ,还能做相应的触发器来 实现温度的自动调节。 与此同时, 每个 CAN 节点发送数据帧到 CAN 总线, CAN 总线将告知在着单元中的主控制器这温度值, 那么这控制器能便利的作出是否修 改这参数的决定。自从这 CAN 节点有调节温度的单元在,整个房间的温度将保 持均匀。更重要的是,我们也可以通过在主pc上修改温度的设定值来控制这智能 节点。一般来说 ,处理器不擅长即时的复杂的数据处理和数据融合 ,所以如何选择合 适的数据融合算法对系统变得至关重要。后一节中 ,我们将介绍适合于智能 CAN 节点的数据融合方

44、法。4. 多传感器数据融合旨在利用数据融合在分布式温度控制系统中来消除不确定性,获得更精确、可靠是比从限定的传感器的测量数据的算数平均值更重要。当一些传感器的温度传感器变为无效的,这智能 CAN节点还可以通过熔断这些信息而从有用的传感 器获得精确温度。4.1实测数据的一致性核实在我们设计的分布式温度控制系统的温度测量的过程中,突发性干扰或设备故障的影响不可避免的产生测量误差。所以在数据融合前我们应该消除错误的误 差。我们可以利用系统中配备的少量传感器用散点图发消除这个测量误差。用参数来代表数据分布结构包括中值一一Tm,上四位数一一Fv,下四位数一一Fl和分散四位数dF.人们认为每个传感器在温度控制系统的温度测量所得独立。 在系统中,有八 个传感器在各智能CAN节点的温度传感器群。所以我们在每个 CAN节点同一 时刻能获得8个温度值。我们安排收集到的温度数据序列由小到大 :T1,T 2在序列中,T1是最低位而T8是最高位

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