毕业设计外文翻译-基于多数据融合传感器的分布式温度控制系统

1、基于多数据融合传感器的分布式温度控制系统摘要：在过去的儿十年，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

2、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 此，我们应当寻找新的通信的方法来解决用rs-485总线控制系统而产牛的问题。 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。

3、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， 节省资源都是传感器屮的一项重要指标。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。下而的是简短的描述下各模块。3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

4、、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个单片机，a/d转换单元，温度监测单元一传感器群，数字显示器，激发器一一个冷却单元 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

5、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來

6、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牛测量误差。所以在数据融合前我们应该消除错误的误 差

7、。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,下四位数一一丘和分 散四位数一一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。在系统屮，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：a，t2,，t8在序列中，t1是最低位而t8是最高位。我们定义几为：上四位数一一片是区间 t的中值,低四位数一一片是区间t】,tj的 中值，这四位数的离散是："f=f、-fl。该公式，一个是常数，取决于系统测量误差，通常值是

8、0. 5, 1. 0,2.0等等。在 数列中其余的测量值都被看作是于有效值一致的。在智能ca7节点的单片机智将 把一致的测量值融合。5. 温度测量的数据融合的举例分布式温度控制系统运用于一间温室，我们从8个温度传感器获得一组8 个温度值如下s)s2s?s4s。s?sg28.132.031.929.936.629.32&028.3八个温度测量值的结果亍=丄扌7>30.5 r.q< 把在这温室中的八个温度的平均值和真实的温度值做比较，我们可以知道测量误 差是+ 0.5°co之后在介绍这个方法前我们消除从这第五个传感器的测量误差， 我们能得到的剩余的七个数据的平均值(7

9、)t = 29. 6°c,测量误差是-04°c.这剩 下的七个传感器被分成两个传感器组，sp s3, s?是第一组，s2, s. s6, s*是第 二组。两组测量数据的算术平均和标准偏差分别如下：7a)= 29.3 *c &二 2.22t(2)= 29.9 *c=1.56根据公式(13),我们可以用七个测量温度确定温度融合值。产"9.7c融合温度的结果的误差是-0. 3°co很明显，数据融合测量结果比算术的平均值更接近于实际值。在实际操作中， 测量温度可能是很分散的变得更大的监测区域，数据融合将更加明显提高了测量 精度。6. 总结这基于多数据融合

10、传感器的分布式温度控制系统是通过can总线构建。它 充分利用了 fdcs即吋总线控制系统的特点。数据采集，数据融合，系统控制用 智能can节点得到实现，而系统管理通过主控制器(host pc)被实现。通过使 用can总线与数据融合技术系统的可靠性和实时的能力被大大提高了。我们确 定它在将来会得到广泛的应用。distributed temperature control system based on multi-sensor data fusion abstract:temperature control system has been widely used over the past de

11、cades. in this paper, a general archilecture of distributed temperature control system is put forward based on multisensor data fusion and can bus. a new method of multi-sensor data fusion based on parameter estimation is proposed for the distributed temperature control system. the major feature of

12、the system is its generality, which is suitable for many fields of large scale temperature control. experiment shows that this system possesses higher accuracy, reliability, good realtime characteristic and wide application prospectkeywords:distributed control system; can bus; intelligent can node;

13、multi-sensor data fusion.1. introductiondistributed temperature control system has been widely used in our daily life and product ion， including intelligent building, greenhouse,constant temperature workshop, large and medium granary, depot, and soi .on this kind of systcm should ensure that the env

14、ironment temperaturc can be kept bet ween two predef ined 1 imi ts. in the conv enti orml tempera ture measurcment systems we build a nctwork through rs485 bus using a single-chip metering system based on temperature sensors. with the aid of the network, we can carry out centralized monitoring and c

15、ontrolling. however, whe n the mon i to ring area is much more widespread and transmissi on di stanee becomes farther, the di sadvantages of rs-485 bus become more obvious. in this situation, the transmission and response speed becomes lower, the anti-interference ability becomes worse. therefore, w

16、e should seek out a new communication method to solve the problems produced by rs-485 bus.during al 1 the communication maimers, the industrial controloriented field bus technology can cnsure that we can break through the limitation of traditional point to point communication mode and build up a rea

17、l distributed control and centralized management system. as a serial communication proto col supporting distributed real-time con trol, can bus has much more merits than rs-485 bus, such as better error correction ability， better real-time ability, lower cost and so on. presently, it has been extens

18、ively used in the implementation of distributed measurement and control domains.with the development of sensory technology, more and more systems begin to adopt multi-sensor data fusion technology to improve their performanccs. multi-scnsor deitei fusion is a kind of paradigm for integrating the dat

19、a from multiple sources to synthesize the new . information so theit the whole is greater than the sum of its parts and it is a critical task both in the contemporary and future systems which have distributed networks of low-cost, resource-constrained sensors2. distributed architecture of the temper

20、ature control systemthe distributed architecture of the temperature control system is depicted in the figure 1. as can be seen, the system consists of two modulesseveral intel 1igent can nodes and a main controller. they are intcreonneeted with each other through can bus. each module performs its pa

21、rt into the distributed architecture. the following is a brief description of each module in the architecture.ialiuigent can node 13. lmain controlleras the system" s main controller, the host pc can communicate with the intelligent can nodes. it is devoted to supervise and control the whole sy

22、stem， such as system configuration, di splaying running condi tion, paramctcr initialization and harmonizing the rclationships betwccn each part. whas more, we can print or store the systemi' s history temperature data, which is very useful for the analysis of the system performance 3.2. intelli

23、gent can nodeeach intelligent can node of the temperature control system includes five units: mcua single chip, a/d conversion unit, temperature monitoring unit一sensor group, digital display unit and actuators一a cooling unit and a heating unit. the operating principle of the intelligent can node is

24、described as follows.in the practical application, we divide 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 convers

25、ion unit. simulta neously, it performs basic data fusion algor it hms to obtain a fusion value which i s more close to the real one. and the digi tai di splay unit displays the fusing resuit of the node timely, so we can understand the environment temperature in every control cell separately.by comp

26、aring the fusion value with the set one by the main controller, the intelligent can node 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 int el lige nt can nod

27、e, t he cooling uni t wil 1 begin to work. ont he con trary, if the fusion result is less than the set value in the node the heating unit will begin to work. by this means we can not only monitor the environment temperature, but also can make the corresponding actuator work so as to regulate the tem

28、perature automatically. at the same time every can node is able to send data frame to the can bus which wi 11 notify the main cont roller the t cmpcra turc value in the cell so that cont roller can conveniently make decisions to modify the parameter or not. since the can nodes can regulate the tempe

29、rature of the cell where they are, the temperature in the whole room will be kept homogeneous. whats more, we can al so control the intel 1 i gent node by modi fying the temperature' s setting value on the host pc.generally, the processors on the spot are not good at complex data processing and

30、data fusing, so it becomes very critical how to choose a suitable data fusion algorithm for the system. in the posterior section, we will introduce a data fusion met hod which is suit abl e for the intclligent can nodes。4. multi-sensor data fusionthe aim to use data fusion in the distributed tempera

31、ture control system is to elimirmte the uncertainty, gain a more precise and reliable value than the arithmctical mcan of the measured data from finite sensors. furtheoiore, when some of the sensors become invalid in the temperature sensor groups, the intelligent can node can still obtain the accura

32、te temperature value by fusing the information from the other valid sensors.4.1. consistency verification of the measured dataduring the process of temperature measurement in our designed distributed temperature control system, measurement error comes into being inevitably because of the influence o

33、f the paroxysmal disturb or the equipment fault. so we should eliminate the careless mistake before data fusion.we can eliminate the measurement errors by using scatter diagram method in the system equipped with little amount of sensors- parameters to represent the data distribution strueture inelud

34、e mediantm, upper quartile number一fv, lower quartile number一fl and quartile dispersiondf.it is supposed that each sensor in the tcmpcrature control systemproceeds temperature measurement independently. in the system, there are eight sensors in each temperature sensor group of the intel 1 igent can n

35、ode. so we can obtain eight temperature values in each can node at the seime time. we arrange the collected tcmpcraturc data in a sequence from small to large:in the sequence, t1 is the limit inferior and t8 is the limit superior.we def i ne the mediantm as:(1)the upper quartilefv is the median of t

36、he interval tm, ts. the 1 ower quartile number一fl is the median of the interval tp tj.the dispersion of the quartile is:“f = f、 f丫9、we suppose that the data is an aberration one if the distanee from the median is greater than adf, that is, the estimation interval of invalid data is:in the formula, a

37、 is a constant, which is dependent on the system measurement error, commonly its value is to be 0. 5, l 0, 2. 0 and so on. the rest values in the measurement column arc considered as to be the valid ones with consistency. and the single-chip in the intelligent can node will fuse the consistent measu

38、rement value to obtain a fusion result5. temperature measurement data fusion experimentby applying the distributed temperature control system to a greenhouse, we obtain an array of eight temperature values from eight sensors as followssis?s4s5s6s?s?28.132.031.929.936.629.328.028.3the mean value of t

39、he eight measurement temperature result is comparing the mean value (8)t with the true temperature 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 obtai

40、n the mean value of the rest seven data (7)t=29. 6°c, the measurement error is -0. 4°c.the seven rest consistent sensor can be divided into two groups with sensor sp s3, s7 in the first group and sensor s2, sp s6, s8 in the seconddata and theone. the arithmeticeil mean of the two groups of

41、 measured standard deviation arc as follows respcctivcly:t(i)= 29.3 c 亍=29.9 caccording towith the seven庁=2.22% =1 56formula (13), we can educe the temperature measured temperature value.=29.7 cfusion valuethe error of the fusion temperature result is -0.3°c.tt is obvious that the measurement r

42、esult from data fusion is more close to the t rue value than that from arithme ti ceil me a n. in the practical application, the measured temperature value may be very dispersive as the monitoring area becomes bigger, data fusion will improve the measuring precision much more obviously.6. conclusion

43、sthe distributed temperatug control system based on multi-sensor data fusion is constructed through can bus. it takes full advantage of the characteristics of field bus control systemfdcs. data acquisition,data fusion and system control 1 ing is carried out in the intel 1 igent can node, and system

44、mcincigement is implemented in the main controller (host pc). by using can bus and data fusion technology 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 waltz e. liinas j, multi-sensor data fusion, artech hou

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48、 of technology, vol 12, no. 1, pp. 20-44, feb 1993.8 tenney r r, jr sandell n r, detection with distributed sensors, aes, vol 17, pp. 501-510, 1981五分钟搞定5000字毕业论文外文翻译，你想要的工具都在这里!在科研过程中阅读翻译外文文献是一个非常重要的环节，许多领 域高水平的文献都是外文文献，借鉴一些外文文献翻译的经验是非常 必要的。由于特殊原因我翻译外文文献的机会比较多，慢慢地就发现 了外文文献翻译过程中的-:大利器：google“翻译,濒道、金山词霸（完 整版本）和cnk广翻译助手”。具体操作过程如下：1 先打开金山词霸自动取词功能，然后阅读文献；2遇到无法理解的长句时，可以交给google处理，处理后的结 果猛一看，不堪入目，可是经过大脑的再处理后句子的意思基本就明 tt；3如果通过google仍然无法理解，感觉就是不同，那肯定是对 其中某个“常用单词”理解有误，因为某些单词看似很简单，但是在文 献中有特殊的意思，这时就可以通过cnki的“翻译助手”来查询相关 单词的意思，由于cnki的单词意思都是来源与大量的文献，所以它 的吻合率很高