本文關(guān)鍵詞： 養(yǎng)豬 無線傳感器網(wǎng)絡(luò) 部署 定位 運(yùn)動(dòng)行為監(jiān)測(cè)　出處：《華中農(nóng)業(yè)大學(xué)》2014年博士論文　論文類型：學(xué)位論文

【摘要】：養(yǎng)豬產(chǎn)業(yè)是我國(guó)最重要的畜牧產(chǎn)業(yè)。隨著現(xiàn)代養(yǎng)豬產(chǎn)業(yè)規(guī)�；l(fā)展,對(duì)養(yǎng)豬自動(dòng)化管理水平提出了越來越高的要求。現(xiàn)有的RFID電子耳標(biāo)技術(shù)通訊距離短、不具有擴(kuò)展性,難以滿足精準(zhǔn)智能化豬養(yǎng)殖的迫切需求。因此將豬的環(huán)境、飲食、行為納入到監(jiān)測(cè)的范圍,實(shí)現(xiàn)養(yǎng)豬過程的全過程、全方位地跟蹤監(jiān)測(cè),能有效推動(dòng)智能化豬飼養(yǎng)水平,提高養(yǎng)豬產(chǎn)業(yè)的管理效率,進(jìn)而提高養(yǎng)豬場(chǎng)的經(jīng)濟(jì)收益。 本文研究了將無線傳感器網(wǎng)絡(luò)(WSN)應(yīng)用于養(yǎng)豬運(yùn)動(dòng)行為監(jiān)測(cè)分析系統(tǒng)中的幾個(gè)關(guān)鍵問題,包括圈養(yǎng)豬舍內(nèi)無線傳感器節(jié)點(diǎn)的邊緣部署問題；豬舍內(nèi)圈養(yǎng)豬的定位問題；豬舍內(nèi)圈養(yǎng)豬的運(yùn)動(dòng)行為監(jiān)測(cè)問題；基于WSN的養(yǎng)豬綜合監(jiān)測(cè)系統(tǒng)的架構(gòu)和實(shí)體-關(guān)系(E-R)模型。研究結(jié)果如下： 1)評(píng)價(jià)圈養(yǎng)豬舍內(nèi)無線傳感器節(jié)點(diǎn)的邊緣部署。在已有的覆蓋率、覆蓋效率、以及覆蓋方差的基礎(chǔ)上,提出了K重覆蓋率、K重覆蓋效率、K重全覆蓋所需最小半徑三個(gè)針對(duì)K重覆蓋問題的評(píng)價(jià)指標(biāo),確立了豬舍內(nèi)無線傳感器節(jié)點(diǎn)部署方案的評(píng)價(jià)指標(biāo)體系,并用該評(píng)價(jià)指標(biāo)體系對(duì)4種可行性的部署方案進(jìn)行了評(píng)價(jià),得出最優(yōu)部署策略,形成一套最優(yōu)部署策略評(píng)價(jià)分析方法。 2)首次建立了K=1邊緣覆蓋問題中最少結(jié)點(diǎn)部署方案的計(jì)算方法。針對(duì)不同豬舍面積,不同節(jié)點(diǎn)通訊半徑,以K=1全覆蓋為目標(biāo),提出一套系統(tǒng)地以最少節(jié)點(diǎn)為目標(biāo)的部署算法。在Adobe Dreamweaver軟件開發(fā)平臺(tái)及PHPnow互聯(lián)網(wǎng)應(yīng)用框架上,開發(fā)了豬舍無線網(wǎng)絡(luò)節(jié)點(diǎn)部署邊界條件及最小節(jié)點(diǎn)計(jì)算軟件,對(duì)部署節(jié)點(diǎn)數(shù)進(jìn)行計(jì)算驗(yàn)證；在Matlab軟件平臺(tái)上,開發(fā)了豬舍無線網(wǎng)絡(luò)節(jié)點(diǎn)部署仿真分析軟件,對(duì)部署方案進(jìn)行仿真分析。 3)豬舍的三邊直角加權(quán)質(zhì)心算法的確立。對(duì)不同廠家的無線傳感器節(jié)點(diǎn)進(jìn)行研究和測(cè)試,運(yùn)用曲線擬合,取得了0-80m和0-20m接收信號(hào)強(qiáng)度值(RSSI)與距離關(guān)系的最優(yōu)模型；在三邊加權(quán)質(zhì)心算法的基礎(chǔ)上,開發(fā)出針對(duì)豬舍的三邊直角加權(quán)質(zhì)心算法,并設(shè)計(jì)了該算法的具體運(yùn)算步驟；10.43m×5.72m室內(nèi)空間的測(cè)試驗(yàn)證表明,該算法可以達(dá)到平均誤差1.346m,去掉兩個(gè)特殊位置點(diǎn)后,平均定位誤差可降低到1.0875m,每次定位時(shí)間間隔為10s。 4)研究了圈養(yǎng)豬運(yùn)動(dòng)行為的監(jiān)測(cè)方法。設(shè)計(jì)了無線傳感器節(jié)點(diǎn)的三軸加速度傳感器硬件,以Z-stack協(xié)議棧為基礎(chǔ)開發(fā)了加速度數(shù)據(jù)采集軟件,并確定了與PC機(jī)通訊的通訊方法和通訊協(xié)議,實(shí)現(xiàn)了三軸加速度數(shù)據(jù)采集和通訊。 5)建立了神經(jīng)網(wǎng)絡(luò)模式識(shí)別分類算法。在神經(jīng)網(wǎng)絡(luò)模式識(shí)別算法的理論基礎(chǔ)上構(gòu)建了二層運(yùn)動(dòng)行為識(shí)別神經(jīng)網(wǎng)絡(luò)分類器,并設(shè)計(jì)了Matlab軟件實(shí)現(xiàn)對(duì)四種運(yùn)動(dòng)行為(分別為走、跑、跳、靜止)的識(shí)別。模擬試驗(yàn)證明,在85組訓(xùn)練樣本試驗(yàn)時(shí)識(shí)別率達(dá)到100%,在439組大樣本時(shí),神經(jīng)網(wǎng)絡(luò)方法對(duì)走和靜止兩種狀態(tài)的識(shí)別率達(dá)到100%,而跑和跳兩種運(yùn)動(dòng)行為由于實(shí)際數(shù)據(jù)特征比較接近,其識(shí)別率分別達(dá)到99.1%和96.1%,整體識(shí)別率達(dá)98.9%。 6)圈養(yǎng)豬綜合運(yùn)動(dòng)行為監(jiān)測(cè)的研究。首次采用短時(shí)能量和短時(shí)過零率計(jì)算方法分析計(jì)算三軸加速度運(yùn)動(dòng)數(shù)據(jù),設(shè)計(jì)了短時(shí)能量和短時(shí)過零率運(yùn)動(dòng)行為分類算法、FFT快速傅立葉運(yùn)動(dòng)行為分類算法和標(biāo)準(zhǔn)差運(yùn)動(dòng)行為分類算法。并基于VS2010平臺(tái)開發(fā)了實(shí)時(shí)綜合豬運(yùn)動(dòng)行為監(jiān)測(cè)軟件,通過實(shí)時(shí)模擬試驗(yàn)證明,采用短時(shí)能量分類法優(yōu)于FFT快速傅立葉分類算法和標(biāo)準(zhǔn)差算法,對(duì)走、靜止、跳和跑三大類運(yùn)動(dòng)行為進(jìn)行識(shí)別分類時(shí),識(shí)別率約為100%左右,區(qū)分跳、跑兩種運(yùn)動(dòng)行為時(shí),識(shí)別率約80%左右。 7)基于WSN的養(yǎng)豬綜合精準(zhǔn)監(jiān)測(cè)系統(tǒng)框架的分析的設(shè)計(jì)。確立了基于WSN的養(yǎng)豬綜合精準(zhǔn)監(jiān)測(cè)系統(tǒng)的框架結(jié)構(gòu)和工作原理,并設(shè)計(jì)了網(wǎng)絡(luò)化綜合監(jiān)測(cè)信息系統(tǒng)的實(shí)體-關(guān)系(E-R)模型。 前期研究了染色竹條分級(jí)流水線的自動(dòng)控制系統(tǒng)及高通量下水稻育種網(wǎng)絡(luò)信息管理系統(tǒng),在此研究的技術(shù)基礎(chǔ)上,提出了基于WSN的養(yǎng)豬綜合監(jiān)測(cè)系統(tǒng)關(guān)鍵技術(shù)的研究。本文研究結(jié)果為無線傳感器網(wǎng)絡(luò)應(yīng)用于養(yǎng)豬綜合監(jiān)測(cè)系統(tǒng)尋求了科學(xué)的解決方案,為后期進(jìn)一步實(shí)現(xiàn)養(yǎng)豬綜合精準(zhǔn)監(jiān)測(cè)系統(tǒng)提供了技術(shù)基礎(chǔ),并有著廣闊的應(yīng)用前景。
[Abstract]:The pig breeding industry is one of the most important animal husbandry industries in China . With the development of modern pig breeding industry , the demand for automatic management of pig is put forward . The existing RFID electronic ear tag technology has short communication distance and no expansibility , it is difficult to meet the urgent need of precision intelligent pig breeding . Therefore , the whole process of pig breeding process is realized , the monitoring can be carried out in all directions , the intelligent pig raising level can be effectively promoted , the management efficiency of the pig industry is improved , and the economic benefit of the pig farm is improved . This paper studies several key problems in the monitoring and analysis system of pig ' s movement behavior by applying wireless sensor network ( WSN ) to pig ' s movement behavior monitoring and analysis system , including the problem of edge deployment of pig house wireless sensor node , the problem of pig ' s movement behavior monitoring in pig house , and the structure and entity - relation ( E - R ) model of pig integrated monitoring system based on WSN . The results are as follows : 1 ) Based on the existing coverage , coverage efficiency and coverage variance , three evaluation indexes of K weight coverage , K weight covering efficiency and minimum radius required for K weight full coverage are put forward . The evaluation index system of wireless sensor node deployment scheme in pigsty is established , and four feasible deployment schemes are evaluated by using the evaluation index system , and an optimal deployment strategy evaluation method is formed . 2 ) The calculation method of minimum node deployment scheme in K = 1 edge coverage problem is established for the first time . For different pigsty area , different node communication radius and K = 1 full coverage , a set of deployment algorithm is proposed , which is based on minimum node . On the framework of Adobe Dreamweaver software development platform and PHPnow Internet application framework , the deployment boundary conditions and minimum node computing software are developed , and the deployment node number is calculated and verified . On the Matlab software platform , the deployment simulation analysis software of the wireless node of the pigsty is developed , and the deployment plan is simulated and analyzed . 3 ) The establishment of a three - sided right - angle weighted centroid algorithm for pigsty . The wireless sensor nodes of different manufacturers are studied and tested . Based on the three - side weighted centroid algorithm , a three - sided right - angle weighted centroid algorithm is developed for pigsty . The algorithm can achieve the average error of 1.346m , and the average positioning error can be reduced to 1.0875m after removing two special position points , and the time interval is 10s . 4 ) The monitoring method of the movement behavior of the loop pig is studied . The hardware of the triaxial acceleration sensor of the wireless sensor node is designed , the acceleration data acquisition software is developed based on the Z - stack protocol stack , and the communication method and the communication protocol for communication with the PC are determined , and the three - axis acceleration data acquisition and communication are realized . 5 ) The neural network pattern recognition classification algorithm is established . Based on the theory of neural network pattern recognition algorithm , two - layer motion behavior recognition neural network classifier is constructed , and Matlab software is designed to realize the recognition of four kinds of motion behaviors ( walking , running , jumping and rest ) . 6 ) The research on the monitoring of the comprehensive sports behavior of the pigs . The short - time energy and the short - time zero - crossing rate calculation method are used to analyze the three - axis acceleration motion data , the short - time energy and the short - time zero - crossing rate motion behavior classification algorithm , the FFT fast Fourier motion behavior classification algorithm and the standard deviation motion behavior classification algorithm are designed . The real - time comprehensive swine motion behavior monitoring software is developed based on the VS2010 platform . 7 ) The design of the framework of the pig comprehensive precision monitoring system based on WSN is designed . The frame structure and working principle of the pig integrated precision monitoring system based on WSN are established , and the entity - relation ( E - R ) model of the networked integrated monitoring information system is designed . This paper studies the automatic control system and the information management system of rice breeding network under high flux . Based on this research , the key technology of pig comprehensive monitoring system based on WSN is studied in this paper . The result is that wireless sensor network is applied to pig comprehensive monitoring system to seek scientific solution , which provides the technical basis for further realization of pig comprehensive precision monitoring system in the later stage , and has wide application prospect .

【學(xué)位授予單位】：華中農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP212.9;TN929.5;S828

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本文編號(hào)：1523979