本文關(guān)鍵詞： 無(wú)線傳感器網(wǎng)絡(luò) 污染源探測(cè) 污染源定位 水環(huán)境　出處：《武漢科技大學(xué)》2016年博士論文　論文類型：學(xué)位論文

【摘要】：水環(huán)境中污染源的探測(cè)與定位問(wèn)題對(duì)水環(huán)境保護(hù)有重要的意義。論文將無(wú)線傳感器網(wǎng)絡(luò)應(yīng)用于水環(huán)境監(jiān)測(cè)中,對(duì)網(wǎng)絡(luò)平臺(tái)總體架構(gòu)、污染源探測(cè)和定位等關(guān)鍵問(wèn)題開(kāi)展了深入研究。論文的主要工作如下:(1)提出了網(wǎng)絡(luò)污染源探測(cè)與節(jié)點(diǎn)污染源探測(cè)的方法。針對(duì)靜態(tài)污染源探測(cè)與動(dòng)態(tài)污染源探測(cè)中存在的探測(cè)問(wèn)題,采用假設(shè)檢驗(yàn)方法和相關(guān)二值假設(shè),構(gòu)造了檢驗(yàn)統(tǒng)計(jì)量與檢驗(yàn)方法,檢驗(yàn)了提出的污染源探測(cè)算法。檢驗(yàn)表明:在網(wǎng)絡(luò)污染源探測(cè)中,高檢測(cè)精度與具有較大監(jiān)測(cè)值的觀測(cè)節(jié)點(diǎn)的數(shù)量相關(guān)。而在節(jié)點(diǎn)污染源探測(cè)中,只要參照樣本足夠多,較少的采樣時(shí)間也能得到更為滿意的檢測(cè)精度。(2)提出了兩種湖庫(kù)中近岸排放污染源的定位方法:一種方法是邊界約束最小二乘污染源定位算法,另一種是邊界約束最小一乘污染源定位算法。在一般湖庫(kù)水環(huán)境中,兩種算法都較無(wú)邊界約束情形具有較好的定位效果;在定位節(jié)點(diǎn)中有奇異節(jié)點(diǎn)時(shí),邊界約束最小一乘污染源定位算法較邊界約束最小二乘污染源定位算法具有更好的定位效果。(3)給出了河流中二維污染物濃度分布的通用模型。分析了有邊界和無(wú)邊界下污染源的擴(kuò)散模型,給出了一種考慮邊界影響的二維污染物濃度分布的通用模型。提出一種有邊界約束的非線性最小二乘污染源定位算法。該算法以測(cè)量值與理論值之差的平方和為目標(biāo)函數(shù),具有較好數(shù)值穩(wěn)定性和抗干擾性。通過(guò)仿真討論了測(cè)量濃度噪聲、節(jié)點(diǎn)漂移誤差和反射系數(shù)誤差對(duì)污染源定位估計(jì)精度的影響,驗(yàn)證了所提算法的有效性。(4)建立了面向水環(huán)境監(jiān)測(cè)的分布式無(wú)線傳感器系統(tǒng)結(jié)構(gòu),搭建了該系統(tǒng)污染源定位實(shí)驗(yàn)平臺(tái),通過(guò)該平臺(tái)測(cè)試了污染源的探測(cè)算法與湖庫(kù)水環(huán)境中污染源定位算法。
[Abstract]:The detection and location of pollution sources in water environment is of great significance to the protection of water environment. In this paper, wireless sensor networks are applied to water environment monitoring, and the overall architecture of the network platform is discussed. The main work of this paper is as follows: 1). This paper puts forward the methods of network pollution source detection and node pollution source detection, aiming at the problems existing in static pollution source detection and dynamic pollution source detection. By using the hypothesis test method and the correlation binary hypothesis, the test statistics and the inspection method are constructed, and the proposed pollution source detection algorithm is tested. The results show that: in the network pollution source detection. The high detection accuracy is related to the number of observation nodes with larger monitoring values. However, in the detection of node pollution sources, only a sufficient number of reference samples are required. Less sampling time can also get a more satisfactory detection accuracy. 2) two methods are proposed to locate the source of near-shore discharge in lake and reservoir. One method is the boundary constrained least square algorithm. The other is the boundary constraint minimum-multiplicative pollution source location algorithm. In general lake and reservoir water environment, the two algorithms have better localization effect than those without boundary constraint. When there is a singular node in the locator node. The algorithm of boundary constraint least multiplication pollution source location has better localization effect than the boundary constraint least square algorithm. A general model of two-dimensional pollutant concentration distribution in rivers is presented, and the diffusion model of pollution sources with and without boundary is analyzed. In this paper, a general model of two-dimensional pollutant concentration distribution considering the influence of boundary is given. A nonlinear least square source location algorithm with boundary constraints is proposed. The square sum of the difference between the measured and theoretical values is calculated as the sum of the square of the measured value and the theoretical value. Objective function. It has good numerical stability and anti-interference. The effects of measurement concentration noise node drift error and reflection coefficient error on the location estimation accuracy of pollution source are discussed by simulation. The validity of the proposed algorithm is verified. (4) the structure of distributed wireless sensor system for water environment monitoring is established, and the experimental platform of pollution source location of the system is built. Through this platform, the detection algorithm of pollution source and the algorithm of pollution source location in lake and reservoir water environment are tested.
【學(xué)位授予單位】：武漢科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：X832;TP212.9;TN929.5

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本文編號(hào)：1451031