【摘要】：近幾年環(huán)境污染問(wèn)題越來(lái)越嚴(yán)重,其中大氣污染問(wèn)題尤為突出,大氣污染嚴(yán)重影響了我們的健康生活,雖然相關(guān)部門(mén)已經(jīng)實(shí)施了很多措施控制污染物的排放,但是到口前為止一直沒(méi)有效的措施能夠遏止污染的蔓延,大氣污染仍是威脅我們健康的難題,在治理過(guò)程中,對(duì)污染物排放的監(jiān)測(cè)預(yù)測(cè)必不可少。當(dāng)今社會(huì)是一個(gè)物聯(lián)網(wǎng)和互聯(lián)網(wǎng)的時(shí)代,利用探測(cè)傳感器再結(jié)合Web網(wǎng)絡(luò)技術(shù)對(duì)污染物的排放進(jìn)行實(shí)時(shí)監(jiān)控是環(huán)保工作的發(fā)展趨勢(shì)。本文所設(shè)計(jì)的監(jiān)測(cè)預(yù)測(cè)系統(tǒng)的主要特點(diǎn)在于:1、服務(wù)器端利用Socket網(wǎng)絡(luò)編程技術(shù)與下位機(jī)進(jìn)行數(shù)據(jù)交互對(duì)其進(jìn)行數(shù)據(jù)接收以及遠(yuǎn)程控制;2、系統(tǒng)通過(guò)JAVA開(kāi)發(fā)并利用MySQL數(shù)據(jù)庫(kù)對(duì)數(shù)據(jù)進(jìn)行存儲(chǔ),主要利用Ajax技術(shù)進(jìn)行Web系統(tǒng)前后臺(tái)的數(shù)據(jù)交互;3、通過(guò)通過(guò)對(duì)大氣污染物擴(kuò)散模型的研究分析之后提出了融入風(fēng)速、風(fēng)向、雨量以及大氣穩(wěn)定度等影響因素的改進(jìn)版高斯擴(kuò)散模型,并且利用最小二乘法分析大量實(shí)驗(yàn)數(shù)據(jù)總結(jié)出誤差補(bǔ)償算法;4、利用百度地圖的BMap技術(shù)結(jié)合預(yù)測(cè)模型分析出PM2.5的擴(kuò)散分布圖,以不同色塊標(biāo)識(shí)PM2.5的不同濃度值;5、利用了 Web技術(shù)對(duì)采集的數(shù)據(jù)實(shí)現(xiàn)了實(shí)時(shí)數(shù)據(jù)顯示、歷史數(shù)據(jù)管理、用戶管理、遠(yuǎn)程設(shè)備管理、預(yù)警管理以及PM2.5擴(kuò)散預(yù)測(cè)等功能。系統(tǒng)完成建立之后對(duì)無(wú)錫市一工廠的污染排放情況進(jìn)行實(shí)地監(jiān)測(cè),總共設(shè)置了 10個(gè)長(zhǎng)期監(jiān)測(cè)站,在2016年6月至2016年12月采集了六個(gè)多月的數(shù)據(jù),通過(guò)數(shù)據(jù)對(duì)比分析對(duì)預(yù)測(cè)模型進(jìn)行了驗(yàn)證,分析結(jié)果表明預(yù)測(cè)值經(jīng)過(guò)誤差補(bǔ)償后得到的PM2.5濃度值與實(shí)測(cè)值很接近,并且系統(tǒng)能夠合理的預(yù)測(cè)在風(fēng)速風(fēng)向以及大氣穩(wěn)定度發(fā)生變化的情況下PM2.5的擴(kuò)散情況,說(shuō)明系統(tǒng)能夠合理的對(duì)小尺度范圍的污染情況進(jìn)行實(shí)時(shí)監(jiān)測(cè)以及對(duì)污染物擴(kuò)散進(jìn)行有效預(yù)測(cè)。整個(gè)系統(tǒng)的運(yùn)行結(jié)果表明系統(tǒng)可以為有關(guān)環(huán)保部門(mén)的工作及居民的健康出現(xiàn)提供有效的數(shù)據(jù)支持。
[Abstract]:In recent years, the problem of environmental pollution has become more and more serious, especially the problem of air pollution, which has seriously affected our healthy lives, although the relevant departments have implemented many measures to control the discharge of pollutants. However, there are no effective measures to stop the spread of pollution. Air pollution is still a difficult problem that threatens our health. In the process of control, monitoring and forecasting of pollutant discharge is essential. Nowadays, the society is an era of Internet of things and Internet. It is the development trend of environmental protection work to use detection sensors and Web network technology to monitor the emission of pollutants in real time. The main features of the monitoring and forecasting system designed in this paper are: 1, the server uses Socket network programming technology to interact with the lower computer for data receiving and remote control. The system is developed through JAVA and uses MySQL number. The database stores the data, This paper mainly uses Ajax technology to carry out the data exchange between the front and back of Web system. After studying and analyzing the air pollutant diffusion model, the author puts forward the integration of wind speed and wind direction. An improved Gao Si diffusion model for factors such as rainfall and atmospheric stability, The error compensation algorithm is summed up by using the least square method to analyze a large number of experimental data, and the diffusion distribution map of PM2.5 is analyzed by using the BMap technology of Baidu map combined with the prediction model. Using different color blocks to identify the different concentrations of PM2.5, the functions of real-time data display, historical data management, user management, remote equipment management, early warning management and PM2.5 diffusion prediction are realized by using Web technology. After the establishment of the system, on-site monitoring of pollution emissions from a factory in Wuxi was carried out, with a total of 10 long-term monitoring stations and data collected from June 2016 to December 2016 for more than six months. The prediction model is verified by data comparison and analysis. The results show that the PM2.5 concentration obtained by error compensation is very close to the measured value. And the system can reasonably predict the diffusion of PM2.5 when wind speed and wind direction and atmospheric stability change. The results show that the system can monitor the pollution in a small scale in real time and predict the pollutant diffusion effectively. The operation results of the whole system show that the system can provide effective data support for the work of environmental protection departments and the emergence of residents' health.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：X51;X84;TP393.09

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