本文選題：二氧化硫 + 軟測(cè)量技術(shù)　； 參考：《華北電力大學(xué)》2015年碩士論文

【摘要】：人類(lèi)面臨著越來(lái)越嚴(yán)重的環(huán)境問(wèn)題,大氣污染是其中的一個(gè)重要方面�；痣姀S(chǎng)排放的廢氣和煙塵污染物是大氣污染的一個(gè)重要來(lái)源。為了限制火電廠(chǎng)污染物的排放,國(guó)家嚴(yán)格制定了污染物的排放標(biāo)準(zhǔn)。二氧化硫是電廠(chǎng)排放最主要的大氣污染物,本課題的研究對(duì)象是火電廠(chǎng)石灰石-石膏濕法脫硫系統(tǒng)二氧化硫的排放。本文在對(duì)火電廠(chǎng)脫硫系統(tǒng)全面了解的基礎(chǔ)上,分析了影響脫硫效率和二氧化硫排放濃度的主要因素。目前,火電廠(chǎng)對(duì)煙氣污染物的主要監(jiān)測(cè)分析設(shè)備是煙氣連續(xù)排放監(jiān)測(cè)系統(tǒng),它能將污染物排放的數(shù)據(jù)及時(shí)的反映給電廠(chǎng)和監(jiān)管部門(mén)。由煙氣連續(xù)排放監(jiān)測(cè)系統(tǒng)得到的污染物排放濃度,是通過(guò)專(zhuān)門(mén)的污染物分析儀測(cè)得的。而本文通過(guò)軟測(cè)量技術(shù),基于脫硫系統(tǒng)的相關(guān)運(yùn)行參數(shù),建立了能夠預(yù)測(cè)脫硫效率和二氧化硫排放濃度的模型。本文的重點(diǎn)是軟測(cè)量建模階段,通過(guò)對(duì)脫硫效率影響因素的分析,并根據(jù)本文收集數(shù)據(jù)的實(shí)際狀況,選取了漿液pH值、脫硫塔入口二氧化硫濃度、脫硫塔入口煙氣溫度等八個(gè)參數(shù)作為軟測(cè)量建模的輸入。選取了BP神經(jīng)網(wǎng)絡(luò)和支持向量機(jī)兩種方法,分別建立了對(duì)脫硫效率進(jìn)行預(yù)測(cè)的模型。結(jié)果表明兩種方法都能到達(dá)到一定的預(yù)測(cè)效果,而經(jīng)參數(shù)尋優(yōu)后的支持向量機(jī)模型有著更好的預(yù)測(cè)性能。支持向量機(jī)參數(shù)尋優(yōu)的結(jié)果為:懲罰參數(shù)取值0.75786,核函數(shù)參數(shù)取值4.5948。尋優(yōu)后支持向量機(jī)模型預(yù)測(cè)結(jié)果的均方誤差和平均相對(duì)誤差分別為0.179和0.367%。最后,通過(guò)OPC(OLE for Process Control)技術(shù),實(shí)現(xiàn)了MATLAB與污染源過(guò)程監(jiān)控系統(tǒng)中組態(tài)軟件的數(shù)據(jù)交換,使MATLAB和組態(tài)王兩軟件各自的優(yōu)勢(shì)得到了充分的發(fā)揮。理論上實(shí)現(xiàn)了脫硫效率和二氧化硫排放濃度的在線(xiàn)預(yù)測(cè)。
[Abstract]:People are facing more and more serious environmental problems, and air pollution is one of the important aspects. Exhaust gas and soot pollutants emitted from thermal power plants are an important source of air pollution. In order to limit the emission of pollutants from thermal power plants, the state has strictly formulated emission standards for pollutants. Sulfur dioxide is the main atmospheric pollutant emitted from power plant. The object of this paper is the emission of sulfur dioxide from limestone gypsum wet desulfurization system in thermal power plant. Based on the comprehensive understanding of desulfurization system in thermal power plant, the main factors affecting desulfurization efficiency and sulfur dioxide emission concentration are analyzed in this paper. At present, the main monitoring and analysis equipment for flue gas pollutants in thermal power plants is the flue gas continuous emission monitoring system, which can reflect the pollutant emission data to the power plant and the supervision department in time. The pollutant emission concentration obtained from the flue gas continuous emission monitoring system is measured by a special pollutant analyzer. Based on the operating parameters of the desulphurization system, a model for predicting the desulfurization efficiency and the concentration of sulfur dioxide emission is established by soft sensing technology in this paper. The focus of this paper is the soft sensor modeling stage, through the analysis of the factors affecting the desulfurization efficiency, and according to the actual situation of the data collected in this paper, the slurry pH value and the sulfur dioxide concentration at the inlet of the desulfurization tower are selected. Eight parameters, such as flue gas temperature at the inlet of desulfurizer, are used as input for soft sensor modeling. Two methods, BP neural network and support vector machine, are used to predict desulfurization efficiency. The results show that both methods can achieve a certain prediction effect, and the support vector machine model after parameter optimization has better prediction performance. The results of parameter optimization of support vector machine are as follows: the penalty parameter is 0.75786 and the kernel function parameter is 4.5948. The mean square error and average relative error of the prediction results of the optimized support vector machine model are 0.179 and 0.367 respectively. Finally, through OPC(OLE for Process Control) technology, the data exchange between MATLAB and configuration software in pollution source process monitoring system is realized, which makes the advantages of MATLAB and Kingview software fully play. The on-line prediction of desulphurization efficiency and sulfur dioxide emission concentration is realized theoretically.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：X773

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