【摘要】：持久性有機(jī)污染物是人類合成的能持久的存在于自然環(huán)境之中,對(duì)人類及其他生物造成傷害的有毒化學(xué)物質(zhì)。由于人類的大量的使用這類物質(zhì),導(dǎo)致了全球環(huán)境的污染。又因?yàn)槌志眯杂袡C(jī)污染物具有持久性、生物積累性和廣范圍流動(dòng)性,使得持久性有機(jī)污染物的在全球擴(kuò)散和在生物體內(nèi)累積,這些情況加重了持久性有機(jī)污染物對(duì)環(huán)境和人類危害。所以建立一個(gè)對(duì)持久性有機(jī)污染物的監(jiān)測系統(tǒng)就顯得尤為重要。有必要針對(duì)持久有機(jī)污染物對(duì)環(huán)境危害的實(shí)際情況,開發(fā)出持久有機(jī)污染物的檢測設(shè)備,提高持久有機(jī)污染物檢測的效率和準(zhǔn)確性,為對(duì)持久有機(jī)污染物檢測工作做出新的貢獻(xiàn)。本文設(shè)計(jì)制作了一種可攜帶的持久性有機(jī)污染物檢測儀器,可以對(duì)毒殺芬持久性有機(jī)污染物及干擾物進(jìn)行檢測。采用ZnO傳感器與色譜分離相結(jié)合方法,結(jié)合計(jì)算機(jī)技術(shù),達(dá)到對(duì)持久性有機(jī)污染物檢測的目的,具有方便、快速、準(zhǔn)確度高等特點(diǎn)。在儀器裝置檢測到的樣本數(shù)據(jù)進(jìn)行模式特征提取和訓(xùn)練識(shí)別前,我們對(duì)數(shù)據(jù)進(jìn)行歸一化處理,以消除因?yàn)榱烤V、樣品濃度、環(huán)境溫度等外界因素造成的影響。我們對(duì)數(shù)據(jù)進(jìn)行特征提取時(shí),采用PCA算法和LDA算法。最后根據(jù)提取的模式特征使用SVM和徑向基人工神經(jīng)網(wǎng)絡(luò)訓(xùn)練出分類器,對(duì)待測樣本進(jìn)行分類識(shí)別。實(shí)驗(yàn)結(jié)果表明,該檢測系統(tǒng)可以對(duì)持久性有機(jī)污染物進(jìn)行分類識(shí)別,并有很好的分類效果。
[Abstract]:Persistent organic pollutants (pops) are toxic chemicals synthesised by human beings which can persist in the natural environment and cause harm to human beings and other organisms. The massive use of such substances by human beings has led to global environmental pollution. Also because persistent organic pollutants are persistent, bioaccumulative and mobile, leading to the global diffusion and accumulation of persistent organic pollutants in organisms, These conditions exacerbate the environmental and human hazards of persistent organic pollutants. Therefore, the establishment of a persistent organic pollutant monitoring system is particularly important. It is necessary to develop equipment for the detection of persistent organic pollutants in order to improve the efficiency and accuracy of the detection of persistent organic pollutants, in view of the actual situation of environmental hazards caused by persistent organic pollutants, To make a new contribution to the detection of persistent organic pollutants. In this paper, a portable detection instrument for persistent organic pollutants (pops) is designed and manufactured, which can be used to detect toxaphene persistent organic pollutants (pops) and interfering substances. The method of ZnO sensor combined with chromatographic separation, combined with computer technology, is used to detect persistent organic pollutants. It has the advantages of convenience, rapidity, high accuracy and so on. Before the pattern feature extraction and training recognition of the sample data detected by the instrument, we normalize the data to eliminate the influence caused by the external factors, such as dimension, sample concentration, environmental temperature, and so on. PCA algorithm and LDA algorithm are used in feature extraction of data. Finally, a classifier is trained by SVM and radial basis function (RBF) artificial neural network according to the extracted pattern features, and the samples are classified and identified. The experimental results show that the system can be used to classify and identify persistent organic pollutants and has a good classification effect.
【學(xué)位授予單位】：中國科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：X830;TP212.9

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本文編號(hào)：2368729