本文選題：大氣檢測系統(tǒng) + DSP��； 參考：《吉林大學(xué)》2017年碩士論文

【摘要】：近年來愈演愈烈的霧霾天氣使人類意識到大氣環(huán)境質(zhì)量保護(hù)的重要性。環(huán)境質(zhì)量的改善是一項(xiàng)長期的工作,需要對環(huán)境進(jìn)行調(diào)查、檢測后分析、制定治理方案。環(huán)境監(jiān)測需要借助先進(jìn)的監(jiān)測技術(shù)和監(jiān)測儀器,檢測結(jié)果直接影響到環(huán)境治理方案的制定。因此,可靠、準(zhǔn)確地大氣環(huán)境監(jiān)測對大氣環(huán)境的治理和保護(hù)至關(guān)重要。研究基于氣體傳感器陣列的智能化大氣檢測系統(tǒng)實(shí)現(xiàn)對大氣環(huán)境的準(zhǔn)確監(jiān)測。該系統(tǒng)的研究主要從三個(gè)方面進(jìn)行:系統(tǒng)硬件電路的設(shè)計(jì)、GUI(圖形用戶界面,Graphical User Interface)人機(jī)交互界面的制作和自檢測智能算法的研究。系統(tǒng)硬件主要包括氣體傳感器陣列的驅(qū)動(dòng)電路、信號調(diào)理和數(shù)據(jù)采集電路、信息處理單元電路、進(jìn)氣部分控制電路、外部接口電路。主控制器使用DSP2000系列的F28335,該芯片既能實(shí)現(xiàn)對外圍電路的控制。由氣體傳感器陣列的驅(qū)動(dòng)電路、信號調(diào)理和數(shù)據(jù)采集電路、進(jìn)氣部分控制電路和外部接口電路構(gòu)成了數(shù)字信號采集電路,為智能算法處理和人機(jī)交互界面顯示提供了原始數(shù)據(jù),是數(shù)據(jù)流動(dòng)的源頭。人機(jī)交互界面放棄常用的液晶屏顯示方式,基于QT制作類似手機(jī)、平板界面一樣更真實(shí)、美觀的操作界面,完成系統(tǒng)功能高度集成,實(shí)現(xiàn)傻瓜式操作。使用QML渲染界面,建立實(shí)現(xiàn)界面操作行為的C++功能函數(shù)庫,這種非阻塞式設(shè)計(jì)滿足前端與后端的同時(shí)運(yùn)行。用戶通過操作界面觸發(fā)信號控制C++函數(shù),與主控制器F28335交換數(shù)據(jù)和控制指令,實(shí)現(xiàn)硬件電路控制。系統(tǒng)采用主成分分析(PCA:Principal Component Analysis)、支持向量機(jī)(SVM:Support Vector Machine)和支持向量回歸(SVR:Support Vector Regression)三種算法結(jié)合,對大氣氣體鑒別和濃度獲取。使用主成分分析法(PCA)對氣體傳感器采集數(shù)據(jù)進(jìn)行預(yù)處理,通過降低維度來濾除混入的信息,從而實(shí)現(xiàn)降低信號的噪聲。支持向量機(jī)(SVM)是一種學(xué)習(xí)型分類器,通過訓(xùn)練數(shù)據(jù)集建立樣品分類的模型和關(guān)于濃度的支持向量回歸模型,使用測試數(shù)據(jù)檢驗(yàn)?zāi)Ｐ徒⒌男Ч�。使用MATLAB調(diào)試自檢測智能算法,實(shí)現(xiàn)數(shù)據(jù)的處理和結(jié)果圖像的顯示。根據(jù)傳感器的結(jié)構(gòu)特點(diǎn)和專家經(jīng)驗(yàn),通過全面展開傳感器失效機(jī)理的研究,進(jìn)行深入的故障模式的剖析分解,使用支持向量回歸算法建立模型,實(shí)現(xiàn)故障的診斷和恢復(fù)。檢測系統(tǒng)各項(xiàng)功能正常運(yùn)行,以NO_2、SO_2、O_3、CO四種氣體為檢測對象,設(shè)計(jì)四組實(shí)驗(yàn)獲取數(shù)據(jù),使用MATLAB圖像和人機(jī)交互界面兩種方式顯示處理結(jié)果。實(shí)驗(yàn)結(jié)果表明系統(tǒng)在氣體鑒別和濃度測試方面具有較高的準(zhǔn)確度,并且操作簡單、成本低廉,具有良好的應(yīng)用前景。
[Abstract]:In recent years, more and more haze weather has made people realize the importance of environmental quality protection. The improvement of environmental quality is a long-term task. Environmental monitoring needs advanced monitoring technology and monitoring instruments, and the results directly affect the formulation of environmental control programs. Therefore, reliable and accurate monitoring of atmospheric environment is very important to the management and protection of atmospheric environment. An intelligent atmospheric detection system based on gas sensor array is studied to realize accurate monitoring of atmospheric environment. The research of the system is mainly carried out from three aspects: the design of the hardware circuit of the system and the design of the graphical User Interface (HMI) and the research of the intelligent algorithm of self-detection. The hardware of the system mainly includes the driving circuit of gas sensor array, signal conditioning and data acquisition circuit, information processing unit circuit, air intake control circuit, external interface circuit. The main controller uses DSP2000 series F28335, which can control the peripheral circuit. The digital signal acquisition circuit is composed of driving circuit of gas sensor array, signal conditioning and data acquisition circuit, air intake control circuit and external interface circuit, which provides raw data for intelligent algorithm processing and man-machine interface display. Is the source of data flow. The man-machine interactive interface gives up the usual LCD display mode, and makes the similar mobile phone based on QT. The flat interface is more realistic and beautiful. The system functions are highly integrated and the fool type operation is realized. Using QML rendering interface, the C function library is established to realize the interface operation behavior. This non-blocking design can meet the needs of the front-end and back-end simultaneously. The user triggers the signal control C function through the operation interface, exchanges data and control instructions with the main controller F28335, and realizes the hardware circuit control. The system adopts three algorithms: principal component analysis (PCA), support vector machine (SVM) and SVR: support Vector (SVR) to identify the atmospheric gas and obtain the concentration. The principal component analysis (PCA) is used to preprocess the data collected by the gas sensor, and to filter out the mixed information by reducing the dimension, so as to reduce the noise of the signal. Support Vector Machine (SVM) is a kind of learning classifier. The model of sample classification and the support vector regression model about concentration are established by training data set, and the effect of the model is verified by test data. The intelligent algorithm of self-detection is debugged by MATLAB to realize the data processing and the display of the result image. According to the structural characteristics and expert experience of the sensor, the failure mechanism of the sensor is studied in an all-round way, the fault mode is analyzed and decomposed deeply, and the support vector regression algorithm is used to establish the model to realize the fault diagnosis and recovery. The functions of the detection system are running normally. Four groups of experiments are designed to obtain the data, and the processing results are displayed by MATLAB images and man-machine interface. The experimental results show that the system has high accuracy in gas identification and concentration measurement, simple operation, low cost and good application prospect.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP18;TP212

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