本文選題：異常檢測(cè)　切入點(diǎn)：氣味模擬　出處：《國(guó)防科學(xué)技術(shù)大學(xué)》2011年碩士論文

【摘要】：載人航天、深海探測(cè)、大型飛機(jī)等技術(shù)的發(fā)展,對(duì)宇宙飛船、潛艇、大型客機(jī)等具有非開(kāi)放空間的大型系統(tǒng)內(nèi)設(shè)備安全運(yùn)行提出了越來(lái)越高的要求。對(duì)于這類系統(tǒng)而言,密閉座艙內(nèi)大量設(shè)備長(zhǎng)期運(yùn)行,特別是狀態(tài)異常所產(chǎn)生的各種污染是影響空氣質(zhì)量的主要原因之一。同時(shí),空氣成份中的這些污染也包含了反映設(shè)備運(yùn)行狀態(tài)的重要信息。 基于仿生原理的人工嗅覺(jué)分析(電子鼻)技術(shù)是對(duì)氣味檢測(cè)的一種重要手段,可望為非開(kāi)放空間設(shè)備密集系統(tǒng)的健康監(jiān)控和早期異常檢測(cè)提供新的技術(shù)途徑。為此,本文在綜述電子鼻技術(shù)研究現(xiàn)狀的基礎(chǔ)上,針對(duì)密閉空間設(shè)備異常容易產(chǎn)生的油液滲漏和導(dǎo)線過(guò)熱問(wèn)題,系統(tǒng)開(kāi)展了設(shè)備異常氣味識(shí)別與分離檢測(cè)方法研究。 本文的主要研究工作包括: (1)在分析電子鼻系統(tǒng)工作原理與結(jié)構(gòu)組成的基礎(chǔ)上,對(duì)嗅覺(jué)檢測(cè)涉及的傳感器陣列、信號(hào)預(yù)處理、模式識(shí)別等關(guān)鍵技術(shù)的國(guó)內(nèi)外研究現(xiàn)狀進(jìn)行了總結(jié)和探討。 (2)對(duì)密閉空間油液滲漏和導(dǎo)線過(guò)熱進(jìn)行了氣味模擬實(shí)驗(yàn)與響應(yīng)分析。在對(duì)實(shí)驗(yàn)環(huán)境、實(shí)驗(yàn)方法及實(shí)驗(yàn)裝置進(jìn)行介紹的基礎(chǔ)上,分析了電子鼻系統(tǒng)傳感陣列響應(yīng)過(guò)程的影響因素,并對(duì)設(shè)備異常傳感陣列信號(hào)進(jìn)行了初步分析。 (3)針對(duì)設(shè)備異常狀態(tài)氣味定性識(shí)別問(wèn)題,在對(duì)實(shí)驗(yàn)數(shù)據(jù)進(jìn)行預(yù)處理的基礎(chǔ)上,通過(guò)主成分分析提取了實(shí)驗(yàn)數(shù)據(jù)的主要特征,分別采用線性判別分析和前饋神經(jīng)網(wǎng)絡(luò)實(shí)現(xiàn)了異常氣味的定性分類。 (4)針對(duì)異常狀態(tài)氣味的定量識(shí)別問(wèn)題,研究了基于補(bǔ)氣過(guò)程中氣味濃度補(bǔ)償?shù)膹?fù)頻域分析方法,提出了嗅覺(jué)傳感器信號(hào)與濃度的非線性關(guān)聯(lián)模型和主成分回歸模型,并利用實(shí)驗(yàn)數(shù)據(jù)對(duì)這兩種模型進(jìn)行了驗(yàn)證。 (5)對(duì)設(shè)備異常狀態(tài)混合氣味的分離識(shí)別問(wèn)題進(jìn)行了探索研究,利用獨(dú)立分量分析,提出了氣味源盲分離模型,并對(duì)混合氣味的實(shí)驗(yàn)數(shù)據(jù)進(jìn)行了分離識(shí)別。
[Abstract]:With the development of manned spaceflight, deep-sea exploration, large aircraft and other technologies, the safe operation of equipments in large systems with closed space, such as spaceships, submarines, airliners, etc., has been put forward more and more high requirements.For this kind of system, a large number of equipments in the airtight cabin run for a long time, especially the pollution caused by abnormal state is one of the main reasons that affect the air quality.At the same time, the air pollution also contains important information to reflect the operation state of the equipment.Artificial olfactory analysis (electronic nose) based on biomimetic principle is an important means of odour detection, which is expected to provide a new technical approach for health monitoring and early abnormal detection of closed space equipment intensive systems.In this paper, based on the review of the current research situation of electronic nose technology, aiming at the problems of oil leakage and overheating caused by abnormal equipment in confined space, the methods of equipment odour recognition and separation detection are studied systematically.The main research work of this paper includes:1) based on the analysis of the principle and structure of electronic nose system, the research status of sensor array, signal preprocessing, pattern recognition and other key technologies involved in olfactory detection are summarized and discussed.(2) the odour simulation experiment and response analysis of oil leakage and wire overheating in airtight space were carried out.Based on the introduction of the experimental environment, the experimental method and the experimental device, the factors influencing the response of the sensor array in the electronic nose system are analyzed, and the signal of the abnormal sensor array of the equipment is analyzed preliminarily.3) aiming at the problem of qualitative identification of odour in abnormal state of equipment, the main characteristics of experimental data are extracted by principal component analysis on the basis of pretreatment of experimental data.Linear discriminant analysis (LDA) and feedforward neural network (FNN) are used to classify odors qualitatively.(4) aiming at the problem of quantitative identification of odors in abnormal state, the complex frequency domain analysis method based on the compensation of odor concentration in the process of replenishing gas is studied, and the nonlinear correlation model and principal component regression model of the signal and concentration of olfactory sensors are proposed.The two models are verified by experimental data.In this paper, the problem of separation and recognition of mixed odors in abnormal state of equipment is studied. By using independent component analysis, a blind separation model of odour source is proposed, and the experimental data of mixed odors are separated and recognized.
【學(xué)位授予單位】：國(guó)防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：TH165.3;TB17

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王惠文;王R，

本文編號(hào)：1718884