本文關(guān)鍵詞： 系統(tǒng)可靠性預(yù)測(cè) 緩慢故障 貝葉斯理論 數(shù)據(jù)驅(qū)動(dòng)算法 田納西-伊斯曼過(guò)程　出處：《哈爾濱工業(yè)大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：先進(jìn)控制技術(shù)在過(guò)程控制中的應(yīng)用不斷加大，使得過(guò)程控制系統(tǒng)變得越來(lái)越復(fù)雜，由此帶來(lái)系統(tǒng)故障種類的增多。對(duì)于某些工業(yè)過(guò)程來(lái)說(shuō)，故障帶來(lái)的損壞是永久的，無(wú)法修復(fù)或者修復(fù)系統(tǒng)的代價(jià)極其昂貴。若能掌控系統(tǒng)的工作狀態(tài)并預(yù)測(cè)出系統(tǒng)可能發(fā)生故障的時(shí)間節(jié)點(diǎn)，及時(shí)更換相關(guān)故障環(huán)節(jié)的設(shè)備避免故障發(fā)生，就可以避免由于系統(tǒng)故障帶來(lái)的經(jīng)濟(jì)損失，，因此預(yù)測(cè)出系統(tǒng)的可靠程度對(duì)系統(tǒng)的維護(hù)至關(guān)重要。 一般的工業(yè)過(guò)程控制系統(tǒng)發(fā)生的故障可以分為兩類分別為：突發(fā)性故障和緩慢故障。突發(fā)性故障是指系統(tǒng)由于不可測(cè)外力作用而導(dǎo)致的即時(shí)故障，隨機(jī)性強(qiáng)，發(fā)生一般無(wú)征兆，因而一般不考慮其可靠性。緩慢故障是指系統(tǒng)由于自身設(shè)備磨損或元器件老化導(dǎo)致的延時(shí)性故障，系統(tǒng)正常工作時(shí)故障表現(xiàn)不明顯，故而可以通過(guò)對(duì)系統(tǒng)易發(fā)生故障的部分進(jìn)行實(shí)時(shí)監(jiān)控來(lái)預(yù)測(cè)系統(tǒng)可能發(fā)生故障的節(jié)點(diǎn)。本文即針對(duì)這種故障來(lái)展開(kāi)討論的。 本文通過(guò)四章來(lái)對(duì)系統(tǒng)的可靠性預(yù)測(cè)問(wèn)題加以敘述。在第一章中對(duì)系統(tǒng)可靠性預(yù)測(cè)的研究現(xiàn)狀作了簡(jiǎn)要的介紹，同時(shí)給出了本文所要研究的主要內(nèi)容。第2章中給出了通過(guò)系統(tǒng)監(jiān)控?cái)?shù)據(jù)得到系統(tǒng)可靠性指標(biāo)的方法，文中給出了兩種方法，可以根據(jù)不同的數(shù)據(jù)使用不同的方法來(lái)得到系統(tǒng)可靠性指標(biāo)。第3章提出了基于AR模型的貝葉斯預(yù)測(cè)方法，給出了具體的預(yù)測(cè)方案。第4章中對(duì)前面提出的方法基于TE過(guò)程的故障數(shù)據(jù)進(jìn)行仿真，并最終得到系統(tǒng)可靠性的預(yù)測(cè)曲線。 綜上，本文給出了一種針對(duì)具有緩慢故障的工業(yè)過(guò)程控制系統(tǒng)進(jìn)行可靠性預(yù)測(cè)的方法，將故障診斷于可靠性預(yù)測(cè)聯(lián)系到一起，使得一些能用于故障診斷的方法應(yīng)用到對(duì)系統(tǒng)可靠性預(yù)測(cè)領(lǐng)域當(dāng)中。
[Abstract]:The application of advanced control technology in process control is increasing, which makes the process control system become more and more complex, resulting in an increase in the types of system failures. For some industrial processes. The damage caused by the failure is permanent, and it is extremely expensive to repair or repair the system. If you can control the working state of the system and predict the time node when the system may fail. It is very important to forecast the reliability of the system to avoid the economic loss caused by the system failure by replacing the equipment of the relevant fault link in time to avoid the failure. The common industrial process control system fault can be divided into two types: sudden failure and slow fault. Sudden fault refers to the system due to the role of undetectable external forces caused by the instant failure, strong randomness. Slow fault refers to the delay fault of the system caused by wear and tear of its own equipment or the aging of the components. The fault performance of the system is not obvious when it works normally. Therefore, it is possible to predict the possible nodes of the system by monitoring the vulnerable parts of the system in real time. In this paper, the reliability prediction of the system is described in four chapters. In the first chapter, the research status of the reliability prediction of the system is briefly introduced. At the same time, the main contents of this paper are given. In chapter 2, the method of obtaining system reliability index by system monitoring data is given, and two methods are given in this paper. According to different data, different methods can be used to obtain system reliability index. In chapter 3, Bayesian prediction method based on AR model is proposed. In chapter 4, the proposed method is simulated based on the fault data of te process, and the prediction curve of system reliability is obtained. In summary, this paper presents a method of reliability prediction for industrial process control system with slow fault, which connects fault diagnosis with reliability prediction. Some methods used in fault diagnosis can be applied to the field of system reliability prediction.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP273;TB114.3

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本文編號(hào)：1482788