本文關(guān)鍵詞：電梯故障診斷專家系統(tǒng)的研究與開發(fā)　出處：《東北大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 電梯 故障診斷 專家系統(tǒng) 支持向量機(jī)

【摘要】：近幾十年我國經(jīng)濟(jì)發(fā)展迅猛,樓房的平均高度也在不斷增加,電梯越來越成為人們生活和工作中必不可少的工具。電梯的可靠性和安全性時刻在威脅著人們的人身和財產(chǎn)安全,因此必須做到及時發(fā)現(xiàn)和處理電梯故障。要保證電梯的可靠性需要做到以下兩點：在電梯正式出廠安裝使用之前對電梯進(jìn)行可靠性測試；及時發(fā)現(xiàn)和處理電梯運(yùn)行過程中出現(xiàn)的故障。根據(jù)當(dāng)前對電梯故障診斷的需要,本文研究了專家系統(tǒng)和支持向量機(jī)用于故障診斷的相關(guān)理論,在專家系統(tǒng)的推理機(jī)中融入支持向量機(jī),利用支持向量機(jī)的數(shù)據(jù)挖掘能力,從故障數(shù)據(jù)中分析出電梯故障原因。通過專家系統(tǒng)建立知識庫并進(jìn)行管理維護(hù),使用規(guī)則對電梯故障進(jìn)行推理診斷并用解釋器做出相應(yīng)的解釋說明。系統(tǒng)發(fā)揮了兩者的優(yōu)勢,提高診斷能力。本文的主要研究內(nèi)容如下：首先本文介紹了故障診斷技術(shù),對故障診斷方法進(jìn)行了分析與比較,介紹了幾種典型的故障診斷專家系統(tǒng),并分析了電梯的常見故障。其次建立電梯故障診斷專家系統(tǒng)模型,選取產(chǎn)生式規(guī)則表示法、正向推理分別對知識進(jìn)行表示和推理。再次研究了電梯故障診斷算法,包括支持向量機(jī)的基本原理及其關(guān)鍵點；選用徑向基核函數(shù),對其參數(shù)的選擇采用交叉驗證和網(wǎng)格搜索的方法,用“一對一”的方法來處理故障診斷的多分類問題,建立了支持向量機(jī)故障診斷多分類器模型。最后本文采用了專家系統(tǒng)與支持向量機(jī)相結(jié)合的方法,建立了電梯故障診斷專家系統(tǒng)。實現(xiàn)了專家系統(tǒng)知識的獲取、知識的表示、知識庫、推理機(jī)及解釋器。
[Abstract]:In recent years China's rapid economic development, the average height of the building is also increasing, elevator has become more and more indispensable in people's work and life tools. Lift the reliability and safety of threaten people's personal and property safety, and therefore must be timely detection and treatment of elevator fault to ensure the reliability of the elevator. Need to do the following two points: testing the reliability of the elevator installation before officially lift the factory; failure to timely detection and treatment of elevator operation. According to the current needs of elevator fault diagnosis, this paper studies expert system and support vector machine theory for fault diagnosis, into the support vector machine in expert system in the use of support vector machine data mining ability, analysis of the reasons of elevator fault from fault data. Through the establishment of expert system knowledge Management and maintenance of knowledge base and reasoning rules, using the diagnosis of elevator fault and interpreter to make the appropriate explanation. The system can play the advantages of both, to improve the diagnosis ability. The main contents of this paper are as follows: firstly, this paper introduces the fault diagnosis technology, the fault diagnosis methods are compared and analyzed, introduced several the typical fault diagnosis expert system, and analyzes the common faults of the elevator. Secondly, the fault diagnosis expert system of elevator model, selection of generative rule representation and reasoning are representation and reasoning of knowledge. Another study of elevator fault diagnosis algorithm, including the basic principle of support vector machine and its key points; the radial basis kernel function of the parameter selection using cross validation method and grid search, use the multi classification problem of method "to deal with the fault diagnosis A support vector machine, fault diagnosis of multi classifier model. Finally this paper adopts the method of combining expert system with support vector machine, a fault diagnosis expert system of elevator. The knowledge acquisition of expert system, knowledge representation, knowledge base, inference engine and the interpreter.

【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TU857

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本文編號：1388763