本文選題：故障診斷 + 離心式壓縮機　； 參考：《西南石油大學》2017年碩士論文

【摘要】：離心式壓縮機是石油化工企業(yè)的關鍵設備,具有流向大,轉速高,占地面積小等優(yōu)點,承擔著為整套設備和循環(huán)介質(zhì)提供循環(huán)動力的任務。若離心壓縮機產(chǎn)生故障,極其容易形成巨大的安全事故,給當事企業(yè)造成巨大危害。因此,如何在離心式壓縮機出現(xiàn)故障征兆時盡可能快地采取措施規(guī)避故障事故的發(fā)生;如何在設備故障后快速找出原因并加以排除,將離心式壓縮機故障事故降低到最低限度就成為了一個非常重要的研究課題。本文采用基于Petri網(wǎng)的故障診斷技術對離心式壓縮機故障系統(tǒng)進行狀態(tài)分析故障診斷。首先對基本Petri網(wǎng)的基礎性知識和根本性規(guī)則進行定義和分析,接著再建立作用于故障信息傳播演變推導分析的離心式壓縮機故障Petri網(wǎng)系統(tǒng)模型,對離心式壓縮機系統(tǒng)故障進行系統(tǒng)性推理分析,并利用模型的關聯(lián)矩陣及其狀態(tài)方程式分析法對故障信息的傳播路徑進行模擬論證�？墒枪收螾etri網(wǎng)為具備模糊性以及不確定性的故障源進行反向診斷推導時具有嚴重缺陷,導致推導過程難以為繼,對故障Petri網(wǎng)進行改進,使之能夠符合故障診斷需要。為克服故障Petri網(wǎng)在推理分析復雜、不確定的故障信息中的不足,首先引入置信度最大及深度搜索優(yōu)先的診斷辦法,同時綜合Petri網(wǎng)和模糊推導知識,形成并進一步定義出模糊Petri網(wǎng)診斷推理方法及其概念與規(guī)則表示,依照其反向診斷推理算法并基于已形成的故障來研判分析出故障源,同時分析羅列出該診斷推理方法的流程步驟,同時結合正向推理分析算法,通過邏輯推理和系統(tǒng)狀態(tài)推理運算對離心式壓縮機故障系統(tǒng)進行推導分析。經(jīng)過對離心式壓縮機系統(tǒng)進行正向推導分析及其反向診斷推導,得出了一致的結論,研判出系統(tǒng)中的故障源以及它們引發(fā)故障的可信度,由此論證了算法的有效性、可行性和準確性,進一步提升了故障診斷的準確性和高效性,為工作人員對離心式壓縮機設備系統(tǒng)進行日常維護和故障診斷提供了一種新辦法、新思路。
[Abstract]:Centrifugal compressor is the key equipment in petrochemical enterprises, which has the advantages of large flow direction, high speed, small area, and so on. It undertakes the task of providing circulating power for the whole equipment and circulation medium. If centrifugal compressor failure, it is easy to form a huge safety accident, causing great harm to the enterprise concerned. Therefore, how to take measures to avoid fault accidents as soon as possible, how to find out the cause quickly after the equipment failure and how to eliminate it. Reducing the fault of centrifugal compressor to the minimum has become a very important research topic. In this paper, fault diagnosis technology based on Petri net is used for fault diagnosis of centrifugal compressor fault system. Firstly, the basic knowledge and fundamental rules of basic Petri net are defined and analyzed, then the fault Petri net system model of centrifugal compressor is established, which is used to deduce and analyze the evolution of fault information. The fault of centrifugal compressor system is analyzed by systematic reasoning, and the propagation path of fault information is simulated by using the correlation matrix of the model and the analysis of the state equation. However, fault Petri nets have serious defects in the reverse diagnosis derivation for fault sources with fuzziness and uncertainty, which makes the derivation process difficult to continue. The fault Petri nets are improved to meet the needs of fault diagnosis. In order to overcome the shortcomings of fault Petri nets in reasoning and analysis of complex and uncertain fault information, a diagnosis method of maximum confidence and depth search priority is introduced, and Petri nets and fuzzy derivation knowledge are synthesized at the same time. The fuzzy Petri net diagnosis reasoning method and its concept and rule representation are formed and further defined. According to its reverse diagnosis reasoning algorithm and based on the fault that has been formed, the fault source is analyzed and analyzed. At the same time, the process steps of the diagnostic reasoning method are listed, and the fault system of centrifugal compressor is deduced and analyzed by logical reasoning and system state reasoning combined with forward reasoning analysis algorithm. After the forward derivation and reverse diagnosis of the centrifugal compressor system, a consistent conclusion is drawn, and the fault source and the reliability of the fault caused by the fault are studied, and the validity of the algorithm is demonstrated. The feasibility and accuracy improve the accuracy and efficiency of fault diagnosis, and provide a new method and new idea for the routine maintenance and fault diagnosis of centrifugal compressor equipment system.
【學位授予單位】：西南石油大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TQ051.21;TP301.1

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