The Study of Fault-Diagnosis Method of Reciprocating Compressor Based on Fuzzy Fault Tree Theory

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Since working condition of reciprocating compressor is awfully bad and it has bigger risk in operation and higher fault rate,it is of importance to study reciprocating compressor fault. Fault tree has been established in this paper by analyzing factors leading reciprocating compressor fault based on the method of fault tree. 21 minimum cut sets leading to reciprocating compressor fault can be gotten through qualitative analyses on this fault tree,the happening probability of the top event can be calculated and the importance of the basic event s can be analyzed through quantitative analysis. The expert inquiry method combined with fuzzy sets theory is adopted to assess the happening probability of the basic events and top events.

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2649-2653

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November 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Jilong Zhang The research and Application of Fuzzy diagnosis method for reciprocating compressor,[D],Dalian University of Technology,2005. In Chinese

Google Scholar

[2] DinghuaShi , Songrui Wang. The fault tree analysis method and theory [M]. Beijing Normal University press,(1993)

Google Scholar

[3] Jidong Ding, Yuling Jin . Reciprocating gas compressor common faults and troubleshooting [J ]. China Equipment Engineering,2004,1: 39-40. In Chinese

Google Scholar

[4] JiangZhu , Quang zhi Lou . A large reciprocating compressor are examples of common faults and analysis [J ]. Compressor technology,2004,6: 33-35. In Chinese

Google Scholar

[5] Junchao Wu ,The reciprocating compressor fault analysis [J]. Chemical equipment technology,2007,28,4: 65-67

Google Scholar

[6] Shi Wang equivalent. Fuzzy mathematics application in artificial intelligence [M]. Mechanical Industry Press,(1991)

Google Scholar

[7] Chen Shu-Jen , H Wang Chin G-Lai. Fuzzy multi2ple attribute decision making method sand applications[M] .Berlin :Springer-Verlag , 1990 :250-252

Google Scholar

[8] L IN CHIN-TORNG, WANG MAO-J IUN J . Hybrid fault tree analysis using fuzzy set s [J ] . Reliability Engi2neering and System Safety, 1997 (58) :205-213.

DOI: 10.1016/s0951-8320(97)00072-0

Google Scholar