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《Thermal Power Generation》 2010-02
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DIAGNOSIS OF VIBRATION FAULT ON TURBO-GENERATOR SET BASED ON ROUGH SET THEORY AND NAIVE BAYESIAN CLASSIFICATION ALGORITHM

GAO Jun-shan,LANG Ping,SUN Zhen-heCollege of Automation,Harbin University of Science and Technology,Harbin 150080,Heilongjiang Province,PRC  
The complexity of turbo-generator set's structure and it's vibration make its fault to have multigradation and randomness,as well as the fault information being not complete.For this,a method to diagnose fault of turbo-generator set's vibration based on rough set theory and naive Bayesian classificatin algorithm has been put forward.The minmum attribute reduction set is sought by using the rough set,and then the bigger area in which the faults may occur has been diagnosed by using the naive Bayesian classification algorithm,and finally,directing against the concrete fault settings,the said method being validated.Results of practical calculation examples show that the the said method can get better diagnosis result when the fault information isn't complete,and even the kernel attribute being lost,enhancing the fault-tolerance capability of the diagnosis system.
【CateGory Index】: TM311
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