A method which integrates expert evaluation method and support vector machine(SVM) method is introduced for failure mode criticality analysis(FMCA) about the gearbox device. An expert evaluation standard is built by u...A method which integrates expert evaluation method and support vector machine(SVM) method is introduced for failure mode criticality analysis(FMCA) about the gearbox device. An expert evaluation standard is built by using expert evaluation method. The experts make scores about the gearbox failure mode. In order to overcome the subjectivity of expert evaluation method, we use SVM method to make a comprehensive prediction about the scores. According to the comprehensive prediction evaluation results, the FMCA of the gearbox device can be obtained. The analysis shows that the method used in this paper not only can effectively solve the problem which is unable to get specific failure rate in the qualitative analysis, but also can solve the problem which needs lots of data in the quantitative analysis.展开更多
基金the National Natural Science Foundation of China(No.11272070)the Natural Science Foundation of Liaoning Province(No.2014028020)+1 种基金the Dalian Science and Technology Project(No.2015A11GX026)the Educational Commission Project of Liaoning Province(No.L2013182)
文摘A method which integrates expert evaluation method and support vector machine(SVM) method is introduced for failure mode criticality analysis(FMCA) about the gearbox device. An expert evaluation standard is built by using expert evaluation method. The experts make scores about the gearbox failure mode. In order to overcome the subjectivity of expert evaluation method, we use SVM method to make a comprehensive prediction about the scores. According to the comprehensive prediction evaluation results, the FMCA of the gearbox device can be obtained. The analysis shows that the method used in this paper not only can effectively solve the problem which is unable to get specific failure rate in the qualitative analysis, but also can solve the problem which needs lots of data in the quantitative analysis.
