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The fault diagnosis method based on ambiguity domain and support vector machine

WANG Sheng-chun1,2,HAN Jie2,LI Zhi-nong2,LI Jian-feng2   

  1. 1. School of Mechanical Engineering, Shandong University,Jinan 250061,China;2. Research Institute of Vibration Engineering,Zhengzhou University,Zhengzhou 450002,China
  • Received:2006-03-29 Revised:1900-01-01 Online:2006-12-24 Published:2006-12-24
  • Contact: WANG Sheng-chun

Abstract: By combining ambiguity domain with support vector machine(SVM), a new method of fault diagnosis was presented. The proposed method used the local energy in ambiguity domain as a feature vector to input the SVM classifier to identify faults. The local information of signal can be fully reflected by using ambiguity domain distribution. Compared with the feature extracted from the timefrequency plane, the dimensions of feature vector can be greatly reduced. The recognition results are analyzed for different kernel functions. The experiment results show that the best classify efficiency can be obtained without any kernel function in ambiguity domain.

Key words: support vector machine(SVM), kernel function, fault diagnosis , ambiguity domain

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