Description: Gear Fault Diagnosis based on Evidence Theory
Xiong Wei Cheng Jiatang Xu Shaokun
(Engineering College, Honghe University, Mengzi 661100,China)
Abstract For the reason of low-reliability exists in the gear fault diagnosis of traditional methods, a method
based on evidence theory hybrid diagnosis algorithm is presented. According to the fault feature vectors, two parallel
BP neural networks are used to carry on local fault diagnosis to acquire the independent evidences each other. Then
evidence theory is employed to fuse evidences, and gear fault diagnosis is fulfilled finally. Example shows that, vari-
ous faults redundant and complement information can be sufficiently used and the reliability of diagnosis is effectively
improved.
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基于谐波小波重构相位谱的齿轮故障诊断.caj
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