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.

基于证据理论的齿轮故障诊断.caj

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