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《Bearing》 2009-08
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Faults Diagnosis of Roller Bearings Based on Knowledge Increasable Neural Network

JIANG Yu1,LI Zhi-xiong2,TANG Ming2,LI Li2 (1.College of Information Engineering,Huangshan University,Huangshan 245021,China;2.College of Mechanical and Material Engineering,Three Gorges University,Yichang 443002,China)  
The rolling bearing faults diagnosis is studied,and the wavelet packet and BP neural network faults diagnosis method is described.With consideration of the weakness of ANN when solving large-scale and complicated problem,in the view of generalization ability,the faults diagnosis structure is designed by using wavelet packet and knowledge increasable neural network method.Based on experimental analysis,multi-site single and compounded bearing faults are identified correctly.The results show that this method is available to recognize the fault location and pattern accurately and better than that without knowledge increase ability.
【CateGory Index】: TH133.33
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