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- W2348490199 abstract "The micro-vibration mechanism and fault characteristics of micro-gears were described,and the three layer wavelet neural network was constructed and the algorithm was proposed,and also the principles and steps of differential evolution algorithm were presented.The micro-vibration mechanism and fault characteristics of micro-gears were described and the faults were classified with no fault,gear crack,gear face wear,tooth face attrition,and tooth face crack.The diagnosis information acquired with vibration experiment and designed as training samples of wavelet neural networks,and the network was optimized with differential evolution algorithm.Simulation result shows the new method can avoid normal neural networks with convergence quality and enhance learning speed,and also the higher diagnosis precision and efficiency was got,and this proposed method can be effectively used in engineering diagnosis system." @default.
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- W2348490199 date "2012-01-01" @default.
- W2348490199 modified "2023-09-26" @default.
- W2348490199 title "Application of Differential Evolution Wavelet Neural Networks in Micro-Gears Fault Diagnosis" @default.
- W2348490199 hasPublicationYear "2012" @default.
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