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Content Provider | IEEE Xplore Digital Library |
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Author | Xiang Zhou Ligang Hou Chengli Su Yanliang Xiao Yong Zhang |
Copyright Year | 2011 |
Abstract | In order to eliminate the noise in original signals about gear fault, wave filtering is put into use in this paper, and Wave Neural Network which is based on that is built. In the network training, it mainly applies Gradient Descent Method and Adaptive Learning Rate Adjustment Method to optimize every parameter. Furthermore the arithmetic of the gradient and learning rate is improved. Finally, the trained Wave Neural Network is used to diagnose gear fault. The simulation results show that the use of filtered information and Wavelet Neural Network can accurately identify the gear fault. |
Starting Page | 2939 |
Ending Page | 2942 |
File Size | 193954 |
Page Count | 4 |
File Format | |
ISBN | 9781424487370 |
e-ISBN | 9781424487387 |
DOI | 10.1109/CCDC.2011.5968755 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-05-23 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Fault diagnosis Gears Wave filtering Noise reduction Artificial neural networks Wave Neural Network Wavelet analysis Wavelet packets Gear fault |
Content Type | Text |
Resource Type | Article |
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