Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification
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- 作者：Chen Lua ; b ; Zhen-Ya Wanga ; b ; Wei-Li Qina ; Jian Maa ; b ; majian3129@126.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：Fault diagnosis ; Stacked denoising autoencoder ; Health state identification ; Deep learning
- 刊名：Signal Processing
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：130
- 期：Complete
- 页码：377-388
- 全文大小：1494 K
文摘
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Deep neural network is developed for fault diagnosis of typical dynamic systems.
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Better robustness is achieved under various working conditions and ambient noise.
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The method helps salient fault characteristic mining and intelligent diagnosis.
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Validity of the SDA is verified via comparative experiments.