An automatic and robust features learning method for rotating machinery fault diagnosis based on contractive autoencoder

Fault diagnosis of rotating machinery is vital to improve the security and reliability as well as avoid serious accidents. For instance, robust fault features are crucial to achieve a high diagnosis precision. However, traditional feature extraction methods rely on an abundant amount of expertise an...

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Vydané v:	Engineering applications of artificial intelligence Ročník 76; s. 170 - 184
Hlavní autori:	Shen, Changqing, Qi, Yumei, Wang, Jun, Cai, Gaigai, Zhu, Zhongkui
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.11.2018
Predmet:	Contractive autoencoder Correlation analysis Fault diagnosis Robust features Contractive autoencoder Fault diagnosis Robust features Correlation analysis
ISSN:	0952-1976, 1873-6769
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