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...

Full description

Bibliographic Details

Published in:	Engineering applications of artificial intelligence Vol. 76; pp. 170 - 184
Main Authors:	Shen, Changqing, Qi, Yumei, Wang, Jun, Cai, Gaigai, Zhu, Zhongkui
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2018
Subjects:	Contractive autoencoder Correlation analysis Fault diagnosis Robust features Contractive autoencoder Fault diagnosis Robust features Correlation analysis
ISSN:	0952-1976, 1873-6769
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!