Deep hypergraph autoencoder embedding: An efficient intelligent approach for rotating machinery fault diagnosis

Intelligent fault diagnosis based on deep learning (DL) has been widely used in various engineering practices. However, when confronting massive unlabeled industrial data, traditional data-driven intelligent fault diagnosis approaches cannot fully mine the correlation geometric structure information...

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Veröffentlicht in:	Knowledge-based systems Jg. 260; S. 110172
Hauptverfasser:	Shi, Mingkuan, Ding, Chuancang, Wang, Rui, Song, Qiuyu, Shen, Changqing, Huang, Weiguo, Zhu, Zhongkui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 25.01.2023
Schlagworte:	Deep hypergraph autoencoder embedding Extreme learning machine autoencoder Higher-order structure information Intelligent fault diagnosis Subspace structure Higher-order structure information Extreme learning machine autoencoder Deep hypergraph autoencoder embedding Intelligent fault diagnosis Subspace structure
ISSN:	0950-7051, 1872-7409
Online-Zugang:	Volltext
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