Multi-source domain adversarial graph convolutional networks for rolling mill health states diagnosis under variable working conditions

As the rolling mill often encounters variable and complicated working conditions and shock loads, unsupervised domain adaptive (UDA) methods are imperative in its health monitoring. However, efforts of applying UDA methods on the rolling mill are negligible, and many existing approaches have constra...

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Veröffentlicht in:	Structural health monitoring 2024-11, Vol.23 (6), p.3505-3524
Hauptverfasser:	Zhao, Shuai, Bao, Leping, Hou, Changhui, Bai, Yang, Yu, Yue
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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