RAAN: A Gaussian Prior Domain Adaptive Network for Rolling Bearing Fault Diagnosis Under Variable Working Conditions

In the field of fault diagnosis for rolling bearings under variable working conditions, significant progress has been made using methods based on unsupervised domain adaptation (UDA). However, most existing UDA methods primarily achieve identification by directly aligning the distributions of the so...

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主要な著者:	Kang Liu, Yang Yu, Yuanjiang Li, Tao Lang, Ruochen Liu
フォーマット:	Artigo
言語:	Inglês
出版事項:	Tsinghua University Press 2025-03-01
シリーズ:	Complex System Modeling and Simulation
主題:	domain adaptation indirect potential alignment rolling bearings variable operating conditions fault diagnosis
オンライン･アクセス:	https://www.sciopen.com/article/10.23919/CSMS.2024.0026
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