Intelligent fault diagnosis of partial deep transfer based on multi-representation structural intraclass compact and double-aligned domain adaptation

Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study

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Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

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Condition Monitoring of Bearing Damage in Electromechanical Drive Systems by Using Motor Current Signals of Electric Motors: A Benchmark Data Set for Data-Driven Classification

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A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges

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Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study

Zhibin Zhao, Tianfu Li, Jingyao Wu et al. · ISA Transactions · 2020 · 634 citations · Full text

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