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Exploring Sample/Feature Hybrid Transfer for Gear Fault Diagnosis Under Varying Working Conditions
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Unknown environmental noise and varying operation conditions negatively affect gear fault diagnosis (GFD) performance. In this paper, the sample/feature hybrid transfer learning (TL) strategies are adopted for GFD under ...
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