Dynamic Condition Adversarial Adaptation for Fault Diagnosis of Wind Turbine Gearbox
Hongpeng Zhang,
Xinran Wang,
Cunyou Zhang
et al.
Abstract:While deep learning has found widespread utility in gearbox fault diagnosis, its direct application to wind turbine gearboxes encounters significant hurdles. Disparities in data distribution across a spectrum of operating conditions for wind turbines result in a marked decrease in diagnostic accuracy. In response, this study introduces a tailored dynamic conditional adversarial domain adaptation model for fault diagnosis in wind turbine gearboxes amidst cross-condition scenarios. The model adeptly adjusts the … Show more
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