基于全仿真数据驱动的多相变换器故障诊断域泛化方法

This article investigates the generalization capabilities of deep learning models for diagnosing faults in multiphase converter power switch devices. Traditional fault diagnosis approaches depend heavily on real-world fault data for model training. However, in industrial settings, the infrequent failures of multiphase converters and the prohibitive costs of fault experiments result in a significan...