船电技术2026，Vol.46Issue(9)：1-5,5.
基于二维CNN和GRU的五相逆变器故障诊断
Fault Diagnosis of Five-Phase Inverters Based on 2D Convolutional Neural Network-GRU
摘要
Abstract
Aimed at the open-circuit of power switches in the five-phase voltage source inverter,the paper designs a CNN-GRU network architecture with two convolutional(2D)layers and proposes a fault diagnosis method for five-phase inverters based on 2D convolutional neural networks and gated recurrent units(GRU).A sample dataset is established based on positive-sequence symmetrical components,which is fed into the two-dimensional CNN model.The spatial-temporal features of samples are extracted by the 2D CNN-GRU units,and the fault diagnosis results of the inverter are obtained via the output layer.Experimental results show that the proposed method can diagnose open-circuit faults of the inverter effectively and accurately.关键词
故障诊断/卷积神经网络/门控循环单元/五相逆变器Key words
Fault diagnosis/Convolutional neural network/Gated recurrent units(GRU)/Five-phase inverter分类
信息技术与安全科学引用本文复制引用
崔林涛..基于二维CNN和GRU的五相逆变器故障诊断[J].船电技术,2026,46(9):1-5,5.基金项目
国家自然科学基金(51779102) （51779102）
