苏州科技大学学报（自然科学版）2026，Vol.43Issue(3)：83-88,6.DOI:10.12084/j.issn.2096-3289.2026.03.010
基于多传感器图Transformer的高频电力电子变换器故障诊断研究
Fault diagnosis of high-frequency power electronic converters based on multi-sensor graph transformer
摘要
Abstract
Fault diagnosis of power electronic converters is crucial for maintaining their normal operation.In view of the deficiency in accuracy of the current fault diagnosis methods for power electronic converters,a fault diagnosis model for converters based on multi-sensors and graph Transformer is proposed.We employed multiple sensors to monitor the converter,and adopted dynamic time wrapping and continuous wavelet transform for data processing.Fi-nally,a graph Transformer module was constructed for feature extraction and fault diagnosis.In the simulation ex-periment,the detection accuracy rates of the proposed model for capacitor faults and inductor faults were 99.87%and 99.91%respectively,and the detection accuracy rate for diode short circuits was 99.67%,both of which were higher than those of the comparison model,demonstrating better diagnostic performance.The experimental results show that the model proposed has higher accuracy in fault diagnosis and can complete the fault diagnosis task of high-frequency power electronic converters precisely.关键词
电力电子变换器/图卷积/Transformer/小波变换/传感器Key words
power electronic converter/graph convolution/Transformer/wavelet transform/sensor分类
信息技术与安全科学引用本文复制引用
刘宇环,金占双..基于多传感器图Transformer的高频电力电子变换器故障诊断研究[J].苏州科技大学学报（自然科学版）,2026,43(3):83-88,6.基金项目
安徽省高等学校自然科学研究重点项目(2023AH052565) （2023AH052565）
