机械科学与技术2025，Vol.44Issue(11)：1884-1892,9.DOI:10.13433/j.cnki.1003-8728.20230381
联合分布自适应对抗网络故障诊断方法
A New Fault Diagnosis Method with Joint Distribution Adaptive Adversarial Network
摘要
Abstract
Aiming at the problem that the current unsupervised cross-domain fault diagnosis methods are often difficult to align the edge distribution and the conditional distribution at the same time,which leads to low diagnosis accuracy,a joint distributed adaptive adversarial network fault diagnosis method is proposed.Firstly,the original vibration signal is preprocessed by using fast Fourier transform,and the residual neural network is constructed to extract the deep features of the samples.Secondly,the class discrimination information passed by the classifier is used to assist the conditional domain adversarial network to reduce the distribution difference between domains.At the same time,the combined maximum mean difference and the output information of multiple fully connected layers are introduced to realize the adaptive edge distribution and conditional distribution of the cross-domain diagnostic model.Finally,the proposed method is tested by using the data set of Paderborn University in Germany and the data set of laboratory bearings,and the effectiveness and feasibility of the proposed fault diagnosis method in different migration scenarios are proved.关键词
故障诊断/域自适应/对抗训练/联合最大均值差异Key words
fault diagnosis/domain adaptive/adversarial training/joint maximum mean difference分类
机械制造引用本文复制引用
汪超,王波,张猛,徐浩,杨文龙..联合分布自适应对抗网络故障诊断方法[J].机械科学与技术,2025,44(11):1884-1892,9.基金项目
安徽省高校自然科学研究项目(KJ2021A1086)、安徽省高校优秀拔尖人才培育项目(gxgnfx2022071)及滁州学院科研启动基金项目(2024qd22) （KJ2021A1086）
