Adaptive inter-intradomain alignment network with class-aware sampling strategy for rolling bearing fault diagnosis  

作　　者：GAO QinHe HUANG Tong ZHAO Ke SHAO HaiDong JIN Bo LIU ZhiHao WANG Dong 

机构地区：[1]National Key Discipline Laboratory of Armament Launch Theory&Technology,Rocket Force University of Engineering,Xi’an 710025,China [2]Key Laboratory of Road Construction Technology&Equipment Ministry of Education,Chang’an University,Xi’an 710054,China [3]College of Mechanical and Vehicle Engineering,Hunan University,Changsha 410082,China [4]Institute of Systems and Robotics,Department of Electrical and Computer Engineering,University of Coimbra,Coimbra 3030-290,Portugal

出　　处：《Science China(Technological Sciences)》2023年第10期2862-2870,共9页中国科学（技术科学英文版）

基　　金：the National Natural Science Foundation of China(Grant Nos.52275104,51905160);the Natural Science Fund for Excellent Young Scholars of Hunan Province(Grant No.2021JJ20017)。

摘　　要：Existing unsupervised domain adaptation approaches primarily focus on reducing the data distribution gap between the source and target domains,often neglecting the influence of class information,leading to inaccurate alignment outcomes.Guided by this observation,this paper proposes an adaptive inter-intra-domain discrepancy method to quantify the intra-class and inter-class discrepancies between the source and target domains.Furthermore,an adaptive factor is introduced to dynamically assess their relative importance.Building upon the proposed adaptive inter-intradomain discrepancy approach,we develop an inter-intradomain alignment network with a class-aware sampling strategy(IDAN-CSS)to distill the feature representations.The classaware sampling strategy,integrated within IDAN-CSS,facilitates more efficient training.Through multiple transfer diagnosis cases,we comprehensively demonstrate the feasibility and effectiveness of the proposed IDAN-CSS model.

关 键 词：unsupervised domain adaptation inter-class domain discrepancy intra-class domain discrepancy class-aware sampling strategy 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TH133.33[自动化与计算机技术—控制科学与工程]