A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

作     者：Shuhui WANG Yaguo LEI Na LU Xiang LI Bin YANG Shuhui WANG;Yaguo LEI;Na LU;Xiang LI;Bin YANG

作者机构：Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing SystemXi’an Jiaotong UniversityXi’an 710049China Systems Engineering InstituteXi’an Jiaotong UniversityXi’an 710049China 

出 版 物：《机械工程前沿:英文版》 (Frontiers of Mechanical Engineering)

年 卷 期：2023年第18卷第2期

页      面：267-281页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 080201[工学-机械制造及其自动化] 

基　　金：supported by the National Natural Science Foundation of China(Grant No.52025056) the Fundamental Research Funds for the Central Universities 

主　　题：fault recognition fault localization multi-sensor relations network analysis graph neural network 

摘      要：Recently,advanced sensing techniques ensure a large number of multivariate sensing data for intelligent fault diagnosis of *** the advantage of obtaining accurate diagnosis results,multi-sensor fusion has long been studied in the fault diagnosis ***,existing studies suffer from two ***,the relations of multiple sensors are either neglected or calculated only to improve the diagnostic accuracy of fault ***,the localization for multi-source faults is seldom investigated,although locating the anomaly variable over multivariate sensing data for certain types of faults is *** article attempts to overcome the above weaknesses by proposing a global method to recognize fault types and localize fault sources with the help of multi-sensor relations(MSRs).First,an MSR model is developed to learn MSRs automatically and further obtain fault recognition ***,centrality measures are employed to analyze the MSR graphs learned by the MSR model,and fault sources are therefore *** proposed method is demonstrated by experiments on an induction motor and a centrifugal *** show the proposed method’s validity in diagnosing fault types and sources.