Fault Diagnosis of Induction Motor by Hierarchical Classifier

계층구조의 분류기에 의한 유도전동기 고장진단

  • 이대종 (충북대학교 충북정보기술사업단) ;
  • 송창규 (충북대학교 충북정보기술사업단) ;
  • 이재경 (충주대학교 정보제어공학과) ;
  • 전명근 (충북대학교 전기전자컴퓨터공학부)
  • Published : 2007.06.01


In this paper, we propose a fault diagnosis scheme tor induction motor by adopting a hierarchical classifier consisting of k-Nearest Neighbors(k-NN) and Support Vector Machine(SVM). First, some motor conditions are classified by a simple k-NN classifier in advance. And then, more complicated classes are distinguished by SVM. To obtain the normal and fault data, we established an experimental unit with induction motor system and data acquisition module. Feature extraction is performed by Principal Component Analysis(PCA). To show its effectiveness, the proposed fault diagnostic system has been intensively tested with various data acquired under the different electrical and mechanical faults with varying load.


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