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Induction Motor Diagnosis System by Effective Frequency Selection and Linear Discriminant Analysis

유효 주파수 선택과 선형판별분석기법을 이용한 유도전동기 고장진단 시스템

  • 이대종 (충북대학교 제어로봇공학과 컴퓨터정보통신연구소) ;
  • 조재훈 (충북대학교 제어로봇공학과 컴퓨터정보통신연구소) ;
  • 윤종환 (충북대학교 제어로봇공학과 컴퓨터정보통신연구소) ;
  • 전명근 (충북대학교 제어로봇공학과 컴퓨터정보통신연구소)
  • Received : 2010.04.03
  • Accepted : 2010.04.30
  • Published : 2010.06.25

Abstract

For the fault diagnosis of three-phase induction motors, we propose a diagnosis algorithm based on mutual information and linear discriminant analysis (LDA). The experimental unit consists of machinery module for induction motor drive and data acquisition module to obtain the fault signal. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by mutual information As the next step, feature extraction is performed by LDA, and then diagnosis is evaluated by k-NN classifier. The results to verify the usability of the proposed algorithm showed better performance than various conventional methods.

본 논문에서는 3상 유도전동기의 고장진단을 수행하기 위해 상호정보량과 선형판별분석기법에 기반을 둔 진단 알고리즘을 제안한다. 실험 장치는 유도전동기 구동의 기계적 모듈과 고장신호를 구하기 위한 데이터 획득 모듈로 구성하였다. 제안된 방법은 취득된 전류신호를 DFT에 의해 주파수 영역으로 변환한 후 분산정보를 이용하여 고장상태별로 차별성이 큰 순서대로 유효 주파수 성분을 추출한다. 다음 단계로 선택된 주파수 성분에 대해서 선형판별분석기법을 적용하여 고장상태별 특징들을 추출한 후 k-NN 분류기에 의해 유도전동기의 상태를 진단하게 된다. 제안된 방법의 타당성을 보이기 위해 다양한 조건하에서 실험한 결과 기존방법에 비하여 우수한 결과를 나타냈다.

Keywords

References

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