Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Fault Diagnosis of Induction Motors by DFT and Wavelet

DFT와 웨이블렛을 이용한 유도전동기 고장진단

  • 권만준 (충북대학교 전기전자컴퓨터공학부) ;
  • 이대종 (충북대학교 BK21충북정보기술사업단) ;
  • 박성무 (한국폴리텍 IV대학 청주캠퍼스 전기과) ;
  • 전명근 (충북대학교 전기전자컴퓨터공학부)
  • Published : 2007.12.25
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Abstract

In this paper, we propose a fault diagnosis algorithm of induction motors by DFT and wavelet. We extract a feature vector using a fault pattern extraction method by DFT in frequency domain and wavelet transform in time-frequency domain. And then we deal with a fusion algorithm for the feature vectors extracted from DFT and wavelet to classify the faults of induction motors. Finally, we provide an experimental results that the proposed algorithm can be successfully applied to classify the several fault signals acquired from induction motors.

본 논문에서는 DFT(Discrete Fourier Transform)과 웨이블렛을 이용한 고장진단 알고리즘을 제안한다. 제안된 방법은 주파수 기반의 DFT에 의한 고장패턴의 추출방법과 시간-주파수 기반의 웨이블렛을 이용한 고장패턴의 추출방법을 이용하여 특징점을 추출하였으며, 유도전동기의 최종진단은 DFT와 웨이블렛에 의해 추출된 특징값들을 효과적으로 융합할 수 있는 융합 알고리즘에 의해 수행한다. 개발된 알고리즘은 다양한 실측 데이터에 적응하여 그 타당성을 보였다.

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References

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