Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Fault Detection and Diagnosis of Induction Motors using LPC and DTW Methods

LPC와 DTW 기법을 이용한 유도전동기의 고장검출 및 진단

  • Hwang, Chul-Hee (School of Electrical Engineering, University of Ulsan) ;
  • Kim, Yong-Min (School of Electrical Engineering, University of Ulsan) ;
  • Kim, Cheol-Hong (Dept. of Electronics and Computer Eng., Chonnam National University) ;
  • Kim, Jong-Myon (School of Electrical Engineering, University of Ulsan)
  • 황철희 (울산대학교 전기공학부) ;
  • 김용민 (울산대학교 전기공학부) ;
  • 김철홍 (전남대학교 전자컴퓨터공학과) ;
  • 김종면 (울산대학교 전기공학부)
  • Received : 2010.11.18
  • Accepted : 2010.12.01
  • Published : 2011.03.31
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Abstract

This paper proposes an efficient two-stage fault prediction algorithm for fault detection and diagnosis of induction motors. In the first phase, we use a linear predictive coding (LPC) method to extract fault patterns. In the second phase, we use a dynamic time warping (DTW) method to match fault patterns. Experiment results using eight vibration data, which were collected from an induction motor of normal fault states with sampling frequency of 8 kHz and sampling time of 2.2 second, showed that our proposed fault prediction algorithm provides about 45% better accuracy than a conventional fault diagnosis algorithm. In addition, we implemented and tested the proposed fault prediction algorithm on a testbed system including TI's TMS320F2812 DSP that we developed.

본 논문은 유도전동기의 고장검출 및 진단을 위한 효율적인 2-단계 고장예측 알고리즘을 제안한다. 첫 번째 단계에서는 고장 패턴 추출을 위해 선형 예측 부호화 (Linear Predictive Coding: LPC) 기법을 사용하고, 두 번째 단계에서는 고장 패턴 매칭을 위해 동적시간교정법 (Dynamic Time Warping: DTW)을 사용한다. 유도전동기에서 정상 및 각종 이상 상태의 조건을 발생시켜 추출한 샘플링 주파수 8kHz, 샘플링 시간 2.2초의 정상상태 및 비정상 상태의 진동데이터 8개를 사용하여 모의 실험한 결과, 제안한 고장예측 알고리즘은 기존의 고장진단 알고리즘보다 약 45%의 정확도 향상을 보였다. 또한 TI사의 TMS320F2812 DSP를 내장한 테스트베드 시스템을 제작하여 제안한 고장예측 알고리즘을 구현하고 검증하였다.

Keywords

References

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