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2018 Vol.31, Issue 1 Preview Page
Feature Extraction for Bearing Prognostics using Weighted Correlation Coefficient

상관계수 가중치를 이용한 베어링 수명예측 특징신호 추출

Seokgoo Kim1
,
Chaeyoung Lime1
,
Joo-Ho Choi2†
김 석 구1
,
임 채 영1
,
최 주 호2†
1Dept. of Aerospace and Mechanical Engineering, Korea Aerospace Univ., 10540, Korea
2School of Aerospace and Mechanical Engineering, Korea Aerospace Univ., 10540, Korea
1한국항공대학교 항공우주 및 기계공학과
2한국항공대학교 항공우주 및 기계공학부
†Corresponding author : +82-2-300-0117; jhchoi@kau.ac.kr
2018. pp. 63-69
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Abstract

Bearing is an essential component in many rotary machineries. To prevent its unpredicted failures and undesired downtime cost, many researches have been made in the field of Prognostics and Health Management(PHM), in which the key issue is to establish a proper feature reflecting its current health state properly at the early stage. However, conventional features have shown some limitations that make them less useful for early diagnostics and prognostics because it tends to increase abruptly at the end of life. This paper proposes a new feature extraction method using the envelope analysis and weighted sum with correlation coefficient. The developed method is demonstrated using the IMS bearing data given by NASA Ames Prognostics Data Repository. Results by the proposed feature are compared with those by conventional approach.

Keywords
bearing
prognostics and health management(PHM)
feature extraction
correlation coefficient

베어링은 많은 회전체에서 사용되는 핵심부품으로, 예기치 않은 고장을 방지하기 위해 많은 연구가 집중되고 있다. 이때 중요한 것은 되도록 초기에 건전성 상태를 잘 나타내는 적절한 특징신호를 추출하는 것이다. 그러나 기존의 연구들은 주로 진단관점에서 특징신호를 추출하여 고장예지에는 적합하지 않은 측면이 있었다. 본 논문에서는 이러한 문제를 극복하기 위 해 베어링 고장 주파수의 에너지와 시간 사이의 상관계수 가중 합을 이용하여 베어링 수명 예측에 용이한 특징신호를 추출 하는 방법을 개발하였다. 그 결과 일반적으로 고장진단에서 많이 사용되고 있는 특징신호인 RMS에 비해서 결함 초기부터 단조로운 증가 경향의 특징신호를 추출함을 알 수 있었다. 이를 입증하기 위해서 NASA Ames에서 제공한 IMS bearing 진 동 데이터를 이용하였고 제시한 특징신호와 일반적인 RMS와 의 거동을 비교하여 유효성을 검증하였다.

키워드
베어링
고장 예지 및 건전성 관리
특징신호 추출
상관계수
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Information
  • Publisher :Computational Structural Engineering Institute of Korea
  • Publisher(Ko) :한국전산구조공학회
  • Journal Title :Journal of the Computational Structural Engineering Institute of Korea
  • Journal Title(Ko) :한국전산구조공학회 논문집
  • Volume : 31
  • No :1
  • Pages :63-69
  • Received Date : 2018-01-03
  • Revised Date : 2018-01-09
  • Accepted Date : 2018-01-10
  • DOI :https://doi.org/10.7734/COSEIK.2018.31.1.63
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