Session Track
November 01 (Wednesday)
일반기계 및 부품 신뢰성(I)
Oral,
제9발표장(303A호),
14:40~15:40
- 이승표((주)일진글로벌)
We09B-3
14:40~15:40
상관계수 가중치를 이용한 베어링 예측 특징신호 추출
Bearing is an essential mechanical component in 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). Key issues in bearing PHM is to establish a proper health indicator (HI) 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. This paper proposes a feature extraction method using traditional envelope analysis and weighted sum with correlation coefficient. The developed methods are demonstrated using IMS bearing data from NASA Ames Prognostics Data Repository. In the end, proposed feature is compared with traditional time-domain features.
Keywords : Bearing(베어링), Prognostics and Health Management(PHM), Feature(특징신호), Health indicator(건전성 지수), Correlation coefficient(상관계수)
Paper : We09B-3.pdf
(사)대한기계학회, 서울시 강남구 테헤란로 7길 22 한국과학기술회관 신관 702호, Tel: (02)501-3646~3648, E-mail: ksme@ksme.or.kr