- HMM/ANN복합 모델을 이용한 회전 블레이드의 결함 진단
- ㆍ 저자명
- 김종수,유홍희,Kim. Jong Su,Yoo. Hong Hee
- ㆍ 간행물명
- 한국소음진동공학회논문집
- ㆍ 권/호정보
- 2013년|23권 9호|pp.814-822 (9 pages)
- ㆍ 발행정보
- 한국소음진동공학회
- ㆍ 파일정보
- 정기간행물| PDF텍스트
- ㆍ 주제분야
- 기타
For the fault diagnosis of a mechanical system, pattern recognition methods have being used frequently in recent research. Hidden Markov model(HMM) and artificial neural network(ANN) are typical examples of pattern recognition methods employed for the fault diagnosis of a mechanical system. In this paper, a hybrid method that combines HMM and ANN for the fault diagnosis of a mechanical system is introduced. A rotating blade which is used for a wind turbine is employed for the fault diagnosis. Using the HMM/ANN hybrid model along with the numerical model of the rotating blade, the location and depth of a crack as well as its presence are identified. Also the effect of signal to noise ratio, crack location and crack size on the success rate of the identification is investigated.