- SVM과 신경회로망을 이용한 비선형시스템의 고장감지와 분류방법 연구
- ㆍ 저자명
- 이인수,조정환,서해문,남윤석,Lee. In-Soo,Cho. Jung-Hwan,Seo. Hae-Moon,Nam. Yoon-Seok
- ㆍ 간행물명
- 제어·로봇·시스템학회 논문지
- ㆍ 권/호정보
- 2012년|18권 6호|pp.540-545 (6 pages)
- ㆍ 발행정보
- 제어로봇시스템학회
- ㆍ 파일정보
- 정기간행물| PDF텍스트
- ㆍ 주제분야
- 기타
In this paper, we propose a fault diagnosis method using artificial neural network and SVM (Support Vector Machine) to detect and isolate faults in the nonlinear systems. The proposed algorithm consists of two main parts: fault detection through threshold testing using a artificial neural network and fault isolation by SVM fault classifier. In the proposed method a fault is detected when the errors between the actual system output and the artificial neural network nominal system output cross a predetermined threshold. Once a fault in the nonlinear system is detected the SVM fault classifier isolates the fault. The computer simulation results demonstrate the effectiveness of the proposed SVM and artificial neural network based fault diagnosis method.