- 인공신경망 기법과 유전자 기법을 혼합한 결함인식 연구
- ㆍ 저자명
- 서명원,심문보,Suh. Myung-Won,Shim. Mun-Bo
- ㆍ 간행물명
- 한국정밀공학회지
- ㆍ 권/호정보
- 1999년|16권 11호|pp.158-165 (8 pages)
- ㆍ 발행정보
- 한국정밀공학회
- ㆍ 파일정보
- 정기간행물| PDF텍스트
- ㆍ 주제분야
- 기타
It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses hybrid neuro-genetic technique. Feed-forward multilayer neural networks trained by back-propagation are used to learn the input)the location and dept of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this neural network and genetic algorithm, it is possible to formulate the inverse problem. Neural network training algorithm is the back propagation algorithm with the momentum method to attain stable convergence in the training process and with the adaptive learning rate method to speed up convergence. Finally, genetic algorithm is used to fine the minimum square error.