应用数学和力学（英文版）
應用數學和力學（英文版）
응용수학화역학（영문판）
APPLIED MATHEMATICS AND MECHANICS(ENGLISH EDITION)
2005年
1期
44-51
,共8页
唐和生%薛松涛%陈镕%王远功
唐和生%薛鬆濤%陳镕%王遠功
당화생%설송도%진용%왕원공
damage detection%neural network%combined parameter%flexibility
The relative sensitivities of structural dynamical parameters were analyzed using a directive derivation method. The neural network is able to approximate arbitrary nonlinear mapping relationship, so it is a powerful damage identification tool for unknown systems. A neural network-based approach was presented for the structural damage detection. The combined parameters were presented as the input vector of the neural network, which computed with the change rates of the several former natural frequencies (C), the change ratios of the frequencies (R), and the assurance criterions of flexibilities ( A ). Some numerical simulation examples, such as, cantilever and truss with different damage extends and different damage locations were analyzed. The results indicate that the combined parameters are more suitable for the input patterns of neural networks than the other parameters alone.
