基于压缩频响函数的结构损伤识别

结构的损伤识别可作为一个优化问题来处理。本文直接应用频响函数(FRF)进行结构的损伤识别。通过对FRF的主成分分析(PCA)实现数据压缩和特征提取,建立基于压缩FRF的优化目标函数。为了提高算法的收敛速度,以结合局部搜索算法(LS)的遗传算法(GA)为优化工具,并进一步结合子结构识别法来求解。基于桁架的计算结果表明,这种方法具有很好的鲁棒性和识别效果。

Structural Damage Detection Based on Compressed Frequency Response Function(FRF)

The structural damage detection can be taken as an optimization problem. In this paper, the FRFs are used directly for the damage detection. The optimization function is based on compressed FRF data, by applying data reduction and feature extraction techniques based on principal component analysis (PCA). In order to improve the efficiency of computing, genetic algorithm(GA) with a compatible local search algorithm is proposed, and substructural identification is also used here. A numerical example on a truss shows excellent robustness with measurement errors and identification precision.