基于敏感性的结构损伤识别中的噪声分析

针对基于振动测试的结构损伤识别方法很容易受到环境噪声干扰的问题，提出了一种新的噪声分析方法，并结合Monte Carlo 数值模拟技术研究了测量噪声对基于敏感性的损伤识别方法的影响．与普遍采用的摄动法不同，提出的方法直接由敏感性矩阵的Moore-Penrose广义逆推导得出．该方法不仅使得噪声分析过程更简洁而有效，并且能同时分析频率和振型噪声对于识别结果的影响．针对3种常用的基于敏感性的损伤识别方法，通过一个单层门式框架的仿真研究，表明了所提出的噪声分析方法的正确性和有效性．

Noise Analysis for Sensitivity Based Structural Damage Detection

As vibration-based structural damage detection methods are easily affected by the environmental noise,a newly statistic-based noise analysis method was proposed together with Monte Carlo technique to investigate the influence of experimental noise of modal data on sensitivity-based damage detection methods.Different from the commonly used random perturbation technique,the proposed technique is deduced directly by Moore-Penrose generalized inverse of the sensitivity matrix,which does not only make the analysis process more efficient but also can analyze the influence of noise on both frequencies and mode shapes for three commonly used sensitivity-based damage detection methods in a similar way.A one-story portal frame is adopted to evaluate the efficiency of the proposed noise analysis technique.