利用振动响应协方差参数和数据融合的损伤识别方法

使用结构加速度响应协方差和应变响应协方差参数以及基于贝叶斯估计的数据融合理论进行结构损伤判定和损伤位置识别,理论推导证明响应协方差参数是结构模态参数的函数,结构损伤会导致响应协方差参数的改变,当只使用结构损伤前后的响应协方差参数,不使用结构分析模型进行结构损伤识别时,损伤向量会受到激励位置、测试噪声和误差等的影响,所以使用贝叶斯数据融合理论,对来自多种传感器和多种测试环境下得到的多组损伤向量进行数据融合,以提高损伤识别的精度;利用一个七层框架结构进行包括单损伤和多损伤的多种损伤工况的数值模拟,研究所提方法的适用性和有效性,最后对简支钢梁进行实验验证,损伤位置附近的传感器所得到的损伤指标具有最大的损伤概率。

Adoption of vibration response covariance and data fusion for damage identification

It has important theory worth and realistic meaning to perform health monitoring for the in-service civil engineering structure and the infrastructure,in order to discover the damage as early as possible,the feasible preventing and repairing measure will be applied in time.Acceleration and strain response covariance and the Bayesian data fusion technique are used for damage occurrence and damage location identification.From the derivation,the response covariance is the function of modal parameters.Structural damage(stiffness reduction)will lead to the change of the response covariance.When damage detection is based on the change of the response covariance between the damaged and intact structural states without the need of an analytical model,the damage vector will be easily affected by excitation location,measurement noise and so on.In order to improve the results,Bayesian fusion is applied to all damage vectors from different kinds of sensors and many measurements under different environments.A seven-floor frame structure is numerically studied with several damage scenarios,which include single and multiple damages,to demonstrate the applicability and availability of the proposed method.Finally,a simply supported steel beam is tested in the lab to verify the method experimentally.The satisfactory results are obtained.The analysis shows that the proposed method is sensitive to structural damage and robust to noise,and is promising for engineering structures.