Robust structural damage detection and localization based on joint approximate diagonalization technique in frequency domain
Robust structural damage detection and localization based on joint approximate diagonalization technique in frequency domain
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DOI：
10.1088/0964-1726/26/1/015005
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发表时间：
2016
影响因子：
4.1
通讯作者：
S. Cao;H. Ouyang
中科院分区：
文献类型：
--
作者：
S. Cao;H. Ouyang
结构特征挠度形状(如振型和工作挠度形状)对梁式或板式结构的损伤非常敏感。然而，它们很容易受到测量噪声的影响，并可能导致不可接受的识别误差。为了提高基于随机激励振动响应的CDS损伤识别的精度和噪声稳健性，将联合近似对角化(JAD)技术和间隙平滑方法(GSM)相结合，形成了一种灵敏而稳健的损伤指数(DI)，它可以同时检测损伤的存在和定位。此外，该方法还可以应用于环境激励下结构的损伤识别。首先，研究了盲源分离的关键技术JAD方法，该方法同时对角化一组对应于某一固有频率附近频率的功率谱密度矩阵，以估计联合么正对角化器。该联合对角化器的列中含有主导CDS，利用识别出的不同固有频率附近的主导CDS，利用GSM进行损伤特征提取，提出了一种稳健的损伤识别指标。用含裂纹梁的数值算例和实验算例验证了基于JAD的CDS估计和所提出的DI的有效性和抗噪性。与常用的奇异值分解方法相比，利用JAD方法估计的优势CDS进行损伤识别具有更高的精度和较强的抗噪能力。
The structural characteristic deflection shapes (CDS’s) such as mode shapes and operational deflection shapes are highly sensitive to structural damage in beam- or plate-type structures. Nevertheless, they are vulnerable to measurement noise and could result in unacceptable identification errors. In order to increase the accuracy and noise robustness of damage identification based on CDS’s using vibration responses of random excitation, joint approximate diagonalization (JAD) technique and gapped smoothing method (GSM) are combined to form a sensitive and robust damage index (DI), which can simultaneously detect the existence of damage and localize its position. In addition, it is possible to apply this approach to damage identification of structures under ambient excitation. First, JAD method which is an essential technique of blind source separation is investigated to simultaneously diagonalize a set of power spectral density matrices corresponding to frequencies near a certain natural frequency to estimate a joint unitary diagonalizer. The columns of this joint diagonalizer contain dominant CDS’s. With the identified dominant CDS’s around different natural frequencies, GSM is used to extract damage features and a robust damage identification index is then proposed. Numerical and experimental examples of beams with cracks are used to verify the validity and noise robustness of JAD based CDS estimation and the proposed DI. Furthermore, damage identification using dominant CDS’s estimated by JAD method is demonstrated to be more accurate and noise robust than by the commonly used singular value decomposition method.