Zhang HongJie, Sun Qigang, Li DanYu, Li Chen, He Chunhui, Liu Gang
Power Transmission and Transformation Engineering Department, China Electric Power Research Institute, Beijing, 100192, China.
Economic and Technology Research Institute, State Grid Shandong Electric Power Company, Jinan, 250021, China.
Sci Rep. 2024 Jul 13;14(1):16207. doi: 10.1038/s41598-024-67241-0.
A method based on Gabor spectral mode transmissibility functions (GSMTFs) is proposed to detect local damage in a cantilevered structure under nonstationary ambient excitations. Gabor transformation and singular value decomposition are used to reduce the influences of other vibration modes on Gabor spectral mode transmissibility functions and process nonstationary structural responses, respectively. A new state characteristic based on the fundamental structure frequency is formulated on the basis of the GSMTFs, eventually leading to the development of a new damage indicator. The probability density functions of the damage indicator for healthy and damaged states can be estimated from the measured data, and the receiver operating characteristic (ROC) curve derived from these probability distributions and the corresponding area under the ROC curve (AUC) are used to determine the damage location. A six-degree-of-freedom system and a typical transmission tower are numerically studied, and the results show that the proposed method can estimate the structural damage location under nonstationary random loads. The proposed method is further validated with a planar frame in the laboratory, which exhibits multiple damage elements via random force hammer excitations. The results show that the AUC values computed for certain parts of the structure containing the damaged elements are greater than those for other parts of the structure, indicating the effectiveness of the proposed method. Moreover, the proposed method is compared with the dot product difference (DPD) index, and the results from the laboratory planar frame demonstrate that the proposed method can better identify damage.
提出了一种基于伽柏谱模态传递函数（GSMTFs）的方法，用于检测非平稳环境激励下悬臂结构中的局部损伤。伽柏变换和奇异值分解分别用于减少其他振动模态对伽柏谱模态传递函数的影响以及处理非平稳结构响应。基于GSMTFs建立了一种基于结构基频的新状态特征，最终开发出一种新的损伤指标。可以从测量数据中估计健康状态和损伤状态下损伤指标的概率密度函数，并使用从这些概率分布导出的接收者操作特征（ROC）曲线以及ROC曲线下的相应面积（AUC）来确定损伤位置。对一个六自由度系统和一个典型输电塔进行了数值研究，结果表明所提出的方法能够估计非平稳随机载荷作用下的结构损伤位置。通过实验室中的平面框架对所提出的方法进行了进一步验证，该平面框架通过随机力锤激励展示了多个损伤元件。结果表明，对于包含损伤元件的结构某些部分计算得到的AUC值大于结构其他部分的AUC值，表明所提出方法的有效性。此外，将所提出的方法与点积差（DPD）指标进行了比较，实验室平面框架的结果表明所提出的方法能够更好地识别损伤。
