Structural damage detection based on cross-correlation function with data fusion of various dynamic measurements

作     者：Wang, Xiaojuan Chen, Feng Zhou, Hongyuan Ni, Pinghe Wang, Lihui Zhang, Jian 

作者机构：Beijing Univ Technol Key Lab Urban Secur & Disaster Engn Minist Educ Beijing 100124 Peoples R China Beijing Inst Technol State Key Lab Explos Sci & Technol Beijing 100081 Peoples R China Jiangsu Univ Dept Mech & Engn Sci Zhenjiang 212013 Peoples R China 

出 版 物：《JOURNAL OF SOUND AND VIBRATION》 (J Sound Vib)

年 卷 期：2022年第541卷

核心收录：

学科分类：07[理学] 082403[工学-水声工程] 08[工学] 070206[理学-声学] 0802[工学-机械工程] 0824[工学-船舶与海洋工程] 0801[工学-力学（可授工学、理学学位）] 0702[理学-物理学] 

基　　金：National Natural Science Foundation of China (NSFC) [52178096, 51808017, 51778028] National Key Research and Development Project [2019YFD1101005] open project of the State Key Laboratory of Explosion Science and Technology (Beijing Institute of Technology) [KFJJ20-02M] 

主　　题：Structural damage detection Multiple unknown ambient excitations Cross -correlation function Data fusion Intelligent optimization algorithm 

摘      要：To take advantage of various types of dynamic measurement data for structural damage detection, an identification strategy based on cross-correlation function with data fusion of various dynamic measurements was proposed to improve the accuracy of damage identification in the present study. First of all, the cross-correlation functions among the easily acquired strain, acceleration, and displacement responses were theoretically derived when the structure was subjected to ambient excitations. Furthermore, an identification strategy was proposed for structural damage detection with the objective function of minimizing the difference between the measured and computed cross-correlation function under multiple unknown ambient excitations. In the proposed strategy, four optimization methods, namely, gradient search, genetic algorithm, particle swarm optimization, and the hybrid method of particle optimization method and gradient search were applied as the search engine to identify structural unknown damage index. Moreover, the performance of the proposed identification strategy was examined by the numerical studies on a two-dimensional and a three-dimensional truss as well as the experimental study on a cantilever beam. These results showed that the cross-correlation function among different types of vibration measurements could significantly improve the accuracy of the identification results, meanwhile, the proposed strategy exhibited excellent robustness to the measurement noise. In addition, the performance of the proposed strategy with different combinations of vibration data and the influence of reference data on the accuracy of damage identification results were further investigated.