基于混合正则化方法的结构载荷识别与响应重构

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Abstract To identify the load and reconstruct the unknown response using the acceleration response of the finite structural measurement points, a hybrid regularization method combining the least square minimal residual algorithm and Tikhonov regularization method is proposed to solve the ill-posedness of load identification and response reconstruction of structures. Firstly, the transfer matrix of the structure is constructed based on the time-domain state-space model, and the load identification and response reconstruction equations are established. Secondly, the hybrid regularization method is used to improve the ill-posedness of the load identification, and the regular solution of the load is obtained. The displacement, velocity and acceleration responses of the structure are reconstructed by combining the transfer matrix of the response reconstruction equation. Finally, the proposed method is verified by numerical simulation and experimental analysis of simply supported beams. The results show that the proposed method can improve the ill-posedness of the reconstruction equation and effectively reconstruct the unknown load and various types of response of the structure.

Key words： load identification response reconstruction ill-posedness transfer matrix hybrid regularization

Received: 26 April 2023 Published: 28 March 2024

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	PENG Zhenrui
	ZHOU Xuewen

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PENG Zhenrui,ZHOU Xuewen. Structural load identification and response reconstruction based on a hybrid regularization method[J]. JOURNAL OF VIBRATION AND SHOCK, 2024, 43(6): 104-112.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2024/V43/I6/104

[1] Liu R X, Hou Z C, Wu P B, et al. Dynamic load identification for a power battery pack based on a combined regularization algorithm[J]. Journal of Sound and Vibration, 2022, 529: 116928. [2] 张笑华, 肖兴勇, 方圣恩. 面向桥梁结构健康监测的压缩感知动力响应信号重构[J]. 振动工程学报, 2022, 35(3): 699-706. Zhang Xiao-hua, Xiao Xing-yong, Fang Shen-en. Dynamic response reconstruction for bridge structural health monitoring based on compressed sensing[J]. Journal of Vibration Engineering, 2022, 35(3): 699-706. [3] Zhang C D, Xu Y L. Structural damage identification via response reconstruction under unknown excitation[J]. Structural Control and Health Monitoring, 2016, 24(8): 1953.1-1953.11. [4] 李惠, 鲍跃全, 李顺龙, 等. 结构健康监测数据科学与工程[J]. 工程力学, 2015, 32(8): 1-7. LI Hui, BAO Yue-quan, LI Shun-long, et al. Data science and engineering for structural health monitoring[J]. Engineering Mechanics, 2015, 32(8): 1-7. [5] Yun H H, Kim H K, Lee H S. Reconstruction of dynamic displacement and velocity from measured accelerations using the variational statement of an inverse problem[J]. Journal of Sound and Vibration, 2010, 329(23): 4980-5003. [6] Zhang C D, Xu Y L. Optimal multi-type sensor placement for response and excitation reconstruction[J]. Journal of Sound and Vibration, 2016, 360: 112-128. [7] 张笑华, 周海洋, 吴志彪. 子结构传感器位置优化和响应重构[J]. 振动与冲击, 2020, 39(6): 257-262+270. Zhang Xiao-hua, Zhou Hai-yang, Wu Zhi-biao. Sensor location selection and response reconstruction of a substructure[J]. Journal of Vibration and Shock, 2020, 39(6): 257-262+270. [8] 董康立, 殷红, 彭珍瑞. 面向多类型传感器优化布置的结构响应重构[J]. 控制理论与应用, 2018, 35(9): 1339-1346. Dong Kang-li, Yin Hong, Peng Zhen-rui. Structural response reconstruction oriented to optimal multi-type sensor placement[J]. Control Theory and Applications, 2018, 35(9): 1339-1346. [9] He J J, Guan X F, Liu Y M. Structural response reconstruction based on empirical mode decomposition in time domain[J]. Mechanical Systems and Signal Processing, 2012, 28: 348-366. [10] Wan Z M, Li S D, Huang Q B, et al. Structural response reconstruction based on the modal superposition method in the presence of closely spaced modes[J]. Mechanical Systems and Signal Processing, 2014, 42(1-2): 14-30. [11] 王娟, 杨庆山. 基于状态空间的时域动态响应重构方法[J]. 建筑结构学报, 2016, 37(S1): 460-466. Wang Juan, Yang Qing-shan. Dynamic response reconstruction method in time domain based on state space[J]. Journal of Building Structures, 2016, 37(S1): 460-466. [12] Zhang S X, Wang Z Y, Jian Z K, et al. A two-step method for beam bridge damage identification based on strain response reconstruction and statistical theory[J]. Measurement Science and Technology, 2020, 31(7): 075008. [13] Liu J, Li B. A novel strategy for response and force reconstruction under impact excitation[J]. Journal of Mechanical Science and Technology, 2018, 32(8): 3581-3596. [14] Li Y X, Wang X Y, Xia Y. Sparse Bayesian technique for load identification and full response reconstruction[J]. Journal of Sound and Vibration, 2023, 553: 117669. [15] 马超, 华宏星. 基于改进正则化方法的状态空间载荷识别技术[J]. 振动与冲击, 2015, 34(11): 146-149. Ma Chao, Hua Hong-xing. State space load identification technique based on an improve regularized method[J]. Journal of Vibration and Shock, 2015, 34(11): 146-149. [16] Zhen C, Chan T. A truncated generalized singular value decomposition algorithm for moving force identification with ill-posed problems[J]. Journal of Sound and Vibration, 2017, 401: 297-310. [17] Bai X, Huang G X, Lei X J, et al. A novel modified TRSVD method for large-scale linear discrete ill-posed problems[J]. Applied Numerical Mathematics, 2021, 164: 72-88. [18] Jiang J, Ding M, Li J. A novel time-domain dynamic load identification numerical algorithm for continuous systems[J]. Mechanical Systems and Signal Processing, 2021, 160: 107881. [19] 郭荣, 房怀庆, 裘剡, 等. 基于Tikhonov正则化及奇异值分解的载荷识别方法[J]. 振动与冲击, 2014, 33(6): 53-58. Guo Rong, Fang Huai-qing, Qiu Shan, et al. Novel load identification method based on the combination of Tikhonov regularization and singular value decomposition[J]. Journal of Vibration and Shock, 2014, 33(6): 53-58. [20] 肖悦, 陈剑, 李家柱, 等. 动态载荷时域识别的联合去噪修正和正则化预优迭代方法[J]. 振动工程学报, 2013, 26(6): 854-863. Xiao Yue, Chen Jian, Li Jia-zhu, et al. A joint method of denoising correction and regularization preconditioned iteration for dynamic load identification in time domain[J]. Journal of Vibration Engineering, 2013, 26(6): 854-863. [21] Wang L J, Cao H P, Xie Y X. An improved iterative Tikhonov regularization method for solving the dynamic load identification problem[J]. International Journal for Computational Methods in Engineering Science and Mechanics, 2015, 16(5): 292-300. [22] Fong D, Saunders M. LSMR: An iterative algorithm for sparse least-squares problems[J]. Society for Industrial and Applied Mathematics Journal on Scientific Computing, 2011, 33(5): 2950-2971. [23] Li H K, Liu B, Huang W, et al. Vibration load identification in the time-domain of high arch dam under discharge excitation based on hybrid LSQR algorithm[J]. Mechanical Systems and Signal Processing, 2022, 177: 109193. [24] Rezaiee‐Pajand M, Entezami A, Sarmadi H. A sensitivity‐based finite element model updating based on unconstrained optimization problem and regularized solution methods[J]. Structural Control and Health Monitoring, 2020, 27(5): e2481.1-e2481.29. [25] Rezaiee-Pajand M, Sarmadi H, Entezami A. A hybrid sensitivity function and Lanczos bidiagonalization-Tikhonov method for structural model updating: Application to a full-scale bridge structure[J]. Applied Mathematical Modelling, 2021, 89(1): 860-884. [26] Chung J L, Palmer K. A hybrid LSMR algorithm for large-scale Tikhonov regularization[J]. SIAM Journal on Scientific Computing, 2015, 37(5): 562-580.