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兰州交通大学 机电工程学院,兰州 730070
高可乐,男,2000年生,甘肃会宁人,硕士研究生;主要研究方向为动力响应重构研究;E-mail:3124857137@qq.com。
彭珍瑞(通信作者),男,1972年生,甘肃民勤人,教授,博士研究生导师;主要研究方向为结构动力学与模态分析;E-mail:pzrui@163.com。
收稿日期:2023-09-26,
修回日期:2024-01-02,
纸质出版日期:2025-06-15
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高可乐,殷红,彭珍瑞. 改进Tikhonov正则化方法的载荷识别与结构响应重构[J]. 机械强度,2025,47(6):99-105.
GAO Kele,YIN Hong,PENG Zhenrui. Improved Tikhonov regularization method for load identification and structural response reconstruction[J]. Journal of Mechanical Strength,2025,47(6):99-105.
高可乐,殷红,彭珍瑞. 改进Tikhonov正则化方法的载荷识别与结构响应重构[J]. 机械强度,2025,47(6):99-105. DOI: 10.16579/j.issn.1001.9669.2025.06.012.
GAO Kele,YIN Hong,PENG Zhenrui. Improved Tikhonov regularization method for load identification and structural response reconstruction[J]. Journal of Mechanical Strength,2025,47(6):99-105. DOI: 10.16579/j.issn.1001.9669.2025.06.012.
为提高载荷识别与结构响应重构的精度及效率,提出了一种同时考虑传递矩阵误差和测量误差的改进Tikhonov正则化方法。首先,通过结构动力学模型构建状态空间方程和传递矩阵,得到结构载荷和响应的重构方程;其次,利用截断随机奇异值分解方法计算测点位置的近似传递矩阵,同时结合总体最小二乘法(Total Least Squares Method
TLSM)和传统Tikhonov正则化方法识别载荷,再通过待重构位置的传递矩阵重构未知响应;最后,分别对二维桁架和简支梁进行数值仿真和试验分析,验证所提方法的有效性。结果表明,相较于传统Tikhonov正则化方法,所提方法可在保证重构精度的同时提升重构效率。
To improve the accuracy and efficiency of load identification and structural response reconstruction
an improved Tikhonov regularization method that simultaneously considers transfer matrix error and measurement error was proposed. Firstly
the state space equation and transfer matrix were constructed through the structural dynamics model to obtain the reconstruction equation of the structural load and response. Secondly
the truncated randomized singular value decomposition method was used to calculate the approximate transfer matrix at the locations of the measurement points
while the total least squares method (TLSM) and the traditional Tikhonov regularization method were combined to identify the load
and then the unknown response was reconstructed by the transfer matrix at the locations. Finally
a numerical simulation and an experimental analysis were carried out for two-dimensional truss and simply supported beam to verify the proposed method. The results show that compared with the traditional Tikhonov regularization method
the proposed method can improve the reconstruction efficiency while guaranteeing the reconstruction accuracy.
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