This work presents moving load identification on Euler-Bernoulli beams with viscoelastic boundary conditions based on beam acceleration responses. The Tikhonov regularization and generalized cross validation (GCV) methods are used to investigate the performances of different regularization matrices (L matrices) in terms of their effectiveness in reducing errors in load identification. The effects from noises, inaccurate parameters, arrangements of measurement locations, velocities, and spaces of moving loads are included in the investigations. Simulation results demonstrated that the viscoelastic boundary conditions could play an important role in the performance of these time domain moving load identifications. The use of a higher-order regularization matrix (L matrix) can efficiently reduce the relative errors of the identified loads. In these L matrices, the L₁ matrix could provide a compromised approach to reducing the relative errors more efficiently than higher-order L matrices such as L₂, L₃, and L₄.

这项工作提出了基于梁加速度响应的具有粘弹性边界条件的 Euler-Bernoulli 梁的移动载荷识别。Tikhonov 正则化和广义交叉验证 (GCV) 方法用于研究不同正则化矩阵 ( L矩阵) 在减少负载识别错误方面的性能。调查包括噪声、不准确参数、测量位置布置、速度和移动载荷空间的影响。仿真结果表明，粘弹性边界条件可以在这些时域移动载荷识别的性能中发挥重要作用。使用高阶正则化矩阵（L矩阵）可以有效地减少识别载荷的相对误差。在这些L矩阵中，L ₁矩阵可以提供一种折衷的方法来比高阶L矩阵（例如L ₂、L ₃和L _{4 ）}更有效地减少相对误差。