在载荷识别研究中，为克服不适定问题，提出分两步降低传递函数的病态性以及削弱噪声的影响.首先，依据传递函数的条件数通过理论计算获得结构响应的最佳测点组合，并得出病态程度最低的传递函数矩阵；然后，采取Tikhonov正则化方法反演输入载荷，在反演过程中引入B样条函数对L曲线进行插值，以获得更加精确的正则化参数.仿真结果表明：该方法能够有效减小载荷识别的误差，识别出更加准确的载荷时间历程.
To solve the ill-posed problem, a two-step ideology is proposed to reduce the ill condition of transmissibility function and weaken the influence of noise in force identification research. First, the optimal combination of measurement points is calculated based on the conditional number theory of transfer function, and a transfer function matrix with the lowest degree of ill condition is obtained. Then, Tikhonov regularization is adopted to identify input excitation. In the procedure mentioned above, B-spline function is introduced to interpolate L-curve to acquire more exact regularization parameters. Simulation results show that the method proposed is able to effectively reduce force identification error and achieve a more accurate force time history.
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