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Research on Dynamic Load Identification Based on Explicit Wilson-θ and Improved Regularization Algorithm

机译:基于显式Wilson-θ的动态载荷识别及改进正则化算法研究

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摘要

In the research of dynamic load identification, the method of obtaining kernel function matrix is usually rather cumbersome. To solve this problem, an explicit dynamic load identification algorithm based on the Wilson-θ (DLIAEW) method is proposed to easily obtain the kernel function matrix as long as the parameters of the system are known. To aim at the ill-posed problem in the inverse problem, this paper improves the Tikhonov regularization, proposes an improved regularization algorithm (IRA), and introduces the U-curve method to determine the regularization parameters. In the numeric simulation investigation of a four dofs vibrating system, effects of the sampling frequency and the noise level on the regularization parameters and the identification errors of impact and harmonic loads for the IRA are discussed in comparison with the Tikhonov regularization. Finally, the experiments of a cantilever beam excited by impact and harmonic loads are carried out to verify the advantages of the IRA.
机译:在动态载荷识别的研究中,获得核函数矩阵的方法通常相当繁琐。为了解决这个问题,提出了一种基于Wilson-θ(Dliaew)方法的显式动态载荷识别算法,只要系统的参数都是已知的参数,就容易获得内核函数矩阵。为了瞄准逆问题中的不良问题,本文提高了Tikhonov正规化,提出了一种改进的正则化算法(IRA),并介绍了U形曲线方法来确定正则化参数。在四个DOF振动系统的数值模拟调查中,与Tikhonov规则化相比,讨论了采样频率的效果和正则化参数上的噪声水平和IRA的冲击和谐波的识别误差。最后,通过冲击和谐波膨胀激发的悬臂梁的实验来验证IRA的优点。

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