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Design of de-noising FEM-FIR filters for the evaluation of temporal and spatial derivatives of measured displacement in elastic solids

机译:用于评估弹性固体中位移的时间和空间导数的去噪FEM-FIR滤波器的设计

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This paper presents an FEM-FIR filter de-noising measured displacement to estimate temporal and spatial derivatives of displacement in an elastic solid. The filter is formulated by two independent inverse problems, which are defined as the minimization of the difference between measured and de-noised displacement in the temporal and spatial domains. The regularization functions are introduced in the minimization problems to eliminate noise in measured displacement. The L-2-norm of the acceleration and the strain energy of an elastic solid are utilized as the regularization functions in the temporal and spatial domains, respectively, to impose the integrability of the temporal and spatial derivatives. The moving time-window technique is adopted in the temporal filter, and a usual finite element procedure is applied to discretize the minimization problems. The temporal and spatial filters are combined together to form a single, unified filter, which not only denoises measured displacement in both domains but also reconstructs the velocity field. The acceleration field is obtained by the 1st-order central finite difference of the reconstructed velocity field. The strain field is evaluated at the Gauss points of each finite element using the de-noised nodal displacement. The regularization factors, which control the degree of de-noising strength, are determined by the desired accuracy of the filters at the target frequency. It is shown through a numerical simulation study that the proposed filters are capable of de-noising measured displacement effectively and yielding accurate temporal and spatial derivatives. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文提出了一种FEM-FIR滤波器,对测得的位移进行消噪,以估计弹性固体中位移的时间和空间导数。该滤波器由两个独立的反问题构成,这两个反问题定义为在时域和空域中测量和去噪位移之间的差异最小。在最小化问题中引入了正则化函数,以消除测量的位移中的噪声。加速度的L-2-范数和弹性固体的应变能分别用作时间和空间域中的正则化函数,以施加时间和空间导数的可积性。在时间滤波器中采用了移动时间窗口技术,并采用通常的有限元程序来离散化最小化问题。将时间和空间滤波器组合在一起以形成单个统一的滤波器,该滤波器不仅在两个域中对测得的位移进行消噪,而且可以重建速度场。加速度场是通过重建速度场的一阶中心有限差分获得的。使用降噪的节点位移在每个有限元的高斯点评估应变场。控制降噪强度的正则化因子由目标频率下滤波器的期望精度确定。通过数值模拟研究表明,所提出的滤波器能够有效地对测得的位移进行消噪,并产生准确的时间和空间导数。 (C)2018 Elsevier Ltd.保留所有权利。

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