Elastic Net Regularization in Lorentz force evaluation
Elastic Net Regularization in Lorentz force evaluation
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DOI：
10.1016/j.ndteint.2018.07.002
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发表时间：
2018-10-01
影响因子：
4.2
通讯作者：
Haueisen, J.
中科院分区：
文献类型：
--
作者：
Doelker, E. -M;Schmidt, R.;Haueisen, J.
洛仑兹力评估是一种无损评估方法，用于表征由导电材料层组成的样品中的亚表面缺陷。被调查的样品相对于永磁体的运动导致洛伦兹力，该洛伦兹力在存在缺陷的情况下被扰动。一个最小范数估计（MNE）与弹性网络正则化（ENR）相比，MNE与Tikhonov-Phillips正则化（TPR）的能力，以确定力扰动信号的缺陷属性。直径为5 mm，高度为2 mm的圆柱形缺陷在2，4和8 mm的深度进行检查。考虑有限元法和测量数据获得的模拟数据。ENR和TPR在2 mm和4 mm的深度处正确估计了模拟和测量数据的缺陷深度，而在8 mm处，只有ENR正确估计了深度。ENR和TPR的缺损尺寸略微高估。TPR在重建网格的边界处产生了额外的伪解。结果表明，在洛仑兹力的计算中，ENR比TPR更适用于MNE。
Lorentz force evaluation is a nondestructive evaluation method applied for the characterization of sub-surface defects in specimen consisting of layers of conducting material. The movement of a specimen under investigation relative to a permanent magnet leads to Lorentz forces that are perturbed in the presence of a defect. A minimum norm estimation (MNE) with Elastic Net Regularization (ENR) is compared to MNE with Tikhonov-Phillips-Regularization (TPR) regarding the ability to determine defect properties from force perturbation signals. A cylindrically shaped defect with diameter of 5 mm and height of 2 mm is examined at depths of 2, 4 and 8 mm. Simulated data obtained by the finite element method and measured data are considered. ENR and TPR estimated the defect depth correctly for simulation and measurement data at depths of 2 and 4 mm, while at 8 mm, only ENR estimated the depth correctly. The defect sizes were slightly overestimated for both ENR and TPR. TPR produced additional spurious solutions at the boundary of the reconstruction grid. We conclude that ENR is more suitable than TPR for MNE in Lorentz force evaluation.