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Optimization algorithms for ultrasonic array imaging in homogeneous anisotropic steel components with unknown properties

机译:具有未知特性的均匀各向异性钢结构超声阵列成像的优化算法

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In this paper, we investigate the ability of an adaptive ultrasonic method to image point-like reflectors inside anisotropic and homogeneous nuclear steels with unknown properties, such as V-shape welds or cladded components. The optimization scheme combines the Total Focusing Method (TFM) imaging algorithm with a customized gradient ascent method to improve both the quality and the reliability of ultrasound images. A statistical analysis of its robustness is performed with simulated echoes and using a surrogate model to speed up the computation times of the TFM images. Then, the optimization procedure is evaluated with several experimental cases and provides highly enhanced images with a 5 MHz array. The positioning of the artificial defects of 2.0 mm diameter is estimated with less than 1 mm error with respect to their actual position, and the signal-to-noise ratio is increased by up to 10 dB. The elastic properties are also estimated with less than 10% error when compared to their actual values.
机译:在本文中,我们研究了自适应超声波方法对具有未知特性的各向异性和均匀核钢内的图像点状反射器的能力,例如V形焊缝或包覆部件。优化方案将总对焦方法(TFM)成像算法与定制的梯度上升法相结合,以提高超声图像的质量和可靠性。利用模拟回波和使用代理模型来加快TFM图像的计算时间来执行其鲁棒性的统计分析。然后,使用若干实验情况进行评估优化过程,并提供具有5 MHz阵列的高度增强的图像。在其实际位置的误差小于1mm误差,估计了2.0mm直径的人工缺陷的定位,并且信噪比增加到10 dB。与实际值相比,弹性特性也估计小于10%的误差。

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