Moskovchenko Alexey I, Švantner Michal, Vavilov Vladimir P, Chulkov Arsenii O
New Technologies Research Centre, University of West Bohemia, Univerzitní St. 2732/8, 301 00 Plzeň, Czech Republic.
Engineering School of Nondestructive Testing, Tomsk Polytechnic University, 30 Lenin Avenue, 634050 Tomsk, Russia.
Materials (Basel). 2021 Apr 10;14(8):1886. doi: 10.3390/ma14081886.
This study is focused on the quantitative estimation of defect depth by applying pulsed thermal nondestructive testing. The majority of known defect characterization techniques are based on 1D heat conduction solutions, thus being inappropriate for evaluating defects with low aspect ratios. A novel method for estimating defect depth is proposed by taking into account the phenomenon of 3D heat diffusion, finite lateral size of defects and the thermal reflection coefficient at the boundary between a host material and defects. The method is based on the combination of a known analytical model and a non-linear fitting (NLF) procedure. The algorithm was verified both numerically and experimentally on 3D-printed polylactic acid plastic samples. The accuracy of depth prediction using the proposed method was compared with the reference characterization technique based on thermographic signal reconstruction to demonstrate the efficiency of the proposed NLF method.
本研究聚焦于通过应用脉冲热无损检测对缺陷深度进行定量估计。大多数已知的缺陷表征技术基于一维热传导解，因此不适用于评估低纵横比的缺陷。考虑到三维热扩散现象、缺陷的有限横向尺寸以及基体材料与缺陷之间边界处的热反射系数，提出了一种估计缺陷深度的新方法。该方法基于一个已知的解析模型与非线性拟合（NLF）程序的结合。该算法在三维打印的聚乳酸塑料样品上进行了数值和实验验证。将所提方法的深度预测精度与基于热成像信号重建的参考表征技术进行比较，以证明所提NLF方法的有效性。
