The use of full-skip ultrasonic data and Bayesian inference for improved characterisation of crack-like defects
The use of full-skip ultrasonic data and Bayesian inference for improved characterisation of crack-like defects
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DOI：
10.1016/j.ndteint.2021.102467
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发表时间：
2021-05-21
影响因子：
4.2
通讯作者：
Drinkwater, Bruce W.
中科院分区：
文献类型：
--
作者：
Bai, Long;Zhang, Jie;Drinkwater, Bruce W.
在无损检测领域中，超声阵列常用于检测和消除裂纹类缺陷。超声散射矩阵包含缺陷的所有可测量的入射/散射角的远场散射系数。本文研究了在裂缝急剧倾斜的情况下使用散射矩阵来表征小裂缝的情况，这使得直接成像和分析具有挑战性。以及直接散射的信号，它是通过实验和模拟表明，额外的表征信息可以从全跳过射线路径中提取，并用于提高表征性能。与最近邻法相比，对于1.5mm、45 °粗糙裂纹，采用基于贝叶斯推理的统计建模方法，裂纹尺寸和角度的平均误差分别可降低12.1%和17.1%。
Ultrasonic arrays are often used to detect and characterise crack-like defects in the field of non-destructive testing. The ultrasonic scattering matrix contains the far-field scattering coefficients of a defect for all measurable incident/scattering angles. This paper investigates the use of the scattering matrix for characterisation of small cracks in scenarios when the crack is steeply inclined, making direct imaging and analysis challenging. As well as the directly scattered signals, it is shown through experiments and simulations that additional characterisation information can be extracted from the full-skip ray path and used for improving the characterisation performance. Compared to the nearest neighbour approach, the mean errors of crack size and angle can be reduced by 12.1% and 17.1%, respectively, for 1.5 mm, 45 degrees rough cracks by using a statistical modelling approach based on Bayesian inference.