基于多角度相控阵数据集成的超声缺陷识别

IF 2 Q2 ENGINEERING, MULTIDISCIPLINARY
Wei Zhang, Xinyan Wang, Xuefei Guan
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引用次数: 1

摘要

提出了一种利用相控阵超声检测数据进行超声缺陷识别的方法。从相控阵超声检测的每个单独通道获得原始数据。数据修剪和去噪分别用于保留被检测对象边界内的数据和去除原始数据中的散斑噪声成分。结果数据被传递到一系列信号处理操作中,以识别嵌入的缺陷。提出了一种基于形状的滤波方法,以降低由于制造过程中引入的不均匀微结构而产生的几何噪声分量的强度。将得到的数据矩阵进行积分,得到可能缺陷区域的强度矩阵。对强度矩阵进行阈值分割,得到潜在缺陷区域,然后进行连通分量分析,识别缺陷。用实际相控阵实验数据对整个方法进行了论证和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ultrasonic Flaw Recognition by Multi-Angle Phased Array Data Integration
This study presents a method of ultrasonic flaw identification using phased array ultrasonic inspection data. Raw data from each individual channel of the phased array ultrasonic inspection are obtained. The data trimming and de-noising are employed to retain the data within the boundary of the inspected object and remove the speckle noise components from the raw data, respectively. The resulting data are passed into a sequence of signal processing operations to identify embedded flaws. A shape-based filtering method is proposed to reduce the intensity of geometric noise components due to the non-uniform microstructures introduced in the manufacturing process. The resulting data matrices are integrated to obtain the intensity matrix of the possible flaw regions. Thresholding is applied to the intensity matrix to obtain the potential flaw regions, followed by a connected component analysis to identify the flaws. The overall method is demonstrated and validated using realistic phased array experimental data.
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来源期刊
CiteScore
3.80
自引率
9.10%
发文量
25
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