基于递归分析的微裂纹缺陷超声检测技术研究

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振动与冲击 ›› 2020, Vol. 39 ›› Issue (10) : 154-162.

论文

冯玮，杨辰龙，边成亮，周晓军

作者信息 +

Research on microcrack defect ultrasonic detection technology based on recurrence analysis

FENG Wei,YANG Chenlong,BIAN Chengliang,ZHOU Xiaojun

Author information +

文章历史 +

摘要

为准确检测金属构件微裂纹缺陷，采用超声脉冲反射法对金属试块进行检测，并提取超声背散射信号进行分析。通过对背散射信号进行简单的建模，说明其组成要素。由于背散射信号的非线性特征，缺陷回波信号会对系统的递归特性产生影响；在此基础上提出了基于递归分析的方法分别对含人工微裂纹缺陷金属试块的无缺陷区、单裂纹区及双裂纹区背散射信号进行检测研究；通过合理的参数选择，对采样信号进行递归分析并绘制递归图；对比含缺陷信号与无缺陷信号，发现前者会在递归图中产生明显的白色交叉条纹带。使用递归定量分析进一步研究了含缺陷背散射信号的递归特征量。结果表明多种特征量对缺陷回波信号比较敏感，其中递归率（RR）和捕获时间（TT）在缺陷位置有明显的特征。

Abstract

In order to accurately detect microcrack defects of metallic materials, the ultrasonic pulse echo method was adopted to detect the aluminum alloy test block, and the extracted ultrasonic backscattering signal was analyzed.The components of the backscattering signal were illustrated by simple modeling.Due to the nonlinearity of the backscattering signal, the defect echo signal would affect the recurrence characteristics of the system.In this paper, a recurrence analysis method was proposed to detect the backscattering signals in the crack-free zone, single-crackzone and double-crack zone of the metallic test block with artificial microcrack defects.Through reasonable parameters selection, the sampling signal was analyzed recursively and the recurrence plot was drawn.Comparing the defect signal with the defect-free signal, it was found that the obvious white cross stripe appears in the recurrence plot of the former.The recurrence characteristic quantities of the backscattering signals with defects were further studied by using recurrence quantification analysis.The results show that some characteristic quantities are more sensitive to the defect echo signals.The recurrence rate (RR) and trapping time (TT) have obvious characteristics at the defect location.

导出引用

冯玮，杨辰龙，边成亮，周晓军 . 基于递归分析的微裂纹缺陷超声检测技术研究[J]. 振动与冲击, 2020, 39(10): 154-162

FENG Wei,YANG Chenlong,BIAN Chengliang,ZHOU Xiaojun. Research on microcrack defect ultrasonic detection technology based on recurrence analysis[J]. Journal of Vibration and Shock, 2020, 39(10): 154-162

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