变厚度CFRP超声缺陷自动成像的相关性算法研究

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振动与冲击 ›› 2024, Vol. 43 ›› Issue (12) : 232-240.

论文

变厚度CFRP超声缺陷自动成像的相关性算法研究

王涛1，邓婉欣2，王海军3，俞慈君1

作者信息 +

A study on correlation-based algorithms for automatic imaging of variable thickness CFRP ultrasonic defects

WANG Tao1,DENG Wanxin2,WANG Haijun3,YU Cijun1

Author information +

文章历史 +

摘要

针对变厚度碳纤维增强聚合物复合材料（carbon fiber reinforced polymer,CFRP）超声缺陷成像工序繁琐的问题，提出了一种基于相关性的自动成像算法。实验预埋夹杂缺陷，使用超声相控阵检测获取数据，首先依据离散序列互相关理论，对不同厚度CFRP的超声A扫描信号进行底波时移处理，之后利用自相关理论从无缺陷区域生成必要的参考信号。通过相关计算结果，利用欧氏距离区分缺陷信号和非缺陷信号，并依据欧式距离进行颜色编码绘图。最后通过基于机器视觉以及Hough圆变换的边缘检测算法来对缺陷尺寸进行统计测量，总体均值误差率小于7%，最大误差率为16.25%，最小误差率为0.25%。结果表明该算法可广泛应用于变厚度CFRP自动化超声检测。

Abstract

A correlation-based automatic imaging algorithm is proposed to address the labor-intensive process of variable thickness CFRP ultrasonic defect imaging. Embedded artificial defects are prepared in the specimens, and ultrasonic phased array detection is used to acquire data. Firstly, based on the theory of discrete sequence correlation, time-shift processing is applied to the ultrasonic A-scan signals of different thickness CFRP specimens to align the baseline. Subsequently, the necessary reference signals are generated from defect-free regions using autocorrelation theory. By analyzing the correlation results and utilizing the Euclidean distance, defect signals are distinguished from non-defect signals, and a color-coded image is generated based on the Euclidean distances. Ultimately, the defect size was statistically measured using an edge detection algorithm based on machine vision and the Hough circle transform. The overall mean error rate was less than 7%, with a maximum error rate of 16.25% and a minimum error rate of 0.25%. The results demonstrate that this algorithm can be extensively applied to the automated ultrasonic testing of variable thickness CFRP.

导出引用

王涛1, 邓婉欣2, 王海军3, 俞慈君1. 变厚度CFRP超声缺陷自动成像的相关性算法研究[J]. 振动与冲击, 2024, 43(12): 232-240

WANG Tao1, DENG Wanxin2, WANG Haijun3, YU Cijun1. A study on correlation-based algorithms for automatic imaging of variable thickness CFRP ultrasonic defects[J]. Journal of Vibration and Shock, 2024, 43(12): 232-240

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