基于高频超声检测的焊接缺陷识别  

Welding defect identification based on high-frequency ultrasonic testing

作　　者：赵新玉[1] 姜德顺 李正光 张佳莹 ZHAO Xinyu;JIANG Deshun;LI ZhengGuang;ZHANG Jiaying(School of Material Science and Engineering,Dalian Jiaotong University,Dalian 116028,China;School of Software,Dalian University of Foreign Languages,Dalian 116044,China)

机构地区：[1]大连交通大学材料科学与工程学院,大连116028 [2]大连外国语大学软件学院,大连116044

出　　处：《无损检测》2023年第11期20-23,52,共5页Nondestructive Testing

基　　金：国家自然科学基金项目(51905070);辽宁省教育厅2021年度科学研究经费项目(LJKZ0492)。

摘　　要：空洞、分层是钎焊接头中常见的缺陷,其面积大小对钎焊接头的质量会产生很大影响。为了能够准确、高效地计算缺陷面积,提出了一种缺陷识别算法,对缺陷进行标记。首先采用超声显微检测技术对钎焊工件进行检测,生成超声C扫描图像;然后采用基于阈值的图像分割方法对C扫描图像进行二值化处理,最后利用缺陷识别算法标记缺陷和计算缺陷面积,提高了工件缺陷检测的准确率和效率。Cavity and delamination are common defects in brazed joints,and the quality of brazed joints was impacted by the area of defects.In order to calculate the defect area accurately and efficiently,the defect recognition algorithm was proposed to mark the defect.Firstly,ultrasonic microscopy system was used to detect the brazed workpiece and generate ultrasonic C-scan image.Then the C-scan image was binarized with the threshold-based image segmentation method.Finally,the defect was marked and the defect area was calculated using the proposed defect recognition algorithm.The accuracy and efficiency of defect detection was improved.

关 键 词：超声C扫描 钎焊 图像分割 面积计算 

分 类 号：TB553[理学—物理] TG115.28[理学—声学]