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.