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山东大学学报(工学版)

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基于特征提取和极值搜索的焊接缺陷检测算法

梁玮1,2,陶亮3,张光先1,李振华1   

  1. 1.山东大学控制科学与工程学院,山东 济南 250061; 2. 济南工程职业技术学院,山东 济南 250200;
    3. 山东建筑大学信息与电气工程学院,山东 济南 250101
  • 收稿日期:2014-01-08 出版日期:2014-06-20 发布日期:2014-01-08
  • 作者简介:梁玮(1980- ),女,山东济南人,博士研究生,主要研究方向为数字射线无损检测及优化算法. E-mail:dzhlw0918@126.com
  • 基金资助:
    山东省优秀中青年科学家科研奖励基金资助项目(BS2013DX045); 山东省高等学校科研计划资助项目(J13LG52); 山东建筑大学博士科研基金资助项目(XNBS1249)

Welding defect detection method based on feature extraction and extreme searching

LIANG Wei1,2, TAO Liang3, ZHANG Guangxian1, LI Zhenhua1   

  1. 1. School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China;
    2. Jinan Engineering Vocational Technical College, Jinan 250200, Shandong, China;
    3. School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, Shandong, China
  • Received:2014-01-08 Online:2014-06-20 Published:2014-01-08

摘要: 为快速提取金属熔化焊接缺陷位置,提出了一种基于灰度分布曲线特征的算法。首先,通过平板探测器获取焊缝的X射线透射数字图像;第二,针对数字图像随机噪声大、动态范围低的问题,采用时间域序列图像帧积分方法,计算最优的积分时间,降低图像噪声,强化焊缝缺陷特征细节;第三,平行于焊缝方向,计算并形成多组图像灰度值曲线,基于其二阶导数曲线分布规律提取焊缝图像;最后,在焊缝图像曲线中进行极值点搜索,若在曲线存在明显极大值点,则可以确定缺陷的大小和位置。试验结果表明,本算法具有较高的检测精度。

关键词: 无损检测, 缺陷检测, 焊缝分割, 极值搜索, 数字射线成像

Abstract: A location detecting algorithm of the welding defect based on the grayscale distribution curve feature was proposed. At first, the welding line X-ray digital image was acquired by the flat panel detector. Secondly, because the problem of large noise and low dynamic range is ubiquitous, the time domain image frame sequence integration method was adopted to reduce the image noise and enhance the defect detail. Then, the optimal integration time was calculated. Thirdly, the grayscale value curve was drawn parallel to the welding line direction. The welding line image was segmented on the basis of its second derivative curve. At last, extreme point was searched in the welding line image. The size and location were decided if obvious maximum value was existed. Experimental results proved the high accuracy.

Key words: non-destructive testing, defect detection, digital X-ray imaging, welding line segmentation, extreme searching

[1] 方昊,李云. 基于多次随机欠采样和POSS方法的软件缺陷检测[J]. 山东大学学报(工学版), 2017, 47(1): 15-21.
[2] 周新波1,徐向锋2*,张峰3,孙家龙3,齐广志3. 箱梁竖向预应力张拉力无损检测研究[J]. 山东大学学报(工学版), 2013, 43(6): 77-82.
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