| 不等厚板搭接焊缝缺陷数字X射线检测 |
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| 引用本文： | 迟大钊,马子奇,程怡,王梓明. 不等厚板搭接焊缝缺陷数字X射线检测[J]. 焊接学报, 2019, 40(11): 45-48. DOI: 10.12073/j.hjxb.2019400286 |
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| 作者姓名： | 迟大钊 马子奇 程怡 王梓明 |
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| 作者单位： | 哈尔滨工业大学先进焊接与连接国家重点实验室,哈尔滨,150001;上海航天设备制造总厂有限公司,上海,200245 |
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| 基金项目： | 国家自然科学基金（51375002）；上海航天科技创新基金（SAST2017-063） |
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| 摘 要： | 在不等厚钢板搭接焊缝X射线检测图像中，由于工件及焊缝厚度变化带来的图像背景灰度差异、焊缝区灰度连续变化等，给基于图像处理的缺陷自动识别带来困难.同时，被检测焊缝装卡的空间位置具有不确定性，垂直布置的焊缝和重力方向存在一定角度，不便于缺陷自动识别及定位.文中给出一种基于不变矩的X射线图像校正方法，解决焊缝图像倾斜问题；在此基础上，给出一种图像噪声抑制、背景去除、图像分割及数学形态学相结合的缺陷识别方法.结果表明，所提方法能有效识别不等厚搭接焊缝中的气孔类缺陷，适用于自动检测.
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| 关 键 词： | 搭接焊缝 X射线 数字图像处理 缺陷识别 |
| 收稿时间： | 2019-07-06 |
X-ray based defect testing method for a lap joint with unequal thickness steel plates |
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| CHI Dazhao,MA Ziqi,CHENG Yi and WANG Ziming. X-ray based defect testing method for a lap joint with unequal thickness steel plates[J]. Transactions of The China Welding Institution, 2019, 40(11): 45-48. DOI: 10.12073/j.hjxb.2019400286 |
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| Authors: | CHI Dazhao MA Ziqi CHENG Yi WANG Ziming |
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| Affiliation: | 1.State Key Laboratory of Advanced Welding and Joining,Harbin Institute of Technology, Habin 150001, China2.Shanghai Aerospace Equipments Manufacturer Co., Ltd., Shanghai 200245, China |
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| Abstract: | It is difficult to automatically recognize defects using digital image processing method in X-ray image that tested from lap joint with unequal thickness plates. This attributes to the very different gray levels in background image caused by the unequal thickness of the workpiece, and the continuous change gray levels caused by lap joint. Besides, the position of the lap joint is uncertain placed before tested, i.e. there is always an angel between the directions of lap joint and gravity. And this makes it difficult for defect detection and localization. In this paper, a method of X-ray image correction based on invariant moments is presented to solve the problem of image skew. In addition, a defect detection method combined of image noise suppression, background removal, image segmentation and mathematical morphology is presented. The results show that the proposed method can effectively recognize the gas pores in lap joint with unequal thickness, and it is suitable for automatic detection. |
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| Keywords: | lap joint X-ray digital image processing defect detection |
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