| Background removal and weld defect detection based on energy distribution of image |
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| 引用本文： | 迟大钊 刚铁 高双胜. Background removal and weld defect detection based on energy distribution of image[J]. 中国焊接, 2007, 16(1): 14-18 |
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| 作者姓名： | 迟大钊 刚铁 高双胜 |
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| 作者单位： | State Key Laboratory of Advanced Welding Production Technology, Harbin Institute of Technology, Harbin, 150001 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | The lateral wave in ultrasonic TOFD （time of flight diffraction） image has a tail in transit time, which disturbs the detection and evaluation of shallow weld defect. Meanwhile, the lateral wave and back-wall echo that act as background add redundant data in digital image processing. In order to separate defect wave from lateral wave and prepare the way for following image processing, an algorithm of background removal method named as mean-subtraction is developed. Based on this, an improved method by statistic of the energy distribution in the image is proposed. The results show that by choosing proper threshold value according to the axial energy distribution of the image, the background can be removed automatically and the defect section becomes predominant. Meanwhile, diffractive wave of shallow weld defect can be separated from lateral wave effectively.
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| 关 键 词： | 超声检验 TOFD 飞行衍射时间 数字图象处理 背景消除 焊接 缺陷检测 |
Background removal and weld defect detection based on energy distribution of image |
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| Chi Dazhao,Gang Tie,Gao Shuangsheng. Background removal and weld defect detection based on energy distribution of image[J]. China Welding, 2007, 16(1): 14-18 |
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| Authors: | Chi Dazhao Gang Tie Gao Shuangsheng |
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| Abstract: | The lateral wave in ultrasonic TOFD (time of flight diffraction) image has a tail in transit time, which disturbs the detection and evaluation of shallow weld defect. Meanwhile, the lateral wave and back-wall echo that act as background add redundant data in digital image processing. In order to separate defect wave from lateral wave and prepare the way for following image processing, an algorithm of background removal method named as mean-subtraction is developed. Based on this, an improved method by statistic of the energy distribution in the image is proposed. The results show that by choosing proper threshold value according to the axial energy distribution of the image, the background can be removed automatically and the defect section becomes predominant. Meanwhile, diffractive wave of shallow weld defect can be separated from lateral wave effectively. |
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| Keywords: | time of flight diffraction (TOFD) digital image processing background removal defect detection |
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