| 异种材料连接界面弱信号缺陷的提取与量化 |
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| 引用本文： | 高双胜,迟大钊,刚铁.异种材料连接界面弱信号缺陷的提取与量化[J].焊接学报,2010,31(11):81-84. |
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| 作者姓名： | 高双胜 迟大钊 刚铁 |
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| 作者单位： | 1. 沈阳航空航天大学,材料科学与工程学院,沈阳,110036;哈尔滨工业大学,现代焊接生产技术国家重点实验室,哈尔滨,150001
2. 哈尔滨工业大学,现代焊接生产技术国家重点实验室,哈尔滨,150001 |
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| 基金项目： | 现代焊接生产技术国家重点实验室开放课题研究基金项目，中国博士后基金资助项目 |
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| 摘 要： | 采用基于形态学增强和面积重构预处理的分水岭变换方法,对异种材料连接界面的超声检测图像进行了自适应分块阈值化分割处理.为了验证无损检测处理结果的可靠性,根据铜钢堆焊界面检测图像特征,对堆焊接头进行抽样破坏检测.结果表明,通过形态学增强和面积重构的预处理可有效抑制经典分水岭算法的过度分割,实现了检测图像按缺陷的分布特征进行自适应分块,进而通过阈值化分割,达到了超声弱信号缺陷的有效提取与量化的目的.经破坏性试验验证,该方法具有较高的检测可靠性.
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| 关 键 词： | 异种材料连接 C扫描图像 弱信号缺陷 分水岭变换 面积重构 |
| 收稿时间： | 2009/7/27 0:00:00 |
Extraction of weak signal for weld defect and its qualification in joint interface between dissimilar materials |
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| GAO Shuangsheng,CHI Dazhao and GANG Tie.Extraction of weak signal for weld defect and its qualification in joint interface between dissimilar materials[J].Transactions of The China Welding Institution,2010,31(11):81-84. |
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| Authors: | GAO Shuangsheng CHI Dazhao and GANG Tie |
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| Affiliation: | School of Materials Science & Engineering, Shenyang Aerospace University, Shenyang 110036, China;State Key Laboratory of Advanced Welding Production Technology, Harbin Institute of Technology, Harbin 150001, China,State Key Laboratory of Advanced Welding Production Technology, Harbin Institute of Technology, Harbin 150001, China and State Key Laboratory of Advanced Welding Production Technology, Harbin Institute of Technology, Harbin 150001, China |
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| Abstract: | By employing pre-processing of morphologic enhancement and area-reconstruction,a novel method for image segmentation was presented based on watershed transformation.And using the method,ultrasonic test image for a joint interface between dissimilar materials was segmented.To validate the reliability of this method,the sample was destructed and tested.The results show that over-segmentation caused by traditional watershed transformation can be avoided by pre-procession of morphologic enhancement and area-reconstruction.Meanwhile,the test image can be blocked adaptively according to the distribution feature of defect and then the defect can be extracted and quantified by threshold segmentation.Destructive experiment shows the presented method is very efficient with high reliability. |
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| Keywords: | joint between dissimilar materials C-scan image defect with weak signal watershed transformation area-reconstruction |
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