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应用科学学报

• 信号与信息处理 • 上一篇    下一篇

X射线底片焊缝缺陷的支持向量机识别方法

孙 林1 杨世元2 吴德会3   

  1. 1 合肥工业大学 ，应用物理系, 安徽 合肥 230009；

    2 合肥工业大学 仪器科学与光电工程学院,安徽 合肥 230009 ;

    3 九江学院 ，江西 九江 332005）

  • 收稿日期:2007-09-21 修回日期:2007-11-26 出版日期:2008-07-31 发布日期:2008-07-31

Detection of Defects in Welding Line from X-Ray Film Using SVM

SUN Lin1, YANG Shi-yuan2, WU De-hui3   

  1. 1. Department of Application Physics ,Hefei University of Technology, Hefei 230009，China
    2. School of Instrment Science and optoelectronic Engineering ,Hefei University of Technology, Hefei 230009，China
    3. Department of Electronic Engineering,Jiujiang University, Jiujiang 332005,China
  • Received:2007-09-21 Revised:2007-11-26 Online:2008-07-31 Published:2008-07-31

被引次数

18

摘要： 准确识别X射线底片焊缝缺陷类别，可改进焊接工艺、提高焊接质量。该文在分析和比较几种焊缝缺陷识别模式的基础上，提出了基于支持向量机(SVM)的X射线底片焊缝缺陷识别方法。该方法首先对X射线底片进行数字化处理和缺陷特征提取，然后针对X射线底片焊缝缺陷样本特点，建立SVM“一对一”聚类结构并对样本进行识别。实验结果表明，该模型具有识别精度高、速度快、容易实现等优点，适合对X射线底片焊缝缺陷识别。

关键词: X射线底片, 焊缝缺陷, 支持向量机, 识别

Abstract: It is important to detect defects of welding lines on an X-ray film for improving welding techniques and the product quality. This paper proposes a detection method based on support vector machine based on analysis and comparison with several other methods. In the proposed method, the film is first converted into digital format, and characteristics of the defect are extracted. A “one against one” SVM clustering structure is constructed according to the characteristics, and recognition is made. Experiments show high accuracy and processing speed, and easy implementation of the method. The method is suitable for detection and recognition of defects of welding lines from X-ray films.

Key words: X-ray film, defect of welding line, support vector machine, recognition