• 中国科技论文统计源期刊
  • 中文核心期刊
  • 中国科技核心期刊
  • 中国机械工程学会无损检测分会会刊
高级检索

超声相控阵图像中的缺陷识别算法

费学智, 吴军芳, 柳铭哲, 张博南, 李健, 吴迪, 滕永平, 席鹏

费学智, 吴军芳, 柳铭哲, 张博南, 李健, 吴迪, 滕永平, 席鹏. 超声相控阵图像中的缺陷识别算法[J]. 无损检测, 2018, 40(8): 61-66. DOI: 10.11973/wsjc201808013
引用本文: 费学智, 吴军芳, 柳铭哲, 张博南, 李健, 吴迪, 滕永平, 席鹏. 超声相控阵图像中的缺陷识别算法[J]. 无损检测, 2018, 40(8): 61-66. DOI: 10.11973/wsjc201808013
FEI Xuezhi, WU Junfang, LIU Mingzhe, ZHANG Bonan, LI Jian, WU Di, TENG Yongping, XI Peng. Defect Recognition Algorithm in Ultrasonic Phased Array Image[J]. Nondestructive Testing, 2018, 40(8): 61-66. DOI: 10.11973/wsjc201808013
Citation: FEI Xuezhi, WU Junfang, LIU Mingzhe, ZHANG Bonan, LI Jian, WU Di, TENG Yongping, XI Peng. Defect Recognition Algorithm in Ultrasonic Phased Array Image[J]. Nondestructive Testing, 2018, 40(8): 61-66. DOI: 10.11973/wsjc201808013

超声相控阵图像中的缺陷识别算法

详细信息
    作者简介:

    费学智(1982-),男,工程师,本科,主要从事无损检测工作

    通讯作者:

    吴军芳, E-mail:wujunfang@sipo.gov.cn

  • 中图分类号: TG115.28

Defect Recognition Algorithm in Ultrasonic Phased Array Image

  • 摘要: 超声相控阵图像的缺陷处理目前停留在人眼观察和人工标识的阶段。提出了一种自动识别超声相控阵缺陷图像的算法过程。该算法分为预处理、图像滤波、特征提取和多目标缺陷跟踪等步骤。通过分析目标缺陷轨迹的相关参数,结合目标缺陷自身的面积等信息来综合判断目标缺陷是否为实际缺陷。对带孔金属铝试块进行的测试检验了算法和程序的正确性,获得了很好的缺陷跟踪和识别效果。
    Abstract: Ultrasound phased array image process and analysis of the defect still relies on the human eye observation and artificial identification. A scheme for automatically processing and analyzing ultrasonic phased array defective images was proposed. The process is composed of preprocessing, image filtering, feature extraction and multi target defect tracking. By analyzing the relevant parameters of the target defect trajectory and combining the area of the target defect, it is determined whether the targeted one is a real defect. The accuracy of the algorithm and program is determined by the test of metal aluminum specimen with holes,and good effect of defect tracking and recognition is obtained.
  • [1] 白金涛. 视频序列中运动目标跟踪算法的研究[D].天津:天津大学,2009.
    [2] 何春. 一种基于直方图的图像二值化算法[J]. 宜宾学院学报, 2016, 16(12):53-55.
    [3]

    OTSU N. A threshold selection method from gray-level histograms[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9(1):62-66.

    [4] 胡宏伟,王泽湘,王哲,等. 基于迭代法及腐蚀算法的超声相控阵缺陷提取[J]. 电子测量与仪器学报, 2015, 29(12):1765-1771.
    [5]

    GONZALEZ R C, WOODS R E. Digital image processing second edition[M]. Beijing:Publishing House of Electronics Industry, 2002:455.

    [6]

    HARALICK R M, SHAPIRO L G. Computer and robot vision[M]. Reading:Addison-Wesley, 1992:28.

    [7]

    JAMES M. Algorithms for assignment and transportation problems[J]. Journal of the Society for Industrial and Applied Mathematics, 1957,5(1),32-38.

计量
  • 文章访问数:  29
  • HTML全文浏览量:  0
  • PDF下载量:  10
  • 被引次数: 0
出版历程
  • 收稿日期:  2018-02-25
  • 刊出日期:  2018-08-09

目录

    /

    返回文章
    返回