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焊接缺陷磁光成像磁场分布数值模拟与试验分析

代欣欣, 郑俏俏, 季玉坤, 高向东

代欣欣, 郑俏俏, 季玉坤, 高向东. 焊接缺陷磁光成像磁场分布数值模拟与试验分析[J]. 焊接学报, 2019, 40(12): 102-108. DOI: 10.12073/j.hjxb.2019400321
引用本文: 代欣欣, 郑俏俏, 季玉坤, 高向东. 焊接缺陷磁光成像磁场分布数值模拟与试验分析[J]. 焊接学报, 2019, 40(12): 102-108. DOI: 10.12073/j.hjxb.2019400321
DAI Xinxin, ZHENG Qiaoqiao, JI Yukun, GAO Xiangdong. Numerical simulation and experimental analysis of magnetic field distribution of magneto-optical imaging in weld defects[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2019, 40(12): 102-108. DOI: 10.12073/j.hjxb.2019400321
Citation: DAI Xinxin, ZHENG Qiaoqiao, JI Yukun, GAO Xiangdong. Numerical simulation and experimental analysis of magnetic field distribution of magneto-optical imaging in weld defects[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2019, 40(12): 102-108. DOI: 10.12073/j.hjxb.2019400321

焊接缺陷磁光成像磁场分布数值模拟与试验分析

基金项目: 国家自然科学基金资助项目(51675104);广东省教育厅创新团队项目(2017KCXTD010);广州市科技创新发展专项资金项目(202002020430100004)

Numerical simulation and experimental analysis of magnetic field distribution of magneto-optical imaging in weld defects

  • 摘要: 以激光对接焊的焊接缺陷为对象,研究基于数值模拟的焊接缺陷漏磁场的分析方法. 建立对接焊焊接缺陷检测的三维模型,利用漏磁场理论对比分析不同几何缺陷与漏磁场信号之间的关系规律,并用试验进行验证. 结果表明,裂纹的深度越深,磁感应强度越大,未熔合、凹坑分别随着角度、宽度的增大而磁感应强度减小,并且验证漏磁场信号可以作为焊接缺陷检测的依据. 采用RGB分割法对磁光图像进行分割并提取几何特征,用模糊C-均值聚类(FCM)对不同焊接缺陷进行识别,有良好的识别率.
    Abstract: Taking the weld defects of laser butt welding as the object, the analysis method of magnetic leakage field of weld defects was studied based on numerical simulation. The three dimension finite models of the weld defects detection of laser butt welding was established by Magnet. The relationship between different geometrical defects and their leakage magnetic field signals was compared and analyzed by using the theory of leakage magnetic field, and verified by experiments. The numerical simulation results show that the deeper the crack depth is, the larger the magnetic induction intensity is. The magnetic induction intensity decreases with increase of the angle and width of unfused and concave pits. Magnetic leakage signal can be used as the basis of weld defect detection. Besides, the magneto-optical image was segmented by RGB segmentation method and the features were extracted. Fuzzy c-mean clustering (FCM) was used to identify different weld defects. The results show that the recognition rate is good.
  • [1] 李晓延, 武传松, 李午申. 中国焊接制造领域学科发展研究[J]. 机械工程学报, 2012, 48(6):19-31
    Li Xiaoyan, Wu Chuansong, Li Wushen. Research on the development chinese welding manufacturing[J]. Journal of Mechanical Engineering, 2012, 48(6):19-31
    [2] 冯吉才, 王厚勤, 张秉刚, 等. 空间焊接技术研究现状及展望[J]. 焊接学报, 2015, 36(6):107-112
    Feng Jicai, Wang Houqin, Zhang Bingang, et al. Research status and prospects of space welding technology[J]. Transactions of the China Welding Institution, 2015, 36(6):107-112
    [3] 迟大钊, 刚 铁, 赵立彬. 线聚焦超声波法焊接缺陷识别[J]. 焊接学报, 2015, 36(5):29-32
    Chi Dazhao, Gang Tie, Zhao Libin. Line focusing ultrasonic welding defect identification[J]. Transactions of the China Welding Institution, 2015, 36(5):29-32
    [4] Zhang L, Zhang Y, Dai B, et al. Welding defect detection based on local image enhancement[J]. IET Image Processing, 2019, 13(13):2647-2658.
    [5] Kumar S, Menaka M, Venkatraman B. Simulation and experimental analysis of austenitic stainless steel weld joints using ultrasonic phased array[J]. Measurement Science and Technology, 2019, 31(2):024005-1-11.
    [6] Miao R, Gao Y, Ge L, et al. Online defect recognition of narrow overlap weld based on two-stage recognition model combining continuous wavelet transform and convolutional neural network[J]. Computers in Industry, 2019, 112:103115-1-11.
    [7] Gao X, Mo L, You D, et al. Tight butt joint weld detection based on optical flow and particle filtering of magneto-optical imaging[J]. Mechanical Systems and Signal Processing, 2017, 96:16-30.
    [8] Li Y, Gao X, Zheng Q, et al. Weld cracks nondestructive testing based on magneto-optical imaging under alternating magnetic field excitation[J]. Sensors and Actuators A:Physical, 2019, 285:289-299.
    [9] Yan S, Chao Z, Rui L, et al. Theory and application of magnetic flux leakage pipeline detection[J]. Sensors, 2015, 15(12):31036-31055.
    [10] Li Y, Tian G, Ward S. Numerical simulation on magnetic flux leakage evaluation at high speed[J]. NDT & E International, 2006, 39(5):367-373.
    [11] Silva R R D, Siqueira M H S, Souza M P V D, et al. Estimated accuracy of classification of defects detected in welded joints by radiographic tests[J]. Ndt & E International, 2005, 38(5):335-343.
    [12] Liao T W. Classification of welding flaw types with fuzzy expert systems[J]. Expert Systems with Applications, 2003, 25(1):101-111.
    [13] 高向东, 梁剑斌, 刘桂谦, 等. 大功率光纤激光焊熔透状态模糊聚类识别方法[J]. 焊接学报, 2017, 38(5):22-25
    Gao Xiangdong, Liang Jianbin, Liu Guiqian, et al. Fuzzy clustering identification method for high power fiber laser welding penetration state[J]. Transactions of the China Welding Institution, 2017, 38(5):22-25
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出版历程
  • 收稿日期:  2019-07-07

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