Advanced Search
ZHOU Xiaohu, GAO Xiangdong, DU Liangliang, WANG Chuncao. Detection of weld defects based on FGT - FBP reconstruction algorithm[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2020, 41(2): 48-52. DOI: 10.12073/j.hjxb.20190926002
Citation: ZHOU Xiaohu, GAO Xiangdong, DU Liangliang, WANG Chuncao. Detection of weld defects based on FGT - FBP reconstruction algorithm[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2020, 41(2): 48-52. DOI: 10.12073/j.hjxb.20190926002
shu

Detection of weld defects based on FGT - FBP reconstruction algorithm

  • Guangdong Provincial Welding Engineering Technology Research Center, Guangdong University of Technology, Guangzhou, 510006, China

More Information
  • Received Date: September 25, 2019
  • Available Online: July 12, 2020
    Graphical Abstract
    • Abstract
  • An innovative detection method based upon fuzzy gray scale transformation and filter back-projection (FGT-FBP) reconstruction is proposed to study the geometrical characteristics of weld defects. By analyzing the characteristics of magneto-optical images with defects such as cracks and incomplete penetration under alternating magnetic field excitation, a fuzzy rule is designed to carry on fuzzy gray scale transformation of the magneto-optical image. The image contrast is improved to visualize the configuration and trend of weld defects. An image evaluation method without reference models that describes weld defect details of magneto-optical images is realized. The weld defect magneto-optical images processed by FGT are rotated and projected. Fast Fourier transform and improved filter are applied for denoising and filtering. Also, the back-projection transform is used to reconstruct weld defect images after eliminate artifacts. Then FGT-FBP is used to denoise by filtering, and extract defect features from the images. Finally, the proposed method is combined threshold segmentation with edge detection to achieve defect detection. Experiment results show that FGT-FBP reconstruction algorithm can detect weld defects such as cracks and incomplete penetration accurately.
    • FullText(HTML)
    • References (12)
  • Zhang Y X, You D Y, Gao X D, et al. Welding defects detection based on deep learning with multiple optical sensors during disk laser welding of thick plates[J]. Journal of Manufacturing Systems, 2019, 51: 87 − 94. doi: 10.1016/j.jmsy.2019.02.004
    Chen Y Q, Gao X D, Xiao Z L, et al. Experimental study of weld position detection based on keyhole infrared image during high power fiber laser welding[J]. China Welding, 2015, 24(3): 45 − 51.
    Wang J J, Fu P L, Gao R X. Machine vision intelligence for product defect inspection based on deep learning and Hough transform[J]. Journal of Manufacturing Systems, 2019, 51: 52 − 60. doi: 10.1016/j.jmsy.2019.03.002
    Bernieri A, Ferrigno L, Laracca M, et al. Ultrasonic NDT on aluminum bars: an experimental performance comparison of excitation and processing techniques[J]. Measurement, 2018, 128: 393 − 402. doi: 10.1016/j.measurement.2017.10.040
    Ai Y, Jiang P, Wang C, et al. Investigation of the humping formation in the high power and high speed laser welding[J]. Optics and Lasers in Engineering, 2018, 107: 102 − 111. doi: 10.1016/j.optlaseng.2018.03.010
    Li E, Kang Y, Tang J. A new micro magnetic bridge probe in magnetic flux leakage for detecting micro-cracks[J]. Journal of Nondestructive Evaluation, 2018, 37(3): 46:1 − 9.
    Gao X D, Lan C Z, You D Y, et al. Weldment nondestructive testing using magneto-optical imaging induced by alternating magnetic field[J]. Journal of Nondestructive Evaluation, 2017, 36(3): 55:1 − 11.
    Gao X D, Ma N J, Du L L. Magneto-optical imaging characteristics of weld defects under alternating magnetic field excitation[J]. Optics Express, 2018, 26(8): 9972 − 9983. doi: 10.1364/OE.26.009972
    Deng Y, Liu X, Udpa L. Magneto-optic imaging for aircraft skins inspection: a probability of detection study of simulated and experimental image data[J]. IEEE Transactions on Reliability, 2012, 61(4): 901 − 908. doi: 10.1109/TR.2012.2221613
    刘习文, 陈显明, 刘超英. 基于拉东变换和模糊增强的结构光焊缝跟踪图像处理[J]. 焊接学报, 2017, 38(2): 19 − 22.

    Liu Xiwen, Chen Xianming, Liu Chaoying. Image processing in welding seam tracking with structure light based on radon transform and fuzzy-enhancement[J]. Transactions of the China Welding Institution, 2017, 38(2): 19 − 22.
    Pal S K, King R A. Image enhancement using smoothing with fuzzy sets[J]. IEEE Transactions on Systems Man & Cybernetics, 2007, 11(7): 494 − 501.
    Qu H Y, Xu F, Hu X F, et al. A novel denoising method based on Radon transform and filtered back-projection reconstruction algorithm[J]. Optics & Lasers in Engineering, 2012, 50(4): 593 − 598.
    • Related Articles

  • Related Articles

    [1]XU Lianyong, LONG Zhiping, ZHAO Lei, HAN Yongdian, PENG Chentao. Effect of stress concentration at weld toes on combined high and low cycle fatigue of EH36 steel welded joints[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2024, 45(7): 1-9. DOI: 10.12073/j.hjxb.20230619003
    [2]LIU Xue, ZHONG Shifang, XU Lianyong, ZHAO Lei, HAN Yongdian. Corrosion fatigue behavior of X65 pipeline steel welded joints under different stress ranges[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2023, 44(7): 24-31, 78. DOI: 10.12073/j.hjxb.20220830001
    [3]HE Bolin, YE Bin, DENG Haipeng, LI Li, WEI Kang. Very high cycle fatigue properties of SMA490BW steel welded joints for train bogie[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2019, 40(2): 31-37. DOI: 10.12073/j.hjxb.2019400037
    [4]DING Sansan, LI Qiang, GOU Guoqing. Effect of residual stress on fatigue behavior of welded joint of A7N01 aluminum alloy for high-speed trcion[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2016, 37(9): 23-28.
    [5]XUE Bin, ZHANG Tianhui, XU Renping, WANG Shiyue. Effect of residual compressive stress field on fatigue crack growth of B780CF steel welded joints[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2016, 37(6): 103-108.
    [6]YIN Chengjiang, SONG Tianmin, LI Wanli. Effect of high-temperature welding on fatigue life of 2.25Cr1Mo steel joint[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2015, 36(4): 106-108.
    [7]ZHAO Dongsheng, WU Guoqiang, LIU Yujun, LIU Wen, JI Zhuoshang. Effect of welding residual stress on fatigue life of Invar steel welded joint[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2013, (4): 93-95,108.
    [8]XU Jun, ZHANG Yansong, ZHU Ping, CHEN Guanlong. Fatigue life analysis of lap-shear spot weld of dual phase steels[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2008, (5): 45-48.
    [9]WANG Wen-xian, HUO Li-xing, ZHANG Yu-feng, WANG Dong-po. Effect of Transformation Temperature on Improving the Fatigue Strength of Welded Joints[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2002, (3): 15-18.
    [10]Ling Chao, Zheng Xiulin. Overloading effect upon fatigue life of 16Mn steel butt welds[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 1991, (4): 247-251.

Catalog

    Get Citation
    PDF
    XML
    Article views (291) PDF downloads (26) Cited by()
    Turn off MathJax
    Article Contents
    Abstract
    References
    Related Articles

    Website Copyright © Editorial Office of Transactions of the China Welding Institution, Welding Journals Publishing HouseTel：0451-86323218Address：No. 2077, Chuangxin Road, Songbei District, Harbin

    Supported by: Beijing Renhe Information Technology Co. Ltd    Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return