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DING Xiaodong, GAO Xiangdong, LIN Shaoduo, HU Dan, PAN Chunrong. Study on soft-hard threshold compromise denoising method for weld forming measurement[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2021, 42(2): 51-55. DOI: 10.12073/j.hjxb.20200620001
Citation: DING Xiaodong, GAO Xiangdong, LIN Shaoduo, HU Dan, PAN Chunrong. Study on soft-hard threshold compromise denoising method for weld forming measurement[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2021, 42(2): 51-55. DOI: 10.12073/j.hjxb.20200620001
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Study on soft-hard threshold compromise denoising method for weld forming measurement

  • 1.

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

  • 2.

    Jiangxi University of Science and Technology, Ganzhou, 341000, China

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  • Received Date: June 19, 2020
  • Available Online: April 12, 2021
    Graphical Abstract
    • Abstract
  • While a stripe laser vision sensor is used to measure the welded forming size, the noise is often existing in a weld image. Aiming at the deficiencies of hard threshold function and soft threshold function in traditional wavelet threshold denoising algorithm, a denoising algorithm based on Soft-hard Threshold Compromise method is studied. Using db4 wavelet basis function, three layers with wavelet decomposition of laser stripe center are performed. The traditional wavelet threshold function and Soft-hard Threshold Compromise method are applied to denoise the detail coefficients, and the denoising effects of several methods are evaluated by SNR and RMSE. Experimental results show that the Soft-hard Threshold Compromise method is better than the traditional wavelet threshold method for denoising, which can effectively improve the measurement accuracy and stability of weld forming size.
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    • References (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. doi: 10.1364/OE.26.009972
    迟大钊, 马子奇, 程怡, 等. 不等厚板搭接焊缝缺陷数字X射线检测[J]. 焊接学报, 2019, 40(11): 45 − 48. doi: 10.12073/j.hjxb.2019400286

    Chi Dazhao, Ma Ziqi, Cheng Yi, et al. X-ray based defect testing method for a lap joint with unequal thickness steel plates[J]. Transactions of the China Welding Institution, 2019, 40(11): 45 − 48. doi: 10.12073/j.hjxb.2019400286
    Qi Jiyang, Li Jinyan. Feature extraction of welding defect based on machine vision[J]. China Welding, 2019, 28(1): 60 − 66.
    Rodríguez-Martín M, Lagüela S, González-Aguilera D, et al. Procedure for quality inspection of welds based on macro-photogrammetric three-dimensional reconstruction[J]. Optics & Laser Technology, 2015, 73: 54 − 62.
    Park J K, An W H, Kang D J. Convolutional neural network based surface inspection system for non-patterned welding defects[J]. International Journal of Precision Engineering and Manufacturing, 2019, 20(6): 363 − 374.
    Sun J, Li C, Wu X, et al. An effective method of weld defect detection and classification based on machine vision[J]. IEEE Transactions on Industrial Informatics, 2019, 15(12): 6322 − 6333. doi: 10.1109/TII.2019.2896357
    Wang N F, Zhong K, Shi X D, et al. A robust weld seam recognition method under heavy noise based on structured-light vision[J]. Robotics and Computer Integrated Manufacturing, 2020, 61(2): 101821.1 − 101821.9. doi: 10.1016/j.rcim.2019.101821
    张斌, 常森, 王桔, 等. 基于遗传算法的激光视觉焊缝特征点提取[J]. 中国激光, 2019, 46(1): 80 − 90.

    Zhang Bin, Chang Sen, Wang Ju, et al. Feature points extraction of laser vision weld seam based on genetic algorithm[J]. Chinese Journal of Lasers, 2019, 46(1): 80 − 90.
    张鹏贤, 李明, 代敦三. 基于激光扫描的焊缝成形尺寸测量[J]. 上海交通大学学报, 2014, 48(5): 636 − 640.

    Zhang Pengxian, Li Ming, Dai Dunsan. Measurement of welding formation size based on laser line scanning[J]. Journal of Shanghai Jiaotong University, 2014, 48(5): 636 − 640.
    肖静, 游世辉. 基于小波变换的发动机表面缺陷图像去噪方法的研究[J]. 表面技术, 2018, 47(12): 328 − 333.

    Xiao Jing, You Shihui. Denoising method of engine surface defect image based on wavelet transform[J]. Surface Technology, 2018, 47(12): 328 − 333.
    汪殿龙, 张志洋, 梁志敏, 等. 基于小波分析的交流CMT焊接电信号滤波[J]. 焊接学报, 2014, 35(5): 17 − 20.

    Wang Dianlong, Zhang Zhiyang, Liang Zhimin, et al. Electric signals filtering of AC CMT welding based on wavelet analysis[J]. Transactions of the China Welding Institution, 2014, 35(5): 17 − 20.
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