Optics and Precision Engineering, Volume. 24, Issue 4, 930(2016)

Detection and classification of welded defects by magneto-optical imaging based on multi-scale wavelet

GAO Xiang-dong1,*... LI Guo-hua1, XIAO Zhen-lin2 and CHEN Xiao-hui2 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
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    References(11)

    [1] [1] PRAVEEN A, VIJAYAREKHA K, ABRAHAM S T, et al.. Signal quality enhancement using higher order wavelets for ultrasonic TOFD signals from austenitic stainless steel welds [J]. Ultrasonics, 2013, 53(7): 1288-1292.

    [3] [3] HELIFA B, OULHADJ A, BENBELGHIT A, et al.. Detection and measurement of surface crack in ferromagnetic materials using eddy current testing [J]. NDT &E Int, 2006, 39: 384-390.

    [4] [4] LE M, LEE J, SHOJI T. A simulation of magneto-optical eddy current imaging [J]. NDT&E International, 2011, 44(8): 783-788.

    [5] [5] DENG Y M, 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.

    [6] [6] GAO X D, LIU Y H, YOU D Y. Detection of micro-weld joint by magneto-optical imaging [J]. Opt Laser Technol, 2014, 62: 141-151.

    [7] [7] GAO X D, WU J J. Approach of detecting and tracking micro weld joint based on magneto optical imaging [J]. Chin J Mech Eng-En, 2015, 51(4): 71-77. (in Chinese)

    [8] [8] LIN L J, YIN Y, HE M G, et al.. Edge detection algorithm of magnetic tile crack based on wavelet modulus maxima [J]. Journal of University of Electronic Science and Technology of China, 2015, 44(2): 283-288. (in Chinese)

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    GAO Xiang-dong, LI Guo-hua, XIAO Zhen-lin, CHEN Xiao-hui. Detection and classification of welded defects by magneto-optical imaging based on multi-scale wavelet[J]. Optics and Precision Engineering, 2016, 24(4): 930

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    Paper Information

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    Received: Jan. 16, 2016

    Accepted: --

    Published Online: Jun. 6, 2016

    The Author Email: Xiang-dong GAO (gaoxd666@126.com)

    DOI:10.3788/ope.20162404.0930

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