Laser & Optoelectronics Progress, Volume. 57, Issue 21, 211407(2020)

Rapid Detection of Laser Surface Modification Quality Based on Machine Vision

Tian Chongxin1,2, Li Shaoxia1,2, Yu Gang1,2, He Xiuli1,2, and Wang Xu1,2
Author Affiliations
  • 1中国科学院力学研究所, 北京 100190
  • 2中国科学院大学工程科学学院, 北京 100049
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    References(15)

    [1] Yu G, He X L, Li S X[M]. Laser manufacturing and its applications(2016).

    [5] Zhang L T, Yu G, Tian C X et al. Grain refinement of hypereutectic immiscible Cu-50Cr alloy during rapid melting and solidification induced by high power density laser beams[J]. Metals, 9, 585(2019).

    [7] Guo L Q, Jiang M, Wang D Z et al. Visual inspection system for laser quenching quality[J]. Computer Measurement & Control, 26, 23-26(2018).

    [9] Caggiano A, Zhang J J, Alfieri V et al. Machine learning-based image processing for on-line defect recognition in additive manufacturing[J]. CIRP Annals, 68, 451-454(2019).

    [11] Hu M K. Visual pattern recognition by moment invariants[J]. IRE Transactions on Information Theory, 8, 179-187(1962).

    [12] Flusser J, Suk T. Rotation moment invariants for recognition of symmetric objects[J]. IEEE Transactions on Image Processing, 15, 3784-3790(2006).

    [14] Shevchik S A, Le-Quang T, Farahani F V et al. Laser welding quality monitoring via graph support vector machine with data adaptive kernel[J]. IEEE Access, 7, 93108-93122(2019).

    [15] Mittal S, Dutta M K, Issac A. Non-destructive image processing based system for assessment of rice quality and defects for classification according to inferred commercial value[J]. Measurement, 148, 106969(2019).

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    Tian Chongxin, Li Shaoxia, Yu Gang, He Xiuli, Wang Xu. Rapid Detection of Laser Surface Modification Quality Based on Machine Vision[J]. Laser & Optoelectronics Progress, 2020, 57(21): 211407

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    Paper Information

    Category: Lasers and Laser Optics

    Received: Feb. 6, 2020

    Accepted: --

    Published Online: Nov. 9, 2020

    The Author Email:

    DOI:10.3788/LOP57.211407

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