Laser & Optoelectronics Progress, Volume. 61, Issue 23, 2312003(2024)

Inversion of Light Scattering for Optical Component Defects Using a Cascaded Machine Learning Algorithm

Weibin Cai1,2, Feibin Wu2, Ruyi Li2, and Jun Han2、*
Author Affiliations
  • 1College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, Fujian , China
  • 2Quanzhou Equipment Manufacturing Research Center, Haixi Institutes, Chinese Academy of Sciences, Quanzhou 362200, Fujian , China
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    References(19)

    [4] Xu X B, Duan M H, Fan X et al. Surface defect detection of transparent objects based on fringe modulation[J]. Acta Optica Sinica, 43, 0512003(2023).

    [5] Xiang Y C, Lin Y X, Ren Z Y. Study on surface defect detection method of optical element[J]. Optical Instruments, 40, 78-87(2018).

    [6] Lai L. The particle simulation of dynamic processes of laser damage induced by surface microdefects of KDP crystals[D], 28-70(2020).

    [9] Li M Z, Hou X, Zhao W C et al. Current situation and development trend of aspheric optical surface defect detection technology (invited)[J]. Infrared and Laser Engineering, 51, 20220457(2022).

    [18] Wang S T. Imaging theoretical modeling and system analysis of smooth surface defect evaluation based on light scattering method[D], 41-53(2015).

    [19] Wu F. Detection canability improvement technology for weak defects on smooth surfaces based on dark field scattering[D], 26-28(2020).

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    Weibin Cai, Feibin Wu, Ruyi Li, Jun Han. Inversion of Light Scattering for Optical Component Defects Using a Cascaded Machine Learning Algorithm[J]. Laser & Optoelectronics Progress, 2024, 61(23): 2312003

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Feb. 5, 2024

    Accepted: Apr. 3, 2024

    Published Online: Nov. 19, 2024

    The Author Email: Jun Han (junhan@fjirsm.ac.cn)

    DOI:10.3788/LOP240664

    CSTR:32186.14.LOP240664

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