Automatic Defect Detection Instrument for Spherical Surfaces of Optical Elements

被引:0
|
作者
Shi, Yali [1 ]
Zhang, Mei [2 ]
Li, Mingwei [1 ]
机构
[1] Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
[2] Acad Mil Sci, Inst Syst Engn, Chinese Peoples Liberat Army, Beijing 100141, Peoples R China
关键词
computer vision; defect detection; spherical optical element; INSPECTION; SYSTEM; FLAWS;
D O I
10.3390/photonics11070681
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In order to realize automatic surface defect detection for large aperture precision spherical optical elements, an automatic surface defect detection instrument has been designed. The instrument consists of a microscopic imaging system, illumination system, motion scanning system, and a software algorithm system. Firstly, a multi-angle channel illumination source and a coaxial illumination source were designed. Bright and dark field images of surface defects were captured by cooperating with an automatic zoom microscope. Then, algorithms for scanning trajectory planning, image stitching, and intelligent defect recognition were designed to achieve full-aperture surface image acquisition and defect quantification detection. The automated defect detection process of the instrument is summarized and introduced. Finally, the experimental platform was constructed, which can work well for the optical elements with a maximum diameter of 400 mm and a relative aperture R/D value of 1. It takes about 15 min to detect an optical element with a diameter of 200 mm in dark-field imaging mode. As a result, the minimum line width of scratch detectable is 2 mu m and the minimum diameter of pitting detectable is 4 mu m. Clearly, the instrument can realize the automatic detection of surface defects of spherical optical elements, and has the advantages of a high efficiency, stability, reliability, quantification, and data traceability.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] A surface defect detection instrument for large aperture spherical optical elements
    Mingwei Li
    Yali Shi
    Zhengtao Zhang
    Xian Tao
    Xiuqin Shang
    Neural Computing and Applications, 2025, 37 (7) : 5815 - 5829
  • [2] Defect detection of optical elements surfaces using curvelet transform
    Li, LinFu
    Chen, JianJun
    Huang, Jinbao
    OPTICAL METROLOGY AND INSPECTION FOR INDUSTRIAL APPLICATIONS VI, 2019, 11189
  • [3] AUTOMATIC DEFECT DETECTION - INSTRUMENT COMPARISON AND APPLICATION
    BRACKEN, RC
    RIZVI, SA
    REEVES, AE
    PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS, 1981, 275 : 76 - 91
  • [4] SIMULATION OF AUTOMATIC DEFECT-DETECTION FOR WOOD SURFACES
    PLINKE, B
    HOLZ ALS ROH-UND WERKSTOFF, 1988, 46 (04) : 146 - 146
  • [5] Soldering defect detection in automatic optical inspection
    Dai, Wenting
    Mujeeb, Abdul
    Erdt, Marius
    Sourin, Alexei
    ADVANCED ENGINEERING INFORMATICS, 2020, 43
  • [6] Automatic detection instrument for defects of optic fiber imaging elements
    Huang, Yonggang
    Jiao, Peng
    Wang, Yun
    Fu, Yang
    Zhou, You
    Wang, Jiuwang
    Zhao, Ran
    Si, Pan
    OPTICAL DESIGN AND TESTING IX, 2019, 11185
  • [7] HOLOGRAPHIC OPTICAL-ELEMENTS RECORDED ON SPHERICAL SURFACES WITH PHOTOPOLYMERS
    FIMIA, A
    CARRETERO, L
    BELENDEZ, A
    APPLIED OPTICS, 1994, 33 (17) : 3633 - 3634
  • [8] NONDESTRUCTIVE DEFECT DETECTION FROM OPTICAL-SURFACES
    MARRS, CD
    PORTEUS, JO
    PALMER, JR
    PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS, 1985, 525 : 51 - 55
  • [9] Automatic defect-detection for inside and outside surfaces of hemispherical shell
    Le, J
    Guo, JJ
    Zhu, H
    Fang, HY
    Wang, W
    He, JD
    Zhang, ZX
    PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON PRECISION MECHANICAL MEASUREMENT, VOL 4, 2002, : 79 - 85
  • [10] Development of optical automatic positioning and wafer defect detection system
    Tien, Chuen-Lin
    Lai, Qun-Huang
    Lin, Chern-Sheng
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2016, 27 (02)