Automatic evaluation system for bulk defects in optics

Wang, Shiling; Sun, Huanyu; Liu, Ang; Zhang, Jianpu; Cheng, Xinglei; Huang, Jin; Wang, Fengrui; Liu, Dong; Liu, Chong

doi:10.1016/j.optlaseng.2020.106380

Cited by 10 publications

(2 citation statements)

References 11 publications

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“…If there are defects, the scattering light is generated and can be received by the microscopy system (not shown in the figure), so a dark-field image with bright defects can be obtained. Since transmissive optics can be penetrated by the incident light, covered SSDs and bulk defects [23] will also be illuminated and generate scattering light, but the strength is relatively weak. Fluorescence imaging is similar to scattering imaging.…”

Section: Multisensor Imaging Systemmentioning

confidence: 99%

Detection of surface defects and subsurface defects of polished optics with multisensor image fusion

Sun

Wang

et al. 2022

PhotoniX

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Surface defects (SDs) and subsurface defects (SSDs) are the key factors decreasing the laser damage threshold of optics. Due to the spatially stacked structure, accurately detecting and distinguishing them has become a major challenge. Herein a detection method for SDs and SSDs with multisensor image fusion is proposed. The optics is illuminated by a laser under dark field condition, and the defects are excited to generate scattering and fluorescence lights, which are received by two image sensors in a wide-field microscope. With the modified algorithms of image registration and feature-level fusion, different types of defects are identified and extracted from the scattering and fluorescence images. Experiments show that two imaging modes can be realized simultaneously by multisensor image fusion, and HF etching verifies that SDs and SSDs of polished optics can be accurately distinguished. This method provides a more targeted reference for the evaluation and control of the defects of optics, and exhibits potential in the application of material surface research.

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Section: Multisensor Imaging Systemmentioning

confidence: 99%

Detection of surface defects and subsurface defects of polished optics with multisensor image fusion

Sun

Wang

et al. 2022

PhotoniX

Self Cite

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“…As a result, the polarized light has received more and more attention in the research of dark-field detection. Shiling Wang used linear laser beams to illuminate a fused silica sample and detected the position and size of defects using a dark-field imaging system [9]. Wang Yi used linear polarized light in a dark-field imaging system to obtain the qualitative relationship between the scratch size and the electric field intensity on the surface of fused quartz [10].…”

Section: Introductionmentioning

confidence: 99%

Influence of light polarization state on the imaging quality of dark-field imaging system

Chen¹,

Wang²,

Zhang³

2022

J. Opt.

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Annular linear polarized light is used as the illumination source of the reflective dark-field detecting system in this paper. According to the theories of the Bidirectional Reflectance Distribution Function (BRDF) and multi-beam interference, the influence of the light polarization state on the intensity distribution of the scattering light is analyzed in detail. For surface defects, a simulation model of dark-field imaging is established based on the Finite-Difference Time-Domain method (FDTD). Both the near-field and the far-field scattering intensity distribution caused by surface defects are calculated under different illumination conditions. The incidence angle and polarization state of illumination light are optimized. Simulation and experimental results show that the image quality will be minimally affected by the interference effect while P-polarized light illuminates with the incident angle of 45°. The higher measurement accuracy of the dark-field imaging detection system can be obtained when the optimized illumination scheme is used.

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Scanning strategy for surface defects evaluation of large fine optical components

Wang

Sun

et al. 2022

Optics & Laser Technology

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Automatic evaluation system for bulk defects in optics

Cited by 10 publications

References 11 publications

Detection of surface defects and subsurface defects of polished optics with multisensor image fusion

Detection of surface defects and subsurface defects of polished optics with multisensor image fusion

Influence of light polarization state on the imaging quality of dark-field imaging system

Scanning strategy for surface defects evaluation of large fine optical components

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