1. Aperture design to improve the sensitivity of detecting subsurface defects in transparent elements.
- Author
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Chen, Gengyang, Zhang, Tengda, and Lu, Rongsheng
- Subjects
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SURFACE defects , *FUSED silica , *LIGHT scattering , *SIGNAL-to-noise ratio , *IMAGE processing - Abstract
With the increasing quality requirements of transparent elements, the detection of subsurface defects in transparent elements have become a crucial technology. However, as the scale of subsurface defects become smaller and smaller, their detection difficulty gradually increases, mainly due to the increasing interference caused by small surface defects. This article uses a defect scattering light collection method based on an ellipsoidal mirror model to analyze the scattering field distribution of surface small particle defects and subsurface scratch defects. T is defined as the area where the subsurface defect signal is more than three times larger than the surface defect signal. Based on theoretical results, an aperture is made to only allow scattered light from the T area to pass through, improving the signal-to-noise ratio of the subsurface defect signal. The experimental sample is a piece of quartz glass, with two marks processed on its surface. There is a scratch below each mark, and the width of the scratch is 260 nm. By inverting the sample with the scratch side facing downwards, subsurface defect detection is achieved on the sample. The detection result of adding a self-made aperture shows that two marks and two scratches can be detected. The detection result of removing the self-made aperture shows that two marks can be detected, but two scratches cannot be detected. The correctness of theoretical analysis and the importance of self-made apertures for small-scale subsurface defect detection have been demonstrated through experimental comparison. [Display omitted] • Using ellipsoidal mirrors to detect subsurface defects in optical components. • Designed an aperture to improve the signal-to-noise ratio of subsurface defect signals. • Can detect subsurface defects at the level of 260 nanometers. • No image processing required, the system has high detection efficiency. • Effectively avoiding interference from surface defects. [ABSTRACT FROM AUTHOR]
- Published
- 2025
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