Dark field microscopy for ultra-precision surface processing defect measurement

Lulu Li; Qian Liu; Wen Huang

doi:10.1117/12.2523360

6 January 2020 Dark field microscopy for ultra-precision surface processing defect measurement

Lulu Li, Qian Liu, Wen Huang

Proceedings Volume 11383, Sixth Asia Pacific Conference on Optics Manufacture; 1138305 (2020) https://doi.org/10.1117/12.2523360
Event: Sixth Asia Pacific Conference on Optics Manufacture, 2019, Hong Kong, Hong Kong

Abstract

Surface defect is a concerned aspect of surface integrity in ultra-precision machining. The dark field microscopy method is efficient in detecting surface processing defects, and has certain development potential. However, it still has deficiencies on reliability, certainty and cross-scale adaptability. In this paper, several kinds of dark field illumination modes are compared, and high contrast and adaptable illumination modes are defined through experiments. Then a defect detection device is designed, which can detect the surface defects of opaque or transparent components by using the dome light source illumination. To enlarge the field of view (FOV), an X-Y scanning stage is used to obtain sub-area image of the surface, and a stitching method based on feature registration with SURF (Speeded Up Robust Features) is also proposed in the manuscript. Researches show that the defect detection device designed in this paper can obtain detailed, high-contrast, and wide range dark field defect images; SURF registration is insensitive to image translation, rotation, scaling and image noise, and has high calculation speed, which can relax the requirement of image stitching on positioning device and environment. This study provides an effective and low-cost solution for defects detection over large-scale surface in ultra-precision machining.

Citation Download Citation

Lulu Li, Qian Liu, and Wen Huang "Dark field microscopy for ultra-precision surface processing defect measurement", Proc. SPIE 11383, Sixth Asia Pacific Conference on Optics Manufacture, 1138305 (6 January 2020); https://doi.org/10.1117/12.2523360

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KEYWORDS

Light

Defect detection

Image segmentation

Light sources

Imaging systems

Microscopy

Image enhancement

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