High reflectivity surface defect detection system based on laser interferometry and deep learning

Hao He; Hao Chen; Jinfan Cai; Jinsong Yu; Xiao Yuan; Xiang Zhang

doi:10.1117/12.3031613

18 July 2024 High reflectivity surface defect detection system based on laser interferometry and deep learning

Hao He, Hao Chen, Jinfan Cai, Jinsong Yu, Xiao Yuan, Xiang Zhang

Proceedings Volume 13179, International Conference on Optics and Machine Vision (ICOMV 2024); 1317907 (2024) https://doi.org/10.1117/12.3031613
Event: International Conference on Optics and Machine Vision (ICOMV 2024), 2024, Nanchang, China

Abstract

Objects with high reflectivity are used for precision bearings, wafers and cell phone covers. However, the quality of objects is affected by morphological defects, such as pits and scratches. Here, image acquisition and segmentation of the samples were performed based on the double-plate shear laser interference (DPSLI) system and the ConvNeXt convolutional neural network algorithm, respectively. The DPSLI system used can complete the mapping of the sample with a size of 40.4 mm × 29.6 mm within 15 μs. The defect detection results shown that the ConvNeXt algorithm was used to train 5977 batches of 100 training samples and perform image segmentation on 273 actual samples under the RTX-3060 hardware conditions, which results in an accurate classification of surface defects in images with the resolution of 540 × 428 in 15 ms. Meanwhile, the detection accuracies of pits and scratches were 98.2% and 95.52%, respectively, and the total accuracy of defect recognition was 95.6%. The method used herein enables fast and accurate detection of surface defects on objects with high reflectivity.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hao He, Hao Chen, Jinfan Cai, Jinsong Yu, Xiao Yuan, and Xiang Zhang "High reflectivity surface defect detection system based on laser interferometry and deep learning", Proc. SPIE 13179, International Conference on Optics and Machine Vision (ICOMV 2024), 1317907 (18 July 2024); https://doi.org/10.1117/12.3031613

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KEYWORDS

Defect detection

Reflection

Structured light

Reflectivity

Light sources and illumination

Deep learning

Laser systems engineering

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