Paper
13 September 2024 Research of resin lens surface defect detection system
Author Affiliations +
Proceedings Volume 13178, Eleventh International Symposium on Precision Mechanical Measurements; 1317819 (2024) https://doi.org/10.1117/12.3032664
Event: Eleventh International Symposium on Precision Mechanical Measurements, 2023, Guangzhou, China
Abstract
Existing technologies make it difficult to detect multi-scale faults on the surface of resin lenses with great accuracy. An intelligent inspection method for resin lenses is presented using four-step phase-shift grating light. The defect feature extraction approach is optimised using the lightweight feature selection network to increase the model's defect information learning capability. Finally, an experimental test is performed on the resin lens surface using the self-constructed multiscale defect dataset. The results demonstrate that the detection system achieves a worldwide accuracy of 96.3% and a microscopic defect detection accuracy of 63.8%, representing a considerable increase in accuracy and efficiency over previous approaches.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Zhen-Ying Xu, Wei-Tao Yang, Yu-Tong Yang, and Ying-Jun Lei "Research of resin lens surface defect detection system", Proc. SPIE 13178, Eleventh International Symposium on Precision Mechanical Measurements, 1317819 (13 September 2024); https://doi.org/10.1117/12.3032664
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KEYWORDS
Dynamic signature verification

Aspheric lenses

Image processing

Feature extraction

Defect detection

Convolution

Education and training

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