Development of an intelligent multi-scale defect detection system for aspheric lenses with high accuracy and efficiency

Abstract

Existing methods struggle to fulfill the demand for fast and precise detection of multi-scale faults in aspheric lenses. A high accuracy and efficiency intelligent detection system for aspheric lenses is developed, which utilizes four-step phase-shifted grating optical imaging and Fourier low-pass filtering as image acquisition and preprocessing systems. Accurate and efficient defect feature extraction methods are designed based on regression loss and lightweight feature selection networks, and the model's ability to learn multi-scale defect information is improved. Finally, experimental tests were conducted based on the self-constructed multi-scale defect datasets of aspheric lenses. The results show that the detection system achieves a global accuracy of 96.3 %, an accuracy of 63.8 % for tiny defects detection, as well as a single-image detection time of 24.9 ms, which is a significant improvement in terms of accuracy and efficiency compared with existing methods. Therefore, the intelligent detection system can be widely applied to defect detection in aspheric lenses.