Research of resin lens surface defect detection system

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.