Abstract

In the manufacturing process of optical lenses, the lack of monitoring and detection of the central processing process leads to low processing efficiency and difficulty in ensuring product consistency. We propose a digital twin system for alignment processing to address this issue. The system adopts a hierarchical architecture based on the digital twin five-dimensional model, aiming to improve the fidelity and interactivity of the virtual model of the centring lathe by combining dimension-driven virtual models with integrated data and physical models of the turning mechanism. We have successfully achieved the semantic and physical fusion of multi-source heterogeneous data during centring processing using information models and OPC UA-based data interaction methods. In addition, we adopted the VMD-GRU method based on feature fusion for real-time monitoring of critical components of the centring lathe. Finally, we validated the feasibility and effectiveness of the digital twin system for the central lathe through development examples. The application of this system is expected to promote the digital and intelligent development of high-precision optical component processing, providing references including references for related manufacturing fields. In summary, we propose a digital monitoring and detection system for the centring process of optical lens manufacturing. The application of this system will help improve product consistency and processing efficiency while reducing risks and costs in the manufacturing process.

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