Speaker
Description
With the advancement of large-scale scientific projects, engineering control networks face higher demands. This study focuses on particle accelerator tunnel control networks, addressing key challenges in automated design, data fusion, and deformation prediction. Three main contributions are presented:(1) Automated simulation of laser tracker networks using Spatial Analyzer's Measurement Plans, enabling automated station planning and Monte Carlo simulations for design evaluation. (2) Heterogeneous data fusion, integrating laser trackers with precision instruments. For elevation accuracy, differential leveling models are implemented. For planar accuracy, distance-constrained adjustment algorithms are developed. (3) Machine learning-based deformation prediction using long-term observation data. An integrated workflow establishes multiple prediction models including neural networks for 3D coordinate forecasting, supporting maintenance decisions. Demonstrated at Hefei Advanced Light Facility, this research provides transferable solutions for large-scale engineering applications, balancing methodological robustness with practical implementation.
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