适用于铁路站场智能化审查的交付标准精细度研究OA

[Objective]Intelligent review of railway station yards places higher requirements on the completeness,accuracy,and dynamic management of model data.However,existing delivery standards primarily focus on the visual representation and data integrity of the models,making it difficult to meet the deeper requirements of intelligent review.[Methods]To address this issue,this study established a three-level delivery system with high,medium,and low levels of model precision based on TB 10099-2017 Design Code for Railway Stations and Junctions to meet the intelligent review requirements of different scenarios.The low-precision model defined essential data to meet the minimum requirements for basic compliance verification.The medium-precision model strengthened logical relationships and consistency verification among data through a cross-validation mechanism,providing support for multidimensional verification in complex scenarios.The high-precision model,relying on digital twin technology,achieved multidimensional mapping and dynamic updating of the real environment,enabling refined coordinated management throughout the life cycle of design,construction,operation,and maintenance.Using the design provisions for tracks and station equipment as cases,this study verified the precision standards.[Results]The results showed that low-precision models met the basic requirements for provision verification,medium-precision models improved data reliability and consistency through systematic attribute verification,and high-precision models achieved bidirectional association between models and physical entities through dynamic environmental mapping,effectively supporting accurate review and management throughout the life cycle.[Conclusion]The precision delivery system constructed in this study standardizes the entire process from geometric modeling to attribute association,providing an adaptive hierarchical and progressive model delivery standard for intelligent review of railway station yards and laying a theoretical and practical foundation for multi-scenario applications.