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基于BIM显示引擎的多专业数据融合与业务赋能研究OA

中文摘要英文摘要

针对铁路工程多专业协同中信息孤岛、模型格式不统一、协同效率低等问题,该文提出基于 BIM 显示引擎的多专业数据融合与业务赋能技术方案.首先,通过双层映射机制、仿射变换坐标统一、混合几何表示解决语义统一、空间对齐、精度平衡三大核心需求,实现多源数据的语义互通、空间精准对齐与轻量化适配;其次,构建"数据输入—数据融合—跨专业检测—业务赋能"四级技术流程,在设计阶段实现实时协同校验,施工阶段依托进度可视化与 AR 交底优化工序,运维阶段整合多专业数据构建数字孪生体;最后,以某 10 km 高铁区间工程为对象开展实验验证.结果表明,双层映射机制语义匹配准确率达 98.1%,坐标转换偏差小于等于 0.005 m,模型轻量化压缩比最高 8.7:1,跨专业冲突检测覆盖率 98.2%,可减少 70%以上无效沟通时间、降低 30%施工返工率.该方案为铁路工程全生命周期多专业协同提供高效技术支撑,兼具工程实用性与创新性.

In response to the problems of information silos,inconsistent model formats,and low collaboration efficiency in multi-disciplinary railway engineering,this paper proposes a technical solution for multi-disciplinary data integration and business empowerment based on BIM display engines.Firstly,to address the three core demands of semantic unification,spatial alignment,and precision balance,three key technologies including a dual-layer mapping mechanism,affine transformation for coordinate unification,and hybrid geometric representation are developed to achieve semantic interoperability,precise spatial alignment,and lightweight adaptation of multi-source data.Secondly,a four-level technical process of"data input-data fusion-cross-disciplinary detection-business empowerment"is constructed,enabling real-time collaborative verification during the design stage,optimizing work procedures through progress visualization and AR handover during the construction stage,and integrating multi-disciplinary data to build a digital twin during the operation and maintenance stage.Finally,an experimental verification was conducted on a 10-kilometer high-speed railway section project.The results show that the semantic matching accuracy of the dual-layer mapping mechanism is 98.1%,the coordinate transformation deviation is≤0.005 m,the maximum model lightweight compression ratio is 8.7:1,and the cross-disciplinary conflict detection coverage rate is 98.2%,which can reduce ineffective communication time by more than 70%and lower the construction rework rate by 30%.This solution provides efficient technical support for multi-disciplinary collaboration throughout the railway engineering life cycle,and is both practically applicable and innovative.

郑云水;于晨;蔡博

兰州交通大学,兰州 730070京津冀城际铁路投资有限公司,北京 100000兰州交通大学,兰州 730070

交通工程

BIM多专业协同数据融合业务赋能铁路工程

BIMmulti-disciplinary collaborationdata fusionbusiness empowermentrailway engineering

《科技创新与应用》 2026 (15)

83-87,5

国家自然基金重点课题(N2024S013)

10.19981/j.CN23-1581/G3.2026.15.020

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