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为支持BIM(Building Information Modeling)不同项目参与方按需求高效地获取定制信息,提出一种基于IFC(Industry Foundation Class)属性抽取的子模型生成方式。通过分析IFC分类、IFC实体关联机制,根据领域模型信息需求对IFC模型中的数据实现基于属性的自动抽取,去除与需求数据无关的IFC标准、定义及引用关系,提高子模型数据价值密度,简化模型处理复杂度,生成更适应高密度数据交互模式的协同工作的BIM子模型。最后,在开源平台BIMserver上实现并验证了本方法的正确性和可行性。试验证明,抽取的子模型与IFC完备子模型相比在数据量、数据访问时间、内存资源占用和网络传输速度上有着明显优势。
In order to support different project participants in Building Information Modeling (BIM) to efficiently obtain customized information according to the demand, a generation method of sub-models based on Industry Foundation Class (IFC) attribute extraction is proposed. By analyzing the IFC classification, IFC entity association mechanism, according to the information needs of the domain model, the IFC model data is automatically extracted based on attributes, IFC standards, definitions and reference relationships unrelated to the demand data are removed to improve the value density of the sub-model data and simplify Model processing complexity generates BIM sub-models that work more collaboratively with high-density data interaction patterns. Finally, the correctness and feasibility of this method are verified and verified on the open source platform BIMserver. Experiments show that compared with the IFC complete sub-model, the extracted sub-model has obvious advantages in data amount, data access time, memory resource occupation and network transmission speed.