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图学学报 ›› 2021, Vol. 42 ›› Issue (5): 816-822.DOI: 10.11996/JG.j.2095-302X.2021050816

• 建筑与城市信息模型 • 上一篇    下一篇

基于 BIM 的钢筋骨架语义设计点云自动生成算法

  

  1. 清华大学土木工程系,北京 100084
  • 出版日期:2021-10-31 发布日期:2021-11-03
  • 基金资助:
    国家自然科学基金项目(51678345) 

BIM-based algorithm for automatic generation of semantic as-designed point cloud of reinforcement skeleton 

  1. Department of Civil Engineering, Tsinghua University, Beijing 100084, China
  • Online:2021-10-31 Published:2021-11-03
  • Supported by:
    National Natural Science Foundation of China (51678345) 

摘要: 当前预制构配件钢筋骨架质量检查主要依靠人工,存在效率低、容易出错的问题。建筑信息模 型(BIM)、三维重建等技术为改进预制构配件钢筋骨架质量检查方法提供可能。运用这些技术时,有必要由钢 筋骨架 BIM 模型生成可区分每根钢筋的点云。为此,提出了语义设计点云的概念,并构建了基于 BIM 的钢筋 骨架语义设计点云自动生成算法。该算法首先从钢筋骨架 BIM 模型中提取每根钢筋并分别存储于不同的文件, 然后对每根钢筋所在文件进行格式转换,接着生成每根钢筋的语义设计点云,最后基于每根钢筋的语义设计点 云生成钢筋骨架语义设计点云。分别用简单钢筋骨架和复杂钢筋骨架对基于 BIM 的钢筋骨架语义设计点云自 动生成算法进行实验验证,结果表明,该算法能够自动并快速地生成准确的钢筋骨架语义设计点云。 

关键词: 钢筋骨架, 质量检查, 建筑信息模型, 设计点云, 语义点云

Abstract: At present, the quality inspection of the reinforcement skeleton of prefabricated components mainly relies on manual labor, which is time-consuming and error-prone. BIM (building information model), 3D reconstruction and other technologies provide the possibility of improving the quality inspection method of the reinforcement skeleton of the prefabricated components. When using these technologies, it is necessary to generate a point cloud that can distinguish each steel bar from the BIM model of the reinforcement skeleton. Therefore, the concept of the semantic as-designed point cloud was proposed, and a BIM-based algorithm for automatic generation of the semantic as-designed point cloud of reinforcement skeleton was built. First, the algorithm extracts each steel bar from a BIM model and stores them in separate files. Then, the format of these files is converted, and the semantic as-designed point cloud of each steel bar is generated. Finally, a semantic as-designed point cloud of the reinforcement skeleton is generated based on the semantic as-designed point cloud of each steel bar. The algorithm was experimentally verified with a simple reinforcement skeleton and a complex reinforcement skeleton respectively. The result shows that the algorithm can automatically and quickly generate an accurate sematic as-designed point cloud of a reinforcement skeleton. 

Key words:  , reinforcement skeleton, quality inspection, building information model, as-designed point cloud, semantic point cloud 

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