期刊文献+

基于二次度量误差的BIM模型轻量化关键技术研究

Research on key technologies of BIM model lightweight based on quadratic error measure
在线阅读 下载PDF
导出
摘要 目前城市建筑场景愈发复杂,相应的三维BIM模型体量也愈发庞大,本文针对三维模型展示不便、由于体量庞大引起的实时渲染显示慢以及WebGL对一般的Revit文件无法直接支持等问题,提出了基于二次度量误差的BIM模型轻量化展示方法。本文首先通过Revit二次开发将BIM模型转换成.glTF格式文件;其次,使用二次度量误差边折叠算法对模型进行轻量化,并使用Draco算法进行压缩,压缩完成后再通过LOD优化层级算法等方法对其进行Web端的渲染展示。实验结果表明,本文提出的方法可以在有效保留模型几何特征的前提下,实现Web端三维建筑模型的渲染显示,最终数据优化压缩比例最高可达96.36%,Web端实时渲染所需时间最高可提升4.9 s。 At present,urban building scenes are becoming more and more complex,and the corresponding 3D BIM model volume is becoming larger and larger.This paper proposes a lightweight display method of BIM model based on quadratic error measure in view of the inconvenient display of 3D models,the slow real-time rendering display caused by the large volume,and the inability of WebGL to directly support general Revit files.Firstly,convert the BIM model into a.glTF format file through Revit secondary development.Secondly,use the quadratic metric error edge folding algorithm to lighten the model,and then use the Draco algorithm to compress it.Finally,render and show the model which is operated by above methods on the Web side by LOD optimization hierarchy algorithm.Experimental results show that the proposed method can realize the rendering and display of the Web-side 3D architectural model under the premise of effectively retaining the geometric features of the model,and the final data optimization compression ratio can reach up to 96.36%,and the time required for Web-side real-time rendering can be increased by up to 4.9 s.
作者 杨萍 赵荣 YANG Ping;ZHAO Rong(School of Electronic Information and Artificial Intelligence,Shaanxi University of Science and Technology,Xi′an 710021,China)
出处 《智能计算机与应用》 2025年第5期188-193,共6页 Intelligent Computer and Applications
基金 深圳市科技计划项目(JSGG20210802154545031) 陕西省重点研发计划项目(2023-YBGY-208)。
关键词 二次度量误差 BIM模型轻量化 Revit二次开发 WEBGL 渲染优化 quadratic error measure BIM model lightweight Revit secondary development WebGL rendering optimization
  • 相关文献

参考文献6

二级参考文献49

共引文献136

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部