基于VR看房及网络大数据的住宅活荷载建模

Residential Live Load Modeling Based on Panoramic VR Viewing and Network Big Data

摘要:

活荷载取值是建筑结构可靠性设计的基础，样本采集又是荷载建模的关键。针对传统的抽样采集、入户称重的研究方式存在的入户难、称重难、效率低和样本少等问题，提出了基于网络房产中介平台开放的全景虚拟（virtual reality，VR）看房方式及网络大数据研究住宅持久性活荷载的方式。首先，利用VR看房获得房间尺寸、室内物品类型及数量等数据，再通过网络爬虫从互联网大数据资源中获得物品重量，实现非称重方式的活荷载调查。采用该方法调查了9座城市的4 676个住宅房间样本（总面积近75 000m²），通过数据统计分析与荷载组合得到了住宅活荷载标准值，并与现行规范建议值进行了对比。结果表明，任意时点持久性活荷载标准差显著增大，不同城市活荷载变动时间均值不同且整体呈现下降趋势。VR系统结合网络大数据可以实现高效、便捷的住宅活荷载调查，形成一种全新的活荷载研究方式。

Abstract:

Reliable live load value is the prerequisite for reliability design of civil engineering buildings， and the collection of live load samples is the key data foundation for load modeling. Aiming at the problems of difficulty in entering households， weighing， low efficiency， and small samples that exist in the traditional research methods of sample collection and weighing in households， and based on the research thinking of big data， a new research method of residential persistent live load based on panoramic VR（virtual reality） house viewing system is proposed. Through the VR system of open network platform， multi-source heterogeneous data such as pictures and videos， combined with Internet resources， comprehensive network crawler， and other means， live load investigation is realized by non-weighing method， and practical research is conducted by taking residential buildings as examples. The characteristic value of residential live load was obtained by statistical analysis and load combination of 4 676 rooms in 9 cities （with a total area of nearly 75 000 square meters）. The results show that the standard deviation of sustained live loads significantly increases at any given time， the time of live load variations is different among different cities， which， overall， presents a decreasing trend. The combination of VR system and internet big data can achieve efficient and convenient residential live load surveys， forming a new research method for live loads.