DOI: 10.11908/j.issn.0253-374x.19184

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中图分类号: TU312


基金项目: 广东大数据科学中心联合基金重点支持项目(U1711264)




Research on Big Data Survey Method of Building Live Load
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摘要:可靠的荷载取值是建筑结构可靠性设计的基础。传统上采用入户抽样称重的方式调查建筑物活荷载，存在效率低、成本高、周期长、样本少、时效性差以及大件物品称重困难等问题。基于大数据研究思维，提出了室内持久性活荷载的新型研究方式，通过图片、音频、视频、识别码等多源异构数据，结合互联网资源，综合目标检测、图像、语音或文本识别等手段来获得建筑物室内物品的重量。在详细介绍实施方法的流程后，进一步通过案例进行研究，结果表明利用大数据技术可以实现高效、便捷的建筑物活荷载调查，构建全新的荷载研究范式。



Abstract:Reliable live load value is the prerequisite for reliability design of civil engineering buildings. Traditionally, building live loads are investigated by means of indoor objects sampling and weighing. This method has many problems such as low efficiency, high labor cost, long duration, limited samples, poor timelines in reflecting indoor items change and difficulty in weighing large items. Inspired by the big data concept, this paper proposes a new research method for investigating indoor sustained live loads. Through the multi-source heterogeneous data such as photos, videos, identification codes, and voices, combined with internet resources, the weight of objects in the building is obtained by means of object detection, image retrieval, voice or text recognition. After the detailed introduction of the implementation method, further case studies show that the use of big data technology can achieve efficient and convenient building live load survey, and build a new load research paradigm





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