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基于事故致因与 BIM 的中国煤矿建筑合规性检查系统研究。

Research on Coal Mine Building Compliance Inspection System Based on Accident Causation and BIM in China.

机构信息

School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China.

出版信息

Int J Environ Res Public Health. 2022 Dec 8;19(24):16466. doi: 10.3390/ijerph192416466.

Abstract

Coal mine construction projects have high risks, and non-compliant designs generated in the design stage will have adverse effects on subsequent construction and production stages. Therefore, it is of great importance to conduct effective preconstruction compliance inspections on coal mine construction designs. To make the compliance check of coal mine building design more rapid and effective, and to reduce the risks arising from the design phase, this study built a compliance inspection system for coal mine building design from the causes of coal mine accidents, using the Word2Vec word similarity calculation method and BIM platform secondary development technology. The system was tested and was found to be able to detect a 92.82% non-compliant component rate where the correct inspection rate was 97.68%. In addition, the inspection time for a single component was only 0.23 s. The construction of the compliance inspection system based on accident causes has changed the extensive inspection mode in the traditional manual model inspection, and the inspection no longer depends on the experience of inspectors, thus improving the efficiency and accuracy of coal mine building model inspection. The inspection focuses on the building elements with high risks, which achieves the purpose of risk control in the design stage.

摘要

煤矿建设项目风险较高,设计阶段生成的不合规设计将对后续的施工和生产阶段产生不利影响。因此,对煤矿建设设计进行有效的施工前合规性检查非常重要。为了使煤矿建筑设计的合规性检查更加快速有效,并降低设计阶段带来的风险,本研究从煤矿事故的原因出发,利用 Word2Vec 词相似度计算方法和 BIM 平台二次开发技术,构建了煤矿建筑设计合规性检查系统。该系统经过测试,能够检测到 92.82%的不合规组件率,正确检查率为 97.68%。此外,单个组件的检查时间仅为 0.23 秒。基于事故原因的合规性检查系统的构建改变了传统人工模型检查中的广泛检查模式,检查不再依赖于检查人员的经验,从而提高了煤矿建筑模型检查的效率和准确性。检查重点关注高风险的建筑元素,从而达到设计阶段风险控制的目的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0aac/9778409/976591cc3ab4/ijerph-19-16466-g001.jpg

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