利用光谱成像技术开展钢结构智能火灾调查研究

Lina Zhao, Hongyu Zhang, Anna Zhao, Tianhe Wang, Chen Yang, Jihong Wang, Shuozhi Li
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摘要

钢结构因其轻质、低成本等优异的建筑性能,在现代建筑中得到了广泛应用。然而,钢结构耐火性能差,会带来生命安全和经济损失等诸多隐患,因此钢结构建筑成为火灾调查工作的重点研究方向。目前,由于缺乏智能化的方法和设备,火灾调查专家只能通过经验数据对火灾后钢结构表面痕迹进行人工分析,这对调查效率有很大影响。本文提出了一种基于光谱成像技术的钢结构火灾痕迹智能检测方法。通过标准光谱成像设备采集受热钢结构在 400-1000nm 波段的表面光谱和形貌信息,建立最高温度或时间与光谱成像数据特征之间的联系。实验中通过马弗炉和堆火法制备了 150 多组不同温度(包括 100 ℃ 至 1200 ℃)的钢板样品。获得的光谱成像数据导入分类和识别算法后,90% 的样品条件可被准确识别。结果表明,光谱成像技术通过快速、智能地识别火灾痕迹,可有效辅助火灾调查工作的开展,在火灾调查领域具有良好的应用前景。
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Study on intelligent fire investigation in steel structure by spectral imaging technology
Steel structure has been widely used in modern buildings because of its excellent building performance such as lightness, low-cost. However, the poor fire resistant of steel structure can lead to a lot of hidden troubles including life safety and economic losses, cause the construction of steel structure become a key research direction in fire investigationwork. Currently, the experts for fire investigation have to analyse the surface trace of the steel evidence after the fire throughempirical data by person because of the lack of intelligent methods and equipment, which have a great influence on the investigation efficiency. This article proposes an intelligent detection method for steel structure fire traces based spectral imaging technology. The surface spectrum and morphology information of heated steel structure can be collected through standard spectral imaging equipment in 400-1000nm, then establishing the connections between the highest temperature or time and its feature of spectral imaging data. More than 150 groups of steel plate samples were prepared in various temperature including 100 ℃ to 1200 °C by muffle furnace and stacking fire in the experiment. The spectral imaging data can be obtained and imported to the classification and recognition algorithm, 90%of the samples conditions can be identified recognized accurately. The results indicate that spectral imaging technology can effectively assist in the development of fire investigation work by quickly and intelligently identifying fire traces, and has good application prospects in the field of fire investigation.
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