《火灾科学（中英文）》编辑部

王静舞,关劲夫,于淼淼,袁宏永,陈涛,刘小勇,王军.多传感器耦合区域火灾报警技术研究[J].火灾科学,2020,29(4):233-240.

多传感器耦合区域火灾报警技术研究

Study on multi-sensor coupling regional fire alarm technology

DOI：10.3969/j.issn.1004-5309.2020.04.05

基金项目:国家重点研发计划项目(2018YFC0806900); 安徽省科技重大专项(17030901016)

作者	单位
王静舞	清华大学合肥公共安全研究院,合肥,230061
关劲夫	清华大学合肥公共安全研究院,合肥,230061
于淼淼	清华大学工程物理系公共安全研究院,北京,100084
袁宏永	清华大学合肥公共安全研究院,合肥,230061 清华大学工程物理系公共安全研究院,北京,100084
陈涛	清华大学工程物理系公共安全研究院,北京,100084
刘小勇	清华大学合肥公共安全研究院,合肥,230061
王军	清华大学合肥公共安全研究院,合肥,230061

中文关键词: 火灾探测烟气蔓延误报率多传感器建筑结构微元

英文关键词:Fire detection Smoke spread False alarm rate Multi-sensor Building structure micro-element

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中文摘要:

早期预警与低误报率一直是建筑火灾探测面临的挑战与难题。已有研究多针对特殊场所特定燃烧产物或多种传感器耦合,普适性不强,探测设备成本高,无法大规模应用。通过将火灾烟气蔓延规律与探测器信号时空分布融合,在不增加探测器数量和分布的情况下,提出了一种基于建筑结构微元的多传感器耦合区域火灾报警模型。对典型火灾场景的烟气蔓延情况进行了模拟分析,狭长结构中探测器信号强度变化具有一定的规律性。应用区域火灾报警模型后,报警时间较传统模式提前了14.7%,基本杜绝了单个探测器误报引发建筑物火灾报警的问题。结果表明:多传感器耦合探测模式显著缩短了火灾报警时间,降低了火灾探测误报率,实现了火灾的早期准确识别与预警。

英文摘要:

Early warning and low false alarm rate have always been the challenges and problems in building fire detection. Previous research mostly focuses on specific combustion products or coupling multiple sensors in special places, which is not universal. The cost of detection equipment is high, and it cannot be applied on a large scale. This paper proposes a multi-sensor coupled regional fire alarm model based on the building structure micro-elements by combining the fire smoke spread characteristic with the spatial and temporal distribution of detector signal, without increasing the number of detectors. The fire smoke spread of typical fire scenarios was simulated and analyzed. The signal intensity of the detector in a long and narrow structure had a certain regularity. After applying the regional fire alarm model, the alarm time was 14.7% earlier than the traditional model, eliminating the problem of building fire alarms caused by false alarms from a single detector. The results show that the multi-sensor coupling detection mode significantly shortens the fire alarm time, reduces the false alarm rate of fire detection, and achieves accurate early identification and early warning of fire.

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