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Using Sensor Signals to Analyze Fires

机译:使用传感器信号分析火灾

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Building fire sensors are capable of supplying substantially more information to the fire service than just the simple detection of a possible fire. Nelson, in 1984, recognized the importance of tying all the building sensors to a smart fire panel. In order to accomplish a smart fire panel configuration such as envisioned by Nelson, algorithms must be developed that convert the analog/digital signals received from sensors to the heat release rate (HRR) of the fire. Once the HRR of the fire is known, a multiroom zone fire model can be used to determine smoke layers and temperatures in the other rooms of the building. This information can then be sent to the fire service providing it with an approximate overview of the fire scenario in the building. This paper will describe a ceiling jet algorithm that is being developed to predict the heat release rate (HRR) of a fire using signals from smoke and gas sensors. The prediction of this algorithm will be compared with experiments. In addition, an example of the predictions from a sensor-driven fire model, SDFM, using signals from heat sensors, will be compared with measurements from a full-scale, two-story, flashover townhouse fire.
机译:建筑物火灾传感器不仅能够简单地检测可能的火灾,还能够向消防部门提供更多的信息。 1984年,纳尔逊(Nelson)意识到将所有建筑物传感器连接到智能防火面板上的重要性。为了完成纳尔逊(Nelson)设想的智能防火面板配置,必须开发出将从传感器接收到的模拟/数字信号转换为火的放热率(HRR)的算法。一旦知道了火灾的HRR,就可以使用多房间区域火灾模型来确定建筑物其他房间的烟雾层和温度。然后,可以将此信息发送到消防部门,向其提供建筑物中火灾场景的大致概况。本文将描述一种天花板喷射算法,该算法正在开发中,它使用烟雾和气体传感器的信号来预测火灾的放热率(HRR)。该算法的预测结果将与实验进行比较。另外,将使用热传感器的信号将传感器驱动的火灾模型SDFM的预测示例与全尺寸,两层楼高的闪络联排别墅火灾的测量结果进行比较。

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