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利用大气监测系统传感器数据对矿井火灾进行特征描述。

Characterization of a mine fire using atmospheric monitoring system sensor data.

作者信息

Yuan L, Thomas R A, Zhou L

机构信息

Lead general engineer, electronics technician, and mining engineer, respectively, at the Pittsburgh Mining Research Division, National Institute for Occupational Safety and Health, Pittsburgh, PA, USA.

出版信息

Min Eng. 2017 Jun;69(6):57-62. doi: 10.19150/me.7567.

Abstract

Atmospheric monitoring systems (AMS) have been widely used in underground coal mines in the United States for the detection of fire in the belt entry and the monitoring of other ventilation-related parameters such as airflow velocity and methane concentration in specific mine locations. In addition to an AMS being able to detect a mine fire, the AMS data have the potential to provide fire characteristic information such as fire growth - in terms of heat release rate - and exact fire location. Such information is critical in making decisions regarding fire-fighting strategies, underground personnel evacuation and optimal escape routes. In this study, a methodology was developed to calculate the fire heat release rate using AMS sensor data for carbon monoxide concentration, carbon dioxide concentration and airflow velocity based on the theory of heat and species transfer in ventilation airflow. Full-scale mine fire experiments were then conducted in the Pittsburgh Mining Research Division's Safety Research Coal Mine using an AMS with different fire sources. Sensor data collected from the experiments were used to calculate the heat release rates of the fires using this methodology. The calculated heat release rate was compared with the value determined from the mass loss rate of the combustible material using a digital load cell. The experimental results show that the heat release rate of a mine fire can be calculated using AMS sensor data with reasonable accuracy.

摘要

大气监测系统(AMS)在美国的地下煤矿中已被广泛用于检测胶带巷火灾以及监测其他与通风相关的参数,如特定矿井位置的气流速度和甲烷浓度。除了能够检测矿井火灾外,AMS数据还有潜力提供火灾特征信息,如火灾发展情况(以热释放速率衡量)以及确切的火灾位置。这些信息对于制定灭火策略、井下人员疏散和最佳逃生路线的决策至关重要。在本研究中,基于通风气流中的热和物质传递理论,开发了一种利用AMS传感器获取的一氧化碳浓度、二氧化碳浓度和气流速度数据来计算火灾热释放速率的方法。随后,在匹兹堡矿业研究部的安全研究煤矿中,使用配备不同火源的AMS进行了全尺寸矿井火灾实验。利用该方法,将从实验中收集的传感器数据用于计算火灾的热释放速率。将计算得到的热释放速率与使用数字称重传感器根据可燃材料质量损失率确定的值进行比较。实验结果表明,利用AMS传感器数据能够以合理的精度计算矿井火灾的热释放速率。

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本文引用的文献

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