Optimization study of mine fire sensor based on grey correlation analysis

In order to address the issues of fire alarm delay, omission, and false alarms caused by the current setup of mine fire sensors, which collect single disaster information, have fixed distribution, and relatively independent data collection, this study utilized FDS numerical simulation software and fire similarity experiments. The aim was to investigate the characteristics of fire gases, temperature, and wind speed. To optimize the number and location of fire sensors in mines, the mathematical method of grey correlation analysis was proposed. Additionally, the critical time for fire hazards to spread to other tunnels was determined by detecting the CO content of ventilation nodes in tunnels with different wind speeds. Grey correlation analysis was employed to determine the critical time for fire hazards to spread to other tunnels. The CO content of the ventilation node is measured to determine the time at which the fire hazard may spread to other tunnels. Grey correlation analysis is then used to compare and correlate the CO content of the ventilation node and the wind speed with the fire characteristic gases, wind speed, and temperature of the tunnel under different wind speeds. Additionally, taking into account the safe escape time for personnel suggested by Marchant, an optimization scheme for the sensors is proposed.