Optimization study of mine fire sensor based on grey correlation analysis
Xiaokun Zhao, Minghao Ni, Wencai Wang, Jianing Wang, Hongwei Wang
TL;DR
This study optimizes mine fire sensors using grey correlation analysis to reduce false alarms and improve fire detection accuracy.
Contribution
A novel optimization scheme for mine fire sensors using grey correlation analysis and CO content detection is proposed.
Findings
Grey correlation analysis helps determine optimal sensor placement and number in mines.
CO content detection at ventilation nodes identifies fire spread to other tunnels.
Optimized sensors improve detection accuracy and reduce false alarms.
Abstract
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…
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Taxonomy
TopicsFire dynamics and safety research · Evacuation and Crowd Dynamics · Fire effects on ecosystems