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为了实现矿井火灾的早期预警,采用了多源信息融合技术,集成了煤矿安全监控系统、火灾束管监测系统、无线自组网温度监测系统和分布式光纤温度监测系统的指标数据,基于实验研究、现场观测、专家经验等数据,建立了矿井火灾多源信息融合预警系统,结合人工神经网络、多指标预警逻辑推理、运用灰色关联分析法建立实验数据拟合函数的计算方法,实现了矿井火灾多源信息融合算法,处理来自不同位置、具有不同物理意义的多源火灾信息,得出了火灾预警指标体系和火灾发展规律,以及煤自燃程度6个阶段的预警指标气体判定和对应的温度范围.
In order to realize early warning of mine fire, a multi-source information fusion technology is adopted to integrate the index data of coal mine safety monitoring system, fire tube monitoring system, wireless ad hoc network temperature monitoring system and distributed optical fiber temperature monitoring system. Based on the experimental study , Field observation, expert experience and other data, a multi-source information fusion warning system for mine fire was established. Combined with artificial neural network and multi-indicator warning reasoning, a gray correlation analysis method was used to establish the experimental data fitting function calculation method, Multi-source information fusion algorithm to deal with multi-source fire information from different locations and with different physical meaning, and draw fire early warning index system and fire development law as well as early warning index gas judgment and corresponding temperature range of 6 stages of coal spontaneous combustion .