多源信息簇融技术在煤矿瓦斯监测中的应用

Mine gas monitoring by multi-source information clustering fusion

由于煤矿井下环境的复杂性及动态变化性,导致监测煤矿环境中有害气体浓度及准确率难度大大增加。针对传统的传感器监测煤矿井下环境存在采集数据形式单一、可靠性低、误差大等缺点,结合计算机技术与无线传感技术提出了一种对多种异质气体源进行采样,然后利用提出的强分类算法进行优化筛选,筛选出气体浓度前后变化大的几组数据,再进行深度融合的安全监测方法。通过实验验证该方法能够明显地提高矿井监测系统的可靠性。

Due to the complexity and the dynamic changes of the coal mine environment, the concentrations of harmful gases are difficult to be accurately monitored. The traditional monitoring methods use a single sensor to pick-up information, and the collected data have simple data form, low reliability, big error and so on. Concerning these problems, a new method was proposed in this paper, that is, sampling a variety of heterogeneous gases sources, and then taking advantage of the strong classification algorithm to filter, lastly fusing the above obtained information. As experiments state, the new method significantly improve the reliability of the mine monitoring system.