基于概念格的煤矿瓦斯数据融合预警研究  

Early warning of gas data fusion based on concept lattice

作　　者：谢丽明[1] 李建民[2] 

机构地区：[1]平顶山学院计算机科学与技术学院,河南平顶山467002 [2]平顶山学院数学与信息科学学院,河南平顶山467002

出　　处：《计算机工程与设计》2010年第21期4732-4735,共4页Computer Engineering and Design

基　　金：河南省科技攻关基金项目(102102210422)

摘　　要：提出了基于概念格的煤矿瓦斯数据融合预警算法。建立了煤矿瓦斯预警的两级数据融合模型,通过对同质多传感器数据的加权数据融合处理,使检测同一目标的多个数据融合为一个精确的、可靠的数据,减少了通信网络中的数据流量。经过数据级融合的异质多传感器数据描述了导致瓦斯事故的各种因素,利用概念格理论对异质多传感器的历史监测数据进行分析,形成预测煤矿瓦斯安全状态的决策规则。使用该预警系统可以动态监测井下瓦斯安全状况,提高瓦斯事故预警的准确性,为煤矿安全生产提供支持。Gas early-warning algorithm of coal mine based on concept lattice for data fusion is presented. It is established that two levels of data fusion model of gas early warning in mine. Weighted data fusion of homogeneous multi-sensor, more data of the same test target is fused into an accurate, reliable data. It reduces network traffic. Data of heterogeneous multi-sensor describe the factors that led to gas accidents. Using historical monitoring data, we built concept lattice of early-warning of gas, obtained the decision rules fromit. Using the early warning system can dynamically monitor conditions ofgas-related, improve the accuracy ofgas accident warning, and provide the support for the coal mine safety.

关 键 词：数据融合 概念格 瓦斯预警 煤矿安全 传感器网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]