多传感器数据融合在煤矿安全监测中的应用  

Application of Multi-sensor Data Fusion in Coal Mine Safety Monitoring

作　　者：孙延飞[1] 李智超[1] 王静[1] 郭继毅[1] 

机构地区：[1]三一重型装备有限公司(沈阳),辽宁沈阳110027

出　　处：《煤矿安全》2012年第1期102-104,共3页Safety in Coal Mines

摘　　要：将多传感器融合技术应用到煤矿安全监测中,结合煤矿井下的实际环境,提出了一种分级的多传感器数据融合模型,在数据级融合中采用Bayes估计,并通过设定软硬阈值避免传感数据的冗余;基于模糊集系统理论,决策级融合中将数据级融合结果模糊化,结合专家知识库,经过全局融合的合成运算和决策规则,得到煤矿监测环境安全状况的精确估计;该模型即保证了监测结果的准确性,又兼顾了系统的负荷。This paper applies the multi-sensor information fusion technology to Coal Mine Safety Monitoring.Combined with the actual environmental of coal mine,a grading architecture was proposed.Bayes estimation was used in data-level,through set soft and hard threshold to avoid sensor-data redundancy.Based on the fuzzy set theory,the result of data-level fusion was fuzzed in decision fusion.Accurate estimation of Coal Mine Safety obtained by means of expert knowledge database and decision rules.This architecture not only ensures the accuracy of the result,but also consideration to the system load.

关 键 词：煤矿安全 数据融合 BAYES估计 模糊理论 

分 类 号：TD671[矿业工程—矿山机电]