摘要
解决在矿井监控中传统粉尘采样器不能满足在线监控粉尘浓度的问题,采用一台主机带多台分机的实时监测模式,将改进的数据融合算法应用到主机和分机中对粉尘数据进行实时处理.结果表明:改进的数据融合算法使粉尘传感器测量结果的误差得到了有效的控制;一台主机带多台分机分别计算测量参数的模式使矿井粉尘浓度测量实时性得到解决.该成果对煤矿井下粉尘数据在线监控具有一定的理论价值和实用意义.
In order to solve the problem that the traditional dust samplers cannot meet the requirements of online monitoring on dust concentration in a coal mine,this study uses a host with multiple extensions for real-time dust monitoring.In the same time,the improved data fusion algorithm is applied to the host and the extensions to process the dust data in real-time.The study results show that the measurement error of dust sensors is effectively controlled by the improved data fusion algorithm.The model of a host with multiple extensions can effectively monitor the mine dust concentration in real time.The study result has a theoretical and practical significance for online monitoring of dust data in a coal mine.□□□□□□□□□□□□□□□□□
出处
《辽宁工程技术大学学报（自然科学版）》
CAS
北大核心
2012年第6期846-849,共4页
Journal of Liaoning Technical University (Natural Science)
基金
辽宁省百千万人才基金资助项目(2010921098)
辽宁省教育厅基金资助项目(2009A352)
关键词
煤矿
数据融合
粉尘浓度
在线监测
喷雾除尘
多机处理
自适应加权算法
光电式粉尘传感器
coal mine
data fusion
dust concentration
dust real time detection
wet scrubber
on-line monitoring
spraying dust removal system
multi-computer processing
adaptive weighted algorithm
photoelectric dust sensor
