摘要
为了更好地解决目前煤矿自燃火灾探测的误报、漏报及方法单一等问题,提出了一种基于机器视觉的多传感器融合的煤矿自燃火灾智能预警系统。通过构建的煤矿井下视觉网络系统对煤矿自燃可疑区域进行图像采集、分析和处理,结合温湿度传感器、光感传感器在特定环境深度融合技术下采集的煤矿环境参数信息,并将数据信息实时地传输到控制中心。实现了对煤矿自燃火灾的实时监测、预警功能,使煤矿自燃火灾的监测预警的准确性大大提高,具有很好的应用前景。
In order to better solve the spontaneous fire in coal mine detection of false positives and false negatives and single method etc., based on machine vision multi-sensor fusion of coal mine spontaneous fire intelligent early warning system is proposed. Through the construction of coal mine underground visual network system of suspicious of spontaneous combustion in coal mine areas were image acquisition, analysis and processing, combined with temperature and humidity sensor, light sensor in the specific environment depth fusion technology to collect environmental parameters of coal mine information and data information real-time transmission to the control center. The real-time monitoring and early warning function of the coal mine spontaneous combustion fire is realized, and the accuracy of the monitoring and early warning of the spontaneous combustion of the coal mine is greatly improved.
出处
《煤矿机械》
2016年第8期16-17,共2页
Coal Mine Machinery
基金
广东省科技计划资助项目(2015B070701025
2013B061800058
2015B010918001)
关键词
煤矿自燃
机器视觉
多传感器
预警监测
coal spontaneous combustion
machine vision
multi-sensor
warning and monitoring
