China Coal Research Institute Co. , Ltd.
Engineering Research Center of Coal Mines Emergency Technology Equipment Engineering
Beijing Coal Mine Safety Engineering Technology Research Center

煤矿主运输系统普遍存在人工点巡检、无法实现远程集中控制、监测数据不完善、缺乏智能控制机制、无高效的故障检测手段等问题。针对上述问题提出了分段提取关键帧的巡检视频分析方法,形成了煤矿主煤流运输巡检异常检测技术,并将其运用于巡检机器人系统中,提高了故障检出率。设计的主煤流运输智能控制系统,实现了基于煤流跟踪的智能调速和顺煤流一键启动功能,并研究了带式输送机的最优启动速率。基于视觉和激光雷达融合的输送带撕裂视觉检测技术和基于声纹分析的带式输送机状态监测和故障诊断技术,提升了主煤流系统运行的稳定性。

There are many problems in the main transportation system of coal mine, such as manual spot inspection, remote centralized control can not be implemented, monitoring data is incomplete, intelligent control method is lacked, there is no efficient means of fault detection. In view of the above problems, the method of segment extraction key frame inspection video analysis is put forward, and the inspection video anomaly detection technology is developed for coal mine main transportation. The technology is applied in the inspection robot system, and the fault detection rate is improved. The intelligent control system of main coal flow transportation is designed, which realizes the intelligent speed regulation based on coal flow tracking and the one-button down-flow startup function. The stability of the main transportation system is improved using the visual detection technology of conveyor belt tear based on vision and lidar fusion and the state monitoring and fault diagnosis technology based on voiceprint analysis of belt conveyor.

张耀明, 李 标. 煤矿主运输系统智能控制技术研究与应用 [J]. 煤炭工程, 2023, 55(7): 22-27.