煤矿巡检机器人巷道气体环境智能检测系统设计

目前井下危险气体巡检机器人大多采用升降机构或固定探头的形式进行气体环境感知,对机器人的行驶灵活性产生了影响,且受机器人本体结构的限制,大多数巡检机器人只能检测到传感器安装范围内的局部气体环境信息,缺乏针对巷道任意截面空间内的气体浓度检测。针对以上问题,设计了一种基于气体扩散模型的煤矿巡检机器人巷道气体环境智能检测系统。该系统以气体扩散理论为基础,结合煤矿巷道气体环境特点,引入巷道壁帮围岩、风速、气体扩散系数对煤矿巷道气体扩散模型的影响,采用虚拟像源法和遗传算法优化BP神经网络智能算法建立了巷道气体扩散优化模型。通过传感器检测系统获取巡检机器人在行进过程中任意点的气体浓度等环境信息,代入气体扩散优化模型求解最优气体扩散系数,通过输入巷道某点坐标位置,可计算求解相应点的气体浓度分布情况,随着巡检机器人的移动,可获取其路径中不同巷道截面上气体浓度分布数据。实验结果表明,该系统能够解算出符合检测误差要求的巷道任意截面上任意点的气体浓度,并实现动态实时检测;克服了传统煤矿巷道气体检测方法的局限性。利用巡检机器人取代人工巡检作业,为煤矿井下气体智能检测提供了一种新思路与新方法。

Design of intelligent detection system of gas environment in roadway of coal mine inspection robot

At present,most underground gas inspection robots use lifting mechanism or fixed probe to sense gas environment,which influences robot's driving flexibility,and due to the limitation of robot body mechanism,most inspection robots can only detect local gas environment information within sensors installation range,and lack of gas concentration detection in any cross-sectional space of the roadway.In view of the above problems,an intelligent detection system of gas environment in roadway of coal mine inspection robot based on gas diffusion model was designed.The system is based on theory of gas diffusion,combined with gas environment characteristics of coal mine roadways,and introduces influence of wall rock,wind speed and gas diffusion coefficient on gas diffusion model,and establishes a gas diffusion optimization model in roadway by using virtual image source method and BP neural network intelligent algorithm optimized by genetic algorithm.The environmental information such as gas concentration at any point of the inspection robot in the moving process is obtained by the sensor detection system,and the gas diffusion optimization model is substituted to solve the optimal gas diffusion coefficient.The gas concentration distribution at the corresponding point can be calculated and solved by inputting the coordinate position of a certain point in the roadway.With movement of the robot,the gas concentration distribution data on different coal mine roadway sections under its displacement path can be obtained.The experimental results show that the system can calculate gas concentration at any point on any cross-section of the roadway that meets the detection error requirements,and achieve dynamic real-time detection;it overcomes limitations of traditional coal mine roadway gas detection methods.Using inspection robots to replace the manual inspection of coal mine gas can provide a new idea and method for intelligent detection of gas in coal mines.