带式输送机智能巡检系统设计

Design of Intelligent Inspection System of Belt Conveyor

煤炭是我国主体能源和基础产业,虽然其比例正在压缩,但我国能源格局还是以煤为主。近年来,智能工业迅速发展,物联网技术与人工智能技术成为了推动煤矿智能化发展的关键因素。由于输送带存在打滑、撕裂、跑偏、脱轨等问题,因此必须对带式输送机进行监测,考虑到恶劣的巡检工况,基于GatewayWorker技术,设计了机器人智能巡检系统以代替传统的人工巡检;针对原煤中混入大量异物,输送带易跑偏、脱轨等问题,构建基于YOLOv5卷积神经网络(CNN)的异物与输送带识别模型。实验结果表明,系统设计符合可行性要求。

Coal is the main source of energy and basic industry in China.Although its proportion is compressed,China's energy pattern is still dominated by coal.In recent years,coal mine intelligence has developed rapidly.Robotics and artificial intelligence technology are necessary technologies to realize the intelligence of coal mines and improve the level of safe production in the mines.Because the belt conveyor has skidding,tearing,and other problems,it is necessary to monitor the machine.Considering the harsh patrol conditions,based on GatewayWorker technology,a robot intelligent inspection system is designed to replace the traditional manual inspection;for problems such as the amount of matter mixed in the raw coal and the conveyor is easy to run off,a foreign matter and conveyor identification model based on YOLOv5 convolutional neural network(CNN)is constructed.The experimental results show that the system design meets the feasibility requirements.