摘要
针对目前井下带式输送机大多配置变频控制器,但许多变频器在运输过程中被设置在固定频率下运行,特别是较长距离、较大功率的带式输送机可能受到各种综合因素的影响,缺乏对整体运行状态的优化控制的问题,文章基于机器视觉识别技术和物联网传感技术,监测监控带式输送系统运输状态,利用具有人工智能功能的内嵌GPU摄像机和基于5G技术的CPE终端智能设备,通过视频识别技术分析,通过CPE智能终端设备控制带式输送的运行速度,优化带式输送机整体的运行状态,逐步实现对带式输送机传送的智能化控制,达到运行高效、节能环保、绿色开采的目的。
Most of the current underground belt conveyors are equipped with variable frequency controllers,but many inverters are set to operate at a fixed frequency during transportation.Especially for long distance and high power belt conveyors,which may be subjected to various comprehensive factors,the optimal control of the overall operating state is often ignored.the transport status of the belt conveyor system is monitored,based on machine vision recognition technology and Io T sensing technology,AI cameras with embedded GPU and 5 G-based CPE terminal intelligent device are applied to analyze and control the belt conveyor running speed,optimize the overall running state of the belt transportation system,and gradually realizes the intelligent control of the belt transportation,achieving the goal of high efficiency,energy saving and environmental friendly,and green operation.
作者
郝志伟
HAO Zhi-wei(Shanxi Coking Coal Group Co.,Ltd.,Taiyuan 030024,China)
出处
《煤炭工程》
北大核心
2019年第9期37-41,共5页
Coal Engineering
关键词
机器视觉识别
煤矿带式输送
自适应控制系统
machine vision recognition
coal mine belt conveyor
adaptive control system
作者简介
郝志伟(1968—),男,山西太原人,硕士研究生,高级工程师,现任山西焦煤集团有限责任公司大数据中心主任、双创中心主任,主要研究领域为信息化、两化融合,E-mail:haozhiwei@sxcc.com.cn。
