摘要
跑偏是带式输送机常见的运行故障之一,在实际生产中大多通过跑偏传感器和纠偏装置对其进行监测和纠正。随着煤矿智能化建设的进一步深入,对带式输送机的智能化水平也提出了更高的要求。提出了一种基于数字图像处理的带式输送机运行状态监测技术,通过Hough变换对输送带边缘直线特征进行提取和处理,进而实现对跑偏状态的判断以及可视化在线监测。该技术充分利用了机器视觉的非接触无阻无损测量、精度高等特点,为带式输送机运行状态的智能化监测提供了技术方案。
Deviation is one of the common operating fault of belt conveyor.In actual production,deviation sensors and correction devices are used to monitor and correct them.With the further deepening of the intelligent construction of coal mines,higher requirements have been put forward for the intelligent level of belt conveyor.Proposed a belt conveyor operating state monitoring technology based on digital image processing,which extracts and processes the linear features of the conveyor belt edge through Hough transform,and then realizes the judgment of the deviation state and visual online monitoring.The technology makes full use of the non-contact,non-impeded,non-destructive measurement and high precision features of machine vision,and provides a technical solution for the intelligent monitoring of the operating state of belt conveyor.
作者
王平
Wang Ping(College of Marine Science and Engineering,Shandong University of Science and Technology,Qingdao 266590,China)
出处
《煤矿机械》
2021年第2期168-170,共3页
Coal Mine Machinery
关键词
带式输送机
图像处理
机器视觉
跑偏故障
belt conveyor
image processing
machine vision
deviation fault
