基于机器视觉的带式输送机跑偏及堆煤故障诊断系统设计  

Design of Fault Diagnosis System for Belt Conveyor Deviation and Coal Stacking Based on Machine Vision

作　　者：侯小梅 Hou Xiaomei(Equipment Management Center,CHN Energy Shendong Coal Group Co.,Ltd.,Yulin 719315,China)

机构地区：[1]国能神东煤炭集团有限责任公司设备管理中心,陕西榆林719315

出　　处：《煤矿机械》2024年第9期164-166,共3页Coal Mine Machinery

摘　　要：针对带式输送机跑偏及堆煤故障频发的现象,提出了一种基于双基准的检测方法对输送带跑偏进行故障诊断,并采用双目相机对煤流堆煤高度进行实时监测,设定对应的阈值对设备不安全状态进行预警。搭建基于机器视觉的带式输送机跑偏及堆煤故障诊断系统,完成硬件选型及上位机设计。试验结果表明,跑偏故障诊断准确率为99%,跑偏程度计算误差小于3%;堆煤故障诊断准确率为97.5%,煤流高度计算误差在5%以内,可用于工业生产保障。In response to the frequent occurrence of belt conveyor deviation and coal stacking faults,proposed a dual baseline detection method for fault diagnosis of conveyor belt deviation,and used a binocular camera to monitor the coal stacking height of coal flow in real time.Corresponding thresholds were set to warn the unsafe equipment conditions.A fault diagnosis system for belt conveyor deviation and coal stacking based on machine vision was built,and hardware selection and upper computer design were completed.The experimental results show that the accuracy of deviation fault diagnosis is 99%,and the calculation error of deviation amount is less than 3%.The accuracy of coal stacking fault diagnosis is 97.5%,and the calculation error of coal flow height is within 5%.It can be used for industrial production guarantee.

关 键 词：机器视觉 带式输送机 跑偏 堆煤 故障诊断 

分 类 号：TD528.1[矿业工程—矿山机电]