基于图像识别的皮带运输机故障自动诊断方法研究  

Research on Automatic Diagnosis Method of Belt Conveyor Faults Based on Image Recognition

作　　者：党高峰 Dang Gaofeng(Shanxi Coking Coal Shanxi Coal International Hanjiawa Coal Industry Co.,Ltd.,Datong Shanxi 037100,China)

机构地区：[1]山西焦煤山煤国际韩家洼煤业有限公司,山西大同037100

出　　处：《机械管理开发》2025年第3期204-206,共3页Mechanical Management and Development

摘　　要：为提高皮带运输机故障检测的自动化水平,基于皮带运输机结构、工作原理、常见故障类型及自动诊断方法,采用图像采集、预处理、特征识别与分类等技术,设计并实现了皮带运输机故障自动诊断系统,通过图像采集与预处理模块、故障特征识别与分类模块、自动诊断与报警模块等模式来实现皮带运输机故障自动诊断。结果表明,该系统能精准识别皮带运输机运行中的多种常见故障,检测精度高,响应时间短,可全面提升皮带运输机设备故障诊断的效率与准确性。In order to improve the automation level of belt conveyor fault detection,this study is based on the structure and working principle of belt conveyor,common types of faults and automatic diagnosis methods,and designs and implements an automatic diagnosis system for belt conveyor faults by adopting the technologies of image acquisition,pre-processing,feature recognition and classification,etc.The automatic diagnosis system is realised through the modes of image acquisition and pre-processing module,fault feature recognition and classification module,automatic diagnosis and alarm module,and so on.Through the modes of image acquisition and preprocessing module,fault feature recognition and classification module,automatic diagnosis and alarm module,the automatic diagnosis of belt conveyor fault diagnosis is achieved.The results show that the system can accurately identify a variety of common faults in the operation of the belt conveyor,with high detection accuracy and short response time,which can comprehensively improve the efficiency and accuracy of the belt conveyor equipment fault diagnosis.

关 键 词：图像识别 皮带运输机 故障诊断 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]