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作 者:常浩[1]
机构地区:[1]中国矿业大学机电工程学院,江苏徐州221008
出 处:《工矿自动化》2015年第8期100-104,共5页Journal Of Mine Automation
基 金:江苏高校优势学科建设工程资助项目
摘 要:针对现有提升机平衡尾绳故障检测依靠人工检测存在难度大、危险性高等问题,设计了基于机器视觉的提升机平衡尾绳在线监控预警系统。该系统通过CCD摄像机实时采集现场尾绳图像,然后对图像进行积分投影和Hu不变矩图像特征参数提取,最后通过图像特征分类器进行模式识别以获得故障信息,进而进行故障判断。该系统还可利用局域网和以太网实现对提升机尾绳状态的远程监控,可及早发现尾绳绞绳、断绳、尾绳间距不均和弯曲变形等故障,解决了目前尾绳故障检测周期长和无法及时发现的难题。In view of problems of difficult detection and high risk in manual vision inspection of balancing tail rope failures of hoist, an on-line monitoring and early warning system of balancing tail rope of hoist based on machine vision was designed. The system uses CCD camera to real-timely collect on-site images of tail ropes of hoist, extracts characteristic parameters of the image by integration projection and Hu invariant moment, and adopts image feature classifier to do pattern recognition to get fault information and judge fault. Meanwhile, the system can remote monitor state of the tail rope of hoist by local area network and Ethernet, and can find out failures of the hoisting tail ropes, such as twisted rope, broken rope, the disproportional spacing and bending deformation of tail ropes, which solves problem of long detection cycle and fail to find fault of tail ropes timely.
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