摘要
针对现有煤炭铁路装车站车号识别系统存在的不足,提出了基于AI视频识别的煤炭铁路装车车厢信息识别的新方法,即利用一种基于YOLOv5的视频识别系统,以有效解决RFID损坏、漏检等问题。结果表明,该系统在车厢信息识别方面具有较高的识别准确率和较快的处理速度,能够对车厢的编号、车型等信息进行准确的识别和分类。
Aiming at the shortcomings of the existing coal railroad loading station vehicle number recognition system,a new method of coal railroad loading vehicle information recognition based on AI video recognition is proposed,i.e.,utilizing a system based on the Yolov5 video recognition system,in order to effectively solve the problems of RFID damage and leakage detection.The results show that the system has high recognition accuracy and fast processing speed in carriage information recognition,and can accurately recognize and classify carriage numbers,vehicle types,and other information.
作者
白龙
宋万军
李震宇
BAI Long;SONG Wanjun;LI Zhenyu(Guoshen Company Shangyuquan Coal Mine,State Energy Group,Xinzhou,Shanxi 036500,China)
出处
《自动化应用》
2024年第17期27-31,共5页
Automation Application
关键词
铁路装车
人工智能
车厢信息识别
智能装车
railway loading
AI
carriage information recognition
intelligent loading
作者简介
白龙,男,1987年生,硕士,工程师,从事选煤厂管理工作。
