摘要
为解决火车车厢状态监测的实时性与精准性问题,提升铁路运输安全与效率,研究融合物联网(Internet of Things,IoT)与人工智能(Artificial Intelligence,AI)技术,重点分析了高清线阵相机数据采集与智能分析算法,验证了其在车号识别与装载状态监测中的应用效果,并基于分层架构设计,提出了一种智能化监测系统,通过仿真试验与多场景测试验证了其性能。结果表明,该系统车号识别准确率达98.5%,装载状态检测灵敏度为96.8%。它可在复杂光照及天气条件下实现实时异常报警与数据记录,显著提升运输安全性与调度效率。研究成果为铁路行业智能化转型提供了可行的技术参考,具有较高的工程应用价值。
In order to solve the real-time and accuracy problems of train compartment status monitoring and improve the safety and efficiency of railroad transportation,the study integrates Internet of Things(IoT)and artificial intelligence(AI)technologies,focuses on the analysis of data collection by high-definition line array cameras and intelligent analysis algorithms,and verifies their application effects in train number recognition and loading status monitoring.Based on the hierarchical architecture design,an intelligent monitoring system is proposed,and its performance is verified through simulation experiments and multi-scenario tests.The results show that the accuracy rate of train number recognition of this system reaches 98.5%,and the sensitivity of loading status detection is 96.8%.It can achieve real-time abnormal alarm and data recording under complex lighting and weather conditions,significantly improving transportation safety and scheduling efficiency.The research results provide a feasible technical reference for the intelligent transformation of the railway industry and have high engineering application value.
作者
季中林
刘健健
朱良恺
王琨
JI Zhonglin;LIU Jianjian;ZHU Liangkai;WANG Kun(Shandong Matrix Software Engineering Co.,Ltd.,Jinan Shandong 250101,China;Zaozhuang Mining(Group)Co.,Ltd.,Zaozhuang Shandong 277000,China;Shandong Energy Yankuang Energy Jisan Coal Mine Coal Quality Shipping Department,Jining Shandong 272069,China)
出处
《信息与电脑》
2025年第9期83-86,共4页
Information & Computer
关键词
物联网
人工智能
火车车厢状态监测
铁路运输
异常报警
Internet of Things
artificial intelligence
train carriage condition monitoring
railway transportation
abnormal alarm
