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基于WebGL的城际铁路线路运输动态监控系统设计

Design of Dynamic Monitoring System for Intercity Railway Line Transportation Based on WebGL
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摘要 目前设计的城际铁路线路运输动态监控系统耗时过程,动态监测过程稳定性较差。为了解决上述问题,基于WebGL设计了一种新的城际铁路线路运输动态监控系统。采用GPS动态定位传感器、RS485通信装置、STM32F103ZET6控制芯片等硬件设备优化动态监控系统硬件结构,整合划分采集模块、通信模块、主控模块与告警模块四大功能区,提高系统通信与控制效率。对采集到的铁路线路运输数据进行清洗筛选,提取关键特征进行标记存储后,利用WebGL进行三维空间可视化渲染,动态监测运输目标视点的位置变化,并根据时序向量进行合理预测,提高监控系统智能化水平。实验结果证明,文章研究的系统多线程数据处理能力更强,在对1500字节数据进行监测时,耗时低于56ms,稳定性较好,动态预测准确度相对较高,应用效果良好。 The currently designed dynamic monitoring system for intercity railway transportation is timc-consuming and has poor stability in the dynamic monitoring procss.To address the aforementioned issues,a new dynamic monitoring system for intercity railway line transportation was designed based on WebGL.Using GPS dynamic positioning sensors,RS485 communication devices,STM32F103ZET6 control chips and other hardware cquipment to optimize the hardware structure of the dynamic monitoring system,integrating and dividing the acquisition module,communication module,main control module,and alarm module into four functional areas,improving the efficiency of system communication and control.Clean and filter the collected railway transportation data,extract key features for labeling and storage,and use WebGL for 3D spatial visualization rendering.Dynamically monitor the position changes of transportation target viewpoints and make reasonable predictions based on time series vectors to improve the intelligence level of the monitoring system.The experimental results show that the system studied in this article has stronger multi-threaded data processing capabilities.When monitoring 1500 bytes of data,the time consumption is less than 56ms,the stability is good,the dynamic prediction accuracy is relatively high,and the application effect is good.
作者 程胜月 信文雪 CHENG Shengyue;XIN Wenxue(Department Of Infomation Engineering,Zhengzhou Institute of Science and Technology,Zhengzhou Henan 450064,China)
出处 《长江信息通信》 2024年第8期81-84,127,共5页 Changjiang Information & Communications
基金 郑州科技学院校级科研项目:基于深度学习的城市生活垃圾智能分类技术研究及应用:2022XJKY02。
关键词 WEBGL 城际铁路 运输动态 监控系统 WebGL Intercity railway Transportation dynamics Monitoring system
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