铁道货运2024，Vol.42Issue(4)：38-45,8.DOI:10.16669/j.cnki.issn.1004-2024.2024.04.07
基于动态多源数据采集的铁路车辆装载状况检测和智能分析系统
Railway Vehicle Load Condition Detection and Intelligent Analysis System Based on Dynamic Multi-Source Data Collection
摘要
Abstract
By analyzing the shortcomings of current manual detection methods for railway vehicle loading and related existing systems,a railway vehicle load condition detection and intelligent analysis system with dynamic multi-source data collection was designed.This system collects,analyzes,and processes multi-source data on vehicle load conditions by utilizing a combination of multimodal sensors,RS485 transmission,and narrow band Internet of Things(NB-IoT)transmission technologies.Multimodal sensors are integrated with edge computing to achieve manual,automatic,remote,and automatic fault recovery control modes,as well as four functional modules,including basic information management module,detection door system module,alarm system module,and application maintenance module.According to the current status of domestic and international railway freight transportation,this study compared and analyzed the technology and equipment available for railway freight safety detection and monitoring.It demonstrated technical advantages and application effects that can effectively guide loading optimization and enhance efficiency.This system holds significant application value in the railway freight transportation sector.关键词
铁路货运/多源数据/智能分析/决策支持/人工智能Key words
Railway Freight Transportation/Multi-Source Data/Intelligent Analysis/Decision Support/Artificial Intelligence分类
交通工程引用本文复制引用
张志国,傅健,辛向党,李建国..基于动态多源数据采集的铁路车辆装载状况检测和智能分析系统[J].铁道货运,2024,42(4):38-45,8.基金项目
中国铁路兰州局集团有限公司科技研究开发计划课题(LZJKY2023009-1) （LZJKY2023009-1）
国家铁路局高原铁路运输智慧管控铁路行业重点实验室开放基金项目(GYYSHZ2306) （GYYSHZ2306）
