Railway Vehicle Load Condition Detection and Intelligent Analysis System Based on Dynamic Multi-Source Data Collection
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.
国家科技期刊平台
NSTL
万方数据
维普
