摘要
为了提升公路货车特殊车辆车厢状态监测维修系统工作效率,解决目前监控成本高的问题,分析研究货车状态监测维修系统对特殊车辆的修程预测,升级了货车特殊车辆车厢的内置物联网大数据系统,在实地试验中将系统监测数据与原系统监测数据进行对比,结果显示:结构磨损直接监测数据的误差率有所下降,报警数据的敏感度有所提高。
In order to improve the working efficiency of the condition monitoring and maintenance system for special vehicles of highway trucks,control the dynamic operation of trucks in real time,solve the problems of high monitoring cost and high misjudgment rate,analyze and study the repair process prediction and application of the truck condition detection and maintenance system for special vehicles,and improve the safety of special highway transportation,the built-in Internet of things big data system of special vehicle compartments of freight cars is upgraded,and the monitoring data of the new system is compared with that of freight cars under mature technical conditions.It is concluded that the error rate of direct monitoring data of structural wear is decreased,and the sensitivity of indirect data and mining data is improved.Through data analysis,it is considered that the system is more mature,and the monitoring technology of the system for vehicle status can be improved.
作者
孟宪国
Meng Xianguo(China Energy Railway Equipment Co.,Ltd., Beijing, 100120, China)
出处
《机械设计与制造工程》
2022年第3期123-126,共4页
Machine Design and Manufacturing Engineering
关键词
特殊车辆
货车状态监测维修系统
技术应用
highway truck
special vehicles
repair forecast
transportation safety
vehicle internet of things
