轮轨力在线监测类系统设备状态智能预警技术研究

Research on Intelligent Early Warning Technology for Equipment State of Wheel and Rail Force Online Monitoring System

以车辆运行品质轨边动态监测系统为对象,统计分析其不良检测数据,研究影响设备状态的具体因素,确定了以定时消息、过车过程中软件及检测数据状态、数据统计信息状态和日报表为主的自检信息内容及传输机制。通过分析砝码车标准值调整变动规律及运行现状,制定了标准值定期录入机制。研究了设备故障预警评估方法,开发了基于B/S结构的Web系统监控预警平台,可提供分级设备状态监控、趋势展示、预警、查询、统计等功能。预警平台的应用大幅降低了设备维护人员的劳动强度,提高了工作效率,实现了设备故障的超前预判,并能有效缩短故障时间,为设备维护单位提供有力的技术支撑。

Taking the dynamic monitoring system of vehicle operation quality rail edge as the object,through the statistical analysis of its bad detection data,the specific factors affecting the equipment state were studied.Based on the timing message,the software during the passing process,the state of the data,the state of the data statistics and the daily report,the self-test information content and transmission mechanism were determined.The standard value periodic input mechanism was formulated by analyzing the change law and operation state of the standard value adjustment of the standard vehicle.The equipment failure early warning assessment method was researched,and the Web system monitoring and early warning platform based on B/S structure was developed.It can provides hierarchical device state monitoring,trend display,early warning,query,statistics and other functions.The application of the early warning platform can greatly reduce the labor intensity of the equipment maintenance personnel,improve the work efficiency,realize the advance prediction of the equipment failure,effectively shorten the failure time,and provide powerful technical support for the equipment maintenance unit.