摘要
随着城市轨道交通运营可靠性要求的持续提升,站台门系统作为保障乘客安全和运营效率的关键设备,其智能控制单元运维可靠性面临新挑战。针对智能控制单元运维提出完整预测性维护技术框架,依托多源信息感知和状态监测,实时完成关键运行参数采集,经数据融合与特征提取,构建健康状态评估指标。实测数据证实,所提系统可实现故障早期预警,平均预警时间超过500 h,故障识别准确率超96%,维护成本降低约52%,非计划停机减少83%。这一研究为提升站台门系统可靠性和维护效率提供了切实有效的技术支持。
With the continuous improvement of the operational reliability requirements for urban rail transit,the intelligent control unit of the platform door system,as a key equipment for ensuring passenger safety and operational efficiency,faces new challenges in terms of its operational reliability.A complete predictive maintenance technical framework for the operation of the intelligent control unit has been proposed.Relying on multi-source information perception and condition monitoring,it can complete the real-time collection of key operating parameters.Through data fusion and feature extraction,health status evaluation indicators can be constructed.The measured data confirm that the proposed system can achieve early fault warning,with an average warning time exceeding 500 h,a fault identification accuracy rate of over 96%,a maintenance cost reduction of approximately 52%,and a reduction of 83%in unplanned downtime.This research provides practical and effective technical support for improving the reliability and maintenance efficiency of the platform door system.
作者
蔡云龙
CAI Yunlong(Chengdu Metro Operation Co.,Ltd.,Chengdu 610051,China)
出处
《智能物联技术》
2026年第2期160-164,共5页
Technology of Io T& AI
关键词
预测性维护
站台门
智能控制单元
predictive maintenance
platform door
intelligent control unit
