与 VR FleetCare 合作进行预测分析
技术
- 分析与建模 - 边缘分析
- 分析与建模 - 预测分析
- 功能应用 - 远程监控系统
- 基础设施即服务 (IaaS) - 云计算
- 基础设施即服务 (IaaS) - 其他
- 网络与连接 - 网关
适用行业
- 铁路与地铁
适用功能
- 维护
用例
- 预测性维护
客户
VR 车队护理
关于客户
VR FLEETCAREA 多品牌铁路设备服务提供商 VR FleetCare 是芬兰铁路运营商 VR 集团的子公司。我们为客户提供优质的铁路交通设备维修、保养和生命周期服务以及技术
挑战
就生命周期成本和交通安全而言，转向架是铁路车队中最重要的组成部分。除了为铁路车队所有者节省大量成本外，数据驱动的维护还将提高机车车辆的安全性和可用性。预测性维护能力将提高列车的可靠性、成本效益和乘客舒适度。如果能够在机车车辆故障导致交通中断之前对其进行预测，那么列车交通将更加可靠地运行。
解决方案
此次合作基于 VR FleetCare 的铁路车队技术专长和车队维护优化，以及 EKE-Electronics 在列车自动化系统和远程状态监测方面的经验。
目的是开发一个系统来预测维护需求并优化转向架的服务程序。通过传感器和传感器网关从火车上获取数据，并应用云计算和边缘计算的智能组合进行信号分析。该解决方案利用 EKE 的英国子公司 Humaware 开发的自适应异常检测器和预测分析，并集成到 EKE 的基于云的远程监控软件 Smartvision™ 中。
传感器和传感器网关将在今年安装在 VR 集团的机车和电动火车的转向架上。预计明年开发工作将取得更广泛的成果。
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