DepotMATE - Multi-sensor Automated Train Examination

该项目和DepotMATE(多传感器自动列车检查)解决方案的交付旨在应对与车辆段车辆检查相关的安全和效率挑战。多样化和拥堵的英国铁路网依赖于高效的车站运营，以确保客运、货运、轻轨和重轨服务安全、准时运行，并拥有高绩效的资产。由于需要大量的检查计划来确保资产的有效运行，传统的人工检查需要大量资源，这对运营商和乘客都是有成本的，因为服务受到车辆段延误的影响。该项目综合了一系列技术，包括传感器融合、先进的机器学习和One Big Circle行业领先的智能视频专业知识，使操作员能够在更短的时间内远程检查多种资产状况。DepotMATE系统将包括一个多传感器轻型检查系统，部署在车辆段或线路上，并定位为捕获经过的机车车辆。DepotMATE结合了热像、声学和前置摄像机和传感器，以及通过边缘处理额外传输列车上的数据，将在车辆经过时同时捕获过多的关键数据。“即插即用”设计将使合作操作员能够为他们的特定单元配置传感器，有效地针对每个操作员的检查要求和必要的检查区。DepotMATE将为操作员提供广泛的车辆自动化监测数据，以确保在管理车辆段运营时以具有成本效益的方式分配资源，并确保成功交付前瞻性维护，帮助减少昂贵的被动维修并优化车辆资产的维护。DepotMATE将通过应用机器学习模型，帮助车辆检查活动进一步自动化，以自动检测明显的故障/车辆污染、过热的部件以及可能表明车轮或制动系统有缺陷的声发射。数据将通过One Big Circle的自动智能视频审查(AIVR)平台以极低的延迟在线访问，以使车辆段操作员、控制单元、和车队管理人员远程检查他们仓库内的每一辆车。车辆清洁度、资产状态和车辆在车辆段内的分配等方面将只需按一下按钮就可以提供给项目的合作运营商，大大减少了人员在轨道旁行走的要求，同时使用户能够告知预测性维护决策。

This project and the delivery of the DepotMATE (Multi-sensor Automated Train Examination) solution aims to meet the safety and efficiency challenges associated with depot-based rolling stock inspections. The diverse and congested UK rail network relies on efficient depot operations to ensure passenger, freight, light and heavy rail services run safely and on time, with high-performing assets. With the vast volume of inspection scheduling required to ensure assets are operating effectively, traditional manual examinations require a large amount resource, coming at a cost to both the operator and passenger where services are impacted by depot delays. This project collates a host of technologies incorporating sensor-fusion, advanced Machine Learning, and One Big Circle's industry-leading Intelligent Video expertise to enable operators to remotely examine a multitude of asset conditions in a reduced timeframe.The DepotMATE system will incorporate a multi-sensory lightweight inspection system, deployed to depots or sidings and positioned to capture passing rolling stock vehicles. Combining thermographic, acoustic, and Forwards Facing Video cameras and sensors and additional transmission of train-borne data via edge-processing, the DepotMATE will simultaneously capture a plethora of critical data as rolling stock vehicles pass by. A 'plug & play' design will enable partnering operators to configure sensors for their specific units, effectively targeting each operator's examination requirements and necessary inspection zones. DepotMATE will arm operators with automated monitoring data across a breadth of rolling stock, to assure cost-effective delegation of resources when managing depot operations, and successful delivery of proactive maintenance, helping to reduce costly reactive repairs and optimise the maintenance of rolling stock assets.DepotMATE will assist further automation across rolling stock inspection activities through the application of Machine Learning models, to automatically detect visibly apparent faults/vehicle contamination, exceedingly hot components, and acoustic emissions which may signify defective wheels or braking systems.Data will be accessible in extremely low-latency online, via One Big Circle's Automatic Intelligent Video Review (AIVR) platform, to enable depot operatives, control units, and fleet managers to remotely inspect each vehicle within their depot. Aspects of vehicle cleanliness, asset status, and vehicle allocation within a depot will be presented to the project's partnering operators at the touch of a button, massively reducing requirements for personnel to walk trackside whilst empowering users to inform predictive maintenance decisions.