Protection and Resilience for OLE using Computer Vision Techniques (PROLECT)

该项目将利用计算机视觉技术处理现有的视频片段，并捕获一种新型的视频传感器，以解决两项主要挑战，这两项挑战因天气事件而加剧，并可能导致铁路关闭。提供能够预测和预防这类挑战的手段，将有助于使铁路对天气事件和季节不可知性变得更有弹性。将解决以下两个方面的问题：*极端炎热的天气会导致OLE电线延长，并导致张力器接触到地面，从而降低张力，造成损坏或断开电线。利用现有的视频片段，该项目将自动识别OLE张紧器，定位和测量它们，并生成具有当前状态水平的实时资产地图。这可以用作数字孪生模型的一部分，并输入能够提醒维护人员注意问题的系统，以便他们能够采取预防措施。*炎热、寒冷和潮湿的天气也会对绝缘体等电气资产产生电晕放电的影响。电晕放电是设备潜在损坏和故障的早期预警信号，可以作为预测性维护制度的一部分进行测量，以优先考虑预防性维护活动。该项目将在测量车队或现役列车上安装UV Corona相机，通过实时数据传输和处理实现自动数据捕获。结果将由经验丰富的工作组进行评估，以调整和修改电晕事件的级别，以确保达到最佳的精度和召回水平，确保工具在操作上有用。这两件事都会对铁路延误、安全和乘客体验产生很大影响。通过提供能够防止这些情况发生的工具，铁路将增强对天气条件的适应能力。

This project will utilise Computer Vision techniques applied to existing video footage and capturing a new type of video sensor to address two main challenges which are exacerbated by weather events and can result in the railway being closed. Providing means in which these type of challenge can be predicted and prevented will help provide the railway to become more resilient to weather events and season agnostic.The following two areas will be addressed:* Extreme hot weather causes OLE wires to extend and cause the tensioners to come into contact with the ground which can reduce tension and cause damage or event de-wirement. Utilising existing video footage this project will automatically identify OLE tensioners, position and measure them and generate an live asset map with current status level. This can be utilised as part of a digital twin model and fed into systems which are able to alert maintainers to the issue so they are able to take preventative action.* Hot, cold and humid weather can also have an impact causing Corona discharge from electrical assets such as insulators. The Corona discharge is an early warning sign of potential damage and failure of the equipment and can be measured as part of a predictive maintenance regime to prioritise preventative maintenance activities. This project will install a UV Corona camera onto a measurement fleet or in-service train and enable automated data capture with real-time data transmission and processing. The results will be evaluated by experienced working groups to tune and amend the level of Corona events to ensure an optimum level of precision and recall ensuring an operationally useful tool.Both of these events can have very impacts on the railway in terms of delay, safety and customer experience. By providing tools which have the capability of preventing these from occurring the railway will have an increased resilience to the weather conditions.