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

该项目将利用计算机视觉技术应用于现有的视频片段，并捕获一种新型的视频传感器，以解决两个主要挑战，这两个挑战因天气事件而加剧，并可能导致铁路关闭。提供可以预测和预防此类挑战的方法将有助于铁路对天气事件和季节不可知性变得更有弹性。以下两个方面将得到解决：* 极端炎热的天气导致OLE电线延伸，并导致张紧器与地面接触，这可能会降低张力并导致损坏或事件dewirement。利用现有的视频画面，该项目将自动识别OLE张紧器，定位和测量它们，并生成一个实时资产地图与当前状态水平。这可以作为数字孪生模型的一部分，并输入到能够提醒维护人员注意问题的系统中，以便他们能够采取预防措施。炎热、寒冷和潮湿的天气也会产生影响，导致绝缘体等电气资产产生电晕放电。电晕放电是设备潜在损坏和故障的早期警告信号，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服务列车上安装紫外电晕相机，并通过实时数据传输和处理实现自动数据采集。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，以确保最佳的精确度和召回率，从而确保操作上有用的工具。这两种事件都可能在延误，安全和客户体验方面对铁路产生非常大的影响。通过提供具有防止这些发生的能力的工具，铁路将具有对天气条件的增加的弹性。

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.