Photonic sensing within civil nuclear infrastructure for lifetime extension and long-term structural health monitoring of de-commissioned plant

英国现有的核电站（NPP）已经获准延长寿命到2020年代和2030年代。使用寿命的延长与对监控的需求增加有关，以确保安全运行。为了实现这一目标，在降低新仪器基础设施投资成本的同时，需要创新和强大的传感器解决方案以及自动分析测量数据的方法。在核电站退役和部分拆除之后，许多监测系统必须在几十年内继续运行，以提醒核电站管理人任何可能造成进一步损害或人员风险的结构恶化。光子学和纤维光学有望实现高分辨率测量、多路复用、鲁棒性、安全性和寿命。因此，该EngD项目将解决过多的工程问题，为核电厂的关键土木结构开发远程监控系统。除其他事项外，该项目将开发和演示一个组合系统，用于监测容纳先进气体反应堆的压力容器的多个位置的裂纹恶化和CO2泄漏。该项目将评估一些可用于这些任务的竞争性光子技术，包括分布式和半分布式应变传感器，以及与多路复用系统兼容的各种气体传感技术。可能需要使用干涉测量技术来测量应变或位移的微小变化。将开发传感器与工厂集成的方法，确保长期稳定性，同时确保成本效益。机器学习和其他技术，例如，将研究临界点分析，以协助检测结构恶化。在实验室研究之后，将在运行的NPP中部署演示系统。该项目有望在光子系统集成和分布式光子传感器网络的自动数据分析领域推动光纤测量的当前最先进水平。

The existing fleet of nuclear power plants (NPPs) in the UK have been granted life extensions into the 2020s and 2030s. Lifetime extension is associated with an increased need for monitoring to ensure safe operation. To achieve this, while keeping the cost of investment in new instrumentation infrastructure down, innovative and robust sensor solutions and ways to analyse measurement data automatically are required. Following de-commissioning and partial de-construction of NPPs, it is critical that many monitoring systems remain operational for decades to alert the custodian of the plant of any structural deterioration that may cause further damage or risk to personnel. Photonics and fibre optics hold the promise of high-resolution measurement, multiplexing, robustness, security and longevity. Consequently, this EngD project will address the plethora of engineering issues to develop remote monitoring systems for key civil structures with an NPP. Among other things, the project will develop and demonstrate a combined system for monitoring crack deterioration and CO2 leakage in multiple locations of a pressure vessel housing an Advanced Gas Reactor. The project will assess a number of competing photonic techniques that can be employed for these tasks, including distributed and semi-distributed strain sensors, and various techniques for gas sensing, compatible with a multiplexed system. Interferometric techniques may need to be deployed to measure very small changes in strain or displacement. Methods of sensor integration with plant ensuring long-term stability will be developed while ensuring cost effectiveness. Machine learning and other techniques, e.g., tipping point analysis will be investigated to assist in the detection of structural deterioration. Following laboratory investigations, a demonstration system will be deployed within an operating NPP. The project is expected to push the boundaries of the current state of the art in fibre-optic measurement in the areas of photonic systems integration and automatic data analysis from a distributed photonic sensor network.