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Industrial implementation of intelligent system techniques for nuclear power plant condition monitoring

机译:核电厂状态监测智能系统技术的工业实施

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As the nuclear power plants within the UK age, there is an increased requirement for condition monitoring to ensure that the plants are still be able to operate safely. This paper describes the novel application of Intelligent Systems (IS) techniques to provide decision support to the condition monitoring of Nuclear Power Plant (NPP) reactor cores within the UK. The resulting system, BETA (British Energy Trace Analysis) is deployed within the UK's nuclear operator and provides automated decision support for the analysis of refuelling data, a lead indicator of the health of ACR (Advanced Gas-cooled Reactor) nuclear power plant cores. The key contribution of this work is the improvement of existing manual, labour-intensive analysis through the application of IS techniques to provide decision support to NPP reactor core condition monitoring. This enables an existing source of condition monitoring data to be analysed in a rapid and repeat-able manner, providing additional information relating to core health on a more regular basis than routine inspection data allows. The application of IS techniques addresses two issues with the existing manual interpretation of the data, namely the limited availability of expertise and the variability of assessment between different experts. Decision support is provided by four applications of intelligent systems techniques. Two instances of a rule-based expert system are deployed, the first to automatically identify key features within the refuelling data and the second to classify specific types of anomaly. Clustering techniques are applied to support the definition of benchmark behaviour, which is used to detect the presence of anomalies within the refuelling data. Finally data mining techniques are used to track the evolution of the normal benchmark behaviour over time. This results in a system that not only provides support for analysing new refuelling events but also provides the platform to allow future events to be analysed. The BETA system has been deployed within the nuclear operator in the UK and is used at both the engineering offices and on station to support the analysis of refuelling events from two AGR stations, with a view to expanding it to the rest of the fleet in the near future.
机译:随着核电厂在英国时代的到来,对状态监控的要求也越来越高,以确保电厂仍能够安全运行。本文介绍了智能系统(IS)技术的新颖应用,为英国境内核电站(NPP)反应堆堆芯的状态监测提供决策支持。由此产生的系统BETA(英国能源追踪分析)已部署在英国的核运营商内部,并为加油数据的分析提供了自动决策支持,这是ACR(先进气冷堆)核电站核心运行状况的主要指标。这项工作的关键作用是通过应用IS技术改进现有的人工劳动密集型分析,从而为NPP反应堆堆芯状态监测提供决策支持。这使状态监测数据的现有来源能够以快速且可重复的方式进行分析,与常规检查数据相比,可以更规则地提供与核心健康相关的其他信息。 IS技术的应用解决了现有数据手动解释的两个问题,即专业知识的可用性有限和不同专家之间评估的可变性。决策支持由智能系统技术的四个应用程序提供。部署了基于规则的专家系统的两个实例,第一个实例可自动识别加油数据中的关键特征,第二个实例可对特定类型的异常进行分类。应用聚类技术来支持基准行为的定义,该行为用于检测加油数据中是否存在异常。最后,数据挖掘技术用于跟踪正常基准行为随时间的演变。这样就形成了一个系统,该系统不仅为分析新的加油事件提供支持,而且还提供了可以分析未来事件的平台。 BETA系统已在英国的核运营商中部署,并已在工程办公室和在站中使用,以支持对两个AGR站的加油事件进行分析,以将其扩展至英国其他机队。不远的将来。

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