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Development of asset fault signatures for Prognostic and Health Management in the nuclear industry

机译:开发用于核工业的预后和健康管理的资产故障签名

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Proactive online monitoring in the nuclear industry is being explored using the Electric Power Research Institute's Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software. The FW-PHM Suite is a set of web-based diagnostic and prognostic tools and databases that serves as an integrated health monitoring architecture. The FW-PHM Suite has four main modules: (1) Diagnostic Advisor, (2) Asset Fault Signature Database, (3) Remaining Useful Life Advisor, and (4) Remaining Useful Life Database. This paper focuses on development of asset fault signatures to assess the health status of generator step-up generators and emergency diesel generators in nuclear power plants. Asset fault signatures describe distinctive features based on technical examinations that can be used to detect a specific fault type. At the most basic level, fault signatures are comprised of an asset type, a fault type, and a set of one or more fault features (symptoms) that are indicative of the specified fault. The Asset Fault Signature Database is populated with asset fault signatures via a content development exercise that is based on the results of intensive technical research and on the knowledge and experience of technical experts. The developed fault signatures capture this knowledge and implement it in a standardized approach, thereby streamlining the diagnostic and prognostic process. This will support the automation of proactive online monitoring techniques in nuclear power plants to diagnose incipient faults, perform proactive maintenance, and estimate the remaining useful life of assets.
机译:正在使用电力研究所的全车队预后和健康管理(FW-PHM)套件软件来探索核工业中的主动在线监视。 FW-PHM Suite是一组基于Web的诊断和预测工具和数据库,可作为集成的健康监控体系结构。 FW-PHM套件具有四个主要模块:(1)诊断顾问,(2)资产故障签名数据库,(3)剩余有用寿命顾问,以及(4)剩余有用寿命数据库。本文着重于开发资产故障签名,以评估核电站中发电机升压型发电机和应急柴油发电机的健康状况。资产故障签名基于可用于检测特定故障类型的技术检查来描述独特功能。在最基本的级别上,故障特征包括资产类型,故障类型以及一组指示指定故障的一个或多个故障特征(症状)。资产故障签名数据库通过基于深入技术研究的结果以及技术专家的知识和经验的内容开发练习来填充资产故障签名。所开发的故障特征可以捕获该知识,并以标准化的方法加以实施,从而简化诊断和预后过程。这将支持核电厂主动在线监测技术的自动化,以诊断初期故障,进行主动维护并估计资产的剩余使用寿命。

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