Lifecycle Prognostics Architecture for Selected High-Cost Active Components

Abstract

There are an extensive body of knowledge and some commercial products available for calculating prognostics, remaining useful life, and damage index parameters. The application of these technologies within the nuclear power community is still in its infancy. Online monitoring and condition-based maintenance is seeing increasing acceptance and deployment, and these activities provide the technological bases for expanding to add predictive/prognostics capabilities. In looking to deploy prognostics there are three key aspects of systems that are presented and discussed: component/system/structure selection, prognostic algorithms, and prognostics architectures. Criteria are presented for component selection: feasibility, failure probability, consequences of failure, and benefits of the prognostics and health management (PHM) system. The basis and methods commonly used for prognostics algorithms are reviewed and summarized. Criteria for evaluating PHM architectures are presented: open, modular architecture; platform independence; graphical user interface for system development and/or results viewing; web-enabled tools; scalability; and standards compatibility.Thirteen software products were identified and discussed in the context of being potentially useful for deployment in a PHM program applied to systems in a nuclear power plant (NPP). These products were evaluated by using information available from company websites, product brochures, fact sheets, scholarly publications, and direct communication with vendors. The thirteen products were classified into four groups of software: research tools, PHM system development tools, deployable architectures, and peripheral tools. Eight software tools fell into the deployable architectures category. Of those eight, only two employ all six modules of a full PHM system. Five systems did not offer prognostic estimates, and one system employed the full health monitoring suite but lacked operations and maintenance support. Each product is briefly described in Appendix A, "Assessment Criteria." Selection of the most appropriate software package for a particular application will depend on the chosen component, system, or structure. Ongoing research will determine the most appropriate choices for a successful demonstration of PHM systems in aging NPPs.iv v SUMMARYAt the start of 2011, there were 439 nuclear power plants (NPPs) in the commercial global fleet; these plants started operation with 30-or 40-year licenses. The 104 NPPs in the United States represent about 10% of the installed capacity and currently provide about 20% of U.S. electricity. They have become highly efficient with an average capacity factor in excess of 91%, and they are a key element in the delivery of base-load electricity. They were originally licensed for 40 years, and a process has been established to enable license extension, to permit operation from 40 to 60 years. As of July 2011, license extensions have been granted for 71 plants at 40 sites. An additional 13 plants at nine sites are currently ...

Technical Needs for Prototypic Prognostic Technique Demonstration for Advanced Small Modular Reactor Passive Components

“…This broad definition includes condition monitoring, fault detection, and diagnostics in addition to prognostics. Lybeck et al (2011) reviewed selected software packages for PHM system development and deployment. Thirteen products were identified through literature and internet searches and evaluated on six criteria: open, modular architecture; platform independence; graphical user interface for system development and/or results viewing; web-enabled tools; scalability; and standards compatibility.…”

Advances in instrumentation for non-destructive testing and prognostics

“…In looking towards deployment, an integrated framework that combines the understanding of phenomena, the relationships between stressors and systems (or components), estimation of RUL, and actionable guidance to operators is necessary. Current research is generally focused on active components prognostics [2,4], though recent work has demonstrated the potential for passive component prognostics [31]. While the use of prognostics in NPP clearly has potential, several challenges (A-E below) exist in this regard.…”

“…The current data analysis is limited and mostly employing pattern recognition to detect anomalies. Attention is now starting to focus on algorithms with the potential for prognostics: that is, those which give estimates for remaining useful life (RUL) [4].…”

Frequency domain reflectometry for remaining useful life estimation of instrumentation and control cables

“…4 To aid in this selection, a variety of metrics can be used to quantify how well a candidate parameter would perform for RUL estimations. Researchers at the University of Tennessee have developed a set of three metrics for quantifying a candidate parameter's fitness for inclusion in a prognostic model: monotonicity, trendability, and prognosability.…”