APPLICATION OF PROGNOSTIC METHODS FOR PREDICTING REMAINING USEFUL LIFE OF NUCLEAR PLANT EQUIPMENT AND COMPONENTS

摘要

The nuclear industry has benefited from over 20 years of research in the areas of advanced surveillance and diagnostics of plant processes and equipment, and many plants are actively employing these techniques to reduce maintenance workload and detect equipment faults. However, the area of prognostics, which concerns methodologies for predicting the remaining useful life (RUL) of equipment and components, has only recently been given consideration by research organizations and other experts as a promising technology that can be utilized by the nuclear industry. This paper describes activities performed by the authors to expand the research and development (R&D) in prognostic technologies and demonstrate its application in nuclear power plants under a Department of Energy (DOE) Small Business Innovation Research (SBIR) grant. The purpose of this industry-focused work is to identify nuclear power plant applications that are most amenable to this technology, understand the shortfalls that may be present in existing maintenance practices to accommodate prognostics, and quantify practical solutions to these shortfalls, where applicable. In particular, this paper discusses the development and validation of practical prognostics tools for RUL estimation of selected nuclear power plant equipment and components, including prognostic algorithms and software products for traditional reliability analysis, stress-based, and effects-based prognostics. This paper also describes laboratory work performed by the authors that is being used as a developmental test bed for a prognostic toolset that can be practically applied to a variety of nuclear power plant applications. In addition to the laboratory data, results are also included from the applications of prognostic techniques to existing equipment aging data sources such as the Cable Polymer Aging Database (CPAD).