DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Prognostic and health management of active assets in nuclear power plants

Abstract

This study presents the development of diagnostic and prognostic capabilities for active assets in nuclear power plants (NPPs). The research was performed under the Advanced Instrumentation, Information, and Control Technologies Pathway of the Light Water Reactor Sustainability Program. Idaho National Laboratory researched, developed, implemented, and demonstrated diagnostic and prognostic models for generator step-up transformers (GSUs). The Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software developed by the Electric Power Research Institute was used to perform diagnosis and prognosis. As part of the research activity, Idaho National Laboratory implemented 22 GSU diagnostic models in the Asset Fault Signature Database and two wellestablished GSU prognostic models for the paper winding insulation in the Remaining Useful Life Database of the FW-PHM Suite. The implemented models along with a simulated fault data stream were used to evaluate the diagnostic and prognostic capabilities of the FW-PHM Suite. Knowledge of the operating condition of plant asset gained from diagnosis and prognosis is critical for the safe, productive, and economical long-term operation of the current fleet of NPPs. This research addresses some of the gaps in the current state of technology development and enables effective application of diagnostics and prognostics to nuclear plant assets.

Authors:
 [1];  [1];  [1];  [2];  [3]
  1. Idaho National Lab. (INL), Idaho Falls, ID (United States)
  2. Electric Power Research Inst., Charlotte, NC (United States)
  3. Expert Microsystems, Orangevale, CA (United States)
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE)
OSTI Identifier:
1244696
Report Number(s):
INL/JOU-15-34317
Journal ID: ISSN 2153-2648
Grant/Contract Number:  
AC07-05ID14517
Resource Type:
Accepted Manuscript
Journal Name:
International Journal of Prognostics and Health Management
Additional Journal Information:
Journal Volume: 6; Journal Issue: Special; Journal ID: ISSN 2153-2648
Publisher:
Prognostics and Health Management Society
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; online monitoring; diagnosis and prognosis; generator step-up transformer; Chendong Model

Citation Formats

Agarwal, Vivek, Lybeck, Nancy, Pham, Binh T., Rusaw, Richard, and Bickford, Randall. Prognostic and health management of active assets in nuclear power plants. United States: N. p., 2015. Web.
Agarwal, Vivek, Lybeck, Nancy, Pham, Binh T., Rusaw, Richard, & Bickford, Randall. Prognostic and health management of active assets in nuclear power plants. United States.
Agarwal, Vivek, Lybeck, Nancy, Pham, Binh T., Rusaw, Richard, and Bickford, Randall. Thu . "Prognostic and health management of active assets in nuclear power plants". United States. https://www.osti.gov/servlets/purl/1244696.
@article{osti_1244696,
title = {Prognostic and health management of active assets in nuclear power plants},
author = {Agarwal, Vivek and Lybeck, Nancy and Pham, Binh T. and Rusaw, Richard and Bickford, Randall},
abstractNote = {This study presents the development of diagnostic and prognostic capabilities for active assets in nuclear power plants (NPPs). The research was performed under the Advanced Instrumentation, Information, and Control Technologies Pathway of the Light Water Reactor Sustainability Program. Idaho National Laboratory researched, developed, implemented, and demonstrated diagnostic and prognostic models for generator step-up transformers (GSUs). The Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software developed by the Electric Power Research Institute was used to perform diagnosis and prognosis. As part of the research activity, Idaho National Laboratory implemented 22 GSU diagnostic models in the Asset Fault Signature Database and two wellestablished GSU prognostic models for the paper winding insulation in the Remaining Useful Life Database of the FW-PHM Suite. The implemented models along with a simulated fault data stream were used to evaluate the diagnostic and prognostic capabilities of the FW-PHM Suite. Knowledge of the operating condition of plant asset gained from diagnosis and prognosis is critical for the safe, productive, and economical long-term operation of the current fleet of NPPs. This research addresses some of the gaps in the current state of technology development and enables effective application of diagnostics and prognostics to nuclear plant assets.},
doi = {},
journal = {International Journal of Prognostics and Health Management},
number = Special,
volume = 6,
place = {United States},
year = {Thu Jun 04 00:00:00 EDT 2015},
month = {Thu Jun 04 00:00:00 EDT 2015}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
The DOI is not currently available

Save / Share: