Prognostic and Health Management of Active Assets in Nuclear Power Plants
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Published
Nov 3, 2020
Vivek Agarwal
Nancy Lybeck
Binh T. Pham
Richard Rusaw
Randall Bickford
Abstract
This paper 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.
##plugins.themes.bootstrap3.article.details##
Keywords
prognostics, Automatic diagnostics, Generator Step-Up Transformers, Fleet Wide Monitoring
References
Aba-Siada, A. (2011). Correlation of Furan Concentration and Spectral Response of Transformer Oil Using Expert Systems. IEEE/IET Science, Measurement and Technology, 5(5), pp. 183-188. doi: 10.1049/ietsmt. 2011.0017
Abu-Elanien, A. E. B., & Salama, M. M. A. (2010). Asset Management Techniques for Transformers. Electric Power Systems Research, 80(4), pp. 456-464. doi:10.1016/j.epsr.2009.10.008
Agarwal, V., Lybeck, N. J., Pham, B. T., Bickford, R., & Rusaw, R. (2015). Implementation of Remaining Useful Lifetime Transformer Models in the Fleet-Wide Prognostic and Health Management Suite. Proceedings of 9th International Conference on Nuclear Plant Instrumentation, Control, & Human-Machine Interface Technologies (NPIC-HMIT), February 23–26, Charlotte, NC.
Agarwal, V., Lybeck, N. J., Bickford, R., & Rusaw, R. (2014). Development of Asset Fault Signatures for Prognostic and Health Management in the Nuclear Industry. Proceedings of IEEE Annual Conference on Prognostics and Health Management, June 21–24, Spokane, WA.
Agarwal, V., Lybeck, N. J., & Pham, B. T. (2014). Diagnostic and Prognostic Models for Generator Step-Up Transformers. INL/EXT-14-33124, Idaho National Laboratory, Idaho Falls, USA.
Agarwal, V., Lybeck, N. J., Pham, B. T., Rusaw, R., & Bickford, R. (2013). Online Monitoring of Assets in Nuclear Industry. Proceedings of Annual Conference on Prognostics and Health Management, October 14–17, New Orleans, LA.
Agarwal, V., Lybeck, N. J., Matacia, L., & Pham, B. T. (2013). Demonstration of Online Monitoring for Generator Step-up Transformers and Emergency Diesel Generators, INL/EXT-13-30155, Idaho National Laboratory, Idaho Falls, USA.
Baird, P. J., Herman, H., Stevens, G. C., & Jarman, P. N. (2006). Non-destructive Measurement of the Degradation of Transformer Insulation Paper. IEEE Transactions on Dielectrics and Electrical Insulation, 13(1), pp. 309-318. doi: 10.1109/TDEI.2006.1624275
Coble, J. B., (2010). Merging Data Sources to Predict Remaining Useful Life – An Automated Method to Identify Prognostic Parameters. Doctoral Dissertation, The University of Tennessee, Knoxville, USA.
Chendong, X. (1991). Monitoring Paper Insulation Aging by Measuring FurFural Contents in Oil. Proceedings of 7th International Symposium on High Voltage Engineering, Dresden, Germany, August 28–30, 1991, pp. 139–142.
Cheim, L., Platts, D., Prevost, T., & S. Xu. (2012). Furan Analysis for Liquid Power Transformers. IEEE Electrical Insulation, 28(2), pp. 8-21. doi: 10.1109/MEI.2012.6159177
Duval, M. (2002). A Review of Faults Detectable by Gasin-Oil Analysis in Transformers. IEEE Electrical Insulation Magazine, 18(3), pp. 8-17. doi: 10.1109/MEI.2002.1014963
Electric Power Research Institute (EPRI) (2012). Fleet-Wide Prognostics and Health Management Application Research. Report 1026712. Electric Power Research Institute, Charlotte, NC, USA.
Electric Power Research Institute (EPRI) (2011). EPRI Power Transformer Guidebook Development: The Copper Book, Report 1021892, Electric Power Research Institute, Palo Alto, CA, USA.
Emsley, A.M., & Stevens, G.C. (1994). Review of Chemical Indicators of Degradation of Cellulosic Electrical Paper Insulation in Oil-filled Transformers. IEE Proceedings on Science, Measurement, and Technology, 141(5), pp. 324-334. doi: 10.1049/ip-smt:19949957
Emsley, A.M., Xiao, X., Heywood, R.J., & Ali, M. (2000). Degradation of Cellulosic Insulation in Power Transformers – Part 2: Formation of Furan Products in Insulating Oil. IEE Proceedings on Science, Measurement, and Technology, 147(3), pp. 110-114. doi: 10.1049/ip-smt:20000259
Hohlein, I., & Kachler, A. (2005). Aging of Cellulose at Transformer Service Temperatures – Part 2. Influence of Moisture and Temperature on Degree of Polymerization and Formation of Furanic Compounds in Free-breathing Systems. IEEE Electrical Insulation Magazine, 21(5), pp. 20-24. doi: 10.1109/MEI.2005.1513426
Institute of Electrical and Electronics Engineers (IEEE) (2012). IEEE Guide for Loading Mineral Oil Immersed Transformers and Step Voltage Regulators. IEEE Std C57.91 2011, New York, March.
Institute of Electrical and Electronics Engineers (IEEE) (2008). IEEE Guide for Interpretation of Gases Generated in Oil-Immersed Transformers. In IEEE Standards C57.104 by IEEE Power & Energy Society.
Johnson, P. (2012). Fleet wide asset monitoring: Sensory data to signal processing to prognostics. Proceedings of Annual Conference of the Prognostics and Health Management Society, September 23–27, Minneapolis, MN. ISBN-978-1-036263-05-9.
Johnson, P. (2014). Lessons Learned in Fleet wide Asset Monitoring of Gas Turbines and Supporting Equipment in Power Generation Applications. Proceedings of European Conference of the Prognostics and Health Management Society, July 8–10, Nantes, France. ISBN-978-1-936263-16-5.
Medina-Oliva, G., Voisin, A., Monnin, M., Peysson, F., & Leger, J. B. (2012). Prognostic assessment using fleetwide ontology. Proceedings of Annual Conference of the Prognostics and Health Management Society, September 23–27, Minneapolis, MN. ISBN-978-1- 036263-05-9
Monnin, M., Voisin, A., Leger, J., & Lung, B. (2011). Fleetwide health management architecture. Proceedings of Annual Conference of the Prognostics and Health Management Society, September 25–29, Montreal, Quebec, Canada. ISBN-978-1-936263-03-5.
Monnin, M., Abichou, B., Voisin, A., & Mozzati, C. (2011). Fleet historical case for predictive maintenance. Proceedings of International Conference on Surveillance 6, October 25–26, Compiegne, France.
Lundgaard, L. E., Hansen, W., & Ingebrigtsen, S. (2008). Ageing of Mineral Oil impregnated Cellulose by Acid Catalysis. IEEE Transactions on Dielectrics and Electrical Insulation, 15(2), pp. 540-546. doi: 10.1109/TDEI.2008.4483475
Lybeck, N. J., Agarwal, V., Pham, B. T., Medema, H., & Fitzgerald, K. (2012). Online monitoring technical basis and analysis framework for large power transformers. INL/EXT-12-27181. Idaho National Laboratory, Idaho Falls, USA.
Patrick, R., Smith, M. J., Byington, C. S., Vachtsevanos, G. J., Tom, K., & Ly, C. (2010). Integrated software platform for fleet data analysis, enhanced diagnostics, and safe transition to prognostics for helicopter component CBM. Proceedings of the Annual Conference of the Prognostics and Health Management Society, October 13–16, Portland, OR. ISBN-978-1-936263-01-1.
Pham, B. T., Lybeck, N. J., and Agarwal, V. (2012). Online Monitoring Technical Basis and Analysis Framework for Emergency Diesel Generators: Interim Report for FY 2013. INL/EXT-12-27754, Idaho National Laboratory, Idaho Falls, USA.
Umiliacchi, P., Lane, D., & Romano, F. (2011). Predictive maintenance of railway subsystem using an Ontology based modeling approach. Proceedings of 9th World Conference on Railway Research, May 22–26, Lille, France.
Wang, T., Yu, J., Siegel, D., & Lee, J. (2008). A similaritybased prognostics approach for remaining useful life estimation of engineered systems. Proceedings of International Conference on Prognostics and Health Management, October 06–09, Denver, CO.
World Nuclear Association, (2015). Nuclear Power in the USA. URL: www.world-nuclear.org/info/countryprofile/ countries-T-Z/USA--Nuclear-Power/YouTube Video, (2014). Online Monitoring for Improved Power Plant Equipment Operating Life and Productivity, EPRI, 2012.
http://www.youtube.com/watch?v=8JCchydWlcg&feature=c4-overview&list=UUctcciH1NrAGpwMnKwvnLgQ
Zhang, X., & Gockenbach, E. (2008). Asset-Management of Transformers Based on Condition Monitoring and Standard Diagnosis. IEEE Electrical Insulation Magazine, 24(4), pp. 26-40. doi: 10.1109/MEI.2008.4581371
Abu-Elanien, A. E. B., & Salama, M. M. A. (2010). Asset Management Techniques for Transformers. Electric Power Systems Research, 80(4), pp. 456-464. doi:10.1016/j.epsr.2009.10.008
Agarwal, V., Lybeck, N. J., Pham, B. T., Bickford, R., & Rusaw, R. (2015). Implementation of Remaining Useful Lifetime Transformer Models in the Fleet-Wide Prognostic and Health Management Suite. Proceedings of 9th International Conference on Nuclear Plant Instrumentation, Control, & Human-Machine Interface Technologies (NPIC-HMIT), February 23–26, Charlotte, NC.
Agarwal, V., Lybeck, N. J., Bickford, R., & Rusaw, R. (2014). Development of Asset Fault Signatures for Prognostic and Health Management in the Nuclear Industry. Proceedings of IEEE Annual Conference on Prognostics and Health Management, June 21–24, Spokane, WA.
Agarwal, V., Lybeck, N. J., & Pham, B. T. (2014). Diagnostic and Prognostic Models for Generator Step-Up Transformers. INL/EXT-14-33124, Idaho National Laboratory, Idaho Falls, USA.
Agarwal, V., Lybeck, N. J., Pham, B. T., Rusaw, R., & Bickford, R. (2013). Online Monitoring of Assets in Nuclear Industry. Proceedings of Annual Conference on Prognostics and Health Management, October 14–17, New Orleans, LA.
Agarwal, V., Lybeck, N. J., Matacia, L., & Pham, B. T. (2013). Demonstration of Online Monitoring for Generator Step-up Transformers and Emergency Diesel Generators, INL/EXT-13-30155, Idaho National Laboratory, Idaho Falls, USA.
Baird, P. J., Herman, H., Stevens, G. C., & Jarman, P. N. (2006). Non-destructive Measurement of the Degradation of Transformer Insulation Paper. IEEE Transactions on Dielectrics and Electrical Insulation, 13(1), pp. 309-318. doi: 10.1109/TDEI.2006.1624275
Coble, J. B., (2010). Merging Data Sources to Predict Remaining Useful Life – An Automated Method to Identify Prognostic Parameters. Doctoral Dissertation, The University of Tennessee, Knoxville, USA.
Chendong, X. (1991). Monitoring Paper Insulation Aging by Measuring FurFural Contents in Oil. Proceedings of 7th International Symposium on High Voltage Engineering, Dresden, Germany, August 28–30, 1991, pp. 139–142.
Cheim, L., Platts, D., Prevost, T., & S. Xu. (2012). Furan Analysis for Liquid Power Transformers. IEEE Electrical Insulation, 28(2), pp. 8-21. doi: 10.1109/MEI.2012.6159177
Duval, M. (2002). A Review of Faults Detectable by Gasin-Oil Analysis in Transformers. IEEE Electrical Insulation Magazine, 18(3), pp. 8-17. doi: 10.1109/MEI.2002.1014963
Electric Power Research Institute (EPRI) (2012). Fleet-Wide Prognostics and Health Management Application Research. Report 1026712. Electric Power Research Institute, Charlotte, NC, USA.
Electric Power Research Institute (EPRI) (2011). EPRI Power Transformer Guidebook Development: The Copper Book, Report 1021892, Electric Power Research Institute, Palo Alto, CA, USA.
Emsley, A.M., & Stevens, G.C. (1994). Review of Chemical Indicators of Degradation of Cellulosic Electrical Paper Insulation in Oil-filled Transformers. IEE Proceedings on Science, Measurement, and Technology, 141(5), pp. 324-334. doi: 10.1049/ip-smt:19949957
Emsley, A.M., Xiao, X., Heywood, R.J., & Ali, M. (2000). Degradation of Cellulosic Insulation in Power Transformers – Part 2: Formation of Furan Products in Insulating Oil. IEE Proceedings on Science, Measurement, and Technology, 147(3), pp. 110-114. doi: 10.1049/ip-smt:20000259
Hohlein, I., & Kachler, A. (2005). Aging of Cellulose at Transformer Service Temperatures – Part 2. Influence of Moisture and Temperature on Degree of Polymerization and Formation of Furanic Compounds in Free-breathing Systems. IEEE Electrical Insulation Magazine, 21(5), pp. 20-24. doi: 10.1109/MEI.2005.1513426
Institute of Electrical and Electronics Engineers (IEEE) (2012). IEEE Guide for Loading Mineral Oil Immersed Transformers and Step Voltage Regulators. IEEE Std C57.91 2011, New York, March.
Institute of Electrical and Electronics Engineers (IEEE) (2008). IEEE Guide for Interpretation of Gases Generated in Oil-Immersed Transformers. In IEEE Standards C57.104 by IEEE Power & Energy Society.
Johnson, P. (2012). Fleet wide asset monitoring: Sensory data to signal processing to prognostics. Proceedings of Annual Conference of the Prognostics and Health Management Society, September 23–27, Minneapolis, MN. ISBN-978-1-036263-05-9.
Johnson, P. (2014). Lessons Learned in Fleet wide Asset Monitoring of Gas Turbines and Supporting Equipment in Power Generation Applications. Proceedings of European Conference of the Prognostics and Health Management Society, July 8–10, Nantes, France. ISBN-978-1-936263-16-5.
Medina-Oliva, G., Voisin, A., Monnin, M., Peysson, F., & Leger, J. B. (2012). Prognostic assessment using fleetwide ontology. Proceedings of Annual Conference of the Prognostics and Health Management Society, September 23–27, Minneapolis, MN. ISBN-978-1- 036263-05-9
Monnin, M., Voisin, A., Leger, J., & Lung, B. (2011). Fleetwide health management architecture. Proceedings of Annual Conference of the Prognostics and Health Management Society, September 25–29, Montreal, Quebec, Canada. ISBN-978-1-936263-03-5.
Monnin, M., Abichou, B., Voisin, A., & Mozzati, C. (2011). Fleet historical case for predictive maintenance. Proceedings of International Conference on Surveillance 6, October 25–26, Compiegne, France.
Lundgaard, L. E., Hansen, W., & Ingebrigtsen, S. (2008). Ageing of Mineral Oil impregnated Cellulose by Acid Catalysis. IEEE Transactions on Dielectrics and Electrical Insulation, 15(2), pp. 540-546. doi: 10.1109/TDEI.2008.4483475
Lybeck, N. J., Agarwal, V., Pham, B. T., Medema, H., & Fitzgerald, K. (2012). Online monitoring technical basis and analysis framework for large power transformers. INL/EXT-12-27181. Idaho National Laboratory, Idaho Falls, USA.
Patrick, R., Smith, M. J., Byington, C. S., Vachtsevanos, G. J., Tom, K., & Ly, C. (2010). Integrated software platform for fleet data analysis, enhanced diagnostics, and safe transition to prognostics for helicopter component CBM. Proceedings of the Annual Conference of the Prognostics and Health Management Society, October 13–16, Portland, OR. ISBN-978-1-936263-01-1.
Pham, B. T., Lybeck, N. J., and Agarwal, V. (2012). Online Monitoring Technical Basis and Analysis Framework for Emergency Diesel Generators: Interim Report for FY 2013. INL/EXT-12-27754, Idaho National Laboratory, Idaho Falls, USA.
Umiliacchi, P., Lane, D., & Romano, F. (2011). Predictive maintenance of railway subsystem using an Ontology based modeling approach. Proceedings of 9th World Conference on Railway Research, May 22–26, Lille, France.
Wang, T., Yu, J., Siegel, D., & Lee, J. (2008). A similaritybased prognostics approach for remaining useful life estimation of engineered systems. Proceedings of International Conference on Prognostics and Health Management, October 06–09, Denver, CO.
World Nuclear Association, (2015). Nuclear Power in the USA. URL: www.world-nuclear.org/info/countryprofile/ countries-T-Z/USA--Nuclear-Power/YouTube Video, (2014). Online Monitoring for Improved Power Plant Equipment Operating Life and Productivity, EPRI, 2012.
http://www.youtube.com/watch?v=8JCchydWlcg&feature=c4-overview&list=UUctcciH1NrAGpwMnKwvnLgQ
Zhang, X., & Gockenbach, E. (2008). Asset-Management of Transformers Based on Condition Monitoring and Standard Diagnosis. IEEE Electrical Insulation Magazine, 24(4), pp. 26-40. doi: 10.1109/MEI.2008.4581371
Section
Technical Papers