Nuclear Power Plant Instrumentation and Control Cable Prognostics Using Indenter Modulus Measurements

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Nov 3, 2020
Dan McCarter Brent Shumaker Bryan McConkey Hash Hashemian

Abstract

As the fleet of nuclear power plants (NPPs) approach their1 original qualified life (typically 40 years) and operators seek license extensions, regulators require assurance that they can continue to operate safely in the decades to come. Some of the most important, yet often overlooked components, are the cables that provide the signal paths for instrumentation and control (I&C) systems used to ensure safe and efficient operation of NPPs.
In response to this, the authors explore the use of expanding indenter modulus (IM), an industry-accepted technique for cable condition monitoring, into a prognostic tool for predicting the remaining useful life (RUL) of I&C cables. Not only is this technique non-destructive, but it can be performed while NPP cables are in service, thus making it practical for adoption into existing cable condition monitoring programs. In this paper, the authors describe an accelerated aging cable test bed used to acquire several types of measurement parameters as cables age. Additionally, practical techniques are described in which simple IM measurements can be leveraged for condition monitoring and RUL estimation.
Error analysis indicates the proposed method is superior to conventional RUL estimation techniques, such as simple trending and curve fitting. The authors demonstrate that using IM can potentially provide a non-destructive, in-situ estimation of RUL for I&C cables. As described in this paper, the IM data clearly shows trends as a function of cable age, and shows promising performance for RUL estimation especially compared with conventional techniques.

Abstract 437 | PDF Downloads 319

##plugins.themes.bootstrap3.article.details##

Keywords

Data-driven prognostics, cables, indenter modulus, nuclear power plant, instrumentation and control, polymers, elongation at break, i&c

References
Coble, J.B., Ramuhalli, P., Bond, L.J., Hines, J.W., Upadhyaya, B.R., Pacific Northwest National Laboratory (PNNL) (2012). Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications. PNNL, Richland, Washington. 21515
Coble, J., and Hines, J.W. (2011). "Applying the General Path Model to Estimation of Remaining Useful Life." International Journal of Prognostics and Health Management, pp. 72-84.
Coble, J., (2010). Merging data sources to predict remaining useful life – An automated method to identify prognostic parameters. Doctoral dissertation. The University of Tennessee, Knoxville, Tennessee.
Electric Power Research Institute (EPRI) (1996). Evaluation of Cable Polymer Aging Through Indenter Testing of In-Plant and Laboratory-Aged Specimens. EPRI, Palo Alto, California. 104075.
Hines, J.W., Garvey, J.J., Preston, J., Usynin, A. (2008). Empirical methods for process and equipment prognostics. 53rd Reliability and Maintainability Symposium (RAMS) 2008 Proceedings. January 28-31, 2008, Las Vegas, Nevada.
Institute of Electrical and Electronic Engineers (IEEE) (2012) Nuclear Power Plants: Instrumentation and Control Important to Safety – Electrical Equipment Condition Monitoring Methods – Part 3: Elongation at Break. 62582-3-2012
Lindely, D.V., Smith, A.F. (1972). “Bayes Estimates for Linear Models,” Journal of the Royal Statistical Society (B), Vol 34, No. 1, pp. 1-41.
Lu, C.J., Meeker, W. (1993). Using Degradation Measures to Estimate a Time-to-Failure Distribution. Technometrics, vol.35 (2), pp. 161-174.
Sikorska, J.Z., Hodkiewicz, M., and Ma, L., “Prognostic Modeling Options for Remaining Useful Life Estimation by Industry,” Mechanical Systems and Signal Processing, 25, pp. 1803-1836, 2011.
Shumaker, B. D., McCarter, D. E., Hashemian, H. M., & O’Hagan, R.D. (2014). Frequency domain reflectometry for remaining useful life estimation of instrumentation and control cables. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. doi:10.1177/1748006X14545623
Toman, G.J., Electric Power Research Institute (EPRI) (2002). Cable System Aging Management. EPRI, Palo Alto, California. 1003317.
Toman, G.J., Electric Power Research Institute (EPRI) (2003). Integrated Cable System Aging Management Guidance – Low Voltage Cable. EPRI, Palo Alto, California and U.S. Department of Energy, Washington, D.C. 1003663.
Toman, G.J., Electric Power Research Institute (EPRI) (2005). Initial Acceptance Criteria Concepts and Data for Assessing Longevity of Low-Voltage Cable Insulations and Jackets. EPRI, Palo Alto, California. 1008211.
Villaran, M., Lofaro, R., Brookhaven National Laboratory (BNL) (2009). Essential Elements of an Electric Cable Condition Monitoring Program. BNL-NUREG-90318-2009. Upton, New York.
Yang, G., (2007). Life cycle reliability engineering. Hokoken: John Wiley & Sons.
Section
Technical Papers