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

Dan McCarter, Brent Shumaker, Bryan McConkey, and Hash Hashemian
Publication Target: 
IJPHM
Publication Issue: 
Special Issue Nuclear Energy PHM
Submission Type: 
Full Paper
Supporting Agencies (optional): 
US Department of Energy
AttachmentSizeTimestamp
ijphm_14_016.pdf1.04 MBJanuary 28, 2015 - 5:03pm

As the fleet of nuclear power plants (NPPs) approach their 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 showed trends as a function of cable age, and shows promising performance for RUL estimation especially compared with conventional techniques

Publication Year: 
2014
Publication Volume: 
5
Publication Control Number: 
016
Page Count: 
10
Submission Keywords: 
Data-driven prognostics
nuclear power plant
cables
indenter modulus
instrumentation and control
polymers
elongation at break
i&c
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
Industrial applications
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