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

• Main Authors: Dan McCarter, Brent Shumaker, Bryan McConkey, Hash Hashemian
• Format: Article
• Language: English
• Published: The Prognostics and Health Management Society 2015-12-01
• Series: International Journal of Prognostics and Health Management
• Subjects: data-driven prognostics; cables; indenter modulus; nuclear power plant; instrumentation and control; polymers; elongation at break; i&c
• Online Access: https://papers.phmsociety.org/index.php/ijphm/article/view/2261

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.