Discriminating and Localizing Thermal Aging in Low Voltage Polymeric Cables using Non-Destructive Electrical Diagnostics

Abstract

Currently, in North America and Europe, significant attention is being paid to the condition of LV electrical cable systems in nuclear power plants (NPPs), given industry and governmental efforts to extend the operational life of numerous existing NPPs well beyond their initial 40-year design life / license period. Thermal degradation is a key cause of long-term aging of LV NPP polymeric cable insulation materials in normally dry areas, and in-situ condition monitoring techniques form an important means of diagnosing its deleterious effects within the scope of a LV cable aging management program. However, key knowledge gaps have thus far precluded the development and deployment of quantitative assessment criteria or predictive modelling/classification methods which can be practically applied towards in-situ, electrically-based diagnostics of thermally aged LV NPP cables across varying insulation types, environmental conditions, rates of dielectric aging, and aging volumes/damage ratios.

This thesis investigates fundamental and practical aspects of applying a combined electrical diagnostic approach using DC time-domain, low frequency (0.001 – 1000 Hz) AC, and travelling wave (RF) based in-situ terminal electrical diagnostic techniques to discriminate and localize thermal aging in LV NPP cables. A unique custom experimental set-up is designed and constructed to subject 197 XLPE and EPR prepared LV shielded cable test specimens (prepared from full-scale LV NPP cables) to accelerated thermal aging, whilst simultaneously considering the influence of varying, field-representative experimental conditions. Representative diagnostic data based on approximately 2120 low frequency dielectric spectroscopy (LFDS)/polarization depolarization current (PDC) and 1175 frequency domain reflectometry (FDR) measurements on these test specimens are subjected to varying forms of data analytics including empirical analysis of full spectra, partial least squares regression based predictive modelling, supervised ensemble decision tree-based (random forest) classification and predictor importance analysis.

Experimental results from AC/DC (LFDS, PDC-based) electrical diagnostic tests, reference physical-chemical material characterization tests and related data analytics illustrate that material and dielectric changes due to accelerated thermal aging can be discriminated using LFDS and PDC-based electrical diagnostics in combination with interpretable empirical, statistical or supervised ML-based techniques. It is however important to derive a suitably wide range of physically meaningful potential predictor metrics based on the underlying full spectrum dielectric data, including real permittivity (ε′), imaginary permittivity (ε″), polarization current and depolarization current. It is also imperative to undertake all analyses on an insulation-specific basis for LV NPP cables given differences in polymer formulations and physical-chemical evolutions with accelerated thermal aging, and undertake quantitative, insulation-specific approaches to interpret which predictors bear higher responsibilities for the observed dielectric data variance and trends (with respect to thermal aging). Experimental results from RF (FDR-based) electrical diagnostic tests and related data analytics show that thermal aging can be localized using differential, inverse fast Fourier transform (IFFT) converted S11 responses, in combination with advanced window-based signal processing methods and interpretable, supervised ML-based binary anomaly classification techniques. The research supports the premise that FDR measurements should be utilized for defect localization (ideally based on long-term monitoring/trending) rather than condition assessment, especially for samples in early stages of thermal degradation (e.g., antioxidant depletion, start of mechanical hardening) as present in this research.

The research outcomes highlight the importance of utilizing an experimental design and broad population dataset for LV NPP cable aging management research which at minimum, considers field-representative variations in thermal aging rates, thermal aging volume/damage ratio, thermal aging locations, measurement (ambient temperatures), and insulation type. Adopting such an approach in this work has allowed for a robust, insulation-specific assessment of critical diagnostic predictors for thermal aging discrimination and localization, and proof-of-concept development and validation of predictive/classification-based models which can yield conservative performance assessments for new (i.e., previously unseen) diagnostic data obtained from field-representative populations. The research undertaken can thus be considered a key knowledge development step to facilitate the deployment of AC, DC and RF electrical non-destructive examination (NDE) techniques towards the aging management of thermally degraded LV cables installed in NPPs or other critical environments.