Abstract

Crosslinked polyethylene (XLPE) distribution cables are prone to segmented thermal aging after long-term operation owing to the large spatial spans and complex operating environments, and accurate residual life prediction of each aging cable segment could provide a theoretical basis and reference for performance monitoring, maintenance and the replacement of cables. Existing studies mainly focus on the residual life prediction methods for uniform aging cables, which are not suitable for segmented-aging cables. In this paper, a residual life prediction method for segmented-aging XLPE distribution cables based on the time-temperature superposition principle (TTSP) by non-destructive BIS measuring on site was proposed. Firstly, the applicability of the TTSP in the transformation of the changing process of elongation at break (EAB) of XLPE at different thermal aging temperatures was verified based on the Arrhenius equation. Secondly, to better simulate the thermal aging process under working conditions, XLPE cables were subjected to accelerated external stress aging at 140 °C for different aging times, and the corresponding changing process of EAB along with aging time was further measured. The relationship between the EAB of XLPE cables and aging time was well fitted by an equation, which could be used as a reference curve to predict the thermal aging trends and residual life of service-aged XLPE cables. After that, a calculation method for the transformation of the changing process of EAB of XLPE at different thermal aging temperatures was proposed, in which the corresponding multiplicative shift factor could be obtained based on the TTSP instead of the Arrhenius equation extrapolation. Moreover, the availability of the above calculation method was further proved by accelerated thermal aging experiments at 154 °C; the results show that the prediction error for the cable's EAB is no more than 3.15% and the prediction error for residual life is within 10% in this case. Finally, the realization of non-destructive residual life prediction combined with BIS measuring on site was explained briefly.

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