Remaining lifespan prediction of cross‐linked polyethylene material based on GM(1, N) grey models
Cross‐linked polyethylene (XLPE) cables are a critical component of power transmission systems. As operating conditions sometimes exceed the thresholds set in discipline, some cables fail to reach their designed lifespan, and consequently evaluating the aging degree of cables is particularly necessa...
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Published in: | IET generation, transmission & distribution Vol. 16; no. 2; pp. 376 - 384 |
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Main Authors: | , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Wiley
01-01-2022
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Online Access: | Get full text |
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Summary: | Cross‐linked polyethylene (XLPE) cables are a critical component of power transmission systems. As operating conditions sometimes exceed the thresholds set in discipline, some cables fail to reach their designed lifespan, and consequently evaluating the aging degree of cables is particularly necessary. Here ten cables with an operating duration between 1 and 11 years from adjacent lines were sampled. Investigations were performed through various aging evaluation methods. Then typical lifespan prediction indices were concluded from test results and filtrated through correlation calculation. Meanwhile, a lifespan prediction method based on GM (1, N) model was proposed to establish the equivalent relationship between operating time and these indices. The research results indicated that, lifespan prediction indices obtained were all significantly correlated with operating time, which can be used to characterize aging degree of XLPE cables. Besides, due to the high prediction accuracy of experimental verification, the GM (1, N) model was proved to be applicable to evaluate the aging degree quantitatively and determine the remaining lifespan (relative to the designed lifespan) of XLPE cables. In future research, this method can be used to formulate a reasonable and economic withdrawal strategy for XLPE cables operating in conditions that exceed the thresholds set in the discipline. |
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ISSN: | 1751-8687 1751-8695 |
DOI: | 10.1049/gtd2.12312 |