2023
DOI: 10.1016/j.gloei.2023.02.004
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Identification of XLPE cable insulation defects based on deep learning

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Cited by 9 publications
(4 citation statements)
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“…Defects may have a technological or operational nature of origin. Structural micro-heterogeneity of solid insulating materials is confirmed by effective methods [1][2][3][4]. All insulating materials at the micro level change shape under the influence of an electric field.…”
mentioning
confidence: 91%
“…Defects may have a technological or operational nature of origin. Structural micro-heterogeneity of solid insulating materials is confirmed by effective methods [1][2][3][4]. All insulating materials at the micro level change shape under the influence of an electric field.…”
mentioning
confidence: 91%
“…In order to further improve detection accuracy and enhance universality, it is necessary to develop an effective and practical method to ensure the reliability of the power cable system. The harmonic detection method is a newly emerging research perspective [22][23][24]. Most scholars conduct time-frequency analysis on the current signal of power equipment to obtain harmonic information reflecting equipment condition.…”
Section: Introductionmentioning
confidence: 99%
“…Meanwhile, the thermoplastic insulating materials does not require cross‐linking and degassing in the process of cable production, which can significantly shorten the production cycle of the power cable and reduce the energy consumption of production [9]. The removing of cross‐linking process can also increase the purity of insulation, and enhance the insulating performance [10, 11], which is expected to further increase the power transmission capacity or reduce the designed thickness of power cable insulation.…”
Section: Introductionmentioning
confidence: 99%