Abstract
The evolution process of partial discharges generated under typical air gap defects of 10kV XLPE cable intermediate joints was experimentally studied by the built experimental model. In the experimental process, five characteristic parameters representing the severity of partial discharge are extracted, and their change trends with time are analyzed, and the value ranges of various characteristic parameters are divided. Using BP neural network algorithm, the nonlinear relationship network between PD severity and multiple characteristic parameters is established, and the evaluation system of partial discharge severity of cable intermediate joint is constructed. Finally, the correctness and effectiveness of the method is verified by the example testing.
Published Version
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