AC and Lightning Breakdown Voltage Prediction Based on PD Measurements

• 作者: Thomas Huecker
• 来源期刊: 电气工程:英文版
• 学科: 工学
• 关键词: Breakdown voltage prediction partial discharges risk evaluation neural networks
• 年，卷（期）: 2020,（1）
• 页码范围: 1-7
• 页数: 7页
• 分类号: TP3

摘要

Partial discharge(PD)measurements are a standard method to determine insulation integrity since many years.For new equipment,the partial discharge level should be below a certain standardized level to be commissioned successfully.However,what is when a monitoring system detects upcoming partial discharges during the lifetime of an electrical equipment?Unfortunately,the discharge magnitude is not directly proportional to the remaining lifetime or the breakdown risk or breakdown voltage.Expert systems or experienced professionals can identify the PD defect root cause with a good certainty.This helps to determine the given risk.Nevertheless,clear risk quantification is missing.In this paper,a new approach is presented to predict the AC and lightning breakdown voltages of the equipment based on patterns from PD measurements.The method is validated with PD test data of several tip-plate configurations in air.A neuronal network is trained with these measurements.For control measurements with a different tip,it can be shown that the breakdown voltage can be predicted with an average failure of 5.3%for AC and 9.1%for lightning.