重复性
模式识别(心理学)
人工神经网络
局部放电
人工智能
信号(编程语言)
电压
特征(语言学)
特征提取
计算机科学
材料科学
工程类
电气工程
统计
数学
哲学
程序设计语言
语言学
作者
Norfadilah Rosle,Nor Asiah Muhamad,Mohamad Nur Khairul Hafizi Rohani,Mohamad Kamarol Mohd Jamil
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2021-01-01
卷期号:9: 133258-133273
被引量:46
标识
DOI:10.1109/access.2021.3115519
摘要
Partial discharge (PD) signal classification analysis on cross-linked polyethylene (XLPE) cables is complex, requiring a comprehensive understanding of the characteristics of PD patterns. In the realm of high-voltage electrical insulation, PD pattern characteristics, such as PD charge and inception voltage, are essential as assessment criteria in diagnostics systems using PD classifiers. This paper provides a review of various PD patterns and classifiers used by previous researchers, specifically for XLPE cables. In addition, the differences of the research on various sensor development based on PD detection in the past 27 years are also discussed. The repeatability, recognition accuracy, recognition speed, and effect of feature sizes on each PD classification method are reviewed and explained. The review indicates that the pattern recognition for PD signal using artificial neural network (ANN) exhibits better performance in terms of accuracy and repeatability than the other methods, and the reduction of feature size does not affect the accuracy of ANN.
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