The evaluation of neural networks application for recognizing single-source PD forms generated in paper-oil insulation systems based on the AE signal analysis

被引：9

作者：

Borucki, S. ^{[1
]}

Boczar, T. ^{[1
]}

Cichon, A. ^{[1
]}

Lorenc, M. ^{[1
]}

机构：

[1] Tech Univ, Fac Elect Engn Automat & Informat, Inst Elect Power Engn, PL-45758 Opole, Poland

来源：

EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS | 2008年 / 154卷 / 1期

关键词：

Acoustic Emission; European Physical Journal Special Topic; Acoustic Emission Signal; Partial Discharge; Insulation System;

D O I：

10.1140/epjst/e2008-00512-7

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

The genesis of the research work presented in this paper constitutes the issue of the effective and efficient recognition of single-source one-time partial discharge (PD) forms that can occur in insulation systems of power transformers. The paper presents research results referring to the use of single-direction neural networks (SNN) for recognizing basic PD forms that can occur in paper-oil insulation impaired by aging processes. The research work results presented show the recognition effectiveness of basic PD forms depending on the descriptor of the analysis of the acoustic emission (AE) signal analysis.

引用

页码：23 / 29

页数：7