Integrated Classification Technique for Typical Insulation Flaws in Gas Insulated Switchgear Based on Acoustic Detection

SI Wen-rong1; HUANG Hua1; FU Chen-zhao1; LI Yan-ming2

doi:10.13296/j.1001-1609.hva.2011.12.006

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Integrated Classification Technique for Typical Insulation Flaws in Gas Insulated Switchgear Based on Acoustic Detection

更新时间：2025-04-26

- Integrated Classification Technique for Typical Insulation Flaws in Gas Insulated Switchgear Based on Acoustic Detection
- High VoltageApparatus Vol. 47, Issue 12, Pages: 11-18(2011)
- 作者机构：
  
  1. 华东电力试验研究院有限公司
  2. 西安交通大学电力设备电气绝缘国家重点实验室
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2011.12.006
  CLC： TM835.4
- Published：2011
- 稿件说明：
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[1]司文荣,黄华,傅晨钊,李彦明.超声检测进行气体绝缘组合电器典型绝缘缺陷识别[J].高压电器,2011,47(12):11-18.

SI Wen-rong1, HUANG Hua1, FU Chen-zhao1, et al. Integrated Classification Technique for Typical Insulation Flaws in Gas Insulated Switchgear Based on Acoustic Detection[J]. High voltageapparatus, 2011, 47(12): 11-18.
[1]司文荣,黄华,傅晨钊,李彦明.超声检测进行气体绝缘组合电器典型绝缘缺陷识别[J].高压电器,2011,47(12):11-18. DOI： 10.13296/j.1001-1609.hva.2011.12.006.

SI Wen-rong1, HUANG Hua1, FU Chen-zhao1, et al. Integrated Classification Technique for Typical Insulation Flaws in Gas Insulated Switchgear Based on Acoustic Detection[J]. High voltageapparatus, 2011, 47(12): 11-18. DOI： 10.13296/j.1001-1609.hva.2011.12.006.

摘要

介绍了基于超声检测的气体绝缘组合电器（gas insulated switchgear

GIS）典型绝缘缺陷识别技术。该技术由基于幅值模式（amplitude mode

AM）、飞行模式（flying mode

FM）、基于相位模式（phase mode

PM）的特征参数提取与判别3个主要模块组成。其中

针对AM提取的特征参数有频率成分50 Hz和100 Hz

用于区分缺陷信号与背景噪声

以及周期最大最小有效值比和周期最大最小峰值比用于区分自由金属微粒和其他超声信号。基于FM提取的特征参数有等效飞行时宽和等效飞行距离

用于判别超声信号是否来自于自由金属微粒。而基于PM提取的统计放电指纹则用于识别局部放电（partial discharge

PD）缺陷类型

包括母线和筒壁突起、绝缘子内部缺陷和悬浮电极。试验结果验证了该基于超声检测进行GIS典型绝缘缺陷识别技术的可行性和实用性。

Abstract

An integrated classification technique for typical insulation flaws in gas insulated switchgear（GIS） using acoustic detection is presented.This technique includes parameters extraction and classification based on the amplitude mode（AM）

flying mode（FM）

and phase mode（PM）

respectively.The frequency components of 50 Hz and 100 Hz correlated to power cycle

the max/min ratio of root mean square value（RMSV） sequence

and the max/min ratio of periodic peak value（PPV） sequence are extracted from the AM to distinguish the detected acoustic signals of flaws from background noise.The equivalent flying time-width and flying distance are extracted from the FM to identify the detected acoustic signals of free metallic particles

and the statistic fingerprints are deduced from the PM to identify partial discharge mode（corona

inner discharge

or floating discharge）of flaws in GIS.Test results demonstrate that the present technique can be applied to GIS acoustic detection system for typical insulation flaws identification.

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Application of Partial Differential Equation to Suppress White-noise Interference in GIS PD Signals

Study on the Discharge Characteristics on Basin-type Insulator Surface in GIS

Fault Diagnosis of Gas Insulated Switchgear （GIS） Based on Hilbert-Huang Transform （HHT） of On-line Ultrasonic Detection Signals

Research on Application of Microphone-optimized Spiral Arrays-based Acoustic Imaging Devices in Partial Discharge Localization

Study on Fiber Interferometric Partial Discharge Ultrasonic Sensing Method Based on Acoustic-optic Modulation and RF Phase Detection

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