基于超声检测法的GIS内金属微粒参数识别技术

牛博; 杨鼎革; 袁福祥; 何继厚; 任双赞; 郭子豪

doi:10.13296/j.1001-1609.hva.2026.07.008

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基于超声检测法的GIS内金属微粒参数识别技术

研究与分析 | 更新时间：2026-07-06

- 基于超声检测法的GIS内金属微粒参数识别技术
- Ultrasonic Detection-based Parameter Identification for Metal Particles in GIS
- 高压电器 2026年62卷第7期页码：85-94
- 作者机构：
  
  国网陕西省电力有限公司电力科学研究院，西安 710100
  国网陕西省电力有限公司超高压公司，西安 710026
- 作者简介：
  
  牛博（1980—），男，博士，教授级高工，主要研究方向为高电压试验和电力设备故障诊断（通信作者）（E-mail:niubo127@163.com）。
- 基金信息：
  
  国网陕西省电力有限公司科技项目(GIS突发性绝缘故障诱发机制及缺陷检测方法研究);Science and Technology Project of State Grid Shaanxi Electric Power Co., Ltd.Research on the Mechanism of Sudden Insulation Faults in GIS and Methods for Defect Detection
- DOI：10.13296/j.1001-1609.hva.2026.07.008
  中图分类号：
- 收稿：2026-01-07，
  
  修回：2026-03-11，
  
  纸质出版：2026-07-16
- 稿件说明：
移动端阅览
牛博, 杨鼎革, 袁福祥, 等. 基于超声检测法的GIS内金属微粒参数识别技术[J]. 高压电器, 2026,62(7):85-94.

NIU Bo, YANG Dingge, YUAN Fuxiang, et al. Ultrasonic Detection-based Parameter Identification for Metal Particles in GIS[J]. High Voltage Apparatus, 2026, 62(7): 85-94.
牛博, 杨鼎革, 袁福祥, 等. 基于超声检测法的GIS内金属微粒参数识别技术[J]. 高压电器, 2026,62(7):85-94. DOI： 10.13296/j.1001-1609.hva.2026.07.008.

NIU Bo, YANG Dingge, YUAN Fuxiang, et al. Ultrasonic Detection-based Parameter Identification for Metal Particles in GIS[J]. High Voltage Apparatus, 2026, 62(7): 85-94. DOI： 10.13296/j.1001-1609.hva.2026.07.008.

摘要

GIS运行过程中内部不可避免地会产生金属微粒，而金属微粒一直是危害GIS绝缘性能的主要来源之一。基于超声检测法识别金属微粒参数，是对GIS绝缘状态高效监测和在线评估的关键技术。文中基于GIS内金属微粒的运动分析，研究不同超声信号谱图的变化规律，重点研究超声幅值—飞行时间谱图与微粒参数的关系，采用仿真和实验的方法，分析超声幅值—飞行时间谱图中的线性分量和正弦分量与微粒质量、最大飞行高度等参数的量化关系。研究表明，金属微粒主要受重力与电场力作用，其中重力影响谱图中的线性分量，电场力影响谱图中的正弦分量，通过分解出的两种分量可推导微粒参数与之对应的数值关系，据此估算微粒自身特性参数，最后在GIS同轴实验腔体中进行双盲实验验证，结果表明基于超声检测法识别GIS内微粒参量的准确率可在80%以上，具有较好的准确识别能力。

Abstract

Metal particles are inevitably produced in GIS during operation and have always been one of the main sources of harming GIS insulation performance. Identification of metal particle parameters based on ultrasonic detection is a key technology for efficient monitoring and online evaluation of GIS insulation status. Based on the motion analysis of metal particles in GIS

in this paper the variation of different ultrasonic signal spectrums is studied， with the relationship between acoustic amplitude-flight time pattern and particle parameters in particular

and the quantitative relationship among the linear component and sinusoidal component of acoustic amplitude-flight time pattern and particle mass

maximum flight height and other parameters are analzyed by way of simulation and experiment methods. The research shows that metal particles are mainly affected by gravity and electric field force

in which the former affects the linear component of the spectrum and the latter affects the sinusoidal component of the spectrum. The numerical relationship between particle parameters and their corresponding values can be derived from the two decomposed components and

on this basis

the particle's own characteristic parameters can be estimated. Finally

the double-blind experiment is carried out in the GIS coaxial experimental chamber for verification. The results show that the accuracy of particle parameter identification in GIS based on ultrasonic detection method can reach more than 80%

and the method has a good ability of accurate identification.

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