环境技术2024,Vol.42Issue(8) :216-221,227.

基于多特征融合的电力高压试验设备状态检测研究

Research on State Detection of Power High Voltage Test Equipment Based on Multi feature Fusion

王德文 宋强 张振 冀东红 付智鑫
环境技术2024,Vol.42Issue(8) :216-221,227.

基于多特征融合的电力高压试验设备状态检测研究

Research on State Detection of Power High Voltage Test Equipment Based on Multi feature Fusion

王德文 1宋强 1张振 1冀东红 1付智鑫2
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作者信息

  • 1. 国网甘肃省电力公司,兰州 730000
  • 2. 国网甘肃省电力公司白银供电公司,白银 730900
  • 折叠

摘要

电力高压试验设备运行环境往往涉及高电压、高电流等危险因素,对设备状态的检测造成了较大的困难,干扰因素较多,使得检测的结果精度不高.为了解决这一问题,提出了基于多特征融合的电力高压试验设备状态检测方法.计算电力高压试验设备的最大截流过电压,分析其对应的电压波形特征.利用小波分解去噪处理设备的超声波信号后得到相应的信号特征.分别提取设备在紫外脉冲环境下的场强特征及紫外辐射量特征,对于提取到的多种特征进行融合处理后进行电力高压试验设备的状态检测,得到了相关的检测结果.经过测试可知,该方法在电力高压试验设备的状态检测实践中表现出了较高的精度,能够满足电力高压试验设备安全运维工作的实际需求.

Abstract

The operating environment of power high-voltage testing equipment often involves hazardous factors such as high voltage and high current,which makes it difficult to detect the equipment status.There are many interference factors,resulting in low accuracy of the detection results.To address this issue,a state detection method for power high-voltage testing equipment based on multi feature fusion is proposed.Calculate the maximum cut-off overvoltage of the power high-voltage testing equipment and analyze its corresponding voltage waveform characteristics.By using wavelet decomposition to denoise the ultrasonic signal of the equipment,corresponding signal features are obtained.Extract the field strength characteristics and ultraviolet radiation characteristics of the equipment under ultraviolet pulse environment separately,fuse the extracted multiple features,and perform state detection of the power high-voltage test equipment,obtaining relevant detection results.After testing,it is known that this method has shown high accuracy in the state detection practice of power high-voltage testing equipment,and can meet the practical needs of safe operation and maintenance of power high-voltage testing equipment.

关键词

电力高压试验设备/设备状态/状态检测/多特征融合/电压波形特征/小波分解

Key words

electric high voltage testing equipment/equipment status/status detection/multi feature fusion/voltage waveform characteristics/wavelet decomposition

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出版年

2024
环境技术
广州电器科学研究院有限公司

环境技术

CSTPCD
影响因子:0.995
ISSN:1004-7204
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