电气开关2024,Vol.62Issue(6) :88-90,94.

基于神经网络模型的带电设备故障红外诊断的研究

Research on Infrared Diagnosis of Live Device Fault Based on Neural Network Model

周迅 石惠承 莫加辉 陈湘如
电气开关2024,Vol.62Issue(6) :88-90,94.

基于神经网络模型的带电设备故障红外诊断的研究

Research on Infrared Diagnosis of Live Device Fault Based on Neural Network Model

周迅 1石惠承 1莫加辉 1陈湘如1
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作者信息

  • 1. 国网嘉兴供电公司,浙江 嘉兴 314000
  • 折叠

摘要

近年来,红外热成像等带电检测技术在电力系统中得到了普遍应用,并随着技术的进一步成熟,已经成为在不停电条件下精准发现设备过热等缺陷的有力手段.利用红外热成像技术对高压电气设备进行带电检测,有利于及时发现设备发热部位及时判别发热原因,减少非计划停电,为检修决策提供依据,进一步提升电力设备安全管控水平,保障更优质可靠的电力供应,更好地服务经济社会发展和人民美好生活需要.

Abstract

Recently,infrared thermal imaging and other live detection technologies have been widely used in power systems.With the further maturity of the technology,it has become a powerful means to accurately find the defects such as equipment overheating under the condition of no power cut.The use of infrared thermal imaging technology for live detection of high-voltage electrical equipment is conducive to find the heating parts of the equipment timely,identify the causes of heating timely,reduce unplanned power outages,provide a basis for maintenance decisions,further improve the safety control level of power equipment,ensure a higher quality and reliable power supply,and better serve the economic and social development and the needs of people's better life.

关键词

红外检测/故障诊断/神经网络

Key words

infrared detection/fault diagnosis/neural network

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出版年

2024
电气开关
沈阳电气传动研究所

电气开关

影响因子:0.281
ISSN:1004-289X
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