摘要
随着电力系统规模不断扩大,输配电网络日趋复杂,电气设备状态监测与故障诊断技术面临新的挑战。传统电气设备运维方式存在人工巡检效率低、故障预测滞后、数据分析不及时与设备管理欠规范等问题。本文针对电力工程中电气设备状态监测与故障诊断问题,围绕智能化技术在电气设备状态监测与故障诊断领域取得的进展展开研究。计算机视觉技术实现了智能巡检,深度学习算法提升了故障预测准确率,边缘计算加快了数据处理速度。工程实践表明,这些技术创新提高了设备运行可靠性,降低了维护成本,实现了预知维修模式向智能化转型。
With the continuous expansion of power system and the increasing complexity of transmission and distribution network,the technology of condition monitoring and fault diagnosis of electrical equipment is facing new challenges.The traditional operation and maintenance mode of electrical equipment has some problems,such as low efficiency of manual inspection,lagging fault prediction,untimely data analysis and nonstandard equipment management.This paper focuses on the issue of condition monitoring and fault diagnosis of electrical equipment in power engineering,and conducts research on the progress made by intelligent technologies in the field of condition monitoring and fault diagnosis of electrical equipment.Computer vision technology realizes intelligent inspection,deep learning algorithm improves the accuracy of fault prediction,and edge calculation speeds up data processing.Engineering practice shows that these technological innovations improve the reliability of equipment operation,reduce the maintenance cost,and realize the transformation from predictive maintenance mode to intelligence.
作者
孙文锋
SUN Wenfeng(Goldwind Science&Technology Co.,Ltd.,Urumqi 830063,P.R.China)
出处
《灯与照明》
2025年第6期170-172,共3页
Light & Lighting
关键词
电气设备
状态监测
故障诊断
智能化技术
预知维修
electrical equipment
condition monitoring
fault diagnosis
intelligent technology
predictive maintenance
