摘要
随着电力行业的发展,变电站的安全运行对电网的稳定性至关重要。传统的变电站巡检方式存在效率低下、人力成本高等问题。本文针对此问题设计了一种基于机器视觉的变电站智能巡检系统,利用图像处理技术和深度学习算法实现对变电站设备的自动检测和异常识别,从而提高了巡检效率和准确性。
With the development of the power industry,the safe operation of substations is crucial to the stability of the power grid.Traditional substation inspection methods suffer from issues such as low efficiency and high labor costs.To address these issues,this article proposes an intelligent inspection system for substations based on machine vision.By utilizing image processing techniques and deep learning algorithms,the system achieves automatic detection and abnormality identification of substation equipment,thereby improving inspection efficiency and accuracy.
作者
郭晋超
Guo Jinchao(State Grid Jiangsu Electric Power Co.,Ltd.,Suzhou Power Supply Branch,Suzhou,Jiangsu,China,215000)
出处
《仪器仪表用户》
2024年第9期27-29,32,共4页
Instrumentation
关键词
机器视觉
变电站
智能巡检
图像处理
深度学习
machine vision
substation
intelligent inspection
image processing
deep learning
