基于计算机视觉的高压配电开关状态监测与诊断研究

Research on State Monitoring and Diagnosis of High Voltage Distribution Switches based on Computer Vision

计算机视觉通过图像采集、分析处理来获取对象关键特征信息,其已被广泛应用于工业监测和故障诊断中。通过计算机视觉技术,可以实现对高压配电开关状态的实时监测和精准诊断,并及时发现和预防潜在的故障问题,从而提高电力系统的可靠性和安全性。本文首先介绍了计算机视觉在高压配电开关状态监测与诊断中应用的理论基础和关键技术,包括图像处理、特征提取和模式识别,接着详细阐述了高压配电开关自诊断系统的设计要求,包括硬件设计和软件架构的构建,最后通过一系列的技术测试验证了所提方案的有效性,展现了计算机视觉技术在电力系统高压配电开关监测与诊断中的应用潜力和实际效益。

Computer vision can obtain key feature information of objects through image acquisition,analysis and processing,which has been widely used in industrial monitoring and fault diagnosis.Through computer vision technology,real-time monitoring and accurate diagnosis of high-voltage distribution switch status can be realized,and potential fault problems can be discovered and prevented in time,thus improving the reliability and safety of the power system.This paper first introduces the theoretical basis and key technologies of computer vision application in state monitoring and diagnosis of high voltage distribution switches,including image processing,feature extraction and pattern recognition.The design requirements of self-diagnosis system of high voltage distribution switch are described in detail,including hardware design and software architecture construction.Through a series of technical tests,the effectiveness of the proposed scheme is verified,and the application potential and practical benefits of computer vision technology in the monitoring and diagnosis of high-voltage distribution switches in power systems are demonstrated.