基于机器视觉的电力移动巡检作业安全检测方法研究  

Research on Safety Detection Method of Power Mobile Inspection Based on Machine Vision

作　　者：郭瑜 GUO Yu(State Grid Jinhua Power Supply Commpany,Jinhua 321001,China)

机构地区：[1]国网金华供电公司,浙江金华321001

出　　处：《机械制造与自动化》2022年第6期231-234,共4页Machine Building & Automation

摘　　要：由于传统的电力移动巡检作业安全检测方法中图像带有较高噪声,使得检测结果误报率较高,因此设计一种基于机器视觉的电力移动巡检作业安全检测方法。通过VFW体系获取电力移动巡检图像,根据维纳滤波的方法实现巡检图像降噪,应用最大熵去模糊方法完成图像的清晰度提升。利用机器视觉技术提取并匹配巡检图像的特征点,最终完成整体的电力安全检测。仿真分析表明:与传统方法相比,所提方法安全故障的误报率明显降低。To reduce the high false alarm rate of detection result due to the high noise of the image in the traditional safety detection method of power mobile inspection,a safety detection method of power mobile inspection based on machine vision is designed.The power mobile inspection image is obtained through the VFW system,the inspection image noise is reduced by the Wiener filter method,and the maximum entropy deblurring method is applied to improve the definition of the image.Machine vision technology is used to extract and match the feature points of patrol image to complete the overall power security detection.Simulation results show that the false alarm rate of safety fault by the proposed method is significantly reduced compared with the one by traditional method.

关 键 词：机器视觉 移动巡检 电力 安全检测 VFW体系 图像降噪 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]