摘要
针对传统方法在电能表计量误差自动检测中应用效果不佳的问题,本文提出了基于机器视觉的电能表计量误差自动检测方法,先采集电能表图像信息,采用加权平均值法对电能表图像灰度化,然后利用频域滤波技术对图像去噪处理,最后利用机器视觉技术提取图像信息,将其与标准计量数据对比,识别计量误差。实验证明,应用设计方法平均相对误差低于0.1%,漏检率在1%以下,应用效果较好。
In response to the problem of poor performance of traditional methods in automatic detection of metering errors in electric energy meters,this paper proposes a machine vision based automatic detection method for metering errors in electric energy meters.Firstly,the image information of the electric energy meter is collected,and the weighted average method is used to grayscale the image.Then,frequency domain filtering technology is used to denoise the image.Finally,machine vision technology is used to extract image information and compare it with standard metering data,Identify measurement errors.Experimental results have shown that the average relative error of the application design method is less than 0.1%,and the missed detection rate is below 1% The application effect is good.
作者
史三省
付国栋
宋珊珊
SHI Sansheng;FU Guodong;SONG Shanshan(Marketing Service Center,State Grid Henan Electric Power Company,Zhengzhou,Henan 450000,China)
出处
《自动化应用》
2023年第24期222-223,226,共3页
Automation Application
关键词
机器视觉
电能表
计量误差
自动检测
加权平均值
machine vision
electricity meter
measurement error
automatic detection
weighted average
