摘要
为防止电晕放电带来的危害,需要对高压设备进行放电检测,采用日盲紫外成像法并利用开源计算机视觉库(OpenCV)对紫外图像量化分析.提取放电区域的量化参数,达到能量化分析放电量的目的。系统采用一种新的结构,利用单通道双谱紫外放电检测系统,其结构简单且成本较低;利用OpenCV相关函数,将紫外放电图像灰度化、二值化处理;采用一种自适应中值滤波(AMF-PDE)算法对放电图像进行滤波,提取了放电区域面积、周长等量化参数。最后进行对比实验,验证了放电量与光斑面积的正相关关系;同时,实验结果表明,观测距离与放电区域光斑面积呈幕函数关系。研究结果可作为一种新的方法来量化分析电器设备的放电量。
In order to prevent the harm caused by corona discharge, it is necessary to perform discharge detection on high-voltage equipment. The day-blind ultraviolet imaging method is used to quantify the ultraviolet image by OpenCV, and the quantitative parameters of the discharge region are extracted to achieve the purpose of energy-saving analysis of the discharge amount. The system adopts a new structure and utilizes a single-channel bispectral ultraviolet discharge detection system, which has a simple structure and low cost. The OpenCV correlation function is used to gray-scale and binarize the ultraviolet discharge image;The value filtering (AMF-PDE) algorithm denoises the discharge image and extracts the quantization parameters such as the area and perimeter of the discharge area. Finally, a comparative experiment was carried out to verify the positive correlation between the discharge amount and the spot area. At the same time, the experimental results show that the observation distance has a power function relationship with the spot area of the discharge area.
作者
翟世强
马立新
Zhai Shiqiang;Ma Lixin(School of Mechanical Engineering,University of Shanghai for Science and Technology, Shanghai 200093, China)
出处
《电子测量技术》
2019年第16期133-137,共5页
Electronic Measurement Technology
基金
上海张江国家自主创新重点项目(201310-PI-B2-008)资助
