高压设备放电紫外图像光斑区域特征提取

针对传统的高压电气设备紫外漏电检测方法存在的紫外图像处理算法复杂、精确度低等问题，采用基于高斯函数色彩映射的图像分割算法分割进行图像预处理。通过绝缘子污秽放电实验，拍摄高压故障设备紫外辐射图像，对紫外图像进行图像分割处理。从紫外光斑的二值图像中提取故障设备紫外辐射光斑区域特征，评估高压绝缘设备故障等级。实验过程中，在不...

Feature Extraction of Facular Area in Ultraviolet Image of High Voltage Equipment Discharge

Aiming at the problems of the traditional high-voltage electrical equipment ultraviolet image detection method, such as the complexity and low accuracy of the ultraviolet image processing algorithm, an image segmentation algorithm based on Gaussian function color mapping is proposed. Through the discharge experiment of pollution insulators, the ultraviolet images was used to shoot the ultraviolet images of the high-voltage faulty equipment, and the ultraviolet images were segmented. Extract the feature of the facular area of the faulty equipment from the binary image of the ultraviolet facular area, and evaluate the fault class of the high-voltage insulation equipment. During the experiment, ultraviolet images of high-voltage discharge equipment were taken at different distances, and the relationship between the detection distance and the facular area was analyzed. The experimental results show that the Gaussian function color mapping image segmentation algorithm has a better effect on the segmentation of the color facular area; the four characteristic of the discharge equipment ultraviolet spot area, perimeter, long axis, and short axis can be used to characterize the size of the discharge, so as to evaluate the fault class of the high-voltage fault equipment; the characteristic quantity of the leakage facular area has a non-linear negative correlation with the shooting distance.