Research On Corona Discharge Fault Detection Based On UV-Vis Dual Spectrum Fusion

The corona discharge of electrical equipment is one of the reasons for the unstable operation of the power system.If it cannot be detected early,it will cause immeasurable harm to the power system.Therefore,the location of the corona discharge can be detected in time,which will ensure the safety and stability of the power system is important.The UV-Vis dual spectrum fusion imaging system can detect the weak corona discharge phenomenon,collect the UV image and visible image of corona discharge through dual spectrum,and then use image fusion technology to combine the discharge information of the UV image with the background information of the visible image combined,the localization of weak corona discharge can be realized.However,most of the current ultraviolet-visible dual-spectrum fusion imaging systems have problems such as distortion of fusion image details and inability to quantify the discharge intensity.To this end,this topic has done the following research around these issuesFirstly,this paper analyzes the principle of UV-Vis dual-spectrum fusion imaging system,and demonstrates the necessity of image denoising and registration before corona discharge image fusion.Aiming at the image noise generated by ultraviolet ICCD(Intensified Charge Coupled Device)camera,this paper improves the threshold function of wavelet transform,and combines the wavelet transform of the improved threshold function with median filtering to filter out the mixed noise in ultraviolet images;for the ultraviolet ICCD camera and the visible CCD(Charge Coupled Device)camera due to the position deviation caused by the camera.For the mismatch of fusion images,this paper uses the registration algorithm of scale-invariant feature transformation to extract the feature points of the ultraviolet image and the visible light image,and then proposes a random sampling algorithm based on the feature triangle to eliminate the mismatched point pairs.Simulation experiments and evaluation index analysis results shows that the image denoising method in this paper can suppress the mixed noise well,and the registration accuracy and registration speed are improved compared with the traditional algorithm.Secondly,in order to improve the accuracy of locating corona discharge in the ultraviolet-visible dual-spectrum fusion imaging system,a fusion algorithm based on IHS(Intensity-Hue-Saturation)and wavelet transform is proposed.The I component and the ultraviolet image are decomposed by wavelet to obtain their respective high and low frequency components,and a fusion rule is established to process the high and low frequency components to make the fusion image clearer.Then the fusion effect and evaluation index of different algorithms are compared through the image fusion system designed based on MATLAB.The results show that the algorithm in this paper preserves the original detail information of the visible light image and improves the subjective visual effect of the fusion image.Finally,this paper develops a corona discharge intensity quantitative management system based on DELPHI.Firstly,image segmentation technology is used to process the denoised ultraviolet image to obtain the spot area,and then an ultraviolet spot extraction device is designed through experimental simulation to simulate the corona discharge to fit the relationship between the spot area and the discharge intensity,and then through the fitted relationship curve,the design of the corona discharge intensity quantitative management system is realized,thereby realizing the quantification of corona discharge intensity...