| Electricity is an important energy source for the country.Maintaining the normal operation of the transmission line network is an important guarantee for the steady development of the country’s economy.The total number of transmission lines in China is the second in the world.Insulators,as indispensable devices in transmission networks,are of great importance to maintain the safe operation of electrical insulators.Based on the aerial photo insulator image,it is possible to quickly and accurately detect and maintain the status of the insulators in the operating grid.Insulators are widely used in transmission lines.If artificial methods are used to detect human and material resources,insulator fault detection based on UAV aerial images can be easily and efficiently solved.This is of great practical significance.Through the analysis of insulator information in UAV aerial transmission line image,it can quickly and accurately detect the status of insulators in the transmission network and maintain the power grid in time.In view of the above reasons,this thesis has done two parts.The first part is about the preprocessing of the aerial image based on the poor quality of the unmanned aerial image,and so on.The background of the UAV aerial image is complex and diverse Therefore,a set of preprocessing methods of UAV aerial image in complex background is proposed.Firstly,the histogram equalization algorithm based on the gray-scale transform is used to improve the sharpness and contrast of the image.Secondly,through the wavelet denoising algorithm based on edge detection And CNN neural network de-blurring algorithm based on GAN counterintelligence to reduce the noise and blur in aerial images.The second one: UAV aerial image after the first pretreatment,the sharpness of the image has been greatly improved,first through improved Canny edge detection algorithm to detect the edge of the image,you can get clear and accurate image edge information,Then the improved Hough transform method is used to detect the ellipse to obtain the parameters of the insulator ellipse.Finally,the classification algorithm is designed to verify the insulator string through the parameters of the ellipse.In order to prove the feasibility and the superiority of the proposed method,the algorithm proposed in this paper is simulated by using MATLAB 2016 a.The simulation results show that the proposed algorithm is feasible And better than the traditional algorithm.The results show that the proposed method can detect the elliptic parameters of the insulator string in the UAV aerial image,and can judge and locate the insulator fault in the UAV aerial image.The main contents of this paper are the preprocessing methods for the aerial image of UAV and the fault diagnosis and identification of the insulator in the transmission line.The detection of the fault of the insulator in the transmission line by using the image processing technology is achieved initially successfully.Any hidden dangers in transmission lines should be promptly checked to prevent the occurrence of accidents and economic losses that may be caused by accidents.The simulation results show that the algorithm proposed in this paper can accurately detect the outline of the insulator profile of the UAV aerial transmission line and diagnose the fault condition of the insulator.It has high practical significance that can be applied to the actual Engineering.The method proposed in this article is simple and effective,which is a realization of the technology of patrolling the smart grid and provides new ideas and new solutions for the realization of the smart grid... |
