Research On Fault Diagnosis Method Of Substation Equipment Based On Infrared Image Processing

With the continuous enhancement of China's comprehensive national strength,the rapid development of all walks of life,the continuous expansion of scale and strength,followed by higher requirements for the reliability and security of our power grid,which requires us to take appropriate measures and means to improve the reliability of the power grid and the control ability of the power grid operation,when abnormal,staff can be timely warned.To judge equipment defects or abnormal operating conditions of equipment and take appropriate measures to eliminate defects,live detection profession plays the role of "physical examiner" in power grid,and gradually becomes an important detection project in power grid.Infrared detection technology,as one of the important detection means,has been widely used in power system.The application of this technology greatly improves the early warning ability of power system faults and defects,avoids corresponding accidents and reduces unnecessary blackouts to a large extent.However,the current infrared diagnosis technology still needs to rely on the experience and technical level of the inspectors to analyze the infrared image in most cases.Under special circumstances,it is difficult to guarantee the real-time and accuracy of fault analysis and judgment.In this paper,image processing technology is used to realize the fault detection of substation electrical equipment and improve the detection level of infrared diagnosis technology.The main contents of this paper are as follows:Firstly,the development history of infrared detection technology is briefly introduced,and the principle of infrared imaging is introduced,and the imaging characteristics of infrared image are analyzed based on this scientific basis.The common image denoising methods,such as mean filter,adaptive filter and wavelet transform,are introduced,and their denoising effects are analyzed and compared.It is determined that wavelet transform and wavelet transform are selected in this paper.Mean filter combined with denoising method.Secondly,aiming at the low contrast of infrared image,the method of image enhancement is introduced,and the histogram equalization method is used for experimental detection.Thirdly,in the technical means of image segmentation,the methods of edge-based segmentation,threshold-based segmentation,watershed algorithm and clustering algorithm are introduced in detail,and their respective algorithms are introduced and experimented.Finally,a method based on image gray value is proposed to achieve the goal of electrical equipment fault diagnosis,and three groups of examples are used to verify the accuracy of the method,which proves its feasibility.The practicability and popularization can help the inspectors of electric power enterprises to better grasp the operation status of equipment and realize the transformation from power grid to condition-based maintenance in an all-round way.