Study On Discharge And Heating Characteristics Of Suspension Insulator Based On Ultraviolet And Infrared Detection

Insulator is one of the most used devices in power system,and its insulation status directly affects the safety and stable operation of power grid.At present,the physical characteristic quantity of insulator detection is relatively single,so it is difficult to fully identify its defects and operation status.Based on this,this paper proposes a joint detection method of infrared imaging and ultraviolet imaging,studies the heating and discharge problems of deteriorated porcelain insulator and aging composite insulator under different factors,and carries out relevant research on the diagnosis of typical defects.The influence characteristics of detection distance,temperature,humidity,wind speed and air pressure on the quantitative parame ters of UV imaging are analyzed quantitatively.The influence curves of different factors on UV imaging detection are obtained and fitted.On this basis,a normalization method based on correction coefficient is proposed.The corrected relative error is le ss than 20%,This method realizes the normalization of test results under different environmental conditions,which is helpful to the quantitative analysis of insulator defect diagnosis under different factors.The test platform of suspension insulator det ection based on artificial climate chamber was built.The influence of environmental humidity,low zero insulator position and equivalent salt density on the heating and discharge characteristics of110 k V porcelain insulator string was studied by using Flir T450 SC infrared thermal imager and Coro CAM504 ultraviolet imager,and the heating reasons of porcelain insulator string were analyzed;The effects of environmental humidity,salt spray conductivity and rainfall intensity on the discharge and heating of co mposite insulators with different operating years were analyzed.According to the electric field characteristics of water droplets attached to insulators,two simplified analysis models were proposed.The effects of water droplet volume,position,conducti vity and relative permittivity on the corona inception and flashover voltage were studied.Based on the characteristics of insulator discharge and heating,the infrared and ultraviolet characteristic parameters database of typical insulator defects is established,and the ultraviolet parameters are normalized.Using the decision tree diagnosis method based on classification regression tree algorithm and taking the test data as the training sample,the diagnosis model of insulator low zero value and aging defects is established,and the diagnosis system is developed based on Python,which realizes the evaluation and diagnosis of defect type,and puts forward the maintenance suggestions.