Research On Joint Detection And Location Method Of Partial Discharge In GIS Equipment

Gas insulated metal-enclosed switchgear(GIS for short)is a kind of electrical components such as high-voltage circuit breakers,high-voltage disconnectors,voltage transformers,current transformers,busbars,etc.Combined electrical equipment filled with sulfur hexafluoride gas and sealed inside.It has a series of advantages such as small size,high reliability and good adaptability to the environment.However,due to its airtight structure,once an insulation fault occurs inside the cavity,it will bring huge trouble to the maintenance work.The reason for the insulation failure is generally the partial discharge inside the GIS equipment.This paper starts with exploring the principles and causes of partial discharges in GIS equipment,and studies the technical means and fault location methods that can detect partial discharges in GIS equipment.Firstly,the formation principle of partial discharge generated in GIS equipment is studied,the characteristics of partial discharge are analyzed and summarized,several common types of discharge are summarized,and ultrasonic and UHF detection and fault location methods are studied in detail.The applicable scene and detection accuracy are analyzed,the advantages and disadvantages of these methods are analyzed,and a combined acoustic and electrical detection and localization method is proposed.Secondly,starting from the signal acquisition and measurement circuit,the ultrasonic and UHF joint detection hardware system is designed;at the same time,it has the functions of data acquisition,processing,analysis,display and storage,and has the ability to identify and analyze the maps of various discharge types.function and a software system that displays and analyzes the distance between the partial discharge fault source and the sensor.Finally,a GIS equipment partial discharge detection simulation experiment platform was built,and four common partial discharge defect physical models were artificially manufactured.Then,a mathematical model was established based on the discharge signal waveform,and the standard waveform was obtained by fitting the signal waveform,and the characteristic parameters of four kinds of defect discharge signals were extracted by using the binary tree complex wavelet transform algorithm.A part of the samples are input into the designed RBF combined neural network classifier for training and defect type identification.The identification results show that the recognition accuracy rate of this method for four types of partial discharge defects has reached more than 85%.The recognition effect is the best,with an accuracy rate of 98.26%,which verifies the effectiveness and accuracy of the GIS partial discharge joint detection technology proposed in this paper for the identification of partial discharge defect types.