New Design Of Online Diagnosis System For Transformer Fault

Power transformer is one of the most important electrical equipments in the electricsystem. In order to insure the stability of power grid, it is indispensable to be reinforced thetransformer fault diagnosis. Therefore，in recent years，monitoring of power transformer hasbeen given more and more human and material resources，so the level and accuracy ofmonitoring raise much.And monitoring methods are diversity. The study of fault diagnosistechnology based on dissolved gas analysis is very important to maintain the reliable runningof elecrtic power system，and also an efficient method to detect the incipient fault intransformer.The neural network has the paralleling proeessing，learing，memorization，nonlinearitymapping，adaptation ability and robustness etc and strong capability to recognize and classifythe input samples.The possibility of the practical application of artificial neural network todiagnose fault of equipment is come true.So， to study the neural network fault diagnosismethod by the dissolved gases in transformer oil as the characteristics has provided the newway for the transformer failure diagnosis.Selecting and training the BP and RBF neural network which suitable to the powertransformer running condition and fault on-line detection，diagnosis and forecasting.We havediscussed the network construction，optimization and algorithmic，and the simulation resultsshow that the two methods compared with traditional transformer fault diagnosis methodshave obvious superiority and higher fault diagnosis rate..The empirical data result analysisindicated that，the RBF neural network is exuding the higher fault diagnosis rate and thetraining speed obviously compared to the BP neural network. Combining artifieial neuralnetworks and MATLAB experiment with Dissolved Gas Analysis is a typical method and thetransformer fault intelligent diangosis system is of friendly interface and excellent capabilityusing LabVIEW. First of all on the system main hardware devices need configurationselection, and analyses the basic parameters, performance and characteristics of these devices.Then design the software part of the system. Test results show that the new system made itpossible to realize real-time online monitoring of transformer fault diagnosis. And the diagnosis result more accurate and higher precision.In the end，the paper summarizes the excellent capability of the design of the faultdiangosis system and its shortcomings，and then analyses the outlook and development trendof fault intelligent diangosis systems in the future.