Pattern Recognition Method of Power Transformer Fault Maintenance Mode Based on Hybrid Neural Network
In order to ensure the safe operation of power transformer and accurately judge the fault maintenance mode,a fault maintenance mode recognition method based on hybrid neural network algorithm is studied.The hybrid neural network is con-nected with the sensor module,and the radial basis function is combined to analyze the linear mapping relationship between the sample data sets to solve the weight value of the hidden layer center and the output layer in the hybrid neural network.The classified fault data are initialized,and the nearest distance clustering method is used to obtain the node paths under the same density.The different characteristic gases generated by power transformers are analyzed by the characteristic quantities of equal proportion,and are classified into different levels,the propagation direction of power transformer fault data is clarified,and the original fault data are trained independently and normalized.According to the characteristic matrix,the nonlinear vector is out-put,and the output layer outputs a posteriori probability of the fault mode to complete the power transformer fault maintenance mode recognition.The experimental results show that the proposed method has high recognition accuracy,fast iteration effi-ciency and good recognition effect.It provides a new idea for the decision-making of power transformer fault maintenance strat-egy.
万方数据
维普
