Fault Diagnosis Method of Turbofan Engine Based on Capsule Neural Network
In order to solve the problem of low fault classification accuracy of aviation turbofan engine dataset,a fault diagnosis method of turbofan engine based on capsule neural network is proposed.First,the fault type and key variables are determined,then the convolutional capsule neural network model is constructed,and the segmented training set data is input into the model for training.Finally,the diagnostic model is used to diagnose the test set data and calculate the classification recognition accuracy.The proposed algorithm is tested on the NASA turbofan engine dataset,which proves that the classification and recognition accuracy of the model is improved,and can help the development of fault diagnosis of turbofan engine.