Centrifugal Pump Cavitation Fault Diagnosis Based on Artificial Neural Network
In order to study the cavitation fault diagnosis of centrifugal pump and explore the prediction effect of artificial neural network concerning the fault diagnosis,the flow field of centrifugal pump was simulated by numerical simulation,the pressure values and working points of various points in the downstream field in different states were collected as the input characteristics and the volume fraction of the gas in the rotating region was taken as the label characteristic to conduct the neural network modeling for the cavitation state of the centrifugal pump.The LSTM and one-dimensional convolutional network were used to process the time series data,and the regularization loss function was added in feature extraction stage to ensure network sparsity.The accuracy rate of classification task of the trained model on the test set exceeded 95%,which can effectively diagnose the cavitation degree of centrifugal pump.
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