Research on Prediction Method of Measured Swing Signal of Hydraulic Turbine Unit Based on EMD-LSTM Model
The operating condition of hydropower units is greatly related to the safety and stability of power stations and grids.The prediction of swing signals from unit monitoring can improve the defect of fault diagnosis.So,a combina-tion of empirical modal decomposition(EMD)and neural network model was used to put forward an EMD-LSTM-based model for predicting the swing signal of a hydropower station.The proposed model was applied to predict the swing sig-nal of a hydropower station in China,and the results were compared with those of LSTM,GA-BP and EMD-GABP mod-els.The results show that the model exhibits high accuracy in predicting the unit swing signal,outperforming other models.
hydraulic turbine setsswing signalempirical modal decompositionlong and short term memory neural networksprediction accuracy
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