Seismic response prediction of electrical equipment interconnected system of traction station based on LSTM neural network
In the railway traction substation,the flexible conductor-electrical equipment interconnected system has strong geometric nonlinearity.To improve the analysis efficiency of the system,an improved recursive prediction method for the flexible conductor-electrical equipment interconnected system was proposed.The prediction model was established based on recursive long short-term memory(LSTM)neural network and the Dropout regularization.The theoretical analysis model of the interconnected system between the flexible conductors and electrical equipment was established,fully considering the coupling effects of flexible conductors on adjacent equipment.Besides,to fully reflect the generalization ability of the model,41 seismic time histories with large differences in peak ground acceleration(PGA),frequency spectrum,and duration were selected.According to the recursive scheme,the selected seismic time histories,along with the displacement responses obtained by the theoretical analysis model of the flexible conductor-electrical equipment interconnected system,were subjected to sliding-window slicing treatment and established the mapping relationship between model input features and output labels.In addition,the model was used to predict the seismic displacement responses of the interconnected system,and several evaluation indices were used to evaluate the model performance comprehensively.The results indicated that the LSTM recursive prediction model exhibits excellent performance in seismic response prediction.When combined with the Dropout regularization,it effectively prevents model overfitting and improves the adaptability of the model.For seismic time-history data with significant variations,the model can rapidly predict earthquake responses with lower errors and higher correlations,demonstrating high accuracy,efficiency,and generalization capability.This method can quickly and accurately predict the seismic responses of the flexible conductor-electrical equipment interconnected system at any time point,providing a new research idea for the seismic design of railway traction substations.
long short-term memory neural networkelectrical equipmentflexible conductorinterconnected systemseismic response prediction
国家科技期刊平台
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