Failure Diagnosis Method of Gas Turbine Backup Power Supply Operation Based on Wavelet Neural Network
To improve the accuracy of fault diagnosis for gas turbine backup power supply operation,this study proposes a wavelet neural network-based fault diagnosis method for gas turbine backup power supply operation.First,collect power operation parameters through sensors and data acquisition cards.Then use wavelet transform method to extract fault features.Finally,a wavelet neural network model is constructed to achieve comprehensive diagnosis of operational faults in the backup power supply of gas turbines.The experimental results show that the proposed method exhibits high fault diagnosis accuracy and low recognition error after application,effectively improving the accuracy of diagnosis.
wavelet neural networkgas turbinebackup power supply
万方数据
维普
