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.
关键词
小波神经网络/燃气轮机/后备电源
Key words
wavelet neural network/gas turbine/backup power supply
维普
万方数据