Research on Temperature Trend Prediction of Hydrogenerator Thrust Bearings Based on ARIMA and Neural Network
- Resource Type
- Conference
- Authors
- Liu, Yong; Li, Xiaozhi; Xing, Han; Huo, Rui; Zhang, Huan; Chen, Gang
- Source
- 2023 Panda Forum on Power and Energy (PandaFPE) Power and Energy (PandaFPE), 2023 Panda Forum on. :1110-1114 Apr, 2023
- Subject
- Power, Energy and Industry Applications
Signal Processing and Analysis
Hydraulic turbines
Neural networks
Predictive models
Market research
Real-time systems
Generators
Reliability
ARIMA
LSTM
Thrust bearing temperature
Trend forecasting
- Language
The temperature prediction of the hydrogenerator thrust bearing is of great significance to the safe and reliable operation of the unit. A kind of temperature trend prediction based on ARIMA and neural network is proposed. The LSTM neural network is used to predict the thrust bearing temperature. The temperature predicted by the LSTM neural network and the actual temperature difference form a deviation series. The deviation series is modeled and predicted by using ARIMA, and finally the temperature prediction is realized. The example results indicate that the RMSE of the 5-minute prediction of thrust bearing temperature is 0.723°C, which effectively realizes the prediction of thrust bearing temperature trend.