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In the light of the characteristics of Elman neural network model which can be approximate to the arbitrary non-linear function and its ability to reflect the dynamic characteristics of the system, this paper provides a state prediction model of flue gas turbine by applying Elman neural network and makes prediction of the overall vibration value. Compared to traditional static BP network prediction model, examples show that Elman neural network model has simple structure and wonderful dynamic characteristics. This model can accurately predict the state of flue gas turbine, with high convergence rate and precision. It has a good performance in non-linear time series prediction, indicating that this model is feasible in the state prediction of flue gas turbine.
Date of Conference: 16-19 Aug. 2009