This paper documents the set-up and validation of nonlinear autoregressive exogenous (NARX) models of a heavy-duty single-shaft gas turbine. The considered gas turbine is a General Electric PG 9351FA located in Italy. The data used for model training are time series data sets of five different maneuvers taken experimentally during the start-up procedure. The trained NARX models are subsequently used to predict other five experimental data sets and comparisons are made among the outputs of the models and the corresponding measured data. Therefore, this paper addresses the challenge of setting up robust NARX models, by means of an accurate selection of training data sets and a sensitivity analysis on the number of neurons. Moreover, a new performance function for the training process is defined to weigh more the most rapid transients. The final aim of the developed simulation models is the set-up of a powerful and easy-to-build simulation tool which can be used for both control logic tuning and gas turbine diagnostics, characterized by good generalization capability.
Set-up of a Robust NARX Model Simulator of Gas Turbine Start-up
BAHLAWAN, Hilal;MORINI, Mirko;PINELLI, Michele;SPINA, Pier Ruggero;VENTURINI, Mauro
2016
Abstract
This paper documents the set-up and validation of nonlinear autoregressive exogenous (NARX) models of a heavy-duty single-shaft gas turbine. The considered gas turbine is a General Electric PG 9351FA located in Italy. The data used for model training are time series data sets of five different maneuvers taken experimentally during the start-up procedure. The trained NARX models are subsequently used to predict other five experimental data sets and comparisons are made among the outputs of the models and the corresponding measured data. Therefore, this paper addresses the challenge of setting up robust NARX models, by means of an accurate selection of training data sets and a sensitivity analysis on the number of neurons. Moreover, a new performance function for the training process is defined to weigh more the most rapid transients. The final aim of the developed simulation models is the set-up of a powerful and easy-to-build simulation tool which can be used for both control logic tuning and gas turbine diagnostics, characterized by good generalization capability.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
