Prediction of the dynamic behaviors of the heat exchangers with segmental baffles by artificial neural networks

A artificial neural networks (ANNs) model for the identification and prediction of the dynamic behavior of the heat exchangers is designed using ARX dynamic model.Based on finite experimental data,the dynamic behavior of the heat exchangers which use water and oil as wording media can be predicted by using the model.The oil side outlet temperature responses of the heat exchanger with the variation of its single-side flow-rate and the variation of the oil side inlet temperature of it are identified and predicted by means of Levenberg-Marquardt algorithm.The prediction results are compared with numerical results,it is shown that the neural network prediction results have higher precision and better generalization performance.At the same time,it is shown that ANN is competent for the dynamic identification and prediction of complicated systems.