Research on RBF Neural Network of Wet Cooling Tower Under Cross-Wind Conditions

Abstract

Brief description is given of existing appraising methods for the performance of cooling tower and their shortcoming firstly. Then the mathematics model of cooling tower operation performance is given by means of relative perfect RBF neural network. Comparing with the usual linearity and non-linearity cooling tower mathematics model, the RBF neural networks mathematics can more truly reflect cooling tower operation performance. This conclusion is valuable for giving a more true and simple method for appraising the operation performance of cooling tower. In this text, we consider that cross-wind effect operation efficiency, the complex process of heat and mass transfer between gas and water is easily effected by the air temperature of surroundings,humidity and the influence of cross-wind.