Prediction of paint thickness distributions from electrostatic paint spray equipment using phenomenological mathematical models so that computing time and hardware costs are reduced in comparison with physical process models

摘要

Method for determining paint thickness distribution, based on input of spray parameters for an electrostatic paint spray apparatus. Method is based on use of a phenomenological mathematical model to produce a quasi 3-D spray image. The dependence between model parameters and real spray parameters is generated using artificial neuronal networks that have been learnt using real measurements.