| 摘要 |
A method for determining spraying parameters that are suitable as input values for a paint spraying unit that can electrostatically charge a liquid paint. In this case, at least one artificial neural network is used to determine the spraying parameters, an output of such a neural network being available for each spraying parameter. A suitable number of real measured values are fed to the one neural network or a plurality of neural networks as input values, initially in a learning phase. The measured values further contain associated real spraying parameters in addition to a paint thickness distribution in the form of discrete values. Input values are fed to the one neural network or a plurality of neural networks in the application phase. The input values being the result of an analysis of the paint thickness distribution of a targeted, that is to say prescribed, spraying result.
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