Prediction Model of Coating Growth Rate for Varied Dip-Angle Spraying Based on Gaussian Sum Model

Abstract

In automatic spraying of spray painting robot, in order to solve the problems of coating growth rate modeling for varied dip-angle spraying technology, a prediction mode of coating growth rate using the Gaussian sum model is proposed. Based on the Gaussian sum model, a theoretical model for coating growth rate with varied dip-angle spraying is established by using the theory of differential geometry. The coating thickness of the sample points in the distribution range of the coating was obtained by making the experiment of varied dip-angle spraying. Based on the theoretical model, the nonlinear least square method is used to fit the coating thickness of the sample points and the parameter values of the theoretical model are calculated. By analyzing the variation law of the parameters with the spray dip-angle, the prediction model of coating growth rate for varied dip-angle spraying is established. Experiments have shown that the prediction model has good fitting precision; it can satisfy the real-time requirement with varied dip-angle spraying trajectory planning in the offline programming system.