面向机器人喷涂的多变量涂层厚度分布模型
Multivariable coating thickness distribution model for robotic spray painting

为了解决传统机器人喷涂模型在喷涂工艺参数改变时会失效的问题，该文将喷涂工艺参数作为模型变量，研究多变量喷涂模型的建模方法。首先，提出了一种基于β分布的涂层生长速率函数，并通过对其进行积分推导出涂层厚度分布方程；其次，通过分析、拟合喷涂实验数据，分别建立喷枪流量、喷涂距离与涂层生长率最大值的关系式，以及喷枪流量、空气压力与喷幅宽度的关系式，并将其代入到涂层厚度分布方程中，建立了以5种常变喷涂工艺参数为自变量的涂层厚度分布泛化模型；最后，通过实验对模型进行验证。结果表明：该模型能够根据工艺参数的变化预测相应的涂层厚度分布，且平均预测误差小于4.3%。
Abstract：A multivariable robotic spray painting model was developed for a range of painting parameters to improve the restricted traditional model. A β distribution based coating growth rate function was used with a coating thickness distribution formula then deduced from the integral of the growth rate function. The maximum coating growth rate was related to the paint flow rate and painting distance with the paint flow rate related to the painting air pressure and painting width from experimental data. Then, a generalized coating thickness distribution model was developed with five painting parameters as independent variables by substituting these relations into the coating thickness distribution equations. The model was validated through experiments with the results showing that it can predict the coating thickness distribution for various painting parameters with an average forecasting error of less than 4.3%.