基于改进NSGA-Ⅱ的太阳能管屏喷涂工艺优化研究OA

With the application of robotic spraying systems in the coating field,improving both the coating thickness uniformity and spraying efficiency on curved surfaces has become a critical issue.For large-area solar tube panels with high curvature,a multi-objective spraying process optimization approach based on an improved NSGA-Ⅱ algorithm was proposed.A coating thickness growth model for the solar tube panel was established by considering key process parameters,including spraying height,paint flow rate,spray gun movement speed,spray fan pressure,atomization pressure,and spray gun spacing.A multi-objective mathematical model was formulated with the objectives of minimizing the mean square deviation of uniformity and maximizing spraying efficiency.To enhance the search capability and accelerate convergence,NSGA-Ⅱ was improved by introducing a front-rear crowding-distance evaluation mechanism,an external elite archive strategy,and dynamic adjustment of crossover and mutation operators.Multi-objective optimization of coating thickness uniformity and spraying efficiency was achieved,and optimized spraying process parameters were obtained.Simulation results demonstrated that the improved algorithm significantly increased the convergence rate.The convergence rates of uniformity and efficiency were improved by 75.00%and 11.39%,respectively.Under the optimal solution,the uniformity variance is 24.814 μm2 and the spraying efficiency is 1.409×10-3 m3/s.Spraying experiments were conducted to verify the feasibility and effectiveness of the optimized parameters.The experimental results show that qualified coatings with thicknesses of 58～76 μm can be obtained,with a uniformity error within 5.99%and an efficiency error of 5.11%.