论文部分内容阅读
针对船舶外板喷涂机器人多层喷涂轨迹优化问题,以提高喷涂质量和效率为目标,提出一种平面多层喷涂轨迹优化方法。根据平面单层膜厚分布,推导建立平面多层漆膜分布模型,并采用快速非支配排序遗传算法(Non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)优化各层喷涂轨迹。通过对船舶外板进行多层仿真喷涂,与未优化的喷涂轨迹比较,提高了漆膜均匀性和喷涂效率,验证了轨迹优化方法的合理性;与传统遗传算法优化对比,结果验证了NSGA-Ⅱ算法的有效性。
In order to solve the problem of multi-layer spray trajectory optimization for the spray coating robot of ship outer shell, aiming at improving the quality and efficiency of spray coating, a planar multi-layer spray trajectory optimization method is proposed. According to the distribution of single-layer film thickness, the model of multi-layer film distribution was derived. The non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) was used to optimize the spray pattern of each layer. Compared with the unoptimized spray trajectory, the paint film uniformity and spraying efficiency are improved by multi-layer simulation spraying on the outer shell of the ship, and the rationality of the trajectory optimization method is verified. Compared with the traditional genetic algorithm, the results verify that NSGA- Ⅱ algorithm is effective.