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管道清灰机器人变径机构尺度影响机构的运动性能及驱动性能,变径机构尺度优化可有效解决尺寸综合问题。提出了变径机构多目标尺度综合,以变径机构关键零件受力和驱动件运动范围为优化目标建立优化模型,基于快速含有精英策略的非支配排序遗传算法(Non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)求解多目标优化Pareto最优解。计算结果表明:多目标优化后的变径机构在力学性能和运动范围上优于经验设计,不需重复计算可根据设计要求和工程经验权衡选取满足不同要求的优化结果。
The scale of the pipe cleaning robotic reduction mechanism affects the movement performance and driving performance of the mechanism, and the dimension optimization of the reduction mechanism can effectively solve the dimension synthesis problem. The multi-objective scale synthesis of the variable-diameter mechanism was proposed. The optimized model was established based on the optimization of the stress of the key components and the range of motion of the driver. Based on the non-dominated sorting genetic algorithm Ⅱ, NSGA-Ⅱ) to solve the multi-objective optimization Pareto optimal solution. The calculation results show that the multi-objective optimization mechanism is superior to the experience design in the mechanical performance and the range of motion, and the optimization result satisfying different requirements can be selected according to the design requirements and the engineering experience without the double calculation.