基于改进NSGA-Π算法的新型引纬机构的参数优化

Parameter optimization of a new weft insertion mechanism based on improved NSGA-Π

为了得到椭圆齿轮曲柄摇杆新型引纬机构的最佳参数,以剑头加速度变化最小和等腰梯形加速度规律为目标,以满足引纬工艺和机构运动性能要求为约束条件,建立了该机构的优化模型,该模型为高维带约束的非线性多目标优化模型。结合适应性不可行度和精英保留非劣排序遗传算法(NSGA-Π),提出改进优化算法,编写辅助优化程序,得到一组最佳参数,并对该组参数下的引纬机构进行运动分析和比较。结果表明该优化算法能有效地解决多目标非线性约束优化问题。

In order to obtain the optimal parameters of a new elliptic-gear ＆ crank-rocker weft insertion mechanism, optimization mathematical models of the mechanism are established, its objective function is chosen as the minimum fluctuating acceleration of gripper head and ＂isosceles trapezoid shaped＂ acceleration of gripper head in a mation loop, and its constraint equations are the formulas which can meet the requirements of inserting weft and the kinematic behaviors of the mechanism. The models are high-dimensional nonlinear multi- objective models with constraints. Combining adaptive infeasibility degree and elitist non-dominate sorting genetic algorithm（NSGA-Ⅱ）, an improved algorithm is proposed. And an aided-optimization software was compiled. A group of optimal parameters is obtained, and the kinematics performances of the mechanism with the optimal parameters are analyzed and compared with the original. The results show the algorithm is perfectible, which can solve nonlinear multi-objective optimization question with constraints effectively.