多体节叠加型混联机构正运动学建模与优化设计OA

The multi-segment stacked hybrid mechanism consists of multiple parallel segments connected in series,combining the advantages of serial and parallel configurations.However,such mechanisms feature complex structures and exhibit distinct configurations with different numbers of segments,making it difficult to directly obtain unified kinematic position and velocity solutions valid for any number of segments,thereby hindering their design,analysis and optimization.To solve this problem,the multi-segment stacked hybrid mechanism 3-R1S(RS)N-1R2 is selected as the research object,and its forward kinematics modeling and optimal design are carried out based on the finite and instantaneous screw theory.Firstly,the configuration feature of the hybrid mechanism was described,which achieved multi-segment superimposition through a common motion platform and R joints.Meanwhile,the multi-segment motion superimposition and transmission principle of the mechanism was derived using the finite and instantaneous screw theory.Then,the forward kinematics model of a single segment was deduced.By further extension based on the principle of multi-segment motion superposition and transmission,the unified forward kinematics model and velocity Jacobian matrix valid for any number of segments were obtained,and the correctness of the position and velocity models was verified through simulation.Finally,the optimal number of segments was determined by defining standardized equal-weight performance comparison indicator.The multi-objective optimization was conducted using NSGA-Ⅱ(non-dominated sorting genetic algorithm-II),and the optimal solution was selected from the Pareto frontier by using the entropy-weighted TOPSIS(technique for order preference by similarity to an ideal solution)method.The comparison results before and after optimization indicated that the optimal solution improved significantly in four performance indicators,making the optimized hybrid mechanism more suitable for practical engineering applications.The research results provide new ideas for the analysis and optimization of multi-segment stacked hybrid mechanisms.