Multi-objective optimization of RV reducer parameters based on improved NSGA-Ⅱ algorithm
Rotary vector(RV)reducer is the core component of industrial robots,which plays a key role in the performance of robots.In order to improve the comprehensive performance of RV reducer,the multi-objective optimization design of its structural parameters(such as the number of cycloidal gear teeth,short amplitude coefficient,pin diameter coefficient,cycloidal gear width,etc.)was studied starting from optimizing the relevant parameters of transmission pressure angle.Firstly,the relationship between the average pressure angle of the cycloidal gear,transmission efficiency,and the volume of the transmission mechanism were studied.Then,a multi-objective optimization mathematical model was established based on the standard tooth profile equation of the cycloidal gear as the optimization objective.The model adopts an algorithm based on non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ),which improves the generation of cross operator coefficients namely improved NSGA-Ⅱ.Then the Pareto optimal solution set was obtained by solving the model,and the optimal solution was selected according to the relevant methods of fuzzy set theory.Finally,taking a company's 220-BX RV reducer as an example to optimize the design,the 3D model was established for finite element analysis and the experimental prototype was fabricated for transmission efficiency comparison experiment.The experiment results show that the average pressure angle of the cycloid wheel decreases by 7.19%,the volume decreases by 11.1%,and the transmission efficiency increases by4.9%.The research results show that this model has strong interactivity,can improve design efficiency,save design costs,and provide reference for practical engineering optimization design of RV reducer.
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