Multi-objective Moderate Optimization in Cycloid Drive

In order to improve cycloid drive design quality and speed in the complex constrained condition, we could derive to meet the constraints of the Pareto solution set by example and the particle swarm optimization algorithm for constrained multi-objective optimization. As there is objective error in engineering, on the basis of seven factors, nine levels of uniform design and the look mesh characteristics of SNR calculation, We take the most robust design as the final stage from the Pareto which the multi-objective robust design principle is in. By the analysis of the results of the program in the objective function (volume function and the modification error function) to the sensitivity of the various design variables, it concluded that the most sensitive factors of the objective function and their impact on the objective function which can be used to guide the development of tolerance and the actual processing.