In the traditional mechanical design, the design of the drive shaft of the tracked robot requires a certain amount of engineering and practical experience, rather than based on scientific analysis and calculation, resulting in conservative design, long design cycle, and poor reusability. A response surface optimization design method was proposed, and the influence of multiple design variables on the performance of the drive shaft was investigated by a central composite experiment. The least square method was used to fit the approximate points, and the response surface model of the design variables and the performance of the drive shaft was established. The optimal size of the shaft diameter of each drive shaft was solved by a multi-objective genetic algorithm, and finally, three groups of optimization schemes were obtained. After optimization, the maximum equivalent stress, the maximum deformation, and the weight of the drive shaft are improved.
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Wang et al. (2024) studied this question.
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