基于多目标遗传算法的爬壁小车底板优化

Optimization of Wall-climbing Car Floor Based on Multi-objective Genetic Algorithm

为保证大型立式储油罐处于安全运行状态,需使用爬壁小车对其进行定期检查,而小车底板的自重将影响小车的吸附力及爬行高度。为实现小车底板轻量化设计,应用Solidworks建立了小车底板的多目标优化数学模型,基于多目标遗传算法对模型进行计算,求解出最优设计点,实现了爬壁小车模型的轻量化设计。

To ensure the safe operation of large vertical storage tanks,regular volume inspections are required and accomplished by a wall-climbing trolley with load capacity,but trolly's bottom plate weight affectes adsorption forcec and crawling height.To achieve the lightweight design of the wall-climbing trolley floor,a multi-objective optimization mathematical model for the trolley floor was established by Solidworks and caculated based on multi-objective genetic algorithm to solve the optimal design point and realize the model lightweight.