基于遗传算法的化纤落卷任务优化

Optimization of Chemical Fiber Doffing Based on Genetic Algorithm

化纤长丝卷绕生产过程中,因生产线卷绕机数量多,落筒机器人在落卷、转运和置放丝饼过程中存在满卷信号累积的情况,导致超出窗口时间而无法完成落卷。因此,优化落筒机器人处理落卷任务的顺序对减少人工干预具有重要意义。采用遗传算法对落筒机器人处理落卷任务的顺序进行优化,建立了以落卷的窗口时间作为优化目标的数学模型。结果表明,在任务量、生头时间间隔和任务位置不同的情况下,采用遗传算法可明显减少人工干预次数。

During the process of chemical fiber filament winding production, there is a full volume signal accumulation of doffing robot in the process of doffing, transporting and placing the silk cake because of the overmuch winding machines on the production line, leading to the timeout of window time and the doffing task cannot be completed. Thus, it is of great significance to optimize the order of doffing task by doffing robot for the reduction of human intervention. The genetic algorithm was used to optimize the doffing order to fulfill the doffing task, and the mathematical model was established to optimize the window time. The result shows that the algorithm can significantly reduce the number of human intervention times under the circumstance of different task volumes, head time interval and task position.