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Simulated Annealing Optimization of Belt Conveyor Transmission

机译:带式输送机的模拟退火优化

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摘要

The belt conveyor is a transporting machine by friction in a continuous manner.The two order helical gearing reducer may be generally used as conveyor transmission,and can reduce speed and increase torque of belt.The objective function may be specified that that total center distance of the reducer incline to minimum,so the optimization model including the property and boundary constraints is created.Then the objective function with penalty terms is converted by penalty strategy with addition type,so as to transform the constrained optimization into the unconstrained optimization model.Considering the problem of low efficiency and local optimum caused by standard optimization methods,the simulated annealing algorithm is adopted to solve the optimization model of Belt Conveyor Transmission,and neural network method is applied to fit relative coefficient,then BFGS Quasi-Newton method is recalled automatically when the setting working precision is achieved again.So that the optimization process is simplified and global optimum is acquired reliably.
机译:带式输送机是一种连续摩擦的输送机。通常采用二阶斜齿轮减速机作为输送机的传动装置,可以降低速度,增加带的扭矩。将减速器倾斜到最小,从而创建包括属性和边界约束的优化模型。然后,将带有惩罚项的目标函数通过加法类型的惩罚策略进行转换,从而将约束优化转化为无约束优化模型。标准优化方法导致效率低下和局部最优的问题,采用模拟退火算法求解带式输送机的优化模型,并采用神经网络方法拟合相对系数,然后自动调用BFGS拟牛顿法。再次达到设定工作精度。因此优化p流程得到简化,并且可靠地获得了全局最优。

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