基于BP神经网络的喇叭嘴机构动平衡优化方法

An Optimization Method of Dynamic Balance for the Ledger Based on BP Neural Network

目的为了提高烟支端面的切割质量,对喇叭嘴机构的动平衡性能进行优化。方法以两平衡块的设计角度为设计变量,惯性力和惯性力矩的均方根植为优化目标,建立喇叭嘴机构的动平衡优化函数。基于BP神经网络建立喇叭嘴机构动平衡预测模型,利用遗传算法优化该神经网络,以提高其预测精度,且获得最优值。结果优化后的机构动平衡性能得到明显改善,其中惯性力均方根值减小了37.16%,惯性力矩均方根值减小了8.33%。结论采用神经网络与遗传算法对喇叭嘴机构进行动平衡优化效果较好,提高了机构的工作稳定性。

The work aims to improve the cutting quality of the cigarette end face, so as to optimize the dynamic balance of the ledger. The dynamic balance function of the ledger was established, with the design angles of two counterweights as the design variables, and the root mean squares（RMS） of the inertia force and torque as the optimal targets. The prediction model for dynamic balance of the ledger was established based on BP neural network, and then a genetic algorithm（GA） was used to optimize such neural network, in order to improve its prediction accuracy and obtain the optimal value. The results showed that the dynamic balance had significantly been improved after the optimization, in which the RMS of the inertia force was decreased by 37.16% and the RMS of the inertia torque was decreased by 8.33%. With the neural network and GA, the dynamic balance of the ledger is optimized in a better way, and the stability of the ledger is improved.