关键词: 水辅助注塑, LMBP 神经网络, 遗传算法, 逆向过程, 建模

Abstract:

Water-assisted injection molding (W AIM) is a new injection molding technique whose mathematical model is difficult to establish by mathematical method due to the process complexity. In this work , an inverse neural network named GA-LMBP is proposed by combining the genetic algorithm (GA) with the Levenberg-Marquardt back-propagation (LMBP) neural network. Based on the proposed GA-LMBP , a model to predict the W AIM process is developed according to a series of experimental results. It is found from the cross-validation that there is a good agreement between the predicted results by the model and the experimental ones , and that , with the thickness at different locations of molded parts as the system input , the model can quickly and accurately predict such processing parameters as short-shot size , water pressure , water injection delay time , and melt temperature.

Key words: water-assisted injection molding, Levenberg-Marquardt back-propagation neural network, genetic algorithm, inverse process, modeling