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熔融性能是指注射螺杆在塑化过程中对物料的熔融能力,可以用熔融曲线来表示。文章利用自行开发的可视化实验装置,测量得到了不同加工工艺条件下的固相分布,以此为基础建立了基于BP神经网络的固体床宽度分布函数的预测,并利用实验结果对所建网络模型的预测能力进行验证,结果表明该网络模型的预测效果好。利用所建立的模型研究分析了螺杆转速、背压、注射行程等工艺条件对固相宽度分布函数的影响。
Melt performance refers to the injection screw in the plasticizing process of melting ability of the material, you can use the melting curve to represent. In this paper, the self-developed visualization experimental device was used to measure the solid phase distribution under different processing conditions. Based on this, the prediction of the width distribution function of solid bed based on BP neural network was established. Based on the experimental results, The results show that the network model has a good forecasting effect. Based on the established model, the effect of process parameters such as screw speed, back pressure and injection stroke on the distribution function of solid phase width was studied.