BP神经网络在预测注塑模型腔温度中的应用  

Application of BP Neural Network on the Temperature Prediction of Injection Mold Cavity

作　　者：成岗[1] 刘虎[1] 夏文胜[1] 

机构地区：[1]盐城工学院,江苏盐城224001

出　　处：《中国铸造装备与技术》2012年第6期52-54,共3页China Foundry Machinery & Technology

摘　　要：注塑成型的过程中,影响其质量的因素很多,模具型腔的温度就是其一重要因素。它不仅影响到注塑件的质量,而且影响到模具加工的生产效率。运用BP神经网络来预测注塑模型腔温度不仅过程简便,还具有很高的精度,绝对误差小于2℃。In the plastic injection forming process, there are many factors altecting its quality. The mold cavity temperature is one of the important factors. It greatly influences both the quality of plastic product and the efficiency of injection molding. Using the empirical formula to calculating cavity temperature, the task is complicated and error is big. While the use of BP neural network to prediction of injection mold cavity temperature can simplify this process. The results showed that the temperature prediction of injection mold cavity with BP neural network was reliable with absolute error less than 2℃.

关 键 词：BP神经网络 注塑模 型腔温度 

分 类 号：TP391.72[自动化与计算机技术—计算机应用技术] TP183[自动化与计算机技术—计算机科学与技术]