基于神经网络和遗传算法的注射成型工艺优化

论述人工神经网络和遗传算法在塑料注射成型工艺优化中的应用,首先利用人工神经网络建立注射成型工艺参数与塑件翘曲量之间关系的数学模型,然后用遗传算法对工艺参数优化.其中由正交法设计得到实验样本,由数值模拟软件计算得到塑件翘曲量,将其作为优化目标.按优化后的工艺参数进行实验,获得较高质量的塑料制品,从而为建立和控制注射模工艺参数提供一种行之有效的途径.

Processing Optimization of Plastic Injection Based on Neural Network and Genetic Algorithm

The application of artificial neural network and genetic algorithm for processing optimization of plastic injection was discussed. First of all,the mathematics model between the process parameters for injection and the warpage amount of the part was set up with neural network. Then, the process parameters were optimized with genetic algorithm. Design experiment samples were gotten by orthogonal plan method and got the warpage amount of the part which came from the numerical simulating as goal of optimizing. Through doing tests in the light of optimizing parameters, the superior quality part was obtained,so it was a kind of effectual means for setting up and controlling parameters of injection.