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针对高速走丝电火花线切割加工中的电参数选择问题,将加工电参数和工艺指标参数分别作为神经网络的输入和输出,利用神经网络建立电火花线切割工艺模型,使用遗传算法对神经网络模型的权值和阈值进行优化,以加快网络的训练速度和避免网络陷入局部最小值。结合训练好的工艺模型,利用遗传算法以神经网络的误差传递函数作为适应度函数,对电火花线切割加工参数进行多目标优化,以达到对加工参数的优化选取。
Aiming at the selection of electrical parameters in high-speed WEDM, the parameters of electrical and process parameters are taken as the input and output of neural network respectively. The WEDM process model is established by using neural network, and the neural network The weights and thresholds of the model are optimized to speed up the training of the network and prevent the network from falling into a local minimum. Combined with the trained process model, genetic algorithm is used to optimize the parameters of WEDM by using the error transfer function of neural network as the fitness function.