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The Predicting Model of Superplastic Property of Aluminum Bronze and the Superplastic Extrusion Test

机译:铝青铜超塑性预测模型及超塑性挤压试验

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The superplastic properties of aluminum bronze were studied by way of artificial neural network (ANN). The predicting model was established using Levenberg-Marquardt algorithm. And it was perfected by studying the stylebook of superplastic tension such that the superplastic forming parameters were optimized. According to the parameters, the experiment of superplastic deformation of the bearing cage was performed. It is shown that the model reflected well the relationship between superplastic properties of aluminum bronze and superplastic tension conditions. The relative error between the expected values and the predicted outputs of the network is less than 8.5 %, which meets perfectly the demands of superplastic deformation of aluminum bronze. Moreover, the superplastic experiments of the bearing cage of aluminum bronze show that it is feasible to produce the bearing cage using superplastic extrusion process. This extrusion process has remarkable economic benefits as well.
机译:通过人工神经网络(ANN)研究了铝青铜的超塑性。使用Levenberg-Marquardt算法建立了预测模型。并通过研究超塑性张力的样式书进行了完善,从而优化了超塑性成形参数。根据参数,进行了轴承保持架超塑性变形的实验。结果表明,该模型很好地反映了铝青铜超塑性与超塑性拉伸条件之间的关系。网络的期望值和预测输出之间的相对误差小于8.5%,完全满足铝青铜超塑性变形的要求。此外,铝青铜轴承保持架的超塑性试验表明,采用超塑性挤压工艺生产轴承保持架是可行的。该挤出方法也具有显着的经济效益。

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