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Predictive Model Of Superplastic Properties Of Aluminum Bronze And Of The Superplastic Extrusion Test

机译:铝青铜超塑性的预测模型及超塑性挤压试验

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摘要

The superplastic properties of aluminum bronze were studied by way of artificial neural network. The model was established using Levenberg-Marquardt algorithm. It was improved by studying superplastic tension test data of aluminum bronze such that the superplastic forming parameters were optimized. According to the parameters, the experiment of superplastic extrusion of a solid bearing 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 test values and the predicted values of the network is less than 8.5%, which meets perfectly the demands of superplastic deformation of aluminum bronze. Moreover, the superplastic forming of solid cage of aluminum bronze show that it is feasible to produce solid cage using superplastic extrusion process. This extrusion process has remarkable economic benefits as well.
机译:通过人工神经网络研究了铝青铜的超塑性。使用Levenberg-Marquardt算法建立模型。通过研究铝青铜的超塑性拉伸试验数据对它进行了改进,从而优化了超塑性成形参数。根据参数,进行了固体轴承的超塑性挤压实验。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。测试值与网络预测值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,铝青铜实心保持架的超塑性成形表明,采用超塑挤压工艺生产实心保持架是可行的。该挤出方法也具有显着的经济效益。

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