Transactions of Materials and Heat Treatment

Title：Diagnosis of defects in ball spinning deformation of thin-walled tubular part based on ANN

Authors： JIANG Shu-yong~(1) XUE Ke-min~(2) LI Chun-feng~(3) ZHANG Jun~(1)(1.Center for Engineering Training Harbin Engineering University Harbin Heilongjiang 150001 China 2.School of Materials Science and Engineering Hefei University of Technology Hefei Anhui 2300

Unit：

KeyWords： ball spinning power spinning artificial neuron networks aluminum alloy

ClassificationCode：TG376

year,vol(issue):pagenumber：2006,31(3):79-83

Abstract：

As a successively and locally plastic deformation process,ball spinning is applied in order to manufacture high-strength and high-precision thin-walled tubular part with longitudinal inner ribs.By using aluminum alloy as spinning material,based on the experiments,not only the basic principle with respect to non-steady flow of metal material in ball spinning,but also the reasons for surface quality defects of the spun parts are analyzed.On the basis of artificial neural networks(ANN),the surface quality defects of the spun parts is predicted.Experiments have proved that ANN can predict and diagnose the surface quality defects of the spun part successfully.

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Reference：

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