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Proceedings Paper

Forecasting model for the machining accuracy of aspheric surface
Author(s): Dongju Chen; Yong Zhang; Feihu Zhang
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Paper Abstract

Forecasting the accuracy of a machined surface shape is of a great concern for ultra-precision machining. Quick and accurate selection of the machining parameters and prediction of the measuring accuracy of the machined surface may reduce the time of experiment, shorten the cycle of machining and lower down production costs. This paper studied the parabolic aspheric surface, analyzed the main machining factors that affect the aspheric accuracy and established its back-propagation (BP) Neural Network (NN) model with experimental data taken into account. The model was used to predict the machining accuracy of the aspheric surface which is affected by various factors. Its prediction proves that the method is highly accurate.

Paper Details

Date Published: 14 November 2007
PDF: 7 pages
Proc. SPIE 6722, 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, 67220J (14 November 2007); doi: 10.1117/12.782847
Show Author Affiliations
Dongju Chen, Harbin Institute of Technology (China)
Yong Zhang, Harbin Institute of Technology (China)
Feihu Zhang, Harbin Institute of Technology (China)


Published in SPIE Proceedings Vol. 6722:
3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies

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