Forecasting model for the machining accuracy of aspheric surface

Dongju Chen; Yong Zhang; Feihu Zhang

doi:10.1117/12.782847

14 November 2007 Forecasting model for the machining accuracy of aspheric surface

Dongju Chen, Yong Zhang, Feihu Zhang

Proceedings Volume 6722, 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies; 67220J (2007) https://doi.org/10.1117/12.782847
Event: 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes, 2007, Chengdu, China

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.

Citation Download Citation

Dongju Chen, Yong Zhang, and Feihu Zhang "Forecasting model for the machining accuracy of aspheric surface", Proc. SPIE 6722, 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, 67220J (14 November 2007); https://doi.org/10.1117/12.782847

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