Cutting force regression modeling approach for turning Hastelloy X alloy by genetic algorithms

Chao Yu; Jianye Guo; Yanli Zhang; Jingkui Li

doi:10.1117/12.920454

13 January 2012 Cutting force regression modeling approach for turning Hastelloy X alloy by genetic algorithms

Chao Yu, Jianye Guo, Yanli Zhang, Jingkui Li

Proceedings Volume 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis; 83492V (2012) https://doi.org/10.1117/12.920454
Event: Fourth International Conference on Machine Vision (ICMV 11), 2011, Singapore, Singapore

Abstract

According to tradition empirical formula form, the cutting force regression model for turning Hastelloy X alloy is assigned for the exponential form. Turning experiments were carried out based on the experimental plan designed on the principle of the quadratic rotary combination design technique. By identifying regression coefficient using genetic algorithm toolbox in MALAB7.1, cutting force regression models were established. The rule that the prediction models reveal is identical with both visual analyses result of experiment data and tradition basic cutting theory, in addition the residual error is smaller, so the regression models are fitted very well.

Citation Download Citation

Chao Yu, Jianye Guo, Yanli Zhang, and Jingkui Li "Cutting force regression modeling approach for turning Hastelloy X alloy by genetic algorithms", Proc. SPIE 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, 83492V (13 January 2012); https://doi.org/10.1117/12.920454

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