Title :
Surface roughness regression modeling approach for turning Hastelloy X alloy by genetic algorithms
Author :
Yu, Chao ; Guo, Jianye ; Zhang, Yanli ; Li, Jingkui
Author_Institution :
Sch. of Mech. & Electr. Eng., Shenyang Aerosp. Univ., Shenyang, China
Abstract :
Turning Hastelloy X alloy experiments was carried out according to the experimental plan designed based on the quadratic rotary combination design technique. The regression model of average surface roughness (Ra) is assigned for the exponential form. By identifying regression coefficient using genetic algorithm toolbox in MALAB7.1, a regression model of Ra was obtained. The residual error of regression model is smaller, and the rule that the regression model reveals is identical with both visual analyses result of experiment data and experimental phenomena, so the regression model is fitted very well.
Keywords :
genetic algorithms; iron alloys; molybdenum alloys; nickel alloys; regression analysis; surface roughness; FeJkJk; Hastelloy; MALAB7.1; NiCrCoMoWCuJk; average surface roughness; genetic algorithm; hastelloy X alloy; quadratic rotary combination design technique; regression model; residual error; Atmospheric modeling; Copper; Educational institutions; Nickel; Numerical models; Rough surfaces; Surface roughness; Hastelloy X alloy; genetic algorithm; regression model; surface roughness;
Conference_Titel :
Information Networking and Automation (ICINA), 2010 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-8104-0
Electronic_ISBN :
978-1-4244-8106-4
DOI :
10.1109/ICINA.2010.5636525