Title :
Predicting residual stress characteristics based on BP artificial neural network in precision hard turning
Author :
Tao Chen ; Mingjun Zhang ; Xianli Liu ; Yuhui Shen
Author_Institution :
Sch. of Mech. & Electr. Eng., Harbin Eng. Univ., Harbin, China
Abstract :
The prediction models of residual stress on surface are built using BP artificial neural network in precision hard turning, which defines tool parameters and cutting parameters as input values, and the values of residual stress characteristics as output, and the models are verified by experiment. Finally, MATLAB is used to develop prediction system of the residual stress in precision hard turning with PCBN tools. The system has realized higher-accuracy prediction of surface integrity in precision hard turning.
Keywords :
backpropagation; cutting tools; internal stresses; neural nets; prediction theory; production engineering computing; turning (machining); BP artificial neural network; PCBN tools; cutting parameters; precision hard turning; residual stress characteristics; surface integrity; Ceramics; Educational institutions; Predictive models; Residual stresses; Training; Turning; BP artificial neural network; precision hard turning; prediction; residual stress;
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang, China
Print_ISBN :
978-1-61284-087-1
DOI :
10.1109/EMEIT.2011.6023364
