RT Journal Article
SR Electronic
A1 Guo, Shuailiang
A1 Zheng, Han
A1 Liu, Xiangzeng
A1 Gu, Lizhi
T1 Comparison on Milling Force Model Prediction of New Cold Saw Blade Milling Cutter Based on Deep Neural Network and Regression Analysis
JF Manufacturing Technology Journal
YR 2021
VO 21
IS 4
SP 456
OP 463
DO 10.21062/mft.2021.053
UL https://journalmt.com/artkey/mft-202104-0003.php
AB A four factors and three levels orthogonal milling force (MF) test is designed, which qualitatively obtains the influence of four factors, namely workpiece material, workpiece diameter, milling speed and feed per tooth, on MF of the new cold saw blade milling cutter (NCSBMC), then further verifies the reliability of test data with simulation analysis of MF. The multiple linear regression analysis and deep neural network (DNN) are used to accurately fit and predict the magnitude of MF in three directions of NCSBMC, taking into account the influence of workpiece material factors on MF. Compared with the results of empirical formula, DNN has higher prediction accuracy. The research results provide theoretical guidance for the optimization of milling parameters in actual machining process.