TY - JOUR
T1 - Industry-oriented method for dynamic force identification in peripheral milling based on FSC-LSQR using acceleration signals
AU - Hou, Maxiao
AU - Cao, Hongrui
AU - Li, Qi
AU - Shi, Jianghai
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
PY - 2022/8
Y1 - 2022/8
N2 - Online measurement of milling force is very important for machining process monitoring and control. In practice, it is difficult to measure the milling force directly during the milling process. This paper develops a method for milling force identification called least square QR-factorization with the fast stopping criterion (FSC-LSQR) method, and the queue buffer structure (QBS) is employed for the online identification of milling force using acceleration signals. The convolution integral of milling force and acceleration signals is discretized, which turns the problem of milling force identification into a linear discrete ill-posed problem. The FSC-LSQR algorithm is adopted for milling force identification because of its high efficiency and accuracy, which can effectively handle the linear discrete ill-posed problem. The online identification of milling force can be realized using the acceleration signal enqueue and the milling force dequeue operations of the QBS. Finally, the effectiveness of the method is verified by milling tests under different milling parameters.
AB - Online measurement of milling force is very important for machining process monitoring and control. In practice, it is difficult to measure the milling force directly during the milling process. This paper develops a method for milling force identification called least square QR-factorization with the fast stopping criterion (FSC-LSQR) method, and the queue buffer structure (QBS) is employed for the online identification of milling force using acceleration signals. The convolution integral of milling force and acceleration signals is discretized, which turns the problem of milling force identification into a linear discrete ill-posed problem. The FSC-LSQR algorithm is adopted for milling force identification because of its high efficiency and accuracy, which can effectively handle the linear discrete ill-posed problem. The online identification of milling force can be realized using the acceleration signal enqueue and the milling force dequeue operations of the QBS. Finally, the effectiveness of the method is verified by milling tests under different milling parameters.
KW - Dynamic force identification
KW - Peripheral milling
KW - Queue buffer structure
UR - https://www.scopus.com/pages/publications/85135564905
U2 - 10.1007/s00170-022-09697-w
DO - 10.1007/s00170-022-09697-w
M3 - 文章
AN - SCOPUS:85135564905
SN - 0268-3768
VL - 121
SP - 7793
EP - 7809
JO - International Journal of Advanced Manufacturing Technology
JF - International Journal of Advanced Manufacturing Technology
IS - 11-12
ER -