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- W4289731201 abstract "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." @default.
- W4289731201 created "2022-08-04" @default.
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- W4289731201 date "2022-08-01" @default.
- W4289731201 modified "2023-10-03" @default.
- W4289731201 title "Industry-oriented method for dynamic force identification in peripheral milling based on FSC-LSQR using acceleration signals" @default.
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- W4289731201 doi "https://doi.org/10.1007/s00170-022-09697-w" @default.
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