Online identification of milling forces using acceleration signals

Milling force is one of the key output variables related to milling efficiency and accuracy. However, the time-consuming identification of milling forces cannot be evaluated online for machining performance during the milling process. In this paper, a novel millisecond-level method is developed to identify the milling forces online using acceleration signals. Firstly, the milling force identification problem is transformed into an ill-posed problem in the time-domain convolution framework. Next, the advantages of the regularization method for the ill-posed problem are analyzed. Then, the properties of the transfer matrix and the regularization operator are used to reduce the milling force identification time. Lastly, the proposed method is verified with several sets of milling experiments, and the results show that the accuracy of milling force identification is acceptable and the identification time is less than 10 ms.