@article{1,
  keywords = {Monitoring, Identification, Machining},
  author = {Benedikt Schmucker and Chia-Pei Wang and Michael Zaeh and Kaan Erkorkmaz},
  title = {Wide-bandwidth cutting force monitoring via motor current and accelerometer signals},
  abstract = {<p>Cutting forces are valuable for monitoring machining processes, as they allow the evaluation of tool wear, process stability, and workpiece quality. This paper presents a new non-intrusive method for monitoring cutting forces using a&nbsp;Kalman filter&nbsp;(KF) and Rauch-Tung-Striebel (RTS) smoothing. The method incorporates structural&nbsp;acceleration measurements&nbsp;as well as feed drive motor currents, thereby achieving wide estimation bandwidth and steady-state (DC) gain preservation. The KF&nbsp;+&nbsp;RTS smoothing are parameterized using spindle speed-sweeping cutting tests, which significantly reduces the experimental effort for model identification. The approach was validated in different machining conditions, which demonstrated good agreement with&nbsp;dynamometer&nbsp;measurements.</p>
},
  year = {2023},
  journal = {CIRP Annals},
  volume = {72},
  pages = {309-312},
  issn = {0007-8506},
  url = {https://www.sciencedirect.com/science/article/pii/S000785062300046X},
  doi = {10.1016/j.cirp.2023.04.012.},
}