Upgraded Regularized Deconvolution of complex dynamometer dynamics for an improved correction of cutting forces in milling. (1st March 2022)

• Record Type: Journal Article
• Authors: Totis, G.; Sortino, M.
• Is Part Of: Mechanical systems and signal processing. Volume 166(2022)
• Publication Date: 2022-03-01
• Subjects: Milling -- Cutting forces -- Dynamometer -- dynamics -- Compensation -- Regularized Deconvolution; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2021.108412
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: In order to characterize cutting mechanics during high-speed milling and micromilling applications, high-end piezoelectric dynamometers with a wide frequency bandwidth are necessary. Nevertheless, when installed into the machine tool their signal bandwidth is limited by the dynamic behaviour of the machining system. Thus, special filters have to be adopted for dynamics compensation. State of the art filters are based on a simplistic 3 × 3 dynamic model of device transmissibility without taking into account the influence of input force location with respect to the centre of the sensing platform. The Upgraded Augmented Kalman Filter has been recently proposed for solving this problem. Although it outperformed the other state of the art filters, it was based on the preliminary identification of a parametric mathematical model that is generally a difficult and non-automatic task. Here a novel non-parametric filter is introduced, that was based on a more general and abstract model of dynamometer dynamics considering both input force direction and location. By so doing, impressive results were found both from modal analysis and from real cutting tests, showing the potential of the new method for an effective and almost completely automatic cutting force dynamic compensation. Highlights: Upgraded deconvolution is conceived for effective cutting force filtering in milling. The method is completely non-parametric: no complex identification is required. The influence of both force direction and location are incorporated in the filter. Successful experimental validation through modal analysis and cutting tests. The method outperformed state of the art filters used in this field.