Alternative experimental methods for machine tool dynamics identification: A review

Iglesias A., Taner Tunç L., ÖZŞAHİN O., Franco O., Munoa J., Budak E.

Mechanical Systems and Signal Processing, vol.170, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 170
  • Publication Date: 2022
  • Doi Number: 10.1016/j.ymssp.2022.108837
  • Journal Name: Mechanical Systems and Signal Processing
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Keywords: Dynamic characterization, Machine tool dynamics, FRF identification, POSITION-DEPENDENT DYNAMICS, RANDOM CUTTING EXCITATION, FACE MILLING OPERATIONS, CHATTER STABILITY, MODAL-ANALYSIS, DRIVE CONTROL, FORCE MEASUREMENT, DAMPING SYSTEM, PREDICTION, SPINDLE
  • Middle East Technical University Affiliated: Yes

Abstract

© 2022An accurate machine dynamic characterization is essential to properly describe the dynamic response of the machine or predict its cutting stability. However, it has been demonstrated that current conventional dynamic characterization methods are often not reliable enough to be used as valuable input data. For this reason, alternative experimental methods to conventional dynamic characterization methods have been developed to increase the quality of the obtained data. These methods consider additional effects which influence the dynamic behavior of the machine and cannot be captured by standard methods. In this work, a review of the different machine tool dynamic identification methods is done, remarking the advantages and drawbacks of each method.