346 / 2021-07-05 09:43:33
Modelling the Dynamics of a CNC Spindle for Tool Condition Identification based on On-Rotor Sensing
Vibration; Tool wear condition; Finite element model; On-Rotor Sensing; Dynamic characteristics of spindle
Draft Accepted
Chun Li / Beijing Institute of Technology Zhuhai
Dawei Shi / Shandong University of Science and Technology
Bing Li / Beijing Institute of Technology Zhuhai
Hongjun Wang / Beijing Information Science and Technology University
Guojin Feng / University of Huddersfield
Fengshou Gu / University of Huddersfield
Andrew D Ball / University of Huddersfield
Cutting tool plays an important role in modern manufacturing industry but tool wear is unavoidable and may degrade productivity. Aiming at studying an appropriate and efficient tool condition monitoring method to improve the accuracy of finished parts, the roughness of the turned surface, a novel On-Rotor Sensing (ORS) is installed on the rotating workpiece to obtain vibration signals. To get an in-depth understand of the vibration data, a multi-degree-of-freedom (MDOF) system consisted of spindle, chuck and workpiece is established. It is found that the dynamic response of the spindle end determines machining accuracy in the turning process. Such, the multi-mode natural frequency of the system is obtained by finite element modeling (FEM) and verified by experiments. It shows that the first several modes in the frequency range within 2000Hz are the main responses of the system, which can be effectively captured by the ORS. Especially, the modal responses are examined when the mass of workpieces decrease during the turning process and the spring stiffness is determined by FEM results. Based on the analysis, two frequency bands are advocated for ORS based online monitoring of tool wear conditions.

 
Important Date
  • Conference Date

    Nov 01

    2022

    to

    Nov 03

    2022

  • Oct 30 2022

    Draft paper submission deadline

  • Nov 09 2022

    Registration deadline

Sponsored By
Qingdao University of Technology