Experimental Study on Entropy Features in Machining Vibrations of A Thin-walled Tubular Workpiece

Kaibo Lu; Xin  Wang; Xun Chen; Xinyu  Pang; Fengshou  Gu

doi:10.37965/jdmd.2023.155

Authors

Kaibo Lu College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Shanxi 030024, China https://orcid.org/0000-0002-0614-2339
Xin Wang College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Shanxi 030024, China https://orcid.org/0009-0008-7038-5272
Xun Chen General Engineering Research Institute, Liverpool John Moores University, Liverpool, L3 5UX, UK https://orcid.org/0000-0003-2547-9022
Xinyu Pang College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Shanxi 030024, China https://orcid.org/0000-0001-7302-2479
Fengshou Gu School of Computing and Engineering, University of Huddersfield, Huddersfield, HD1 3DH, UK https://orcid.org/0000-0003-4907-525X

DOI:

https://doi.org/10.37965/jdmd.2023.155

Abstract

In machining processes, chatter vibrations are always regarded as one of the major limitations for production quality and efficiency. Accurate and timely monitoring of chatter is helpful to maintain stable machining operations. At present, most chatter monitoring methods are based on the energy level at specified chatter frequencies or frequency bands. However, the spectral features of chatter could change during machining operations due to complexity and time-varying dynamics of the physical machining process. The purpose of this paper is to investigate the time-varying chatter features in turning of thin-walled tubular workpieces from the perspective of entropy. The airborne acoustics was selected as the source of information for machining condition monitoring. First, corresponding to the distinguishing surface topographies relevant to machining conditions, the features of the sound signal emitted during turning of the thin-walled cylindrical workpieces were extracted using the spectral analysis and wavelet packet transform, respectively. It was shown that the dominant vibration frequency as well as the energy distribution could shift with the transition of the machining status. After that, two relative entropy indicators based on the spectrum and the wavelet packet energy were constructed to identify chattering events in turning of the thin-walled tubes. The experimental results demonstrate that the proposed indicators could accurately reflect the transition of machining conditions with high sensitivity and robustness in comparison with the traditional FFT-based methods. The achievement of this study lays the foundations of the online chatter monitoring and control technique for turning of the thin-walled tubular workpieces.

Conflict of Interest Statement

The authors declare no conflicts of interest.