Multi-scale Shell Vibration Signal Analysis of Ball Mill in Grinding Process

DOI

10.2991/lemcs-14.2014.43How to use a DOI?

Keywords

multi-scales decomposes algorithm; Empirical mode decomposition; ensemble empirical decomposition; Hilbert vibration decomposition; shell vibration signals

Abstract

Component decomposition and physical interpretation of shell vibration signal of ball mill in grinding process is very difficult. Aim to this problem, several multi-scales decomposition algorithms are used to analyze shell vibration signal in this paper. Empirical mode decomposition, ensemble empirical mode decomposition and Hilbert vibration decomposition algorithms decompose shell vibration signal to a series of multi-scale sub-signals. Correlation coefficients between these sub-signals and original vibration signal were calculated. Power density spectrums of different multi-scale sub-signals used also to analyze and explain the shell vibration signal. Results show that different decomposition algorithms have different advantages and shortcomings. The further research direction is that how to fuse these sub-signals and model load parameters inside the ball mill.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Jian Tang
AU  - Zhuo Liu
PY  - 2014/05
DA  - 2014/05
TI  - Multi-scale Shell Vibration Signal Analysis of Ball Mill in Grinding Process
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 185
EP  - 189
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.43
DO  - 10.2991/lemcs-14.2014.43
ID  - Tang2014/05
ER  -