Analysis Method of Multi-scale Frequency Spectral Latent Feature based on the Mutual Information

DOI

10.2991/icmmita-15.2015.91How to use a DOI?

Keywords

Multi-scale Frequency Spectra; Latent Features extraction; Mutual Information

Abstract

Heavy rotating mechanical devices, such as ball mills in the mineral grinding process, produce strong mechanical vibration and acoustic signals. These signals consist of multiple components with different time scales and physical interpretations. Frequency spectra of these multi-scale sub-signals contain interesting information related to some difficulty-to-measure process parameters. Latent feature extraction methods based on principal component analysis and partial least squares with their kernel versions are used widely for high dimensional spectra data. How to estimate their effect and select important sub-signals are important issues. Thus, aim to these problems, mutual information is used in this paper. Analysis results based on the shell vibration frequency spectra of a laboratory-scale wet ball mill shows that the proposed method is helpful and effective.

Copyright

© 2015, 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/).

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TY  - CONF
AU  - Zhuo Liu
AU  - Jian Tang
AU  - Meiying Jia
AU  - Xiaojie Zhou
PY  - 2015/11
DA  - 2015/11
TI  - Analysis Method of Multi-scale Frequency Spectral Latent Feature based on the Mutual Information
BT  - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 462
EP  - 467
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-15.2015.91
DO  - 10.2991/icmmita-15.2015.91
ID  - Liu2015/11
ER  -