Blind source separation based on JADE algorithm and application

DOI

10.2991/icmra-15.2015.50How to use a DOI?

Keywords

blind source separation; sound detection; joint approximate diagonalization

Abstract

Fault monitoring or detection online is very important for the safe operation of power equipment. The traditional contact-type detection system based on vibration feature exist some troubles under the high voltage and strong electromagnetic field conditions. In this paper, a non-contact sound detection method is proposed, which is based on audio features blind source separation (BSS). The joint approximate diagonalization of eigenmatrices JADE algorithm is applied in the detection method, which makes use of the forth order statics to automatically suppress Guassian background noises and enhance the non-Gaussian source signals. Compared with the fast independent component analysis (Fast ICA) algorithm, a clearer source signal can be estimated and separated. The simulation experiment results show that by the JADE algorithm, the similar coefficients between the separated signals and the original source signals are all above 0.9, far greater than that by Fast ICA algorithm. So it concludes that the sound BSS method can effectively separate source vibration sound of power equipment and JADE is more efficient than Fast ICA in the fault diagnosis for power equipment

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  - Kangrong Zhang
AU  - Guanyu Tian
AU  - Tian Lan
PY  - 2015/04
DA  - 2015/04
TI  - Blind source separation based on JADE algorithm and application
BT  - Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation
PB  - Atlantis Press
SP  - 252
EP  - 255
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmra-15.2015.50
DO  - 10.2991/icmra-15.2015.50
ID  - Zhang2015/04
ER  -