A Mechanical Fault Feature Extraction Method Based on Volterra Series Model for EEMD Decomposition

DOI

10.2991/icmii-15.2015.36How to use a DOI?

Keywords

analytical model EEMD Volterra series model rotating machinery fault

Abstract

This paper, based on the existed EMD decomposition to extract the fault feature signal, will apply the analytical model named Volterra series model of chaotic time series to the fault diagnosis of rotating machinery. The method of combining EEMD decomposition and Volterra series model is proposed to extract the feature information of mechanical fault. Compared with the traditional fault feature extraction methods, this method has the advantages of adequate theoretical basis, novel method, obvious extraction features , better anti-noise interference ability simple computation and so on. Simulation experiments show that the proposed method can effectively extract the feature parameters. By applying the method to the fault feature extraction of rotating machinery,the results are obtained satisfactorily.

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  - Kai Long
AU  - Guochu Chen
AU  - Haiqun Wang
PY  - 2015/10
DA  - 2015/10
TI  - A Mechanical Fault Feature Extraction Method Based on Volterra Series Model for EEMD Decomposition
BT  - Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics
PB  - Atlantis Press
SP  - 196
EP  - 201
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmii-15.2015.36
DO  - 10.2991/icmii-15.2015.36
ID  - Long2015/10
ER  -