A Mechanical Fault Feature Extraction Method Based on Volterra Series Model for EEMD Decomposition
- https://doi.org/10.2991/icmii-15.2015.36How to use a DOI?
- analytical model EEMD Volterra series model rotating machinery fault
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/icmii-15.2015.36 ID - Long2015/10 ER -