Proceedings of the 2016 6th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2016)

Turboprop Engine Fault Diagnosis Based on Hilbert Spectrum and Singular Value Decomposition

Authors
Feng Ding, Zhi Qi
Corresponding Author
Feng Ding
Available Online December 2016.
DOI
https://doi.org/10.2991/mcei-16.2016.265How to use a DOI?
Keywords
Fault diagnosis; Feature extraction; Hilbert spectrum; Singular value decomposition; RBF network
Abstract
In order to solve the time-frequency feature extraction problem of the vibration signal, a fault diagnosis method based on Hilbert spectrum and singular value decomposition is proposed and applied to engine fault diagnosis. Firstly, the vibration signals are decomposed into a series of intrinsic mode functions by using empirical mode decomposition method. Secondly, Hilbert transform is applied to each intrinsic mode function and Hilbert spectrum of the vibration signal is got. Then the singular value method is applied to the Hilbert spectrum and the singular value vector is acquired. Finally, as feature vectors, singular value vectors are input into RBF network for identifying the different fault. Experimental simulation shows that this method can extract effectively the engine fault vibration signal characteristics.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2016 6th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2016)
Part of series
Advances in Intelligent Systems Research
Publication Date
December 2016
ISBN
978-94-6252-282-4
ISSN
1951-6851
DOI
https://doi.org/10.2991/mcei-16.2016.265How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Feng Ding
AU  - Zhi Qi
PY  - 2016/12
DA  - 2016/12
TI  - Turboprop Engine Fault Diagnosis Based on Hilbert Spectrum and Singular Value Decomposition
BT  - 2016 6th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2016)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/mcei-16.2016.265
DO  - https://doi.org/10.2991/mcei-16.2016.265
ID  - Ding2016/12
ER  -