Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications

Bearing Fault Detection Based on TQWT and Hilbert Envelope

Authors
Qi Liu
Corresponding Author
Qi Liu
Available Online January 2017.
DOI
https://doi.org/10.2991/icmmita-16.2016.101How to use a DOI?
Keywords
Bearing; fault detection; TQWT; Hilbert envelope.
Abstract

Bearings always work under harsh environment, which makes them easily to failure. Fault detection of the bearing is a key issue for maintaining the whole machinery system. In this paper, a novel method is proposed to detect the fault of bearings. Tunable Q-factor wavelet transform (TQWT) is used to decompose the original vibration bearing signal to several levels, the Hilbert envelope analysis method is applied to each wavelet decomposed signal. The fault feature of the bearing can be detected from the envelope spectrum. Both the simulation study and the application demonstrate the effectiveness of the proposed method.

Copyright
© 2017, 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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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
Series
Advances in Computer Science Research
Publication Date
January 2017
ISBN
978-94-6252-285-5
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmmita-16.2016.101How to use a DOI?
Copyright
© 2017, 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  - Qi Liu
PY  - 2017/01
DA  - 2017/01
TI  - Bearing Fault Detection Based on TQWT and Hilbert Envelope
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 548
EP  - 551
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.101
DO  - https://doi.org/10.2991/icmmita-16.2016.101
ID  - Liu2017/01
ER  -