Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications

Generator Looseness Fault Diagnosis Based on Time-Frequency Analysis

Authors
Ting Li, Chen Liu, ChenDong Duan, Xia Qi
Corresponding Author
Ting Li
Available Online May 2016.
DOI
10.2991/wartia-16.2016.4How to use a DOI?
Keywords
Frequency Slice Wavelet Transform, Looseness Fault, Feature Extraction
Abstract

In order to extract looseness fault feature for a generator set, the paper introduces a new time-frequency analysis method, called frequency slice wavelet transform (FSWT). The time-frequency distribution of signal is firstly processed by the FSWT. Then some interesting regions on the FSWT time-frequency map are selected for further analysis. Based on zoom and refine analysis, fault features are finally extracted and separated. Experiment and engineering application research showed that this method is effective.

Copyright
© 2016, 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 2nd Workshop on Advanced Research and Technology in Industry Applications
Series
Advances in Engineering Research
Publication Date
May 2016
ISBN
978-94-6252-195-7
ISSN
2352-5401
DOI
10.2991/wartia-16.2016.4How to use a DOI?
Copyright
© 2016, 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  - Ting Li
AU  - Chen Liu
AU  - ChenDong Duan
AU  - Xia Qi
PY  - 2016/05
DA  - 2016/05
TI  - Generator Looseness Fault Diagnosis Based on Time-Frequency Analysis
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 17
EP  - 21
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.4
DO  - 10.2991/wartia-16.2016.4
ID  - Li2016/05
ER  -