Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)

Analog Circuit Fault Diagnosis Method Based on Preferred Wavelet Packet and ELM

Authors
Haitao Shi, Qide Tan, Chenggang Li, Xiangyu Lv
Corresponding Author
Haitao Shi
Available Online April 2017.
DOI
https://doi.org/10.2991/eame-17.2017.1How to use a DOI?
Keywords
wavelet packet transform; extreme learning machine (ELM); analog circuit; fault diagnosis; feature departure degree
Abstract

In order to improve the effectiveness of fault feature extraction and achieve the accurate classification of fault patterns in analog circuit, the paper proposed a new analog circuit fault diagnosis method based on preferred wavelet packet and extreme learning machine (ELM). The concept of feature departure degree is defined, which can be used as a measure of wavelet packet transform to obtain the fault features using different wavelet basis function, and the wavelet basis function with maximum feature departure degree is selected and used to extract the fault feature. Further, the ELM is introduced for fault classification and identification, and the diagnosis result is compared with those using three popular neural networks. The simulation results show that the better diagnosis precision can be achieved using the preferred wavelet packet, and the test time and the classification precision of the ELM are all better than those using other methods.

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/).

Download article (PDF)

Volume Title
Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
978-94-6252-332-6
ISSN
2352-5401
DOI
https://doi.org/10.2991/eame-17.2017.1How 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  - Haitao Shi
AU  - Qide Tan
AU  - Chenggang Li
AU  - Xiangyu Lv
PY  - 2017/04
DA  - 2017/04
TI  - Analog Circuit Fault Diagnosis Method Based on Preferred Wavelet Packet and ELM
BT  - Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)
PB  - Atlantis Press
SP  - 1
EP  - 4
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-17.2017.1
DO  - https://doi.org/10.2991/eame-17.2017.1
ID  - Shi2017/04
ER  -