Power Transformer Partial Discharge Fault Diagnosis Based on Multidimensional Feature Region
Joint Authors
Jia, Rong
Xie, Yongtao
Wu, Hua
Dang, Jian
Dong, Kaisong
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-09
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Effectively extracting power transformer partial discharge (PD) signals feature is of great significance for monitoring power transformer insulation condition.
However, there has been lack of practical and effective extraction methods.
For this reason, this paper suggests a novel method for the PD signal feature extraction based on multidimensional feature region.
Firstly, in order to better describe differences in each frequency band of fault signals, empirical mode decomposition (EMD) and Hilbert-Huang transform (HHT) band-pass filter wave for raw signal is carried out.
And the component of raw signals on each frequency band can be obtained.
Secondly, the sample entropy value and the energy value of each frequency band component are calculated.
Using the difference of each frequency band energy and complexity, signals feature region is established by the multidimensional energy parameters and the multidimensional sample entropy parameters to describe PD signals multidimensional feature information.
Finally, partial discharge faults are classified by sphere-structured support vector machines algorithm.
The result indicates that this method is able to identify and classify different partial discharge faults.
American Psychological Association (APA)
Jia, Rong& Xie, Yongtao& Wu, Hua& Dang, Jian& Dong, Kaisong. 2016. Power Transformer Partial Discharge Fault Diagnosis Based on Multidimensional Feature Region. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1112232
Modern Language Association (MLA)
Jia, Rong…[et al.]. Power Transformer Partial Discharge Fault Diagnosis Based on Multidimensional Feature Region. Mathematical Problems in Engineering No. 2016 (2016), pp.1-11.
https://search.emarefa.net/detail/BIM-1112232
American Medical Association (AMA)
Jia, Rong& Xie, Yongtao& Wu, Hua& Dang, Jian& Dong, Kaisong. Power Transformer Partial Discharge Fault Diagnosis Based on Multidimensional Feature Region. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1112232
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112232