Publication:
Wavelet based de-noising for on-site partial discharge measurement signal

cris.author.scopus-author-id 56878313200
cris.author.scopus-author-id 16642710600
cris.author.scopus-author-id 56177750400
cris.author.scopus-author-id 57189241581
cris.author.scopus-author-id 24830345300
cris.author.scopus-author-id 57201667197
cris.author.scopus-author-id 57213599593
dc.contributor.author Abdullah A.Z.B.
dc.contributor.author Isa M.B.
dc.contributor.author Arshad S.N.B.M.
dc.contributor.author Rohani M.N.K.H.
dc.contributor.author Halim H.S.A.
dc.contributor.author Nanyan A.N.B.
dc.contributor.author Hamid H.B.A.
dc.date.accessioned 2024-12-11T07:42:37Z
dc.date.available 2024-12-11T07:42:37Z
dc.date.issued 2019-10-01
dc.description.abstract This paper presents, wavelet based de-noising technique for on-site partial discharge (PD) measurement signal. The signal is measured from medium voltage power cable at 11 kV distribution substation. The best mother wavelet, decomposition level and the type of threshold for the de-noising technique are selected based on the signal to noise ratio (SNR) aggregation. The SNR aggregation is determined based on the minimum, maximum, mean and standard deviation parameters. The same standard de-noising procedure is applied for two different PD signals and the selection parameters are done based on the accuracy of de-noising analysis. The analysis is performed in MATLAB software environment and Daubechies 2 (db2) is found as the best mother wavelet at tenth decomposition levels with soft threshold type. This study is specifically performed to develop the de-noising procedure for on-site PD measurement. Overall results indicate that the right selection of the de-noising procedure will help to improve the PD signal detection from on–site measurement.
dc.identifier.doi 10.11591/ijeecs.v16.i1.pp259-266
dc.identifier.scopus 2-s2.0-85071300344
dc.identifier.uri https://hdl.handle.net/20.500.14170/10071
dc.relation.funding Ministry of Higher Education
dc.relation.grantno undefined
dc.relation.ispartof Indonesian Journal of Electrical Engineering and Computer Science
dc.relation.ispartofseries Indonesian Journal of Electrical Engineering and Computer Science
dc.relation.issn 25024752
dc.rights open access
dc.subject De-Noising | Measurement | On-Site | Partial Discharge | Wavelet Transform
dc.title Wavelet based de-noising for on-site partial discharge measurement signal
dc.type Journal
dspace.entity.type Publication
oaire.citation.endPage 266
oaire.citation.issue 1
oaire.citation.startPage 259
oaire.citation.volume 16
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Tenaga Nasional Berhad
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
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person.identifier.scopus-author-id 56878313200
person.identifier.scopus-author-id 16642710600
person.identifier.scopus-author-id 56177750400
person.identifier.scopus-author-id 57189241581
person.identifier.scopus-author-id 24830345300
person.identifier.scopus-author-id 57201667197
person.identifier.scopus-author-id 57213599593
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