dc.contributor.author |
Xue, L |
|
dc.contributor.author |
Zhu, Y |
|
dc.contributor.author |
Yang, C |
|
dc.contributor.author |
Kumarawadu, S |
|
dc.date.accessioned |
2023-04-25T03:52:15Z |
|
dc.date.available |
2023-04-25T03:52:15Z |
|
dc.date.issued |
2020 |
|
dc.identifier.citation |
Xue, L., Zhu, Y., Yang, C., & Kumarawadu, S. (2020). Online quantitative partial discharge monitor based on interferometry. Scientific Reports, 10(1), 19047. https://doi.org/10.1038/s41598-020-76134-x |
en_US |
dc.identifier.issn |
2045-2322 |
en_US |
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/20948 |
|
dc.description.abstract |
Interferometry-based online partial discharge (PD) monitor presented in this paper can detect the occurrence of PD sensitively, evaluate the peak value of the discharge inception voltage with random waveform and the damage extent relatively cost effectively. The interferograms affected by the PD are collected online. By extracting the phase information of the interference fringes quantitatively, the peak value of the discharge inception voltage with random waveform can be retrieved real-time. Merits of the proposed method as an online quantitative PD monitor are validated via theoretical analysis as well as experimentations by the use of an artificially localized PD source. Furthermore, the proposed method can capture the light signal emitted by the discharge. Quite in contrast to many commonly used sensor-based methods, our approach avoids the need of amplifying the light signal strength making its practical implantation much convenient. The proposed method promises strong potential for field application. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.title |
Online quantitative partial discharge monitor based on interferometry |
en_US |
dc.type |
Article-Full-text |
en_US |
dc.identifier.year |
2020 |
en_US |
dc.identifier.journal |
Scientific Reports |
en_US |
dc.identifier.issue |
1 |
en_US |
dc.identifier.volume |
10 |
en_US |
dc.identifier.database |
PubMed Central |
en_US |
dc.identifier.pgnos |
19047 |
en_US |
dc.identifier.doi |
10.1038/s41598-020-76134-x. |
en_US |