PDTools: A toolbox of partial discharge (PD) signal analysis for transformer condition assessment
Paper
Paper/Presentation Title | PDTools: A toolbox of partial discharge (PD) signal analysis for transformer condition assessment |
---|---|
Presentation Type | Paper |
Authors | Ma, Hui (Author), Saha, Tapan (Author), Seo, Junhyuck (Author), Chan, Jeffery (Author) and Cui, Yi (Author) |
Journal or Proceedings Title | Proceedings of the 2017 IEEE Power and Energy Society General Meeting (PESGM) |
ERA Conference ID | 50486 |
Number of Pages | 5 |
Year | 2017 |
Place of Publication | Chicago, United States |
ISBN | 9781538622124 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/PESGM.2017.8273888 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/abstract/document/8273888 |
Conference/Event | 2017 IEEE Power and Energy Society General Meeting (PESGM) |
IEEE Power and Energy Society General Meeting | |
Event Details | 2017 IEEE Power and Energy Society General Meeting (PESGM) Event Date 16 to end of 20 Jul 2017 Event Location Chicago, United States |
Event Details | IEEE Power and Energy Society General Meeting PES-GM |
Abstract | Partial discharge (PD) measurement of power transformers provides a means for condition assessment of their insulation systems. To reach an informed assessment on the condition of a transformer's insulation system, it needs to appropriately analyze the measured PD signals. Though abundant methods have been proposed for PD signal analysis, it is still a non-trivial task and especially for non-expert. Thus, this paper develops an open source toolbox for PD signal analysis. The toolbox consists of various PD signal analysis algorithms, from PD signal de-noising to PD signal representation, and to multiple PD source separation and PD source classification. The toolbox can be readily used by researchers and utility engineers to process and interpret the signals obtained from PD measurements of transformers at laboratory and field. |
Keywords | Condition assessment; Insulation; Partial discharge; Signal analysis; Transformer |
ANZSRC Field of Research 2020 | 400803. Electrical energy generation (incl. renewables, excl. photovoltaics) |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Queensland |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q7w27/pdtools-a-toolbox-of-partial-discharge-pd-signal-analysis-for-transformer-condition-assessment
45
total views2
total downloads5
views this month0
downloads this month