Details
| Original language | English |
|---|---|
| Qualification | Doctor of Engineering |
| Awarding Institution | |
| Supervised by |
|
| Date of Award | 29 Sept 2020 |
| Place of Publication | Garbsen |
| Print ISBNs | 9783959005913, 3959005911 |
| Electronic ISBNs | 978-3-95900-609-5 |
| Publication status | Published - 2021 |
Abstract
The first method is based on calculated sectional transfer function of the winding in power transformers with design information. This method is based on the multi-conductor transmission line theory which improves the accuracy of PD localization using the design information of the transformer. And further software provided for PD localization is presented.
The second method, a highly functional and simplified method is discussed. This method allows investigating and suggesting the possibility of detection of failures of PD with the least amount of time and information regarding the interior design of power transformer.
The third method utilizes a machine learning algorithm by simplification of the measurements. The proposed method uses measured partial discharge signals with high frequency current transformer (HFCT) and processed them using a curve fitting (CF) method with a high rated fitting quality. The extracted coefficients of the selected function terms are then evaluated in order to find the PD location.
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
Garbsen, 2021. 139 p.
Research output: Thesis › Doctoral thesis
}
TY - BOOK
T1 - Methods of partial discharge localization in high voltage transformers
AU - Rahimbakhsh, Mahdi
N1 - Doctoral thesis
PY - 2021
Y1 - 2021
N2 - In this thesis, three PD localization methods are developed and discussed.The first method is based on calculated sectional transfer function of the winding in power transformers with design information. This method is based on the multi-conductor transmission line theory which improves the accuracy of PD localization using the design information of the transformer. And further software provided for PD localization is presented.The second method, a highly functional and simplified method is discussed. This method allows investigating and suggesting the possibility of detection of failures of PD with the least amount of time and information regarding the interior design of power transformer.The third method utilizes a machine learning algorithm by simplification of the measurements. The proposed method uses measured partial discharge signals with high frequency current transformer (HFCT) and processed them using a curve fitting (CF) method with a high rated fitting quality. The extracted coefficients of the selected function terms are then evaluated in order to find the PD location.
AB - In this thesis, three PD localization methods are developed and discussed.The first method is based on calculated sectional transfer function of the winding in power transformers with design information. This method is based on the multi-conductor transmission line theory which improves the accuracy of PD localization using the design information of the transformer. And further software provided for PD localization is presented.The second method, a highly functional and simplified method is discussed. This method allows investigating and suggesting the possibility of detection of failures of PD with the least amount of time and information regarding the interior design of power transformer.The third method utilizes a machine learning algorithm by simplification of the measurements. The proposed method uses measured partial discharge signals with high frequency current transformer (HFCT) and processed them using a curve fitting (CF) method with a high rated fitting quality. The extracted coefficients of the selected function terms are then evaluated in order to find the PD location.
M3 - Doctoral thesis
SN - 9783959005913
SN - 3959005911
T3 - Berichte aus dem IfES
CY - Garbsen
ER -