Multi-Source Information Fusion for Power Transformer Condition Assessment
Paper
Paper/Presentation Title | Multi-Source Information Fusion for Power Transformer Condition Assessment |
---|---|
Presentation Type | Paper |
Authors | Cui, Yi (Author), Ma, Hui (Author) and Saha, Tapan (Author) |
Journal or Proceedings Title | Proceedings of the 2016 IEEE Power and Energy Society General Meeting (PESGM) |
Number of Pages | 5 |
Year | 2016 |
Place of Publication | Boston, United States |
ISBN | 9781509041688 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/PESGM.2016.7741121 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/7741121 |
Conference/Event | 2016 IEEE Power and Energy Society General Meeting (PESGM) |
Event Details | 2016 IEEE Power and Energy Society General Meeting (PESGM) Event Date 17 to end of 21 Jul 2016 Event Location Boston, United States |
Abstract | This paper presents a multi-source data and information fusion framework for power transformer condition assessment. The proposed method adopts Bayesian Network (BN), which can integrate every piece of data and information obtained from different transformer diagnostic measurements. Within the Bayesian Network, Monte Carlo and Bootstrap methods are employed to extract the most informative characteristics regarding transformer condition from different diagnostic measurements. Reliability metrics are computed to evaluate the effectiveness of combinations of different type diagnostic measurements and subsequently facilitate determining optimal diagnostic strategies involved in transformer condition assessment. Theories, implementations, and results of the proposed method are presented using case studies in this paper. |
Keywords | Bayesian network; Condition assessment; Data and information fusion; Multiple source; 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/q7w3z/multi-source-information-fusion-for-power-transformer-condition-assessment
46
total views2
total downloads3
views this month0
downloads this month