@inproceedings{70330dc02c594fc3beee9b02d700b163,
title = "Online Evaluation of Potential Transformer Operating Conditions Based on Similarity and Cluster Analysis",
abstract = "The paper proposes a comprehensive method for online monitoring of potential transformers (PTs) based on similarity coefficient clustering and health index evaluation. By collecting and analyzing real-time operational data, the method calculates similarity coefficients to assess the condition of PTs and employs cluster analysis to group transformers with similar characteristics. A health index model is developed to provide an accurate evaluation of PT status, enabling more effective maintenance and fault prediction. The approach has been verified through case studies, demonstrating its potential for early fault detection, improved PT management, and reduced maintenance costs in power systems.",
keywords = "Potential transformer (PT), cluster analysis, fault detection, health index, online monitoring, similarity coefficient",
author = "Ying Tang and Dake He and Junyou Shi and Yuwei Chen",
note = "Publisher Copyright: {\textcopyright}2024 IEEE.; 4th IEEE International Conference on Data Science and Computer Application, ICDSCA 2024 ; Conference date: 22-11-2024 Through 24-11-2024",
year = "2024",
doi = "10.1109/ICDSCA63855.2024.10860010",
language = "英语",
series = "2024 IEEE 4th International Conference on Data Science and Computer Application, ICDSCA 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "426--430",
booktitle = "2024 IEEE 4th International Conference on Data Science and Computer Application, ICDSCA 2024",
address = "美国",
}