The State of the Art in transformer fault diagnosis with artificial
intelligence and Dissolved Gas Analysis: A Review of the Literature
- URL: http://arxiv.org/abs/2304.11880v1
- Date: Mon, 24 Apr 2023 07:50:35 GMT
- Title: The State of the Art in transformer fault diagnosis with artificial
intelligence and Dissolved Gas Analysis: A Review of the Literature
- Authors: Yuyan Li
- Abstract summary: Transformer fault diagnosis (TFD) is a critical aspect of power system maintenance and management.
This review paper provides a comprehensive overview of the current state of the art in TFD using artificial intelligence (AI) and dissolved gas analysis (DGA)
- Score: 1.0152838128195467
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Transformer fault diagnosis (TFD) is a critical aspect of power system
maintenance and management. This review paper provides a comprehensive overview
of the current state of the art in TFD using artificial intelligence (AI) and
dissolved gas analysis (DGA). The paper presents an analysis of recent
advancements in this field, including the use of deep learning algorithms and
advanced data analytics techniques, and their potential impact on TFD and the
power industry as a whole. The review also highlights the benefits and
limitations of different approaches to transformer fault diagnosis, including
rule-based systems, expert systems, neural networks, and machine learning
algorithms. Overall, this review aims to provide valuable insights into the
importance of TFD and the role of AI in ensuring the reliable operation of
power systems.
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