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.

翻译：变压器故障诊断（TFD）是电力系统运维管理的关键环节。本文全面综述了当前基于人工智能（AI）与溶解气体分析（DGA）的变压器故障诊断技术最新进展。文章深入分析了该领域的新兴成果，包括深度学习算法与先进数据分析技术的应用，及其对变压器故障诊断乃至整个电力行业的潜在影响。本综述还系统评估了不同诊断方法的优劣，涵盖基于规则的专家系统、神经网络与机器学习算法等。总体而言，本文旨在阐述变压器故障诊断的重要性，阐明人工智能在保障电力系统可靠运行中的关键作用。