REVIEW article
Front. Chem.
Sec. Analytical Chemistry
This article is part of the Research TopicAdvancements in Analytical ChemistryView all 5 articles
Research Progress of Online Monitoring Techniques for Dissolved Gas Analysis in Insulating Oil
Provisionally accepted
- 1State Grid Sichuan Electric Power Research Institute, Chengdu, China
- 2Power System Security and Operation Key Laboratory of Sichuan Province, Chengdu, China
- 3Gaoxin District Branch, Sichuan Shuneng Electric Power Co., Ltd, Chengdu, China
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Dissolved gas analysis (DGA) in insulating oil can achieve early warning of local discharge, overheating or arc failure in transformers. It can also quantitatively evaluate the aging degree of insulating equipment, providing a basis for formulating predictive maintenance strategies, so as to improve the reliability of power grid power supply. At present, the existing common offline detection methods take a long time, and the dissolved gases in transformers are usually flammable and explosive, posing potential hazards to on-site maintenance personnel. Therefore, it is urgent to develop online detection methods for DGA. This article introduces the types and milestone research progress of DGA online detection methods in recent years (2019-2025). The instant sensing methods of dissolved gas in transformer oil are summarized and analyzed, including on-line gas chromatography analysis system, spectral analysis, and gas sensor methods. Through summarizing the advantages of different methods in terms of detection limit, response speed, operation and maintenance cost, etc., it puts forward the development trend of promoting intelligent and accurate power equipment status monitoring. This review aims to promote the further development of on-line DGA and contribute to the construction of an intelligent grid protection system by providing important technical insights.
Keywords: dissolved gas analysis, Fault diagnosis, Insulating oil, online monitoring, transformer
Received: 10 Oct 2025; Accepted: 03 Dec 2025.
Copyright: © 2025 Mao, Wang, Wang, Ma, Wang, Peng, Geng and Lan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jie Wang
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