Trend Prediction of Power Transformers from DGA Data Using Artificial Intelligence Techniques

Author:

Lekshmi A. S. Kunju,Kumar Deepa S.,Beevi K. Sabeena

Publisher

Springer Nature Singapore

Reference16 articles.

1. IEC Standard 61181 (2012) Electrical mineralization—the use of gas analysis (DGA) in factory testing of electrical equipment and AMD1

2. IEEE Standard C57.130 (2015) IEEE guide to the use of disposable gas system used in factory temperature testing in testing transformers in blood and oil transformers

3. Xu H (2012) Study on transformer oil dissolves gas online monitoring and fault diagnosis method. In: IEEE International Conference on Condition Monitoring and Diagnosis, pp 593–596

4. Ding H, Heywood R, Lapworth J, Josebury R, Roxborough A, McCulloch E (2017) The experience of making molten gas in transformer oil to detect incoming errors. In: IEEE 19th International Conference on Dielectric Liquids (ICDL), pp 1–5

5. Golarz J (2016) Understanding dissolve gas analysis (DGA) techniques and definitions. In: IEEE/PES Transmission and Distribution Conference and Exposition (T&D), pp 1–5

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