FAULTS OF POWER TRANSFORMERS AND BASIC DIAGNOSTIC METHODS
1,2T.K. Nurubeyli
2024   03   az   p.38-43

ABSTRACT

This article examines advanced diagnostic techniques for assessing the condition and potential faults of transformer insulation systems, with a primary focus on transformer oil. The purpose of the study is based on the effect of temperature, electrical voltage and specific electrical parameters such as dielectric loss coefficient (tgδ) on the indicator of wear processes and possible degradation. It discusses the benefits of nanofillers in improving breakdown voltage by binding moisture at low temperatures and trapping charge at higher temperatures. Techniques such as partial discharge (PD) measurements, frequency response analysis (FRA) and dielectric frequency analysis (DTA) are evaluated for their effectiveness in early fault detection. The study also explores the use of ultraviolet spectroscopy and artificial neural networks (ANNs) to accurately estimate the interphase voltage (IFT) of transformer oil. In addition, the detection of substances such as furfural using Raman spectroscopy provides insight into the aging and longevity of transformer systems. These advances in diagnostics increase the reliability and longevity of transformers and offer solutions to reduce maintenance costs and prevent faults early, ultimately reducing operating costs and increasing system efficiency.

Keywords: transformer oil, furfural substances, malfunctions, artificial neural networks.
DOI:10.70784/azip.2.2024338

Received: 27.09.2024
Internet publishing: 02.10.2024

AUTHORS & AFFILIATIONS

1. Institute of Physics Ministry of Science and Education Republic of Azerbaijan, 131 H.Javid ave, Baku, AZ-1143, Azerbaijan
2. Azerbaijan State Oil and Industry University, 20 Azadlig ave. Baku, AZ 1010, Azerbaijan
E-mail: aem05@rambler.ru

Graphics and Images

                  

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