A condition monitoring and fault detection in the windings of power transformer using impulse frequency response analysis

Ritesh Kumar (), Adavelli Vaijayanthi, Ram Deshmukh (), B. Vedik () and Chandan Kumar Shiva ()
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Ritesh Kumar: SR University
Adavelli Vaijayanthi: SR University
Ram Deshmukh: SR University
B. Vedik: SR University
Chandan Kumar Shiva: SR University

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 4, No 38, 2062-2074

Abstract: Abstract The power transformer is one of the most important pieces of equipment and plays a vital role in the power system. Failure of the transformer may cause an outage of the power supply, which may affect the utility. The main reasons for the transformer’s failure include insulation degradation and/or deformation of its windings which occurs due to the transient phenomenon and overloading conditions, and it leads to the turn-to-turn fault (TTF) in windings of the transformer. This TTF in turn may lead to a catastrophic fault in the windings of the transformer. Frequency response analysis (FRA), commonly, used an offline method to detect these faults, however, leads to an outage of power supply. The main aim of this paper is to diagnosis the transformer windings and detect the early faults if any. In this paper, two methods are simulated and discussed, namely impulse frequency response analysis (IFRA) and Lightning impulse analysis (LIA). These methods are capable of diagnosis winding deformation and short circuit faults on live transformers. An injecting of the impulse signal into the electrical model of a high voltage power transformer winding through the bushing capacitive coupling circuit are studied. The obtained simulation results are observed by comparing the obtained frequency response for a healthy and faulty condition for both online and offline transformers.

Keywords: Power transformer; Fault detection; Turn-to-turn fault; Condition monitoring; Frequency response analysis (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-022-01619-z

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