Novel Calculation Method of Indices to Improve Classification of Transformer Winding Fault Type, Location, and Extent

Tarimoradi, Hadi; Gharehpetian, Gevork B.

doi:10.1109/tii.2017.2651954

Cited by 73 publications

(34 citation statements)

References 23 publications

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“…In addition of improving the accuracy, phase function increases the convergence speed too. Even with all useful effects of the phase function, it is not often considered by researchers, for the sake of simplicity, increasing the convergence rate or evading a multiobjective problem . For simplifying the problem at first level, the number of considered frequency points decreased and only 1/10 of all frequency points are used at this level.…”

Section: The Proposed Multilevel Approachmentioning

confidence: 99%

“…Even with all useful effects of the phase function, it is not often considered by researchers, for the sake of simplicity, increasing the convergence rate or evading a multiobjective problem. [14][15][16][17][18]22,24 For simplifying the problem at first level, the number of considered frequency points decreased and only 1/10 of all frequency points are used at this level. The second objective function computes the normalized Euclidean distance among the magnitude of the reference frequency points and the calculated FR points.…”

Section: Defining Parameters Of the Detail Modelmentioning

confidence: 99%

“…A novel technique for frequency response analysis is presented in Aljohani and Abu‐Siada by integrating the finite element analysis technique and the magnitude and phase of FR, to simulate winding deformation at different locations of the transformer. A calculation technique for transfer function (TF) comparison indices, entitled windowed calculation, is offered in Tarimoradi and Gharehpetian for determining the winding fault. A simple technique is proposed in Haghjoo and Mostafaei, to diagnose the location of turn‐to‐turn faults in power transformers by using core flux‐based method.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Detecting the location and severity of transformer winding deformation by a novel adaptive particle swarm optimization algorithm

Jahan

Keypour

Izadfar

et al. 2018

Int Trans Electr Energ Syst

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Summary Transformers as 1 of the most important and expensive equipment of power network are under continuous exposure of faults. Periodic examinations for detecting and locating trivial deformation occurrences are indispensable for preventing their unexpected outage and costly, time‐consuming repair procedure. The most crucial step for fault detection is obtaining parameters of the detailed model. Acquiring parameters of the detailed model (APDM) is a nonlinear, nonconvex, and large‐scale problem that requires a powerful method to be solved. This paper proposed a novel method that gains benefit from new efficient functions of Fourier series coefficient and phase functions, an adaptive version of the PSO and fast calculation of coupled network matrices, to solve the problem. Experimental results on 2.64 and 120 kV set of transformer windings, constructed for this study, verified the precision of the proposed method for discovering the position and severity of the disk space variation fault.

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Section: The Proposed Multilevel Approachmentioning

confidence: 99%

Section: Defining Parameters Of the Detail Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Detecting the location and severity of transformer winding deformation by a novel adaptive particle swarm optimization algorithm

Jahan

Keypour

Izadfar

et al. 2018

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…In order to use this method, transformer components should be presented by electrical parameters comprising resistors, capacitors, and self/mutual inductances, whose values vary due to any winding displacement causing changes in the FRA characteristics. As a result, the FRA characteristic of a healthy condition is different from that of a faulty condition [1,6,21,22]. Although a large number of studies have been performed on the detection of the winding axial displacement using FRA method [6], [17][18][19][20][21], [23][24][25], [27,28] but having said that, they have considered only the symmetrical axial displacement of the windings and none of them have worked on the asymmetrical axial displacement of windings which is a very common case.…”

Section: Introductionmentioning

confidence: 99%

“…2-Huge repair and replacement costs of transformers. With these in mind, the advantages of the on-time condition assessment of transformers is undeniable [1,2]. It has been indicated in [3,4] that 19% of the total faults occur in the windings which include short circuit between winding turns [5], a short circuit between ground and winding turns, and a short circuit between LV and HV windings.…”

Section: Introductionmentioning

confidence: 99%

Effect of the Asymmetrical Axial Displacement of Transformer Windings on Fra Characteristics

Ansari¹,

Vahedi²

2020

jcr

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Frequency response analysis (FRA) is one of the most reliable and useful methods for mechanical fault detection in transformers. The winding axial displacement is one of the mechanical fault types that can occur in transformers. Axial displacements causes the detailed model parameters changing, in response to which FRA characteristics will also change. Numerous researchers have considered winding axial displacements as a symmetrical movement of disks. However, one of the most prevalent types of winding axial displacements is asymmetrical axial displacement which has not been considered by any prior studies. In this paper, physical asymmetrical and symmetrical axial displacements of the first disk of the LV winding were simulated and FRA characteristics were obtained for these cases. Finally, experimental tests were performed on an experimental transformer to validate the simulation results.

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Power Transformer Winding Deformation Diagnosis Based on the Sum of Two‐Way Shortest Distance

Dong,

Wang,

2023

IEEJ Transactions Elec Engng

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Frequency response analysis (FRA) method has been widely used in the world, but the interpretation of its signatures is still a hard problem to solve. This paper introduces a method of the sum of two‐way shortest distance for transformer winding deformation fault diagnosis, which is based on trajectory similarity between FRA signatures. Compared with most existing methods, it does not need order preservation; however, it focuses more on the trajectory itself. The geometric principle of the sum of two‐way shortest distance is introduced and analyzed in detail. By using the circuit analysis software, the equivalent circuit model of the transformer is established, a group of the FRA signatures of three types of transformer winding fault, including axial displacement, radial deformation, and disk space variation fault, are obtained. The distribution of different type of faults is studied by using the sum of two‐way shortest distance to process the FRA signatures in three different frequency bands. Using the sum of two‐way shortest distance as input, the support vector machine (SVM) is employed to train a predictive engine for transformer winding deformation fault diagnosis. Result shows that the proposed method can well classify and diagnose transformer winding deformation fault. © 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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Novel Calculation Method of Indices to Improve Classification of Transformer Winding Fault Type, Location, and Extent

Cited by 73 publications

References 23 publications

Detecting the location and severity of transformer winding deformation by a novel adaptive particle swarm optimization algorithm

Detecting the location and severity of transformer winding deformation by a novel adaptive particle swarm optimization algorithm

Effect of the Asymmetrical Axial Displacement of Transformer Windings on Fra Characteristics

Power Transformer Winding Deformation Diagnosis Based on the Sum of Two‐Way Shortest Distance

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