Interpretation of transformer winding deformation fault by the spectral clustering of FRA signature

Zhao, Zhongyong; Tang, Chao; Chen, Yu; Zhou, Qu; Yao, Chenguo; Islam, Syed

Title: Interpretation of transformer winding deformation fault by the spectral clustering of FRA signature
Creator: Zhao, Zhongyong; Tang, Chao; Chen, Yu; Zhou, Qu; Yao, Chenguo; Islam, Syed
Date: 2021
Type: Text; Journal article
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/176390
Identifier: vital:15134
Identifier: https://doi.org/10.1016/j.ijepes.2021.106933
Identifier: ISBN:0142-0615 (ISSN)
Abstract: Frequency response analysis (FRA) has been accepted as a widely used tool for the power industry. The interpretation of FRA can be achieved by the conventional mathematical indicators-based method, which is mostly used in the past. The newly developing artificial intelligence (AI)-based method also provides an alternative interpretation. However, in most reported AI techniques, the features of FRA signatures are directly input into the AI model to obtain the classification results. Few studies have concentrated on the separability of winding deformation faults. In this context, a spectral clustering algorithm is studied to aid in FRA interpretation. The electrical model simulation and experimental tests are performed. The FRA data processing results verify the feasibility, effectiveness and superiority of the proposed method. © 2021 Elsevier Ltd
Publisher: Elsevier Ltd
Relation: International Journal of Electrical Power and Energy Systems Vol. 130, no. (2021), p.
Rights: All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
Subject: 0906 Electrical and Electronic Engineering; Artificial intelligence; Fault analysis; Power transformers; Spectral clustering; Winding deformation
Reviewed
Funder: This work was supported in part by the National Natural Science Foundation of China under Grant 51807166 and in part by the Natural Science Foundation of Chongqing under Grant cstc2019jcyj-msxmX0236.

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