Detection of interturn faults during transformer energization using wavelet transform

Juan C. Olivares-Galvan; R. Escarela-Perez; J. Alberto Ávalos González; Jaime Cerda Jacobo; Daniel Guillén; Fermin P. Espino-Cortés

doi:10.1109/ROPEC.2016.7830612

Detection of interturn faults during transformer energization using wavelet transform

Juan C. Olivares-Galvan, R. Escarela-Perez, J. Alberto Ávalos González, Jaime Cerda Jacobo, Daniel Guillén, Fermin P. Espino-Cortés

Escuela Superior de Ingeniería Mecánica y Eléctrica (ESIME), Unidad Zacatenco

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

Interturn faults are a critical problem in power transformers that can eventually escalate into catastrophic faults and probably result in an overall network failure. Also, failures in transformer windings are still a major cause of transformer outages, and failure rates vary widely between different countries and systems, depending on many factors. Therefore, in this work, interturn faults with various levels of severity were imposed on the winding of a 120 VA, 24/125 V dry type transformer to diagnose it. The obtained signals during the experiments are processed using the Wavelet Transform and correlation modes. This technique only takes into account the high frequency information produced during the energization of a winding with interturn faults.

Original language	English
Title of host publication	2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509037940
DOIs	https://doi.org/10.1109/ROPEC.2016.7830612
State	Published - 23 Jan 2017
Event	2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016 - Ixtapa, Guerrero, Mexico Duration: 9 Nov 2016 → 11 Nov 2016

Publication series

Name	2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016

Conference

Conference	2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016
Country/Territory	Mexico
City	Ixtapa, Guerrero
Period	9/11/16 → 11/11/16

Keywords

interturn faults
transformer energization
wavelet correlation modes
wavelet transform

Access to Document

10.1109/ROPEC.2016.7830612

Cite this

Olivares-Galvan, J. C., Escarela-Perez, R., González, J. A. Á., Jacobo, J. C., Guillén, D., & Espino-Cortés, F. P. (2017). Detection of interturn faults during transformer energization using wavelet transform. In 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016 Article 7830612 (2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ROPEC.2016.7830612

Olivares-Galvan, Juan C. ; Escarela-Perez, R. ; González, J. Alberto Ávalos et al. / Detection of interturn faults during transformer energization using wavelet transform. 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. (2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016).

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title = "Detection of interturn faults during transformer energization using wavelet transform",

abstract = "Interturn faults are a critical problem in power transformers that can eventually escalate into catastrophic faults and probably result in an overall network failure. Also, failures in transformer windings are still a major cause of transformer outages, and failure rates vary widely between different countries and systems, depending on many factors. Therefore, in this work, interturn faults with various levels of severity were imposed on the winding of a 120 VA, 24/125 V dry type transformer to diagnose it. The obtained signals during the experiments are processed using the Wavelet Transform and correlation modes. This technique only takes into account the high frequency information produced during the energization of a winding with interturn faults.",

keywords = "interturn faults, transformer energization, wavelet correlation modes, wavelet transform",

author = "Olivares-Galvan, {Juan C.} and R. Escarela-Perez and Gonz{\'a}lez, {J. Alberto {\'A}valos} and Jacobo, {Jaime Cerda} and Daniel Guill{\'e}n and Espino-Cort{\'e}s, {Fermin P.}",

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year = "2017",

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doi = "10.1109/ROPEC.2016.7830612",

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Olivares-Galvan, JC, Escarela-Perez, R, González, JAÁ, Jacobo, JC, Guillén, D & Espino-Cortés, FP 2017, Detection of interturn faults during transformer energization using wavelet transform. in 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016., 7830612, 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016, Ixtapa, Guerrero, Mexico, 9/11/16. https://doi.org/10.1109/ROPEC.2016.7830612

Detection of interturn faults during transformer energization using wavelet transform. / Olivares-Galvan, Juan C.; Escarela-Perez, R.; González, J. Alberto Ávalos et al.
2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7830612 (2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Detection of interturn faults during transformer energization using wavelet transform

AU - Olivares-Galvan, Juan C.

AU - Escarela-Perez, R.

AU - González, J. Alberto Ávalos

AU - Jacobo, Jaime Cerda

AU - Guillén, Daniel

AU - Espino-Cortés, Fermin P.

PY - 2017/1/23

Y1 - 2017/1/23

N2 - Interturn faults are a critical problem in power transformers that can eventually escalate into catastrophic faults and probably result in an overall network failure. Also, failures in transformer windings are still a major cause of transformer outages, and failure rates vary widely between different countries and systems, depending on many factors. Therefore, in this work, interturn faults with various levels of severity were imposed on the winding of a 120 VA, 24/125 V dry type transformer to diagnose it. The obtained signals during the experiments are processed using the Wavelet Transform and correlation modes. This technique only takes into account the high frequency information produced during the energization of a winding with interturn faults.

AB - Interturn faults are a critical problem in power transformers that can eventually escalate into catastrophic faults and probably result in an overall network failure. Also, failures in transformer windings are still a major cause of transformer outages, and failure rates vary widely between different countries and systems, depending on many factors. Therefore, in this work, interturn faults with various levels of severity were imposed on the winding of a 120 VA, 24/125 V dry type transformer to diagnose it. The obtained signals during the experiments are processed using the Wavelet Transform and correlation modes. This technique only takes into account the high frequency information produced during the energization of a winding with interturn faults.

KW - interturn faults

KW - transformer energization

KW - wavelet correlation modes

KW - wavelet transform

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T3 - 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016

BT - 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016

Y2 - 9 November 2016 through 11 November 2016

ER -

Olivares-Galvan JC, Escarela-Perez R, González JAÁ, Jacobo JC, Guillén D, Espino-Cortés FP. Detection of interturn faults during transformer energization using wavelet transform. In 2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7830612. (2016 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2016). doi: 10.1109/ROPEC.2016.7830612

Detection of interturn faults during transformer energization using wavelet transform

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