Application of wavelet transform for recognition of acoustic signals of various defects of power transformers

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Abstract

Background: This study discusses the use of wavelet transform for processing acoustic signals when diagnosing power transformers. A simulator with various defects was used to explore the application of continuous wavelet transform. The study also outlines an algorithm for obtaining signal standards to identify different types of defects.

Aim. To develop a mathematical model for constructing reference acoustic control signals when processing data from a simulator with various defects. These signals will be used to identify and diagnose defects in real power transformers during their operation.

Methods. The study introduces expressions for signal transformation, presents acoustic control signals, and explains the formation of reference signals. It also describes the process of recognizing the closest signals in form, corresponding to different types of defects.

Results. The key results include expressions for signal transformation, acoustic control signals, and the formation of reference signals. The closest matching signals were identified, enabling accurate recognition of different defect types.

Conclusion. The research proposes a method for processing acoustic control signals, allowing the reproduction of various insulation defects of power transformers and the recognition of such defects according to the proposed parameters of the wavelet transform.

About the authors

Andrey A. Kuznetsov

Omsk State Transport University

Author for correspondence.
Email: kuznetsovaa.omgups@gmail.com
ORCID iD: 0000-0002-1815-4679
SPIN-code: 5259-0531

Doctor of Technical Science, professor

Russian Federation, Omsk

Anton V. Ponomarev

Omsk State Transport University

Email: antonyswork@gmail.com
ORCID iD: 0000-0003-1468-5402
SPIN-code: 8927-5050

Candidate of Technical Science, Associate Professor

Russian Federation, Omsk

Anton V. Gorlov

Omsk State Transport University

Email: anton.gorlov@mail.ru
ORCID iD: 0000-0002-8413-6612
SPIN-code: 8845-5070

Postgraduate student

Russian Federation, Omsk

Maria A. Volchanina

Omsk State Transport University

Email: kuznetcova994@gmail.com
SPIN-code: 2130-4637

Candidate of Technical Science, engineer

Russian Federation, Omsk

References

  1. Ser’eznov AN, Stepanova LN, Murav’ev VV. Diagnostics of transport objects using acoustic emission method. Moscow: Mashinostroenie; 2004. (In Russ).
  2. Kuznecov AA, Volchanina MA, Gorlov AV. Comparison of acoustic signals and video images of high-voltage discharges in oil in problems of power transformer diagnostics. Izvestiya Transsiba. 2023;4(56):121–134. (In Russ). EDN: OZHBWL
  3. Volchanina MA, Kuznecov AA, Gorlov AV. Increasing the Reliability of Power Transformers Diagnosing under Seasonal Temperature Changes. Electrotechnical Systems and Complexes. 2021;4(53):33–38. (In Russ). doi: 10.18503/2311-8318-2021-4(53)-33-38
  4. Cheremisin VT, Kuznecov AA, Volchanina MA, Gorlov AV. Measuring the acoustic signals parameters of the defect simulator of power transformers. Transportation Systems and Technology. 2020;6(4):161–171. (In Russ). doi: 10.17816/transsyst202064161-171 EDN: DRLMYV
  5. Gorlov AV, Volchanina MA, Ponomarev AV, Kuznecov AA. Investigation of high-voltage discharge in oil on a simulator with a different set of defects. Modern Transportation Systems and Technologies. 2023;9(1):83–94. (In Russ). doi: 10.17816/transsyst20239183-94 EDN: WPBXRM
  6. Dyakonov VP. Wavelets. From Theory to Practice. Moscow: SOLON-Press; 2010. (In Russ).
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  8. Osipov DC, Dolgih NN, Dyuba EA. Analysis of non-sinusoidal non-stationary modes of electric networks based on the wavelet transformation. Yugra State University Bulletin. 2023;3:117–126. (In Russ). doi: 10.18822/byusu202303117-126
  9. Osipov DC. Development of criterion for choosing optimal type of mother wavelet in problem of calculating active and reactive power at power systems. Omsk Scientific Bulletin. 2018;6(162):71–75. (In Russ). doi: 10.25206/1813-8225-2018-162-71-75
  10. Stepanova LN, Ser’eznov AN, Kabanov SI. Ramazanov IS. Wavelet transform application for acoustic emission signals location. Kontrol. Diagnostika. 2017;10:18–26. (In Russ). doi: 10.14489/td.2017.10

Supplementary files

Supplementary Files
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1. JATS XML
2. Fig. 1. Example of the function under study

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3. Fig. 2. Three-dimensional representation of the scalegram of the reduced signal

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4. Fig. 3. Two-dimensional representation of the scalegram of the signal under study with the designation of time and scale slice lines линий временных и масштабных срезов

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5. Fig. 4. Slices of the scalegram at t = 150 ms, t = 350 ms and t = 450 ms

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6. Fig. 5. Time slices of the scalegram at three main scales

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7. Fig. 6. Acoustic signals recorded during the simulation of the defect «insulation breakdown»

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8. Fig. 7. Scalegrams of acoustic signals recorded during the simulation defect “insulation breakdown”

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9. Fig. 8. The original signal (a) and the time slice of its scalegram on a fixed scale (b)

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10. Fig. 9. Time slice of the scalegram of the studied signal fs(t) and reference slices of various defects

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11. Fig. 10. Dynamics of change in the coefficient Ks when comparing the studied signal with three reference ones

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Copyright (c) 2024 Kuznetsov A.A., Ponomarev A.V., Gorlov A.V., Volchanina M.A.

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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