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Abstract

The paper presents the results of the application of the hierarchical clustering methods for the classification of the acoustic emission (AE) signals generated by eight basic forms of partial discharges (PD), which can occur in paper-oil insulation of power transformers. Based on the registered AE signals from the particular PD forms, using a frequency descriptor in the form of the power spectral density (PSD) of the signal, their representation in the form of the set of points on plane XY was created. Next, these sets were subjected to analysis using research algorithms consisting of selected clustering methods. Based on the suggested numeric performance indicators, the analysis of the degree of reproduction of the actual distribution of points showing the particular time waveforms of the AE signals from eight adopted PD forms (PD classes) in the obtained clusters was carried out. As a result of the analyses carried out, the clustering algorithms of the highest effectiveness in the identification of all eight PD classes, classified simultaneously, where indicated. Within the research carried out, an attempt to draw general conclusions as to the selection of the most effective hierarchical clustering method studied and the similarity function to be used for classification of the selected basic PD forms.
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Bibliography

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Authors and Affiliations

Sebastian Borucki
1
Jacek Łuczak
1
Marcin Lorenc
1

  1. Opole University of Technology, Opole, Poland
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Abstract

The subject presented in this paper refers to measurements and assessment of the corrected sound pressure level values (noise) occurring around a medium-power transformer. The paper presents the values of noise accompanying the operation of the power object before and after its modernization, which consisted in repeated core pressing and replacement of the cooling system. The main aim of the research work was the assessment of the influence of the repair work on the noise level emitted into the environment.

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Authors and Affiliations

Sebastian Borucki
Andrzej Cichoń
Tomasz Boczar
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Abstract

On-load tap changers (OLTC) are some of the main transformer elements that make voltage adjustment in a power network possible. Their failures often cause shutdowns of distribution transformers. The paper presents research work aimed at the assessment of the technical condition of OLTCs by the acoustic emission method (EA). This method makes the OLTC diagnosis possible without the need of disconnecting the transformer from the system. The measurements were taken in laboratory conditions. The influence on the operation non-concurrence of the power tap changer contacts on the AE registered signals has been investigated. The signals registered were subjected to analyses in the time and time-frequency domains. The result analysis in the time domain was carried out using the Hilbert transform and calculating characteristic times for the particular runs. A short-time Fourier transform was used for the assessment of results in the time-frequency domain.

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Authors and Affiliations

Andrzej Cichoń
Sebastian Borucki
Tomasz Boczar
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Abstract

An acoustic emission method (AE) is widespread and often applied for partial discharge (PD) diagnostics, mainly due to its ease of application as well as noninvasiveness and relatively high sensitivity. This paper presents comparative analysis of AE signals measurement results archived under laboratory conditions as well as on-site actual AE signals generated by inside PDs in electrical power transformer during its normal service. Three different PD model sources are applied for laboratory research: point to point, multipoint to plate and surface type. A typical measuring set up commonly used for on-site transformer PD diagnostics is provided for the laboratory tasks: piezoelectric joint transducer, preamplifier, amplifier and measuring PC interface. During the on-site research there are three measuring tracks applied simultaneously. Time domain, time-frequency domain and statistical tools are used for registered AE signals analysis. A number of descriptors are proposed as a result of the analysis. In the paper, at- tempt of AE signals descriptors, archived under laboratory condition application possibilities for on-site PD diagnostics of power transformers during normal service is made.
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Authors and Affiliations

Michał Kunicki
Andrzej Cichoń
Sebastian Borucki
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Abstract

The article presents the results concerning the use of clustering methods to identify signals of acoustic emission (AE) generated by partial discharge (PD) in oil-paper insulation. The conducted testing featured qualitative analysis of the following clustering methods: single linkage, complete linkage, average linkage, centroid linkage and Ward linkage. The purpose of the analysis was to search the tested series of AE signal measurements, deriving from three various PD forms, for elements of grouping (clusters), which are most similar to one another and maximally different than in other groups in terms of a specific feature or adopted criteria. Then, the conducted clustering was used as a basis for attempting to assess the effectiveness of identification of particular PD forms that modelled exemplary defects of the power transformer’s oil-paper insulation system. The relevant analyses and simulations were conducted using the Matlab estimation environment and the clustering procedures available in it. The conducted tests featured analyses of the results of the series of measurements of acoustic emissions generated by the basic PD forms, which were obtained in laboratory conditions using spark gap systems that modelled the defects of the power transformer’s oil-paper insulation.
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Authors and Affiliations

Sebastian Borucki
Jacek Łuczak
Dariusz Zmarzły

Authors and Affiliations

Krzysztof Klimaszewski
Sebastian Borucki
Jacek Łuczak
Dariusz Zmarzły
Michał Kunicki
Andrzej Cichoń
Franciszek Witos
Czesław Leśnik
Dariusz Pleban
Milan Timko
Tomasz Rogala
Piotr Serafin
Tadeusz Gudra
Jerzy Filipiak
Dariusz Banasiak
Krzysztof Herman
Krzysztof Opieliński
Tomasz Hejczyk
Krzysztof Jasek
Mateusz Pasternak
Michał Grabka
Witold Kardyś
Andrzej Milewski
Adam Kawalec
Marta Okoń-Fąfara
Bartłomiej Fąfara
Aneta Olszewska
Piotr Pruchnicki
Marcin Wrzosek
Józef Nicpoń
Przemysław Podgórski
Tadeusz Pustelny
Marcin Szugajew
Olga Stec
Grzegorz Szerszeń
Daria Wotzka
Agnieszka Boruń
Adam Bald
Marzena Dzida
Sylwia Jężak
Monika Geppert-Rybczyńska
Katarzyna Kaczmarek
Tomasz Hornowski
Arkadiusz Józefczak
M. Kubovčíková
A. Skumiel
Z. Rozynek
M. Timko
Peter Kopcansky
Bogumił Linde
Vyacheslav N. Verveyko
Marina V. Verveyko
Darya V. Verveyko
Andrey Yu. Verisokin
Nikita S. Chebrov
Witold Mikulski
Danuta Augustyńska
Bożena Smagowska

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