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Open AccessArticle

Classification of Low Frequency Signals Emitted by Power Transformers Using Sensors and Machine Learning Methods

1
Department of Computer Science and Automatics, University of Bielsko-Biala, 43-309 Bielsko-Biala, Poland
2
Institute of Electric Power Engineering and Renewable Energy, Opole University of Technology, 45-758 Opole, Poland
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(22), 4909; https://doi.org/10.3390/s19224909 (registering DOI)
Received: 14 October 2019 / Revised: 3 November 2019 / Accepted: 8 November 2019 / Published: 10 November 2019
(This article belongs to the Special Issue Artificial Intelligence and Sensors)
This paper proposes a method of automatically detecting and classifying low frequency noise generated by power transformers using sensors and dedicated machine learning algorithms. The method applies the frequency spectra of sound pressure levels generated during operation by transformers in a real environment. The spectra frequency interval and its resolution are automatically optimized for the selected machine learning algorithm. Various machine learning algorithms, optimization techniques, and transformer types were researched: two indoor type transformers from Schneider Electric and two overhead type transformers manufactured by ABB. As a result, a method was proposed that provides a way in which inspections of working transformers (from background) and their type can be performed with an accuracy of over 97%, based on the generated low-frequency noise. The application of the proposed preprocessing stage increased the accuracy of this method by 10%. Additionally, machine learning algorithms were selected which offer robust solutions (with the highest accuracy) for noise classification. View Full-Text
Keywords: low-frequency sensor; power transformer; machine learning; low-frequency noise; classification low-frequency sensor; power transformer; machine learning; low-frequency noise; classification
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Jancarczyk, D.; Bernaś, M.; Boczar, T. Classification of Low Frequency Signals Emitted by Power Transformers Using Sensors and Machine Learning Methods. Sensors 2019, 19, 4909.

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