Title:	Comparison of One-Dimensional and Two-Dimensional Reference Signal Representation for Insulation Aging State Recognition
Authors:	Olkhovskiy, Mikhail Müllerová, Eva Martínek, Petr
Citation:	OLKHOVSKIY, M. MÜLLEROVÁ, E. MARTÍNEK, P. Comparison of One-Dimensional and Two-Dimensional Reference Signal Representation for Insulation Aging State Recognition. In Proceedings of the 2022 International Conference on Diagnostics in Electrical Engineering (Diagnostika) : CDEE 2022. Pilsen: University of West Bohemia in Pilsen, 2022. s. nestránkováno. ISBN: 978-1-66548-082-6
Issue Date:	2022
Publisher:	University of West Bohemia in Pilsen
Document type:	konferenční příspěvek ConferenceObject
URI:	2-s2.0-85141397372 http://hdl.handle.net/11025/50534
ISBN:	978-1-66548-082-6
Keywords in different language:	one-dimensional neural networks;convolutional networks;reference signal processing;signal analysis;cable insulation;classification accuracy
Abstract in different language:	This paper compares the performance of one-dimensional and two-dimensional convolutional neural networks in the task of analyzing a reference signal while determining the degradation level of single-core polymer-insulated cable. In this work was designed the set of reference signals and several forms of representing of these signals in the form of one-dimensional and two-dimensional tensors. Then, an experimental determination of the most effective version of the reference signal is carried out in terms of classification accuracy and the most effective form of representation of this signal was found, as well as most efficient type of neural network.
Rights:	© IEEE
Appears in Collections:	OBD

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