Issue |
ITM Web Conf.
Volume 49, 2022
International Conference on Applied Mathematics and Numerical Methods – fourth edition (ICAMNM 2022)
|
|
---|---|---|
Article Number | 01006 | |
Number of page(s) | 13 | |
Section | Applied Mathematics | |
DOI | https://doi.org/10.1051/itmconf/20224901006 | |
Published online | 16 November 2022 |
Optimized use of Wavelet Packet Trees for the analysis of electrical waveforms
1
Department of Computer Science and IT, University of Craiova, DJ 200440, ROMANIA
2
Department of Electrical Engineering, Energetic and Aerospatial, University of Craiova, Craiova, DJ 200440, ROMANIA
* e-mail: ileana_nicolae@hotmail.com
** e-mail: npetremarian@yahoo.com
*** e-mail: danny_cr94@yahoo.com
**** e-mail: gheorghe.ilie.d8c@student.ucv.ro
Wavelet packet trees represent a topic which grows in popularity when it comes to analysis of electrical waveforms. It allows for time-frequency analysis providing information on narrower ranges of frequency (as compared to the faster Discrete Wavelet Decomposition), but the computational resources are significantly greater than that involved in other types of wavelet-based analysis. In order to allow for this type of analysis to be usable in real-time applications, that is – to reduce the runtime, original algorithms were conceived and tested. In the first part of this work, previously implemented algorithms are briefly described, along with their pros and cons. Afterward, a new runtime optimization algorithm is proposed. Details on data structures, workflow, tests and study of errors are provided. This algorithm diminishes with up to 59% the runtime required by the application of the superposition theorem in order to evaluate the contribution of clustered harmonics using WPT.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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