Harmonics Signal Feature Extraction Techniques: A Review

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10252680" target="_blank" >RIV/61989100:27240/23:10252680 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2227-7390/11/8/1877" target="_blank" >https://www.mdpi.com/2227-7390/11/8/1877</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/math11081877" target="_blank" >10.3390/math11081877</a>

Result language

angličtina

Original language name

Harmonics Signal Feature Extraction Techniques: A Review

Original language description

Harmonic estimation is essential for mitigating or suppressing harmonic distortions in power systems. The most important idea is that spectrum analysis, waveform estimation, harmonic source classification, source location, the determination of harmonic source contributions, data clustering, and filter-based harmonic elimination capacity are also considered. The feature extraction method is a fundamental component of the optimization that improves the effectiveness of the Harmonic Mitigation method. In this study, techniques to extract fundamental frequencies and harmonics in the frequency domain, the time domain, and the spatial domain include 67 literature reviews and an overall assessment. The combinations of signal processing with artificial intelligence (AI) techniques are also reviewed and evaluated in this study. The benefit of the feature extraction methods is that the analysis extracts the powerful basic information of the feedback signals from the sensors with the most redundancy, ensuring the highest efficiency for the next sampling process of algorithms. This study provides an overview of the fundamental frequency and harmonic extraction methods of recent years, an analysis, and a presentation of their advantages and limitations.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20201 - Electrical and electronic engineering

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Mathematics

ISSN

2227-7390

e-ISSN

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Volume of the periodical

11

Issue of the periodical within the volume

8

Country of publishing house

CH - SWITZERLAND

Number of pages

36

Pages from-to

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UT code for WoS article

000979064100001

EID of the result in the Scopus database

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