| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | IEEE Transactions on Industry Applications (Q1) | ||
| Dergi ISSN | 0093-9994 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Türkçe | Basım Tarihi | 03-2026 |
| Cilt / Sayı / Sayfa | 62 / 2 / 2468–2477 | DOI | 10.1109/TIA.2025.3601094 |
| Makale Linki | https://doi.org/10.1109/tia.2025.3601094 | ||
| UAK Araştırma Alanları |
İşaret İşleme
Kontrol Teorisi ve Uygulamaları
Elektrik Enerjisi ve Güç Sistemleri
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| Özet |
| In this paper, a Least Squares (LS) based harmonic and frequency estimation method is proposed to analyze power signals with rapidly changing characteristics in time such as Electric Arc Furnaces (EAFs) as an alternative to the classical Discrete Fourier Transform (DFT)-based methods. Although DFT based harmonic analysis methods provide fast and accurate solutions for stationary signals, solutions become less accurate under frequency deviations especially when the signal is sampled at low rates. This paper presents an approach which can accurately calculate the harmonic components of the signals, when the fundamental periods cannot be expressed as integer numbers due to the low sampling rate. One of the outstanding parts of the proposed approach is that, it is possible to increase the performance of harmonic and interharmonic estimation by increasing the performance of frequency estimation with … |
| Anahtar Kelimeler |
| Brute-force search | discrete fourier transform (DFT) | electric arc furnace (EAF) | golden-section search | gradient descent | Least Squares (LS) | parallel programming | power system harmonics | spectral leakage | unconstrained optimization |
| Atıf Sayıları | |
| Web of Science | 1 |
| Scopus | 1 |
| Google Scholar | 3 |
| Dergi Adı | IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS |
| Yayıncı | Institute of Electrical and Electronics Engineers Inc. |
| Açık Erişim | Hayır |
| ISSN | 0093-9994 |
| E-ISSN | 1939-9367 |
| CiteScore | 10,1 |
| SJR | 1,626 |
| SNIP | 1,694 |