Fast and Accurate Transient Detection in EAF Current Signals via Statistical Analysis
Yazarlar (3)
Dr. Öğr. Üyesi Erhan SEZGİN Kafkas Üniversitesi, Türkiye
Ebrahim Balouji
Ecophi Ab, İsveç
Ecophi Ab, İsveç
Özgül Salor
Gazi Üniversitesi, Türkiye
Gazi Üniversitesi, Türkiye
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| DOI Numarası | 10.1109/IAS62731.2025.11061670 | ||
| Kongre Adı | 2025 IEEE Industry Applications Society Annual Meeting (IAS) | ||
| Kongre Tarihi | 15-06-2025 / | ||
| Basıldığı Ülke | Tayvan | Basıldığı Şehir | Taıpeı |
| Bildiri Linki | https://doi.org/10.1109/ias62731.2025.11061670 | ||
| UAK Araştırma Alanları |
İşaret İşleme
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| Özet |
| Electric Arc Furnaces (EAFs) are key installations of modern steel production due to their operational flexibility, environmental benefits, and energy efficiency. However, nature of the EAF operation is highly dynamic and stochastic due to the fact that electric arcs are used to melt the metal scrap with various compositions specific to each tap-to-tap time of the operation. Although control systems are used to stabilize the arc length and hence the EAF currents, nature of the operation often causes current transients which negatively impact electrode life, energy efficiency, and power quality. The research work in this paper shows that even if the high frequency components are removed by the analogue anti-aliasing filters of the signal conditioning circuits, traces of the transients exist in the sampled signals of the EAF currents. A novel method is proposed to detect and label transient components of EAF currents based on … |
| Anahtar Kelimeler |
| EAF currents | Electric Arc Furnace (EAF) | Power quality | Transient analysis |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 1 |
| Google Scholar | 1 |