Počet záznamů: 1
Sensor Fusion for Power Line Sensitive Monitoring and Load State Estimation
- 1.
SYSNO ASEP 0574864 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Sensor Fusion for Power Line Sensitive Monitoring and Load State Estimation Tvůrce(i) Schimmack, M. (DE)
Belda, Květoslav (UTIA-B) RID, ORCID
Mercorelli, P. (DE)Celkový počet autorů 3 Číslo článku 7173 Zdroj.dok. Sensors. - : MDPI
Roč. 23, č. 16 (2023)Poč.str. 19 s. Forma vydání Online - E Jazyk dok. eng - angličtina Země vyd. CH - Švýcarsko Klíč. slova soft sensing ; fault detection ; state estimation of electrical systems ; transformers Vědní obor RIV JB - Senzory, čidla, měření a regulace Obor OECD Electrical and electronic engineering CEP GC23-04676J GA ČR - Grantová agentura ČR Způsob publikování Open access Institucionální podpora UTIA-B - RVO:67985556 UT WOS 001055866700001 EID SCOPUS 85168780552 DOI 10.3390/s23167173 Anotace This paper deals with a specific approach to fault detection in transformer systems using the extended Kalman filter (EKF). Specific faults are investigated in power lines where a transformer is connected and only the primary electrical quantities, input voltage, and current are measured. Faults can occur in either the primary or secondary winding of the transformer. Two EKFs are proposed for fault detection. The first EKF estimates the voltage, current, and electrical load resistance of the secondary winding using measurements of the primary winding. The model of the transformer used is known as mutual inductance. For a short circuit in the secondary winding, the observer generates a signal indicating a fault. The second EKF is designed for harmonic detection and estimates the amplitude and frequency of the primary winding voltage. This contribution focuses on mathematical methods useful for galvanic decoupled soft sensing and fault detection. Moreover, the contribution emphasises how EKF observers play a key role in the context of sensor fusion, which is characterised by merging multiple lines of information in an accurate conceptualisation of data and their reconciliation with the measurements. Simulations demonstrate the efficiency of the fault detection using EKF observers. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2024 Elektronická adresa https://www.mdpi.com/1424-8220/23/16/7173
Počet záznamů: 1