| bibtype |
J -
Journal Article
|
| ARLID |
0574864 |
| utime |
20240903114619.6 |
| mtime |
20230827235959.9 |
| SCOPUS |
85168780552 |
| WOS |
001055866700001 |
| DOI |
10.3390/s23167173 |
| title
(primary) (eng) |
Sensor Fusion for Power Line Sensitive Monitoring and Load State Estimation |
| specification |
| page_count |
19 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0258366 |
| ISSN |
1424-8220 |
| title
|
Sensors |
| volume_id |
23 |
| publisher |
|
|
| keyword |
soft sensing |
| keyword |
fault detection |
| keyword |
state estimation of electrical systems |
| keyword |
transformers |
| author
(primary) |
| ARLID |
cav_un_auth*0453494 |
| name1 |
Schimmack |
| name2 |
M. |
| country |
DE |
|
| author
|
| ARLID |
cav_un_auth*0101064 |
| name1 |
Belda |
| name2 |
Květoslav |
| institution |
UTIA-B |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0410019 |
| name1 |
Mercorelli |
| name2 |
P. |
| country |
DE |
| garant |
K |
|
| source |
|
| source |
|
| cas_special |
| project |
| project_id |
GC23-04676J |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0453493 |
|
| abstract
(eng) |
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. |
| result_subspec |
WOS |
| RIV |
JB |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20201 |
| reportyear |
2024 |
| num_of_auth |
3 |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0344798 |
| cooperation |
| ARLID |
cav_un_auth*0453496 |
| name |
Institute for Production Technology and Systems, Leuphana University of Lueneburg |
| country |
DE |
|
| confidential |
S |
| article_num |
7173 |
| mrcbC91 |
A |
| mrcbT16-e |
ENGINEERINGELECTRICALELECTRONIC|CHEMISTRYANALYTICAL|INSTRUMENTSINSTRUMENTATION |
| mrcbT16-j |
0.611 |
| mrcbT16-s |
0.786 |
| mrcbT16-D |
Q3 |
| mrcbT16-E |
Q2 |
| arlyear |
2023 |
| mrcbU14 |
85168780552 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
001055866700001 WOS |
| mrcbU63 |
cav_un_epca*0258366 Sensors 1424-8220 1424-8220 Roč. 23 č. 16 2023 MDPI ONLINE |
|