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Sensor Fusion for Power Line Sensitive Monitoring and Load State Estimation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F23%3A00574864" target="_blank" >RIV/67985556:_____/23:00574864 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.mdpi.com/1424-8220/23/16/7173" target="_blank" >https://www.mdpi.com/1424-8220/23/16/7173</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/s23167173" target="_blank" >10.3390/s23167173</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Sensor Fusion for Power Line Sensitive Monitoring and Load State Estimation

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

    <a href="/en/project/GC23-04676J" target="_blank" >GC23-04676J: Controllable gripping mechanics: Modelling, control and experiments</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Sensors

  • ISSN

    1424-8220

  • e-ISSN

    1424-8220

  • Volume of the periodical

    23

  • Issue of the periodical within the volume

    16

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    19

  • Pages from-to

    7173

  • UT code for WoS article

    001055866700001

  • EID of the result in the Scopus database

    2-s2.0-85168780552