Hyppää sisältöön
    • Suomeksi
    • In English
  • Suomeksi
  • In English
  • Kirjaudu
Näytä aineisto 
  •   Etusivu
  • OSUVA
  • Artikkelit
  • Näytä aineisto
  •   Etusivu
  • OSUVA
  • Artikkelit
  • Näytä aineisto
JavaScript is disabled for your browser. Some features of this site may not work without it.

An Adaptive Denoising Algorithm for Online Condition Monitoring of High-Voltage Power Equipment

Hussain, Amjad; Ahmed, Zeeshan; Shafiq, Muhammad; Zaher, Ashraf; Rashid, Zeeshan; Lehtonen, Matti (2020-10-21)

 
Katso/Avaa
Artikkeli (1.657Mb)
Lataukset: 

URI
https://doi.org/10.1080/15325008.2020.1825554

Hussain, Amjad
Ahmed, Zeeshan
Shafiq, Muhammad
Zaher, Ashraf
Rashid, Zeeshan
Lehtonen, Matti
Taylor & Francis
21.10.2020
doi:10.1080/15325008.2020.1825554
Näytä kaikki kuvailutiedot
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe202103167496

Kuvaus

vertaisarvioitu
©2020 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Electric Power Components and Systems on 21 Oct 2020, available online: http://www.tandfonline.com/10.1080/15325008.2020.1825554
Tiivistelmä
Partial discharge (PD) diagnostic is an effective tool for condition monitoring of the high-voltage equipment that provides an updated status of the dielectric insulation of the components. Reliability of the diagnostics depends on the quality of the PD measurement techniques and the processing of the measured PD data. The online measured data suffer from various inaccuracies caused by external noise from various sources such as power electronic equipment, radio broadband signals and wireless communication, etc. Therefore, extraction of useful data from the on-site measurements is still a challenge. This article presents a discrete wavelet transform (DWT)-based adaptive denoising algorithm and evaluates its performance. Various decisive steps in applying DWT-based denoising on any signal, including selection of mother wavelet, number of levels in multiresolution decomposition and criteria for reconstruction of the denoised signals are taken by the proposed algorithm and vary from one signal to another without a human intervention. Hence, the proposed technique is adaptive. The proposed solution can enhance the accuracy of the PD diagnostic for HV power components.
Kokoelmat
  • Artikkelit [1603]
https://osuva.uwasa.fi
Ota yhteyttä | Lähetä palautetta | Tietosuoja | Saavutettavuusseloste
 

 

Tämä kokoelma

TekijäNimekeAsiasanaYksikkö / TiedekuntaOppiaineJulkaisuaikaKokoelmat

Omat tiedot

Kirjaudu sisäänRekisteröidy
https://osuva.uwasa.fi
Ota yhteyttä | Lähetä palautetta | Tietosuoja | Saavutettavuusseloste