Electric Equipment Diagnosis based on Wavelet Analysis

Dades bibliogràfiques
Parent link:European Physical Journal Web of Conferences (EPJ Web of Conferences)
Vol. 110 : Thermophysical Basis of Energy Technologies.— 2016.— [01059, 4 p.]
Autor corporatiu: Национальный исследовательский Томский политехнический университет
Altres autors: Stavitsky S. A. Sergey, Palukhin N. E. Nikolay, Kobenko Yu. V. Yury Viktorovich, Riabova E. S. Elena
Sumari:Title screen
Due to electric equipment development and complication it is necessary to have a precise and intense diagnosis. Nowadays there are two basic ways of diagnosis: analog signal processing and digital signal processing. The latter is more preferable. The basic ways of digital signal processing (Fourier transform and Fast Fourier transform) include one of the modern methods based on wavelet transform. This research is dedicated to analyzing characteristic features and advantages of wavelet transform. This article shows the ways of using wavelet analysis and the process of test signal converting. In order to carry out this analysis, computer software Mathcad was used and 2D wavelet spectrum for a complex function was created.
Idioma:anglès
Publicat: 2016
Matèries:
Accés en línia:http://dx.doi.org/10.1051/epjconf/201611001059
http://earchive.tpu.ru/handle/11683/33395
Format: Electrònic Capítol de llibre
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=647718
Descripció
Sumari:Title screen
Due to electric equipment development and complication it is necessary to have a precise and intense diagnosis. Nowadays there are two basic ways of diagnosis: analog signal processing and digital signal processing. The latter is more preferable. The basic ways of digital signal processing (Fourier transform and Fast Fourier transform) include one of the modern methods based on wavelet transform. This research is dedicated to analyzing characteristic features and advantages of wavelet transform. This article shows the ways of using wavelet analysis and the process of test signal converting. In order to carry out this analysis, computer software Mathcad was used and 2D wavelet spectrum for a complex function was created.
DOI:10.1051/epjconf/201611001059