Impulse signals classification using one dimensional convolutional neural network

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F20%3A43960437" target="_blank" >RIV/49777513:23220/20:43960437 - isvavai.cz</a>

Výsledek na webu

<a href="http://iris.elf.stuba.sk/JEEEC/data/pdf/6_120-04.pdf" target="_blank" >http://iris.elf.stuba.sk/JEEEC/data/pdf/6_120-04.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2478/jee-2020-0054" target="_blank" >10.2478/jee-2020-0054</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Impulse signals classification using one dimensional convolutional neural network

Popis výsledku v původním jazyce

The main purpose of this work is to propose a modern one-dimensional convolutional neural network (1 D CNN) configurations for distinguishing separate PD impulses from different types of PD sources while the parameters of these sources are changed. Three PD sources were built for signal generation: corona discharge, discharge in a void, and surface discharge. The reason for using separate PD impulses for classification is to develop a universal tool with the ability to recognize an insulation defects by analysing very few events in the insulation in a short range of time. Additionally, we found the optimal sample rates for the data acquisition for these network configurations. The necessity of signal filtering was also tested. The following configurations of a neural network were proposed: configuration for classification raw PD impulses; configuration for classification of PD impulses represented by power spectral density, for both filtered and unfiltered variants.

Název v anglickém jazyce

Impulse signals classification using one dimensional convolutional neural network

Popis výsledku anglicky

The main purpose of this work is to propose a modern one-dimensional convolutional neural network (1 D CNN) configurations for distinguishing separate PD impulses from different types of PD sources while the parameters of these sources are changed. Three PD sources were built for signal generation: corona discharge, discharge in a void, and surface discharge. The reason for using separate PD impulses for classification is to develop a universal tool with the ability to recognize an insulation defects by analysing very few events in the insulation in a short range of time. Additionally, we found the optimal sample rates for the data acquisition for these network configurations. The necessity of signal filtering was also tested. The following configurations of a neural network were proposed: configuration for classification raw PD impulses; configuration for classification of PD impulses represented by power spectral density, for both filtered and unfiltered variants.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

Journal of ELECTRICAL ENGINEERING

ISSN

1335-3632

e-ISSN

—

Svazek periodika

71

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

9

Strana od-do

397-405

Kód UT WoS článku

000604437400004

EID výsledku v databázi Scopus

2-s2.0-85098978061