Localisation of failure in the switchboard room using an artificial neural network

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F13%3A00216962" target="_blank" >RIV/68407700:21110/13:00216962 - isvavai.cz</a>

Result on the web

<a href="http://www.energyspectrum.net" target="_blank" >http://www.energyspectrum.net</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Localisation of failure in the switchboard room using an artificial neural network

Original language description

The article describes application of two types of artificial neural networks for localisation of failure in the substation. The networks are implemented in the substation control system, are robust against image noise and act by signalling conditions ofthe switches and functioning of the switchboard element protections.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JE - Non-nuclear power engineering, energy consumption and utilization

OECD FORD branch

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Project

<a href="/en/project/2A-1TP1%2F051" target="_blank" >2A-1TP1/051: Reduction of building's operating energy consumption by intelligent management systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2013

Confidentiality

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

Name of the periodical

EnergySpectrum

ISSN

1214-7044

e-ISSN

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Volume of the periodical

2013

Issue of the periodical within the volume

8

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

4

Pages from-to

1-4

UT code for WoS article

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EID of the result in the Scopus database

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