Diagnostics of aircraft turbine engine using artificial neural networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00010669%3A_____%2F14%3A%230001729" target="_blank" >RIV/00010669:_____/14:#0001729 - isvavai.cz</a>

Result on the web

<a href="http://www.czaerospace.eu/en/2014-01-49.html" target="_blank" >http://www.czaerospace.eu/en/2014-01-49.html</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Diagnostics of aircraft turbine engine using artificial neural networks

Original language description

The paper deals with composition of an Artificial Neural Network (ANN) applied to technical diagnostics of a small aircraft turboprop engine. A value of thermodynamic parameters describing operating range of the engine are used as an input data further processed to allow optimal training and validation of the Artificial neural network used in diagnostic system of a small aircraft engine. The diagnostic system can be extended by the wear monitoring of the turbine engine parts.

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

JT - Propulsion, engines and fuels

OECD FORD branch

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Project

<a href="/en/project/7E12035" target="_blank" >7E12035: Efficient Systems and Propulsion for Small Aircraft</a><br>

Continuities

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

Publication year

2014

Confidentiality

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

Name of the periodical

Czech Aerospace Proceedings / Letecký zpravodaj

ISSN

1211-877X

e-ISSN

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Volume of the periodical

1/2014

Issue of the periodical within the volume

1

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

6

Pages from-to

20-25

UT code for WoS article

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EID of the result in the Scopus database

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