Using artificial intelligence to determine the type of rotary machine fault
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F18%3APU134096" target="_blank" >RIV/00216305:26210/18:PU134096 - isvavai.cz</a>
Result on the web
<a href="https://mendel-journal.org/index.php/mendel/article/view/10" target="_blank" >https://mendel-journal.org/index.php/mendel/article/view/10</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.13164/2018.2.049" target="_blank" >10.13164/2018.2.049</a>
Alternative languages
Result language
angličtina
Original language name
Using artificial intelligence to determine the type of rotary machine fault
Original language description
The article deals with the possibility of using machine learning in vibrodiagnostics to determine the type of fault of rotating machine. The data source is real measured data from the vibrodiagnostic model. This model allows simulation of some types of faults. The data is then processed and reduced for the use of the Matlab Classification learner app, which creates a model for recognizing faults. The model is ultimately tested on new samples of data. The aim of the article is to verify the ability to recognize similarly rotary machine faults from real measurements in the time domain.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Mendel Journal series
ISSN
1803-3814
e-ISSN
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Volume of the periodical
24
Issue of the periodical within the volume
2
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
6
Pages from-to
49-54
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85071994510