Adaptive Architecture for Fault Diagnosis of Rotating Machinery

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F21%3A43896293" target="_blank" >RIV/44555601:13440/21:43896293 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.researchgate.net/publication/349992022_Adaptive_Architecture_for_Fault_Diagnosis_of_Rotating_Machinery" target="_blank" >https://www.researchgate.net/publication/349992022_Adaptive_Architecture_for_Fault_Diagnosis_of_Rotating_Machinery</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-75078-7_5" target="_blank" >10.1007/978-3-030-75078-7_5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Adaptive Architecture for Fault Diagnosis of Rotating Machinery

Popis výsledku v původním jazyce

In this work, an adaptive architecture has been implemented for rotating machinery fault diagnoses of an industrial machine, where the input data used in this work has been taken from alternative current motors. The data sets for training and testing were recorded with a vibrometer. A dynamic neural architecture is previously trained with the training data set. Furthermore, an online monitoring system is implemented using the testing data set to detect abnormal behaviour of the monitored signal which can lead to a failure of the industrial machine. For the evaluation of the architecture, tests are performed using the obtained signal from different vibration tests.

Název v anglickém jazyce

Adaptive Architecture for Fault Diagnosis of Rotating Machinery

Popis výsledku anglicky

In this work, an adaptive architecture has been implemented for rotating machinery fault diagnoses of an industrial machine, where the input data used in this work has been taken from alternative current motors. The data sets for training and testing were recorded with a vibrometer. A dynamic neural architecture is previously trained with the training data set. Furthermore, an online monitoring system is implemented using the testing data set to detect abnormal behaviour of the monitored signal which can lead to a failure of the industrial machine. For the evaluation of the architecture, tests are performed using the obtained signal from different vibration tests.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 35th International Conference on Advanced Information Networking and Applications (AINA-2021), Volume 1

ISBN

978-3-030-75077-0

ISSN

2367-3370

e-ISSN

2367-3370

Počet stran výsledku

11

Strana od-do

41-51

Název nakladatele

Springer Science and Business Media Deutschland GmbH

Místo vydání

Toronto

Místo konání akce

Toronto, Canada

Datum konání akce

12. 5. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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