Diagnosis of eccentricity and broken rotor bar related faults of induction motor by means of motor current signature analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU114253" target="_blank" >RIV/00216305:26220/15:PU114253 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/7161130?section=abstract" target="_blank" >https://ieeexplore.ieee.org/document/7161130?section=abstract</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EPE.2015.7161130" target="_blank" >10.1109/EPE.2015.7161130</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Diagnosis of eccentricity and broken rotor bar related faults of induction motor by means of motor current signature analysis

Popis výsledku v původním jazyce

Detection of faults in electrical motors is very important for avoiding unpredicted failures of the machines. Early detection and diagnosis of faults that may occur are desirable to ensure that operational effectiveness of an induction motor can be improved. In this paper, faults detection and classification using motor current signature analysis (MCSA) are presented. A series of simulations using the models of three phase cage induction motor is performed in different fault conditions, such as static, dynamic and mixed eccentricity and broken rotor bars. Designed models were implemented with the help of finite element method to provide data that makes it possible to diagnose presence of any type of faults, as well as to analyze obtained and calculated results. Models were designed on the basis of characteristics and parameters of real motor. The results are illustrated in the form of graphs and tables that make visible illustration for effectiveness of the used diagnosis method.

Název v anglickém jazyce

Diagnosis of eccentricity and broken rotor bar related faults of induction motor by means of motor current signature analysis

Popis výsledku anglicky

Detection of faults in electrical motors is very important for avoiding unpredicted failures of the machines. Early detection and diagnosis of faults that may occur are desirable to ensure that operational effectiveness of an induction motor can be improved. In this paper, faults detection and classification using motor current signature analysis (MCSA) are presented. A series of simulations using the models of three phase cage induction motor is performed in different fault conditions, such as static, dynamic and mixed eccentricity and broken rotor bars. Designed models were implemented with the help of finite element method to provide data that makes it possible to diagnose presence of any type of faults, as well as to analyze obtained and calculated results. Models were designed on the basis of characteristics and parameters of real motor. The results are illustrated in the form of graphs and tables that make visible illustration for effectiveness of the used diagnosis method.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/LO1210" target="_blank" >LO1210: Energie v podmínkách udržitelného rozvoje (EN-PUR)</a><br>

Návaznosti

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

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 2015 16th International Scientific Conference on Electric Power Engineering (EPE)

ISBN

978-1-4673-6787-5

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

682-686

Název nakladatele

VSB – Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science

Místo vydání

Ostrava, Czech Republic

Místo konání akce

Kouty nad Desnou

Datum konání akce

20. 5. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000377548600136