1/2017 - 7 |
Vibration Based Broken Bar Detection in Induction Machine for Low Load ConditionsMATIC, D. , KANOVIC, Z. |
Extra paper information in |
Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science |
Download PDF (1,535 KB) | Citation | Downloads: 1,489 | Views: 3,175 |
Author keywords
motor, bar, vibration, fault, detection
References keywords
diagnosis(11), induction(10), rotor(8), detection(8), broken(8), fault(7), sanchez(6), pineda(6), motor(6), vibration(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2017-02-28
Volume 17, Issue 1, Year 2017, On page(s): 49 - 54
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.01007
Web of Science Accession Number: 000396335900007
SCOPUS ID: 85014214831
Abstract
A new method for broken bar detection, based on vibration signal analysis, is presented in this paper. While there are several methods for broken bar detection at low slip based on the current signal analysis, detection based on vibration signals attracts much less attention. In the current paper, detection of the broken bar was conducted by observing fault frequency content of the modulus of the analytical vibration signal. A broken bar feature is extracted from low frequency range even for low slip conditions. Although this method is successfully used for broken bar detection based on current signal analysis, it is important to verify the method when vibration signal is measured. Procedure is verified in a real industrial environment for induction motor of 3.15 MW. |
References | | | Cited By |
Web of Science® Times Cited: 8 [View]
View record in Web of Science® [View]
View Related Records® [View]
Updated 2 days ago
SCOPUS® Times Cited: 11
View record in SCOPUS® [Free preview]
View citations in SCOPUS® [Free preview]
[1] Classification and Authentication of Induction Motor Faults using Time and Frequency Feature Dependent Probabilistic Neural Network Model, Thakur, Arunava Kabiraj, Mukherjee, Alok, Kundu, Palash Kumar, Das, Arabinda, Journal of The Institution of Engineers (India): Series B, ISSN 2250-2106, Issue 3, Volume 104, 2023.
Digital Object Identifier: 10.1007/s40031-023-00872-5 [CrossRef]
[2] Current Park’s Vector Pattern Technique for Diagnosis of Broken Rotor Bars Fault in Saturated Induction Motor, Abdellah, Chaouch, Mama, Chouitek, Meflah Abderrahmane, Mohamed Reda, Mohammed, Belaid, Journal of Electrical Engineering & Technology, ISSN 1975-0102, Issue 4, Volume 18, 2023.
Digital Object Identifier: 10.1007/s42835-022-01342-6 [CrossRef]
[3] Electrical Signature Analysis for Condition Monitoring of Permanent Magnet Synchronous Machine, SALOMON, C. P., FERREIRA, C., LAMBERT-TORRES, G., TEIXEIRA, C. E., BORGES DA SILVA, L. E., SANTANA, W. C., BONALDI, E. L., DE OLIVEIRA, L. E. L., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 18, 2018.
Digital Object Identifier: 10.4316/AECE.2018.04011 [CrossRef] [Full text]
[4] Evaluation and Classification of Double Bar Breakages Through Three-Axes Vibration Sensor in Induction Motors, Goktas, Taner, IEEE Sensors Journal, ISSN 1530-437X, Issue 13, Volume 22, 2022.
Digital Object Identifier: 10.1109/JSEN.2022.3176059 [CrossRef]
[5] Investigation on Electromagnetic Performance of Induction Motor with Rotor Bar Faults considering Motor Current Signals, PARK, Y.-S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 20, 2020.
Digital Object Identifier: 10.4316/AECE.2020.04005 [CrossRef] [Full text]
[6] Broken Rotor Bar Fault Detection in Asynchronous Machines Using Vibration Analysis, Treml, A. E., Flauzino, R. A., Ramos, R. A., Brito, G. C., 2019 IEEE Power & Energy Society General Meeting (PESGM), ISBN 978-1-7281-1981-6, 2019.
Digital Object Identifier: 10.1109/PESGM40551.2019.8973827 [CrossRef]
[7] EMD and MCSA Improved via Hilbert Transform Analysis on Asynchronous Machines for Broken Bar Detection Using Vibration Analysis, Treml, A. E., Flauzino, R. A., Brito, G. C., 2019 IEEE Milan PowerTech, ISBN 978-1-5386-4722-6, 2019.
Digital Object Identifier: 10.1109/PTC.2019.8810643 [CrossRef]
[8] Incipient Broken Rotor Bar Fault Diagnosis Based on Extended Prony Spectral Analysis Technique, Zhuzhi, Jia, Hongyu, Zhu, Xuyang, Liu, Hang, Shang, 2018 37th Chinese Control Conference (CCC), ISBN 978-988-15639-5-8, 2018.
Digital Object Identifier: 10.23919/ChiCC.2018.8483365 [CrossRef]
Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.
Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.