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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Graphical User Interface Aided Online Fault Diagnosis of Electric Motor - DC motor case study

POSTALCIOGLU OZGEN, S. See more information about POSTALCIOGLU OZGEN, S. on SCOPUS See more information about POSTALCIOGLU OZGEN, S. on IEEExplore See more information about POSTALCIOGLU OZGEN, S. on Web of Science
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Download PDF pdficon (528 KB) | Citation | Downloads: 1,116 | Views: 5,664

Author keywords
wavelet analysis, fuzzy logic control, fault diagnosis, graphical user interface

References keywords
fault(14), control(10), tolerant(8), systems(5), detection(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2009-10-26
Volume 9, Issue 3, Year 2009, On page(s): 12 - 17
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2009.03003
Web of Science Accession Number: 000271872000003
SCOPUS ID: 77954697523

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This paper contains graphical user interface (GUI) aided online fault diagnosis for DC motor. The aim of the research is to prevent system faults. Online fault diagnosis has been studied. Design of fault diagnosis has two main levels: Level 1 comprises a traditional control loop; Level 2 contains knowledge based fault diagnosis. Fault diagnosis technique contains feature extraction module, feature cluster module and fault decision module. Wavelet analysis has been used for the feature extraction module. For the feature cluster module, fuzzy cluster has been applied. Faults effects are examined on the system using statistical analysis. In this study Fault Diagnosis technique obtains fault detection, identification and halting the system. In the meantime graphical user interface (GUI) is opened when fault is detected. GUI shows the measurement value, fault time and fault type. This property gives some information about the system to the personnel. As seen from the simulation results, faults can be detected and identified as soon as fault appears. In summary, if the system has a fault diagnosis structure, system dangerous situations can be avoided.

References | Cited By  «-- Click to see who has cited this paper

[1] Blanke M., Marcel S., Wu E.N. (2001), "Concepts and methods in fault tolerant control", Proceedings of the american control conference; 2606-2620
[CrossRef] [SCOPUS Times Cited 210]

[2], (2007), "Fault detection and isolation and fault tolerant control"

[3] Blanke, M., Kinnaert, M., Lunze, J., Staroswiecki, M., (2006) "Diagnosis and Fault-Tolerant Control", 2nd ed., XIX, 672 p. 270 illus., Hardcover ISBN: 978-3-540-35652-3.

[4] Palma L.B., Coito F.V., Silva R.N. (2003), "Fault Diagnosis based on Black-Box Models with Application to a Liquid-Level System", Emerging Technologies and Factory Automation,. Proceedings. ETFA '03. IEEE Conference 2: 739-746
[CrossRef] [SCOPUS Times Cited 6]

[5] Negrea M. D. (2006), "Electromagnetic flux monitoring for detecting faults in electrical machines", Doctoral Dissertation, Helsinki University of Technology Department of Electrical and Communications Engineering; 1-137.

[6] Zhihan X., (2002), "Design of Knowledge-based Fault Detection and Identification for Dynamical Systems", Master of Science, University of Alberta, 1-53.

[7] Huo Y., Ioannou P. A., Mirmirani M., (2002) "Fault- Tolerant Control and Reconfiguration for High Performance Aircraft Review", CATT Technical Report 01-11-01.

[8] Kanev, S. (2004), "Robust fault tolerant control", Ph.D. thesis, University of Twente , The Netherlands; 1-20.

[9] Clements, N.S. (2003), "Fault Tolerant Control of Complex Dynamical Systems", Doctor of Philosophy, Georgia Institute of Technology; 1-37.

[10] Iwan Tabakow, (2007) "Using Place Invariants and Test Point Placement to Isolate Faults in Discrete Event Systems", Journal of Universal Computer Science, vol. 13, no. 2, 224-243 .

[11] Postalcioglu S., Erkan K., Bolat E. (2006), "Discrete Wavelet Analysis Based Fault Detection", Wseas Transactions on Systems, Issue 10, Volume 5: 2391-2398.

[12] Chien-Hsing Lee, Yaw-Juen Wang, and Wen-Liang Huang, (2000). "A Literature Survey of Wavelets in Power Engineering Applications", Proc. Natl. Sci. Counc. ROC(A) Vol. 24, No. 4,. pp. 249-258

[13] R. Supangat, N. Ertugrul, W.L. Soong, D.A. Gray, C. Hansen and J. Grieger, (2005), "Broken Rotor Bar Fault Detection in Induction Motors Using Starting Current Analysis", European Power Electronics Conference, pp:1-10. [PermaLink]

[14] (2009)

[15] Rezas, A. M., (October 19, 1999), "Wavelet Characteristics", White Paper, Spire Lab., UWM

[16] Patton R. J., Uppal F. J., Lopez-Toribio C. J. "Soft computing approaches to fault diagnosis for dynamic systems", survey.

[17] Lee, C., Hanna, D.M., Haskell, R. E., Alena, R. L., (2004). "Using Fuzzy Clustering for Real-time Space Flight Safety", International Conference on Artificial Intelligence [PermaLink]

[18] Postalcioglu, S., Erkan, K., (2009) "Soft Computing and Signal Processing Based Active Fault Tolerant Control for Benchmark Process", Journal of Neural comput. & applications, vol:18, issue:1, pp:77-85
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 8]

[19] Postalcioglu, S., Erkan, K., Dogru Bolat E., (2007), "Implementation of Intelligent Active Fault Tolerant Control System", KES 2007, Lecture notes in Artificial Intelligence 4692, pp. 804-812

References Weight

Web of Science® Citations for all references: 6 TCR
SCOPUS® Citations for all references: 224 TCR

Web of Science® Average Citations per reference: 0 ACR
SCOPUS® Average Citations per reference: 11 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-05-06 13:34 in 29 seconds.

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