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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
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (528 KB) | Citation | Downloads: 1,128 | Views: 5,697

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.

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Cited-By CrossRef

[1] A Novel Method for Inverter Faults Detection and Diagnosis in PMSM Drives of HEVs based on Discrete Wavelet Transform, AKTAS, M., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 12, 2012.
Digital Object Identifier: 10.4316/AECE.2012.04005
[CrossRef] [Full text]

[2] Continuous wavelet transform for ferroresonance detection in power systems, Şengüler, Tayfun, Şeker, Serhat, Electrical Engineering, ISSN 0948-7921, Issue 2, Volume 99, 2017.
Digital Object Identifier: 10.1007/s00202-016-0387-0

[3] Evaluation of pool water quality of trout farms by fuzzy logic: monitoring of pool water quality for trout farms, Yalcuk, A., Postalcioglu, S., International Journal of Environmental Science and Technology, ISSN 1735-1472, Issue 5, Volume 12, 2015.
Digital Object Identifier: 10.1007/s13762-014-0536-9

[4] 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]

[5] Study of fault tree analysis and expert system principle, Cai, Mengxiang, Lin, Jiajian, Wang, Hui, Zhou, Mi, MATERIALS SCIENCE, ENERGY TECHNOLOGY AND POWER ENGINEERING III (MEP 2019), ISBN , Issue , 2019.
Digital Object Identifier: 10.1063/1.5125351

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Faculty of Electrical Engineering and Computer Science
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