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

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


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  2/2013 - 18

Experimental System for Monitoring and Diagnosis of a Static Power Converter

IVANOV, V. I. See more information about IVANOV, V. I. on SCOPUS See more information about IVANOV, V. I. on IEEExplore See more information about IVANOV, V. I. on Web of Science, BROJBOIU, M. D. See more information about  BROJBOIU, M. D. on SCOPUS See more information about  BROJBOIU, M. D. on SCOPUS See more information about BROJBOIU, M. D. on Web of Science, IVANOV, S. S. See more information about IVANOV, S. S. on SCOPUS See more information about IVANOV, S. S. on SCOPUS See more information about IVANOV, S. S. on Web of Science
 
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Download PDF pdficon (733 KB) | Citation | Downloads: 581 | Views: 2,589

Author keywords
fault diagnosis, static power converters, redundancy, reliability theory, monitoring

References keywords
power(11), fault(11), ivanov(10), system(7), systems(6), expert(6), diagnosis(6), brojboiu(5), method(4), faults(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-05-31
Volume 13, Issue 2, Year 2013, On page(s): 113 - 120
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.02018
Web of Science Accession Number: 000322179400018
SCOPUS ID: 84878924715

Abstract
Quick view
Full text preview
The evolution of the computer aided design and control technologies in the field of static power converters leads also to diagnosis systems which include modules based on artificial intelligence. In order to achieve satisfactory reliability, the static power converters must even be assembled by using high reliability devices and/or be conceived as redundant topologies. The paper presents a dedicated monitoring and diagnosis system of the static power converters. It can be used both for the diagnosis of the transistors within an inverter as well as for the analysis and diagnosis of a power bridge rectifier. The diagnosis system dedicated to the power rectifiers uses the fault tree method. Based on the symptoms observed in the behavior of the power rectifiers, the diagnosis and the functional test performed by the developed system is based on consideration of the abnormal comportments and the faults which determine these. The experimental system dedicated to the bridge rectifiers analyses and identifies the causes of the faults which occur during the operation and reduces the displayed results if two sets of values of the sources which determine the same answer, differ by a single input.


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

[1] V. Ivanov, M. Brojboiu, S. Ivanov, "Expert system for reliability analysis of electrical systems using the tree of faults method", Annals of the University of Craiova, Serie Electrical Engineering, nr.33, pp.105-110, 2009.

[2] V. Ivanov, M. Brojboiu, S. Ivanov, "The design of electrical system with microcontroller for the measurement of electrical parameters", Polish journal Electrical Review, Przeglad Elektrotechniczny-Konferencje , nr.2, pp.80-83, 2007.

[3] T. Bajenescu, "Fiabilitatea sistemelor tehnice", Ed. Matrix Rom, Bucuresti, 2003.

[4] V. Ivanov, M. Brojboiu, S. Ivanov, "Diagnosis system for the switches of a static converter", in Proc. 6th Conference on Electrical and Power Engineering, Iasi, vol I, pp. 25-28, 2010.

[5] D. W. Patterson, "Introduction to Artificial Intelligence and Expert Systems", Prentice-Hall International, 1999.

[6] M. O. Popescu, Claudia Laurenta Popescu, s.a., "Sisteme expert pentru diagnoza echipamentelor electrice", Ed. Electra, Bucuresti, 2002.

[7] A. Metatla, S. Benzahioul, T. Bahi, D. Lefebvre, "On Line Current Monitoring and Application of a Residual Method for Eccentricity Fault Detection", Advances in Electrical and Computer Engineering Volume 11, Number 1, pp.69-72, 2011.
[CrossRef] [Full Text] [Web of Science Times Cited 6] [SCOPUS Times Cited 8]


[8] P. L. Cui, J. H. Li and G. Z. Wang, "Improved kernel principal component analysis for fault detection", Expert Systems with Applications, vol.34, pp. 1210-1219, Feb. 2008.
[CrossRef] [Web of Science Times Cited 71] [SCOPUS Times Cited 87]


[9] C. Y. Teo, "A comprehensive fault diagnostic System using artificial intelligence for sub transmission and urban distribution networks", IEEE Transactions on Power Delivery, Vol. 12, Nr. 4, 1997.

[10] Y. Zhang, Z. Wang, J. Zhang, "A Novel Fault Identification Using WAMS/PMU", Advances in Electrical and Computer Engineering Volume 12, Number 2, pp.21-26, 2012.
[CrossRef] [Full Text] [Web of Science Times Cited 10] [SCOPUS Times Cited 11]


[11] Y. G. Zhang, Z. P. Wang, J. F. Zhang and J.Ma, "Fault localization in electrical power systems: A pattern recognition approach", International Journal of Electric Power & Energy Systems, vol.33, pp.791-798, 2011,
[CrossRef] [Web of Science Times Cited 57] [SCOPUS Times Cited 71]


[12] H. Mokhlis, H. Mohamad, H. Li, A. H. A. Bakar, "Voltage Sags Matching to Locate Faults for Underground Distribution Networks", Advances in Electrical and Computer Engineering Volume 11, Number 2, pp.43-48, 2011.
[CrossRef] [Full Text] [Web of Science Times Cited 8] [SCOPUS Times Cited 11]


[13] H. J. Lee, D. Y. Park, B. S. Ahn, Y. M. Park, and S. S. Venkata, "A fuzzy expert system for the integrated fault diagnosis", IEEE Trans. Power Delivery, vol. 15, no. 2, pp. 833-838, 2000.
[CrossRef] [Web of Science Times Cited 56] [SCOPUS Times Cited 93]


[14] Z. Galijasevic, A. Abur, "Fault location using voltage measurements, "IEEE Trans. Power Delivery, vol.17, pp. 441-445, April 2002.
[CrossRef] [Web of Science Times Cited 75] [SCOPUS Times Cited 100]


[15] H. Mokhlis, A.H.A. Bakar, D.N.A.Talib, Hasmaini Mohamad, "The Improvement of Voltage Sags Pattern Approach to Locate a Fault in Distribution Network", International Review of Electrical Engineering (IREE), vol. 5, no. 3, pp 1159-1164, June 2010.

[16] M. Bigdeli, M. Vakilian, E. Rahimpour, "A New Method for Detection and Evaluation of Winding Mechanical Faults in Transformer through Transfer Function Measurements", Advances in Electrical and Computer Engineering Volume 11, Number 2, pp. 23-30, 2011.
[CrossRef] [Full Text] [Web of Science Times Cited 23] [SCOPUS Times Cited 27]


[17] K. S. Swarup, H. S. Chandrasekharalah, "Fault detection and diagnosis of power converters using artificial neural networks", in Proc. The International Conference on Power Electronics, Drives and Energy Systems for Industrial Growth, Vol. 2, pp. 1054- 1058, 1996.
[CrossRef]


[18] Biran, A., Breiner, M., MATLAB for Engineers, Addison-Wesley Publishing Company, 1996.

[19] S. Khomfoi, L. M. Tolbert, "Fault Diagnosis and Reconfiguration for Multilevel Inverter Drive Using AI-Based Techniques", IEEE Trans. Industrial Electronics, Vol. 54, No. 6, pp.2954-2968, 2007.
[CrossRef] [Web of Science Times Cited 166] [SCOPUS Times Cited 214]


[20] A. Chen, L. Hu, L. Chen, Y. Deng, X.He, "A Multilevel Converter Topology With Fault-Tolerant Ability", IEEE Trans. Power Electronics, Vol. 20, No. 2, pp.405-415, 2005.
[CrossRef] [Web of Science Times Cited 111] [SCOPUS Times Cited 137]


[21] [Online] Available: Temporary on-line reference link removed - see the PDF document

[22] ***CLIPS - Reference Manual, Volume I, Basic Programming Guide, Version 6.10, 1998.

[23] V. Ivanov, M. Brojboiu, S. Ivanov, "Diagnosis System for Power Rectifiers Using the Tree of Faults Method", Annals of the University of Craiova, Serie Electrical Engineering, nr.36, ISSN 1842-4805, ISBN 978-1-4673-1808-2, IEEE Catalog number CFP1299S-PRT, pp.350-354, 2012.
[CrossRef] [SCOPUS Times Cited 4]


[24] V. Ivanov, M. Brojboiu, S. Ivanov, "Expert system for power rectifiers diagnosis", Annals of the University of Craiova, Serie Electrical Engineering, Year 34, nr.34, ISSN 1842-4805, pp. 129-132, 2010.

[25] B. Dodson, D. Nolan, "Reliability Engineering Handbook", QA Publishing, LLC, Tucson, ISBN 0-8247-0364-2, 2002.



References Weight

Web of Science® Citations for all references: 583 TCR
SCOPUS® Citations for all references: 763 TCR

Web of Science® Average Citations per reference: 22 ACR
SCOPUS® Average Citations per reference: 29 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 2021-09-15 17:30 in 74 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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