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


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2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

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  3/2014 - 10

A New Contactless Fault Diagnosis Approach for Pantograph-Catenary System Using Pattern Recognition and Image Processing Methods

AYDIN, I. See more information about AYDIN, I. on SCOPUS See more information about AYDIN, I. on IEEExplore See more information about AYDIN, I. on Web of Science, KARAKOSE, M. See more information about  KARAKOSE, M. on SCOPUS See more information about  KARAKOSE, M. on SCOPUS See more information about KARAKOSE, M. on Web of Science, AKIN, E. See more information about AKIN, E. on SCOPUS See more information about AKIN, E. on SCOPUS See more information about AKIN, E. on Web of Science
 
Click to see author's profile on 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 (1,171 KB) | Citation | Downloads: 536 | Views: 3,037

Author keywords
pantograph, catenary, arcing faults, edge detection, Hough transform, fault diagnosis, railways

References keywords
pantograph(15), catenary(8), monitoring(7), detection(7), systems(6), power(5), image(5), contact(5), system(4), railways(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-08-31
Volume 14, Issue 3, Year 2014, On page(s): 79 - 88
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.03010
Web of Science Accession Number: 000340869800010
SCOPUS ID: 84907314934

Abstract
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Comfort and safety of railway transport has become more important as train speeds continue to increase. In electrified railways, the electrical current of the train is produced by the sliding contact between the pantograph and catenary. The quality of the current depends on the reliability of contact between the pantograph and catenary. So, pantograph inspection is very important task in electrified railways and it is periodically made for preventing dangerous situations. This inspection is operated manually by taking the pantograph to the service for visual anomalies. However, this monitoring is impractical because of time consuming and slowness, as locomotive remains disabled. An innovative method based on image processing and pattern recognition is proposed in this paper for online monitoring of the catenary-pantograph interaction. The images are acquired from a digital line-scan camera. Data are simultaneously processed according to edge detection and Hough transform, and then the obtained features are provided to a D-Markov based state machine, and the pantograph related faults, such as overheating of the pantograph strip, bursts of arcing, and irregular positioning of the contact line are diagnosed. The proposed method is verified by real faulty and healthy pantograph videos.


References | Cited By

Cited-By ISI Web of Science

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Cited-By CrossRef

SCOPUS® Times Cited: 5
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Cited-By CrossRef

[1] Fuzzy integral-based multi-sensor fusion for arc detection in the pantograph-catenary system, Aydin, Ilhan, Celebi, Selahattin B, Barmada, Sami, Tucci, Mauro, Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, ISSN 0954-4097, Issue 1, Volume 232, 2018.
Digital Object Identifier: 10.1177/0954409716662090
[CrossRef]

[2] A new arc detection method based on fuzzy logic using S-transform for pantograph–catenary systems, Karakose, Ebru, Gencoglu, Muhsin Tunay, Karakose, Mehmet, Yaman, Orhan, Aydin, Ilhan, Akin, Erhan, Journal of Intelligent Manufacturing, ISSN 0956-5515, 2015.
Digital Object Identifier: 10.1007/s10845-015-1136-3
[CrossRef]

[3] 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
[CrossRef]

[4] A new approach based on firefly algorithm for vision-based railway overhead inspection system, Aydin, Ilhan, Measurement, ISSN 0263-2241, Issue , 2015.
Digital Object Identifier: 10.1016/j.measurement.2015.07.022
[CrossRef]

[5] An Enhanced Artificial Bee Colony-Based Support Vector Machine for Image-Based Fault Detection, Chen, Guijun, Zhang, Xueying, Wang, Zizhong John, Li, Fenglian, Mathematical Problems in Engineering, ISSN 1024-123X, Issue , 2015.
Digital Object Identifier: 10.1155/2015/638926
[CrossRef]

[6] A new object detection and classification method for quality control based on segmentation and geometric features, Aydin, Ilhan, Karakose, Mehmet, Hamsin, G. Ghazi, Sarimaden, Alisan, Akin, Erhan, 2017 International Artificial Intelligence and Data Processing Symposium (IDAP), ISBN 978-1-5386-1880-6, 2017.
Digital Object Identifier: 10.1109/IDAP.2017.8090172
[CrossRef]

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


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