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

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


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  3/2014 - 10

 HIGH-IMPACT PAPER 

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
 
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Download PDF pdficon (1,171 KB) | Citation | Downloads: 1,624 | Views: 6,392

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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Full text preview
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  «-- Click to see who has cited this paper

[1] L. G. C. Hamey, T. Watkins, S. W. T. Yen, "Pancam: In-service Inspection of Locomotive Pantographs," In: IEEE Conference on Digital Image Computing Techniques and Applications, Los Alamitos, 2007, pp. 493-499.
[CrossRef] [SCOPUS Times Cited 32]


[2] C. ODonnell, R. Palacin, J. Rosinski, "Pantograph Damage and Wear Monitoring System,", In: IEEE Conference on Railway Condition Monitoring, London, England, 2006, pp. 178-181.

[3] S. Midya, D. Bormann, T. Schütte, R. Thottappillil, "Pantograph Arcing in Electric Railways-Mechanism and Influence of Various Parameters-Part II: With AC Traction Power Supply," IEEE Trans. on Power Delivery, 2009, pp. 1940-1950.
[CrossRef] [Web of Science Times Cited 92] [SCOPUS Times Cited 138]


[4] W. Zhang, N. Zhou, R. Li, G. Mei, D. Song, "Pantograph and Catenary System with Double Pantographs for High-Speed Trains at 350 Km/H or Higher," Journal of Modern Transportation, vol. 19, pp. 7-11, Mar. 2011.
[CrossRef] [Web of Science Times Cited 34]


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[CrossRef]


[6] S. Barmada, M. Tucci, "Use of Advanced Signal processing Techniques for Arcing Detection on AC Pantograph Catenary Systems," In: Proc. of Pantograph Catenary Interaction Framework for Intelligent Control, Amiens, France, 2011, pp. 1-7.

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[CrossRef] [SCOPUS Times Cited 11]


[8] S. Barmada, M. Raugi, M. Tucci, F. Romano, Arc detection in pantograph-catenary systems by the use of support vector machines-based classification", IET Electr. Syst. Transp.,
[CrossRef] [Web of Science Times Cited 45] [SCOPUS Times Cited 58]


[9] P. Boffi, G. Cattaneo, L. Amoriello, A. Barberis, G. Bucca, M. F. Bocciolone, A. Collina, and M. Martinelli, "Optical Fiber Sensors to Measure Collector Performance in the Pantograph-Catenary Interaction," IEEE Trans. on Sensors, 2009, pp. 635-640.
[CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 68]


[10] R. Uwe, R. Schneider, "Automated optical inspection of overhead contact line systems," Siemens Efficient Railway Solutions, 2010.

[11] O. Bruno, A. Landi, M. Papi, L .Sani, "Phototube sensor for monitoring the quality of current collection on overhead electric railways," Proc. Instn Mech. Engrs, Part F: J. Rail and Rapid Transit, vol. 215, pp. 231-241, 2001.
[CrossRef] [Web of Science Times Cited 31] [SCOPUS Times Cited 51]


[12] A. A. Boguslavskii, S. M. Sokolov, "Detecting Objects in Images in Real-Time Computer Vision Systems Using Structured Geometric Models," Journal of Programming and Software, vol. 32, pp. 177-187, May-June 2006.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 17]


[13] S. Midya, D. Bormann, T. Schütte, and R. Thottappillil, "Pantograph Arcing in Electri?ed Railways-Mechanism and In?uence of Various Parameters-Part I: With DC Traction Power Supply," IEEE Trans. On Power Delivery, 2009, pp. 1931-1939.
[CrossRef] [Web of Science Times Cited 92] [SCOPUS Times Cited 138]


[14] A. Landi, L. Menconi, L. Sani, "Hough Transform and Thermo-Vision for Monitoring Pantograph-Catenary System," Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit, vol. 220, pp. 435-447, July 2006.
[CrossRef] [Web of Science Times Cited 55] [SCOPUS Times Cited 69]


[15] S. Ostlund, A. Gustafsson, L. Buhrkall, M. Skoglund, "Condition Monitoring of Pantograph Contact Strip," In: 4th IET IEEE International Conference on Railway Condition Monitoring, Derby, England, 2008, pp. 1-6.

[16] M. Li, W. Z. Yong, G. X. Rong, W. Li, Y. Kai, "Edge Detection on Pantograph Slide Image," In: 2nd IEEE International Congress on Image and Signal Processing, Tianjin, China, 2009, pp. 1-3.
[CrossRef] [SCOPUS Times Cited 31]


[17] Z. X. Heng, G. X. Rong, W. Z. Yong,W. Li, Y. Kai, "Study on the Edge Detection and Extraction Algorithm in the Pantograph Slipper's Abrasion," In: IEEE International Conference on Computational and Information Sciences, Chengdu, China, 2010, pp. 474-477.
[CrossRef] [SCOPUS Times Cited 30]


[18] T. Koyama, "A Method to Measure the Contact Force of Pantographs through Image Processing," Railway Technology Avalanche, vol. 37, pp. 219, 2011.

[19] P. V. Verschraegen, "A Model of the Pantograph Arc Impedance for 50 Hz Catenary Voltage," Master of Science Thesis, Stockholm, Sweden, 2010.

[20] I. Aydin, M. Karakose, and E. Akin, "A New Contactless Fault Diagnosis Approach for Pantograph-Catenary System," In: 15th IEEE International Conference On Mechatronika, Prague, Czech Republic, 2012, pp. 1-6.

[21] S. Midya, "Conducted and Radiated Electromagnetic Interference in Modern Electric Railways with Emphasis on Pantograph Arcing," PhD Thesis, Kungliga Tekniska Höghskolan, Stockholm, Sweeden, 2009.

[22] R. C. Gonzalez, R. E. Woods, "Digital Image Processing," Prentice Hall; 3 edition, pp. 976, 2007.

[23] J. Canny, "A Computational Approach to Edge Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, 1986, pp. 679-698.
[CrossRef] [Web of Science Times Cited 17322] [SCOPUS Times Cited 24356]


[24] S. Oprisescu, E. Barth, "3D Hand Gesture Recognition using the Hough Transform", Advances in Electrical and Computer Engineering vol. 13, pp. 71-76,
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[25] X. Ning, Y. Wang, "Object extraction from architecture scenes through 3d local scanned data analysis", Advances in Electrical and Computer Engineering, vol. 12, pp. 73-78,
[CrossRef] [Full Text] [Web of Science Times Cited 2] [SCOPUS Times Cited 3]


[26] V. Rajagopalan, A. Ray, R. Samsi, J. Mayer, "Pattern Identification in Dynamical Systems via Symbolic Time Series Analysis," Pattern Recognition, vol. 40, pp. 2897-2907, Nov. 2007.
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[27] R. Samsi, A. Ray, J. Mayer, "Early Detection of Stator Voltage Imbalance in three-phase Induction Motors," Electric Power Systems Research, 2005, pp. 478-483.
[CrossRef] [Web of Science Times Cited 4]


[28] I. Aydin, M. Karakose, E. Akin, "A new method for early fault detection and diagnosis of broken rotor bars," Energy Conversion and Management, vol. 52, pp. 1790-1799, April 2011.
[CrossRef] [Web of Science Times Cited 60] [SCOPUS Times Cited 67]




References Weight

Web of Science® Citations for all references: 17,840 TCR
SCOPUS® Citations for all references: 25,111 TCR

Web of Science® Average Citations per reference: 615 ACR
SCOPUS® Average Citations per reference: 866 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 2024-10-10 18:19 in 130 seconds.




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