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Adaptive Arc Detection Based Image Segmentation in Pantograph Catenary Systems

Year 2017, Volume: 10 Issue: 2, 53 - 63, 26.12.2017

Abstract

In recent years, through the development of electric trains,
the rail system has become a popular mode of transport. This type of transport
is reliable and cost-effective compared to other modes of transport.
Furthermore, the rail transport is more preferred with the emergence of the
electric train.  In order to provide the
electrical energy used by electric trains, pantograph catenary system was
developed. Pantograph system, receives power from the catenary wire and
transmits to train. The catenary system, located along the railway line, it
transmits electricity from the substation to the pantograph system. During contact
with pantograph and catenary system many failures may occur. Early diagnosis of
failures are preventing larger defect. 
In this study, a new image processing based method for arc detection in
pantograph catenary system, which is a part of the rail system, is
proposed.  Real-time images of the
catenary pantograph is taken by cameras placed on the roof of two different
locomotives. The image segmentation is used to identify the differences that
occur in images taken. Also, the Sobel edge extraction algorithm is used for
detecting contact of a pantograph. The arcing at the contacts of the pantograph
is determined by combining properties obtained. The proposed method has been
carried out both in the FPGA environment MATLAB and the results were compared.

References

  • Karakose, E., Gencoglu, M.T., Karakose, M., Yaman, O., Aydin, I., and Akin, E., A new arc detection method based on fuzzy logic using S-transform for pantograph–catenary systems. Journal of Intelligent Manufacturing, 1-18, 2015.
  • Karakose E., Gencoglu MT. An investigation of pantograph parameter effects for pantograph-catenary systems. Innovations in Intelligent Systems and Applications (INISTA) Proceedings, 2014 IEEE International Symposium on. IEEE, 2014.
  • Aydin I, Karakose M, Akin E. Anomaly detection using a modified kernel-based tracking in the pantograph–catenary system. Expert Systems with Applications 42.2, 938-948, 2015.
  • Liu Y, Chang GW, Huang HM. Mayr's Equation-Based Model for Pantograph Arc of High-Speed Railway Traction System, IEEE Transactions on Power Delivery, (25), 2025-2027, 2010.
  • Midya S, Bormann D, Schütte T, Thottappillil R. DC Component From Pantograph Arcing in AC Traction System—Influencing Parameters, Impact, and Mitigation Techniques, IEEE Transactions on Electromagnetic Compatibility, (53), 18-27, 2011.
  • Barmada S, Raugi M, Tucci M, Romano F. Arc detection in pantograph-catenary systems by the use of support vector machines-based classification, IET Electrical Systems in Transportation Institution of Engineering and Technology, 2013.
  • Ostlund S, Gustafsson A, Buhrkall L, Skoglund M. Condition monitoring of pantograph contact strip, International Conference on Railway Condition Monitoring, 1-6, 2008.
  • Hamey LGC, Watkins T, Yen SWT. Pancam: In-Service Inspection of Locomotive Pantographs, 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications, 439-499, 2007.
  • Sacchi M, Cagnoni S, Spagnoletti D, Ascari L, Zunino G, Piazzi A. PAVISYS: A computer vision system for the inspection of locomotive pantographs, Pantograph Catenary Interaction Framework for Intelligent Control, 2011.
  • Ocoleanu CF, Popa I, Manolea G, Dolan AI, Vlase S. Temperature Investigation in Contact Pantograph - AC Contact Line, International Journal Of Circuits. Systems and Signal Processing, 154-163, 2009.
  • Facchinetti A, Bruni S. Hardware-in-the-loop hybrid simulation of pantograph–catenary interaction, Journal of Soundand Vibration, 2783-2797, 2012.
  • Midya S, Bormann D, Schütte T, Thottappillil R. Pantograph Arcing in Electrified Railways—Mechanism and Influence of Various Parameters—Part I: With DC Traction Power Supply, IEEE Transactions on Power Delivery, 1931- 1939, 2009.
  • Boguslavskii AA, Sokolov SM. Detecting Objects in Images in Real-Time Computer Vision Systems Using Structured Geometric Models, Pleiades Publishing, 177–187, 2006.
  • Li M, Ze-yong W, Xiao-rong G, Li W, Kai Y. Edge Detection on Pantograph Slide Image, International Congress on Image and Signal Processing, 1 – 3, 2009.
  • Landi A, Menconi L, Sani L, Hough transform and thermo-vision for monitoring pantograph–catenary system, Proceedings of the Institution of Mechanical Engineers, (220), 435– 447, 2006.
  • Xiao-heng Z, Xiao-rong G, Ze-yong W, Li W, Kai Y. Study on the Edge Detection and Extraction Algorithm in the Pantographslipper's Abrasion, International Conference on Computational and Information Sciences, 474–477, 2010.
  • Aydin, İ., Karaköse, E., Karaköse, M., Gençoğlu, M. T. and Akın, E. A new computer vision approach for active pantograph control. IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA), 1-5, 2013.
  • Chen Q, Zhao L, Lu J, Kuang G, Wang N, Jiang Y. Modified two-dimensional otsu image segmentation algorithm and fast realisation, IET Image Processing, (6)4, 426-433, 2012.
  • AlSaeed DH, Bouridane A, Elzaart A, Sammouda R. Two modified Otsu image segmentation methods based on Lognormal and Gamma distribution models, International Conference on Information Technology and e-Services, 1-5, 2012.
  • BahadarKhan, K., Khaliq, A. A., and Shahid, M.. A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding. PloS one, 11(7), 2016.
  • Li Y, Yao Q, Tian B, Xu W. Fast double-parallel image processing based on FPGA, IEEE International Conference on Vehicular Electronics and Safety, 97-102, 2011.
  • Rao, M. G., Kumar, P. R., and Prasad, A. M. Implementation of real time image processing system with FPGA and DSP. International Conference on Microelectronics, Computing and Communications (MicroCom), 1-4, 2016.

Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti

Year 2017, Volume: 10 Issue: 2, 53 - 63, 26.12.2017

Abstract

Son yıllarda elektrikli trenlerin gelişmesiyle birlikte raylı
sistemler popüler bir ulaşım türü haline gelmiştir. Bu ulaşım türü diğer ulaşım
türlerine göre düşük maliyetli ve güvenilirdir. Ayrıca elektrikli trenlerin
ortaya çıkmasıyla birlikte demiryolu ulaşımı daha çok tercih edilmiştir.
Elektrikli trenlerin kullandığı elektrik enerjisinin temin edilmesi için
pantograf katener sistemleri geliştirilmiştir. Pantograf sistemi, trenin üzerinde
bulunan katener telinden aldığı elektriği trene ileten sistemdir. Katener
sistemi ise, demiryolu hattı boyunca bulunur ve trafo merkezinden alınan
elektriği pantograf sistemine iletmektedir. Pantograf ve katener sistemlerinin
birbiri ile teması sırasında çeşitli arızalar ortaya çıkmaktadır. Oluşan
arızaların erken teşhis edilmesi daha büyük arızaların oluşmasını
engellemektedir. Bu çalışmada, raylı sistemlerin bir parçası olan pantograf
katener sistemlerde ark tespiti için görüntü işleme tabanlı yeni bir yöntem
önerilmektedir. İki farklı lokomotifin çatısına kamera yerleştirilerek
pantograf katener sisteminin gerçek zamanlı görüntüsü alınmıştır. Alınan
görüntülerde oluşan arkların tespiti için görüntü segmantasyonu kullanılmıştır.
Ayrıca pantograf temas bölgesinin tespit edilmesi için Sobel kenar çıkarım
algoritması kullanılmıştır. Elde edilen özellikler bileştirilerek pantograf
temas bölgesinde oluşan arkların tespiti yapılmaktadır. Önerilen yöntem hem
MATLAB hem de FPGA ortamında gerçekleştirilmiştir ve sonuçları
karşılaştırılmıştır. 

References

  • Karakose, E., Gencoglu, M.T., Karakose, M., Yaman, O., Aydin, I., and Akin, E., A new arc detection method based on fuzzy logic using S-transform for pantograph–catenary systems. Journal of Intelligent Manufacturing, 1-18, 2015.
  • Karakose E., Gencoglu MT. An investigation of pantograph parameter effects for pantograph-catenary systems. Innovations in Intelligent Systems and Applications (INISTA) Proceedings, 2014 IEEE International Symposium on. IEEE, 2014.
  • Aydin I, Karakose M, Akin E. Anomaly detection using a modified kernel-based tracking in the pantograph–catenary system. Expert Systems with Applications 42.2, 938-948, 2015.
  • Liu Y, Chang GW, Huang HM. Mayr's Equation-Based Model for Pantograph Arc of High-Speed Railway Traction System, IEEE Transactions on Power Delivery, (25), 2025-2027, 2010.
  • Midya S, Bormann D, Schütte T, Thottappillil R. DC Component From Pantograph Arcing in AC Traction System—Influencing Parameters, Impact, and Mitigation Techniques, IEEE Transactions on Electromagnetic Compatibility, (53), 18-27, 2011.
  • Barmada S, Raugi M, Tucci M, Romano F. Arc detection in pantograph-catenary systems by the use of support vector machines-based classification, IET Electrical Systems in Transportation Institution of Engineering and Technology, 2013.
  • Ostlund S, Gustafsson A, Buhrkall L, Skoglund M. Condition monitoring of pantograph contact strip, International Conference on Railway Condition Monitoring, 1-6, 2008.
  • Hamey LGC, Watkins T, Yen SWT. Pancam: In-Service Inspection of Locomotive Pantographs, 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications, 439-499, 2007.
  • Sacchi M, Cagnoni S, Spagnoletti D, Ascari L, Zunino G, Piazzi A. PAVISYS: A computer vision system for the inspection of locomotive pantographs, Pantograph Catenary Interaction Framework for Intelligent Control, 2011.
  • Ocoleanu CF, Popa I, Manolea G, Dolan AI, Vlase S. Temperature Investigation in Contact Pantograph - AC Contact Line, International Journal Of Circuits. Systems and Signal Processing, 154-163, 2009.
  • Facchinetti A, Bruni S. Hardware-in-the-loop hybrid simulation of pantograph–catenary interaction, Journal of Soundand Vibration, 2783-2797, 2012.
  • Midya S, Bormann D, Schütte T, Thottappillil R. Pantograph Arcing in Electrified Railways—Mechanism and Influence of Various Parameters—Part I: With DC Traction Power Supply, IEEE Transactions on Power Delivery, 1931- 1939, 2009.
  • Boguslavskii AA, Sokolov SM. Detecting Objects in Images in Real-Time Computer Vision Systems Using Structured Geometric Models, Pleiades Publishing, 177–187, 2006.
  • Li M, Ze-yong W, Xiao-rong G, Li W, Kai Y. Edge Detection on Pantograph Slide Image, International Congress on Image and Signal Processing, 1 – 3, 2009.
  • Landi A, Menconi L, Sani L, Hough transform and thermo-vision for monitoring pantograph–catenary system, Proceedings of the Institution of Mechanical Engineers, (220), 435– 447, 2006.
  • Xiao-heng Z, Xiao-rong G, Ze-yong W, Li W, Kai Y. Study on the Edge Detection and Extraction Algorithm in the Pantographslipper's Abrasion, International Conference on Computational and Information Sciences, 474–477, 2010.
  • Aydin, İ., Karaköse, E., Karaköse, M., Gençoğlu, M. T. and Akın, E. A new computer vision approach for active pantograph control. IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA), 1-5, 2013.
  • Chen Q, Zhao L, Lu J, Kuang G, Wang N, Jiang Y. Modified two-dimensional otsu image segmentation algorithm and fast realisation, IET Image Processing, (6)4, 426-433, 2012.
  • AlSaeed DH, Bouridane A, Elzaart A, Sammouda R. Two modified Otsu image segmentation methods based on Lognormal and Gamma distribution models, International Conference on Information Technology and e-Services, 1-5, 2012.
  • BahadarKhan, K., Khaliq, A. A., and Shahid, M.. A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding. PloS one, 11(7), 2016.
  • Li Y, Yao Q, Tian B, Xu W. Fast double-parallel image processing based on FPGA, IEEE International Conference on Vehicular Electronics and Safety, 97-102, 2011.
  • Rao, M. G., Kumar, P. R., and Prasad, A. M. Implementation of real time image processing system with FPGA and DSP. International Conference on Microelectronics, Computing and Communications (MicroCom), 1-4, 2016.
There are 22 citations in total.

Details

Subjects Engineering
Journal Section Makaleler(Araştırma)
Authors

Mehmet Karaköse

Orhan Yaman

İlhan Aydın

Erhan Akın

Publication Date December 26, 2017
Published in Issue Year 2017 Volume: 10 Issue: 2

Cite

APA Karaköse, M., Yaman, O., Aydın, İ., Akın, E. (2017). Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi, 10(2), 53-63.
AMA Karaköse M, Yaman O, Aydın İ, Akın E. Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti. TBV-BBMD. December 2017;10(2):53-63.
Chicago Karaköse, Mehmet, Orhan Yaman, İlhan Aydın, and Erhan Akın. “Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti”. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi 10, no. 2 (December 2017): 53-63.
EndNote Karaköse M, Yaman O, Aydın İ, Akın E (December 1, 2017) Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti. Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi 10 2 53–63.
IEEE M. Karaköse, O. Yaman, İ. Aydın, and E. Akın, “Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti”, TBV-BBMD, vol. 10, no. 2, pp. 53–63, 2017.
ISNAD Karaköse, Mehmet et al. “Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti”. Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi 10/2 (December 2017), 53-63.
JAMA Karaköse M, Yaman O, Aydın İ, Akın E. Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti. TBV-BBMD. 2017;10:53–63.
MLA Karaköse, Mehmet et al. “Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti”. Türkiye Bilişim Vakfı Bilgisayar Bilimleri Ve Mühendisliği Dergisi, vol. 10, no. 2, 2017, pp. 53-63.
Vancouver Karaköse M, Yaman O, Aydın İ, Akın E. Pantograf Katener Sistemlerde Görüntü Segmantasyon Tabanlı Adaptif Ark Tespiti. TBV-BBMD. 2017;10(2):53-6.

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