Abstract
The high-speed railway catenary system, which mainly consists of support devices and suspension devices, is an important part of the high-speed railway and is responsible for providing stable electrical energy for the operation of the train.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Han Z, Liu Z, Zhang G, Yang H (2013) Overview of non-contact image detection technology for pantograph-catenary monitoring. J China Railway Soc 35(6):40–47
Gao S, Liu Z, Yu L (2017) Detection and monitoring system of the pantograph-catenary in high-speed railway (6C). In: 7th international conference on power electronics systems and applications-smart mobility, power transfer and security (PESA). pp 1–7
Liu Z, Song Y, Han Y, Wang H, Zhang J, Han Z (2018) Advances of research on high-speed railway catenary. J Mod Transp 26(1):1–23
Yao D, Chen D, Tao K (2020) Discussions on comprehensive inspection and 31 monitoring technologies for railway infrastructures. Railway Stand Des 32:64
Artagan SS, Bianchini Ciampoli L, D’Amico F, Calvi A, Tosti F (2020) Non-destructive assessment and health monitoring of railway infrastructures. Surv Geophys 41(3):447–483
Yu L, Gao S, Zhang D, Kang G, Zhan D, Roberts C (2021) A survey on automatic inspections of overhead contact lines by computer vision. IEEE Trans Intell Transport Syst
Gao S (2020) Automatic detection and monitoring system of pantograph–catenary in China’s high-speed railways. IEEE Trans Instrum Meas 70:1–12
Liu Z, Liu W, Han Z (2017) A high-precision detection approach for catenary geometry parameters of electrical railway. IEEE Trans Instrum Meas 66(7):1798–1808
Zhan D, Jing D, Wu M, Zhang D, Yu L, Chen T (2018) An accurate and efficient vision measurement approach for railway catenary geometry parameters. IEEE Trans Instrum Meas 67(12):2841–2853
Zhan D, Jing D, Wu M, Zhang D (2018) Study on dynamic vision measurement for locator slope gradient of electrified railway overhead catenary. J Electron Meas Instrum 32(08):50–58
Aydin I, Karakose M, Akin E (2015) Anomaly detection using a modified kernel-based tracking in the pantograph–catenary system. Expert Syst Appl 42(2):938–948
Aydin I, Karaköse M, Akin E (2013) A robust anomaly detection in pantograph-catenary system based on mean-shift tracking and foreground detection. In: IEEE international conference on systems, man, and cybernetics. pp 4444–4449
Wu X, Yuan P, Peng Q, Ngo C-W, He J-Y (2016) Detection of bird nests in overhead catenary system images for high-speed rail. Pattern Recognit 51:242–254
Tan P, Li X-F, Xu J-M, Ma J-E, Wang F-J, Ding J, Fang Y-T, Ning Y (2020) Catenary insulator defect detection based on contour features and gray similarity matching. J Zhejiang Univ-Sci A 21(1):64–73
Karakose E, Gencoglu MT, Karakose M, Aydin I, Akin E (2016) A new experimental approach using image processing-based tracking for an efficient fault diagnosis in pantograph–catenary systems. IEEE Trans Industr Inf 13(2):635–643
Yang H-M, Liu Z-G, Han Z-W, Han Y (2013) Foreign body detection between insulator pieces in electrified railway based on affine moment invariant. J China Railway Soc 35(4):30–36
Yang H, Liu Z, Han Y, Han Z (2013) Defective condition detection of insulators in electrified railway based on feature matching of speeded-up robust features. Power Syst Technol 37(8):2297–2302
Han Y, Liu Z, Han Z, Yang H (2014) Fracture detection of ear pieces of catenary support devices of high-speed railway based on SIFT feature matching. J China Railway Soc 36(2):31–36
Zhang G, Liu Z (2014) Fault detection of catenary insulator damage/foreign material based on corner matching and spectral clustering. Chin J Sci Instrum 35(6):1370–1377
Chan TF, Vese LA (2001) Active contours without edges. IEEE Trans Image Process 10(2):266–277
Han Y, Liu Z, Lee D-J, Zhang G, Deng M (2016) High-speed railway rod-insulator detection using segment clustering and deformable part models. In: IEEE international conference on image processing (ICIP). pp 3852–3856
Xu D, Yu L, Chen T, Wang J (2017) Detection of catenary rotation binaural based on LBP-HOG feature. J Railway Sci Eng 14(2):370–378
Han Y, Liu Z, Geng X, Zhong J (2017) Fracture detection of ear pieces in catenary support devices of high-speed railway based on HOG features and two-dimensional Gabor transform. J China Railway Soc 39(2):52–57
Yang H, Liu Z (2017) Defective condition detection of rotary double ears of junction device of catenary system in electrified railway based on 2~(nd) generation curvelet transform. J China Railway Soc
Zhong J, Liu Z, Zhang G, Han Z (2017) Condition detection of swivel clevis pins in overhead contact system of high-speed railway. J China Railway Soc 39(6):65–71
Chen J, Liu Z, Han Y, Zhong J (2017) Location and fault detection of diagonal tube of overhead contact system of high-speed railway based on local feature description. J China Railway Soc 39(11):30–37
Zhang G, Liu Z, Han Y, Han Z (2017) Loss fault detection for auxiliary catenary wire of high-speed railway catenary wire holder. J China Railway Soc 39(5):40–46
Karaduman G, Karakose M, Akin E (2017) Deep learning based arc detection in pantograph-catenary systems. In: 10th international conference on electrical and electronics engineering (ELECO). pp 904–908
Huang S, Zhai Y, Zhang M, Hou X (2019) Arc detection and recognition in pantograph–catenary system based on convolutional neural network. Inf Sci 501:363–376
Luo Y, Yang Q, Liu S (2019) Novel vision-based abnormal behavior localization of pantograph-catenary for high-speed trains. IEEE Access 7:180935–180946
Wang J, Luo L, Ye W, Zhu S (2020) A defect-detection method of split pins in the catenary fastening devices of high-speed railway based on deep learning. IEEE Trans Instrum Meas 69(12):9517–9525
Chen Y, Song B, Zeng Y, Du X, Guizani M (2021) Fault diagnosis based on deep learning for current-carrying ring of catenary system in sustainable railway transportation. Appl Soft Comput 100:106907
Liu Z, Wang L, Li C, Han Z (2017) A high-precision loose strands diagnosis approach for isoelectric line in high-speed railway. IEEE Trans Industr Inf 14(3):1067–1077
Chen J, Liu Z, Wang H, Núñez A, Han Z (2017) Automatic defect detection of fasteners on the catenary support device using deep convolutional neural network. IEEE Trans Instrum Meas 67(2):257–269
Zhong J, Liu Z, Han Z, Han Y, Zhang W (2018) A CNN-based defect inspection method for catenary split pins in high-speed railway. IEEE Trans Instrum Meas 68(8):2849–2860
Kim K-H, Hong S, Roh B, Cheon Y, Park M (2016) Pvanet: deep but lightweight neural networks for real-time object detection. arXiv preprint arXiv:1608.08021
Liu K, Liu Z, Chen J (2019) Crack detection of messenger wire supporter in catenary support devices of high-speed railway based on Faster R-CNN. J China Railway Soc 41(7):43–49
Kang G, Gao S, Yu L, Zhang D (2018) Deep architecture for high-speed railway insulator surface defect detection: denoising autoencoder with multitask learning. IEEE Trans Instrum Meas 68(8):2679–2690
Wu C, Liu Z, Jiang H (2014) Catenary image enhancement using wavelet-based contourlet transform with cycle translation. Optik 125(15):3922–3925
Wu C, Liu Z, Jiang H (2014) The contourlet transform with multiple Cycles spinning for catenary image denoising. TELKOMNIKA Indonesian J Electr Eng 12(5):3887–3893
Zhou J, Han Z, Yang C (2018) Catenary geometric parameters detection method based on 3D point cloud. Chinese J Sci Instrum 39(4):239–246
Xu J, Liu Z, Han Z, Geng X (2017) Application of point cloud registration in 3D reconstruction of catenary parts based on SIFT and LBP. J China Railway Soc 39(10):76–81
Han Z, Yang C, Liu Z (2019) Cantilever structure segmentation and parameters detection based on concavity and convexity of 3-D point clouds. IEEE Trans Instrum Meas 69(6):3026–3036
Dongjie C, Wensheng Z, Yang Y (2017) Detection and recognition of high-speed railway catenary locator based on deep learning. J Univ Sci Technol China 47(4):320
Zhang G-N, Liu Z, Liu W, Han Z (2014) Non-contact detection of conductor height and stagger of contact line based on camera calibration. J China Railway Soc 36(3):25–30
Zhan D, Yu L, Xiao J, Chen T, She R (2014) Study on high-speed and dynamic vision measurement approach for overhead catenary system geometric parameter inspection. Chinese J Sci Instrum 35(8):1852–1859
Zhang G, Ling C, Wang X (2014) Image detection system design for geometry parameters of contact line. J Tianjin Polytech Univ 33(5):57–62
Duan R, Zhao W, Huang S, Chen J (2010) Automatic inspection method of steady arm slope based on computer vision. In: International conference on measuring technology and mechatronics automation, vol 1. pp 714–718
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Liu, Z., Liu, W., Zhong, J. (2023). Overview of Catenary Detection of Electrified Railways. In: Deep Learning-Based Detection of Catenary Support Component Defect and Fault in High-Speed Railways. Advances in High-speed Rail Technology. Springer, Singapore. https://doi.org/10.1007/978-981-99-0953-7_1
Download citation
DOI: https://doi.org/10.1007/978-981-99-0953-7_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-0952-0
Online ISBN: 978-981-99-0953-7
eBook Packages: EngineeringEngineering (R0)