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Academic literature on the topic 'Railway catenary system'
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Journal articles on the topic "Railway catenary system"
1
Lesnikov, Dmitriy Valentinovich. "Modeling of direct current traction power system with the consideration for earth conductivity." Transport of the Urals, no. 2 (2020): 75–79. http://dx.doi.org/10.20291/1815-9400-2020-2-75-79.
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Nowadays, one of the main tasks facing the JSC Russian Railways is the increase of volumes of freight transportation. The solution of this task is directly connected with the increase of the load on traction power system devices and their strengthening, which is primarily related to railways electrified with direct current that are characterized by high traction currents. In order to assess the possibility to strengthen a railway section and reveal «bottlenecks» in traction power supply system it is necessary to create a mathematical model of traction power system that must consider parameters of a specific section including earth conductivity that affects the values of skin resistance, potential of railway network and stray currents. The paper proposes a mathematical model of direct current traction power system that represents a combination of a catenary model and a model of railway network. The model considers parameters of traction substations, connection scheme of catenary suspensions and possible influence of rails from adjacent tracks on each other.
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Benet, Jesús, Fernando Cuartero, Tomás Rojo, Pedro Tendero, and Enrique Arias. "Numerical Algorithms for the Analysis of Initial Configuration in a Railway Catenary Structure and Its Code Implementation: A Software Tool CALPE." Mathematical Problems in Engineering 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/819165.
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To obtain the best operating conditions in a railway infrastructure, as the pantograph/catenary system, is a priority issue in modern railways, for a correct management and the best performance of this infrastructure. Although most of the published works on this subject are oriented to solving dynamic problems, in order to successfully address these problems a previous static study is necessary. In this paper, we present a methodology for the study of the forces in a railway catenary, according to the equations of statics equilibrium. The results of this work have allowed us to develop two iterative algorithms that calculate a simple and computationally effective lengths of the droppers, which is crucial to determine the initial structural configuration of the catenary parameter. The obtained results have led us to the implementation of a tool to obtain very precise assemblies with significant savings in maintenance, therefore still being used by ADIF, the Spanish railway administration of railways infrastructures.
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Kobayashi, Shigeyuki, David P. Stoten, Yoshitaka Yamashita, and Takayuki Usuda. "Dynamically substructured testing of railway pantograph/catenary systems." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 233, no. 5 (2018): 516–25. http://dx.doi.org/10.1177/0954409718799900.
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This paper presents a methodology for testing railway pantograph/catenary systems based upon the dynamically substructured system approach for combined physical and numerical components, originally developed by Stoten and Hyde. The main advantage of the dynamically substructured system is that it can provide more stable substructured testing than alternative schemes, such as the commonly used hybrid simulation method, often referred to as hardware-in-the-loop simulation. The developed method is validated through experiments using a simple pantograph rig, together with a numerical simulation of the catenary. In order to realise a real-time simulation of the large catenary model, for the first time in dynamically substructured system testing this study uses (i) a modal analysis technique to reduce the dimension of the contact wire model and (ii) a moving window approach to represent long-distance travel of the pantograph. Finally, the experimental dynamically substructured system test results are compared with simulations of the benchmark pantograph/catenary emulated system.
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Zheng, Xue Xian, Xun Wang, Hong Bo Cheng, and Wen Hui Cao. "Lightning Protection Research and Simulation of High-Speed Railway Catenary." Advanced Materials Research 875-877 (February 2014): 1707–11. http://dx.doi.org/10.4028/www.scientific.net/amr.875-877.1707.
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The existing high-speed railway in China is erected on the viaduct. The traction power supply system of high-speed railway consists of catenary with auto-transformer (AT). The catenary above the rails is supported by towers besides the rails. As the increase of the height from top of towers to ground, the probability of the pilot discharging of lightning to catenary will increase. And the pilot striking distance to ground always remains constant. So the horizons shielding effects for catenary will decrese, and the whole catenary naked in the atmosphere extremely easily struck by thunderbolt. In the important places, e.g., substation and areas of frequent lightning, the lightning arrester is installed to limit lightning overvoltage. But the lightning arrester can limit local overvoltage only. In fact, high-speed railway struck by lightning has affected the safety of power supply system in China. So more reasonable lightning protection measures for Chinas high-speed railway will be studied in this paper.
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Han, Ye, Zhigang Liu, DJ Lee, Wenqiang Liu, Junwen Chen, and Zhiwei Han. "Computer vision–based automatic rod-insulator defect detection in high-speed railway catenary system." International Journal of Advanced Robotic Systems 15, no. 3 (2018): 172988141877394. http://dx.doi.org/10.1177/1729881418773943.
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Maintenance of catenary system is a crucial task for the safe operation of high-speed railway systems. Catenary system malfunction could interrupt railway service and threaten public safety. This article presents a computer vision algorithm that is developed to automatically detect the defective rod-insulators in a catenary system to ensure reliable power transmission. Two key challenges in building such a robust inspection system are addressed in this work, the detection of the insulators in the catenary image and the detection of possible defects. A two-step insulator detection method is implemented to detect insulators with different inclination angles in the image. The sub-images containing cantilevers and rods are first extracted from the catenary image. Then, the insulators are detected in the sub-image using deformable part models. A local intensity period estimation algorithm is designed specifically for insulator defect detection. Experimental results show that the proposed method is able to automatically and reliably detect insulator defects including the breakage of the ceramic discs and the foreign objects clamped between two ceramic discs. The performance of this visual inspection method meets the strict requirements for catenary system maintenance.
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Haladin, Ivo, Stjepan Lakušić, and Ivan Duvnjak. "Evaluation of tramway overhead line system in city of Osijek." MATEC Web of Conferences 180 (2018): 06003. http://dx.doi.org/10.1051/matecconf/201818006003.
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Overhead line system is a vital element of any electrified railway infrastructure. Its performance reflects to all vital parameters such as traction, reliability, availability and safety of railway infrastructure. Operator GPP Osijek runs a 27.5 km long tramway network which plays a key role in transit system of the city of Osijek, Croatia. In 2016 GPP Osijek applied to a tender for acquisition of new rolling stock with 85% EU investment. Mayor requirement prior to rolling stock acquisition was to document, analyse and upgrade current infrastructure (including track structure, electric substations and catenary) to an optimal level. Task of measurement and evaluation of tram track structure and catenary has been appointed to University of Zagreb Faculty of Civil Engineering. Overhead line analysis comprised from several measuring procedures, including supporting columns evaluation, catenary stagger, height, shocks and wear. Such extensive analysis included GPS positioning and on-site evaluation of 1214 supporting columns of overhead line, as well as overhead line measurements using an instrumented tram vehicle on 18 km of track. For conducting overhead catenary wire measurements, a tram pantograph has been fitted with equipment for measuring catenary height, accelerometers for shock measurement, camera, ruler and GPS for stagger measurement. Catenary wire wear was checked manually from catenary inspection vehicle. To conduct measurements, power had to be switched off on all electric substation along the route and tram vehicle had to be towed by a catenary inspection vehicle. All the data has been analysed and presented to end user in a user-friendly and intuitive GIS environment capable of further updates and detailed analyses. Evaluation of overhead line based on direct measurement results pointed out all the defects and weak spots on the system. It resulted in a series of recommendations for reconstruction and upgrade of the catenary system to fit the need of existing state and further development of tramway network.
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Lin, Shuai, Cheng Xu, Lipei Chen, Siqi Li, and Xiaohan Tu. "LiDAR Point Cloud Recognition of Overhead Catenary System with Deep Learning." Sensors 20, no. 8 (2020): 2212. http://dx.doi.org/10.3390/s20082212.
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High-speed railways have been one of the most popular means of transportation all over the world. As an important part of the high-speed railway power supply system, the overhead catenary system (OCS) directly influences the stable operation of the railway, so regular inspection and maintenance are essential. Now manual inspection is too inefficient and high-cost to fit the requirements for high-speed railway operation, and automatic inspection becomes a trend. The 3D information in the point cloud is useful for geometric parameter measurement in the catenary inspection. Thus it is significant to recognize the components of OCS from the point cloud data collected by the inspection equipment, which promotes the automation of parameter measurement. In this paper, we present a novel method based on deep learning to recognize point clouds of OCS components. The method identifies the context of each single frame point cloud by a convolutional neural network (CNN) and combines some single frame data based on classification results, then inputs them into a segmentation network to identify OCS components. To verify the method, we build a point cloud dataset of OCS components that contains eight categories. The experimental results demonstrate that the proposed method can detect OCS components with high accuracy. Our work can be applied to the real OCS components detection and has great practical significance for OCS automatic inspection.
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Białoń, Andrzej, and Łukasz Zawadka. "Development issues of catenary surge protection system based on a varistor surge arresters." AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe 19, no. 6 (2018): 43–46. http://dx.doi.org/10.24136/atest.2018.034.
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The article presents na issue of determinating an optimal distance between varistors located on 3 kV DC catenary. Line attenuation as a function of distance has been determined during preliminary tests for the following measurement configurations: catenary network unloaded (open), catenary network charged by a value of resistance close to the value of wave impedance of the catenary network test section, catenary network charged by a low voltage varistor. The results allowed to estimate the optimal distance between the varistors and they were verified on the catenary network on Żmigród Test Ring using a surge generator with an amplitude of about 15 kV and varistors designed to work in railway enviroment. The methodology and results of these studies were presented and analyzed in this paper.
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Kosarev, A. B., A. V. Barch, and E. N. Rozenberg. "Ensuring electrical safety of power supply systems of electrified AC railways for highspeed lines." Vestnik of the Railway Research Institute 77, no. 6 (2018): 337–46. http://dx.doi.org/10.21780/2223-9731-2018-77-6-337-346.
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Abstract. High-speed railways are fast-growing and promising type of traffic. In Russia development of high-speed railway service is associated with the solution of a number of problems, including infrastructure. Authors propose to use earth connection of the railway catenary with the help of an artificial earthing switch on currently designed high-speed line Moscow—Kazan for 2×25 kV power supply system. Taking into account requirements for electrical safety conditions for maintenance of the track and earthed catenary supports, paper justifies method for calculating allowable voltages of rail—earth points and supports of catenary. Methods takes into account structural features of ballastless track superstructure used for high-speed lines. It is estimated that the voltages admissible under the electrical safety conditions are random in nature and distributed logarithmically normal. When calculating probability of safe operation, one should take into account random nature of both permissible stresses and those actually occurring on the track. It is estimated that the probability of safe operation in traction networks of sections with ballastless track superstructure does not exceed a similar value in electrified sections with the conventional structure of a ballast prism. Feasibility of using a 2×25 kV earth system using an artificial earth connection is confirmed, recommendations on its use are given. Authors substantiate allowable values of the rail—earth voltage and catenary supports, which practically exclude the occurrence of hazardous situations for personnel maintaining the track in sections with ballastless track superstructure.
10
Huang, Shize, Wei Chen, Bo Sun, Ting Tao, and Lingyu Yang. "Arc Detection and Recognition in the Pantograph-Catenary System Based on Multi-Information Fusion." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (2020): 229–40. http://dx.doi.org/10.1177/0361198120937964.
Full textAbstract:
The pantograph-catenary system is critical to high-speed railways. Electric arcs in the pantograph-catenary system indicate possible damages to the whole railway system, and detecting them in time has been a critical task. In this paper, a fusion method for the pantograph-catenary arc detection based on multi-type videos is proposed. First, convolutional neural network (CNN) is employed to detect arcs in visible light images, and a threshold method is applied to identify arcs in infrared images. Second, the CNN-based environment perception model is established on visible light images. It obtains the dynamical adjustment of the reliability weights for different scenarios where trains usually work. Finally, the information fusion model based on evidence theory uses those weights and integrates the detection results on visible light images and infrared results. The experimental results demonstrate the fusion method can avoid misjudgments of the two individual detection methods in certain scenarios, and perform better than each of them. This approach can adapt to the complex environments of high-speed trains.