The formation of the delamination wear of the pure carbon strip and its influence on the friction and wear properties of the pantograph and catenary system

Yang, Hang; Wang, Kai; Liu, Yanhua; Fu, Lin; Cui, Xiaolu; Jiang, Gang; Hu, Bo

doi:10.1016/j.wear.2020.203343

Cited by 20 publications

(7 citation statements)

References 25 publications

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“…Thus, the friction coefficient should be considered when the contact mechanical model is established. The results are consistent with reference (Yang et al , 2020).…”

Section: Fractal Contact Resistance Model Considering Self-excited Vi...supporting

confidence: 93%

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Fractal contact resistance model of wind pitch slip ring considering wear and self-excited vibration

Zhang,

Zuo,

Zhou

2024

ILT

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Purpose The purpose of this paper is to reveal the dynamic contact characteristics of the slip ring. Dynamic contact resistance models considering wear and self-excited were established based on fractal theory. Design/methodology/approach The effects of tangential velocity, stiffness and damping coefficient on dynamic contact resistance are studied. The relationships between fractal parameters, wear time and contact parameters are revealed. Findings The results show that the total contact area decreases with the friction coefficient and fractal roughness under the same load. Self-excited vibration occurs at a low speed (less than 0.6 m/s). It transforms from stick-slip motion at 0.4 m/s to pure sliding at 0.5 m/s. A high stiffness makes contact resistance fluctuate violently, while increasing the damping coefficient can suppress the self-excited vibration and reduce the dynamic contact resistance. The fractal contact resistance model considering wear is established based on the fractal parameters models. The validity of the model is verified by the wear tests. Originality/value The results have a great significance to study the electrical contact behavior of conductive slip ring. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2023-0300/

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“…Thus, the friction coefficient should be considered when the contact mechanical model is established. The results are consistent with reference (Yang et al , 2020).…”

Section: Fractal Contact Resistance Model Considering Self-excited Vi...supporting

confidence: 93%

“…Thus, the friction coefficient should be considered when the contact mechanical model is established. The results are consistent with reference (Yang et al, 2020). The relationship between total contact area and load is shown in Figure 3(b).…”

Section: Fractal Contact Resistance Model Considering Selfexcited Vib...supporting

confidence: 90%

Fractal contact resistance model of wind pitch slip ring considering wear and self-excited vibration

Zhang,

Zuo,

Zhou

2024

ILT

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“…In the simulations, the same impact load is applied and the upper surfaces of the positioning support are fixed. The input shocking acceleration spectrum obtained from field testing is applied on the positioning clamp in the vertical direction of 5 , and the acceleration spectrum is given in Figure 13. Different tension force is also applied on the positioning clamp along the axial direction of the steady arm (schematized as 6 ), where tension forces of 0 N, 400 N, 1000 N and 3000 N are adopted.…”

Section: Finite-element Analysis Of Wear Behavior Of Positioning Hookmentioning

confidence: 99%

“…The wear mechanism needs to be further investigated. Most previous studies focus on the tribological performance of strip and contact wire, the fatigue failure of integral droppers [3][4][5], etc. When trains pass by, pantographs impact on the steady clamps and result in rolling and sliding of the positioning hook around the positioning support.…”

Section: Introductionmentioning

confidence: 99%

Influence of Applied Load and Sliding Distance on Wear Performance of AlSi7Mg0.6 Aluminum Alloy

Zhang,

Zhao,

Pan

et al. 2023

Metals

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The wear performance of AlSi7Mg0.6 aluminum alloy, a casting aluminum alloy used in positioning devices for catenary systems of high-speed railways which fail frequently on lines where the speed of trains is higher than 300 m/s, is discussed in this study. It was estimated that sliding contact wear occurred and mainly contributed to the failure. To explore the competing mechanism for frictional wear failure, frictional experiments based on three groups of sliding distance (0.5 mm, 1.5 mm and 3.0 mm) and four groups of applied loads (20 N, 50 N, 100 N and 200 N) were implemented. Three-dimensional morphological observation results revealed that the wear volumes at a sliding distance of 0.5 mm were only about 1/10 of that at a sliding distance of 3.0 mm. It was also revealed that the wear volume based on a sliding distance of 3.0 mm and applied load of 20 N was still much larger than the wear volume under a sliding distance of 0.5 mm and applied load of 200 N. SEM observation of the microstructures revealed that abrasive wear was the dominant wear mechanism in dry sliding friction conditions. A simplified positioning device model was also established to study the influence of tension force on wear performance. The simulation results revealed that smaller tension force between the positioning support and positioning hook would lead to higher relative sliding distance and larger wear depth. Sliding contact friction should be avoided due to relatively large wear efficiency compared with rolling contact friction. Both experimental and simulation results suggested that proper tension force was preferred in assembling components which could ensure rolling contact friction rather than sliding contact friction.

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“…The contact strip of the pantograph is periodically replaced because it wears out owing to frequent contact with the OCL [5]. Deformations such as cracks and chipping often occur on the contact strip owing to friction with fittings on the OCL [6,7]. These deformations affect quality of the power transmission to the railway vehicle because of arcing due to contact loss with the OCL [8].…”

Section: Introductionmentioning

confidence: 99%

Detecting Deformation on Pantograph Contact Strip of Railway Vehicle on Image Processing and Deep Learning

Lee

Shin

et al. 2020

Applied Sciences

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An electric railway vehicle is supplied with electricity by an OCL (Overhead Contact Line) through the contact strip of its pantograph. This transmitted electricity is then used to power the electrical equipment of the railway vehicle. This contact strip wears out due to contact with the OCL. In particular, deformations due to chipping and material loss occur because of friction with the fittings on the OCL. These deformations on the contact strip affect its power transmission quality because of contact loss with the OCL. However, it is difficult to monitor the contact strip during operation and judge its condition in order to implement accident prevention measures. Thus, in this study, we developed a contact strip monitoring method based on image processing for inspection. The proposed method measures the deformation in the contact strip based on an algorithm that determines the wear on the deformed contact strip using deep learning and image processing. The image of the contact strip is acquired by installing a camera and laser to capture the pantograph as it passes the setup. The proposed algorithm is able to determine the wear size by extracting the edges of the laser line using deep learning and estimating the fitted line of the deformations based on the least squares method.

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The formation of the delamination wear of the pure carbon strip and its influence on the friction and wear properties of the pantograph and catenary system

Cited by 20 publications

References 25 publications

Fractal contact resistance model of wind pitch slip ring considering wear and self-excited vibration

Fractal contact resistance model of wind pitch slip ring considering wear and self-excited vibration

Influence of Applied Load and Sliding Distance on Wear Performance of AlSi7Mg0.6 Aluminum Alloy

Detecting Deformation on Pantograph Contact Strip of Railway Vehicle on Image Processing and Deep Learning

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