Railway Pantograph Research Articles

Modelling of a high-speed railway pantograph with non-linear head-suspension mechanism and parameter optimisation

AbstractAccurate pantograph models are crucial to obtain reliable simulations of the pantograph-catenary dynamic interaction. Non-linearities can make it a challenge to find a model design that fits the dynamic behaviour of the real pantograph. In this work, we propose a novel pantograph model including a particular non-linear mechanism, whose dynamic behaviour significantly affects the pantograph response. This mechanism is composed of two rigid bars and an oblique pre-stressed spring with dry friction and exhibits a complex non-linear behaviour. The objective is to design a model capable of reproducing the behaviour of the real pantograph, which is represented by the dataset of dynamic measurements in the pantograph tests. From a proper parametric representation of the model, the optimisation of the parameters by a genetic algorithm has achieved a good agreement with the experimental data. The resulting optimised model behaves similarly to the real pantograph for a wide range of excitations that vary in type, amplitude and position. Since the higher number of simulations performed in the optimisation makes it necessary to use an efficient simulation tool, we propose an efficient strategy to integrate systems with Coulomb’s friction.

Effects of Carbon Type and Composition on the Properties of Carbon-Copper Composite as Pantograph Slide in Railway Application

Carbon-copper composites have wide application prospects as high-speed railway pantograph slides due to the self-lubricating ability of carbon and good conductivity of copper. However, carbon-copper composites produced through powder metallurgy may still encounter challenges, such as poor wettability and lower conductivity. The experimental approach in this work involved the fabrication of carbon-copper composites using the warm compaction method, with different types and proportions of carbon materials, namely local carbon from palm kernel shells (PKS) and graphite. Characterisation and testing of hardness, density, resistivity, transverse rupture strength (TRS), and microstructure of the composites have been conducted. An increase in graphite content was found to improve the electrical conductivity of the carbon-copper composite, while the addition of local carbon has enhanced its hardness. Furthermore, the addition of graphene oxide (GO) as filler has significantly improved the mechanical strength of this composite by up to 61.34%. This research has highlighted the potential of locally sourced carbon for developing advanced pantograph slide materials for railway applications. The findings provided valuable insights into the optimisation of composite compositions to achieve the desired balancebetween electrical conductivity and mechanical performance. These carboncopper composites hold the promise of more efficient and durable pantograph slides, which can contribute to the overall reliability and sustainability of railway systems.

Skyhook-PID Controller for Active Railway Pantograph

Skyhook-PID Controller for Active Railway Pantograph

Leveraging systems’ non-linearity to tackle the scarcity of data in the design of intelligent fault diagnosis systems

Deep transfer learning (DTL) allows for the efficient building of intelligent fault diagnosis systems (IFDS). On the other hand, DTL methods still heavily rely on large amounts of labelled data. Obtaining such an amount of data can be challenging when dealing with machines or structures faults. This document proposes a novel approach to the design of vibration-based IFDS using DTL in condition of strong data scarcity. A periodic multi-excitation level procedure leveraging intrinsic non-linearities of real-world systems is used to produce images that can be conveniently analysed by pre-trained Convolutional Neural Networks to diagnose faults. A new data visualization method and its augmentation technique are proposed in this paper to tackle the typical lack of data encountered during the design of IFDS. Experimental validation on a railway pantograph structure provides effective support for the proposed method.

High Precision Robust Real-Time Lightweight Approach for Railway Pantograph Slider Wear Estimation

High Precision Robust Real-Time Lightweight Approach for Railway Pantograph Slider Wear Estimation

Intelligent fault diagnosis of railway pantograph using a novel graph construction methodology

Railway pantographs provide power for railway vehicles by conducting electrical energy from overhead catenary. The failure of the pantograph tends to damage the contact quality between the pantograph and the catenary, reducing the transmission efficiency of electric energy. Hence, fault diagnosis of pantograph plays a significant role in expanding the service life of railway vehicles. In this work, a novel graph construction method is proposed for the fault diagnosis of pantographs combined with a graph neural network (GNN). In the graph construction method, 1D load signals collected from the test pantograph are firstly transformed into multiple 2D images with the same size in both time and frequency domains using Gramian angular field, Markov transition field and recurrence plot. Secondly, pixel values in images are regarded as features in vertexes of graphs, and graphs can be constructed by connecting neighbor vertexes. Finally, the GNN model is trained by constructed graphs for obtaining the fault diagnosis model of pantographs. Laboratory experiments are implemented to show the advantages of the proposed method by comparing it with other conventional methods.

Structural Performance Analysis and Optimization Design of Railway Pantograph Under High-Speed Operating Conditions

Structural Performance Analysis and Optimization Design of Railway Pantograph Under High-Speed Operating Conditions

Time delay in a mechatronic Power-HIL system: Analysis and model-based compensation

The Power-Hardware-in-the-Loop (PHIL) methodology enables testbed solutions that support the development of complex mechatronic components. In PHIL testing, a unit under test (UUT) is coupled with a virtual representation of its surroundings. As an example, a real railway pantograph current collector UUT can be tested in real-time interaction with a virtual overhead catenary. However, due to the closed-loop feedback interconnection and the exchange of power between real and virtual systems, such a PHIL control structure is highly sensitive to time delays in the signal paths which limits its performance, accuracy, and stability. In this work, methods to evaluate and compensate for the effect of time delays in a typical PHIL structure are proposed. A model-based PHIL control system is introduced to demonstrate the effect of time-delay compensation techniques, including utilising specific reduced-order models to achieve efficient time-delay compensation. The performance of the control system is demonstrated and validated via simulations and experiments on a scaled PHIL test setup, which is related to railway pantograph testing. In addition, criteria to analyse system stability are formulated and demonstrated with respect to uncompensated time delays and unknown UUT contact stiffness.

Analysis of European Systems for Checking and Monitoring of Railway Pantographs: An Opportunity for Indian Railway

Analysis of European Systems for Checking and Monitoring of Railway Pantographs: An Opportunity for Indian Railway

Detecting early damages in the railway pantograph mechanism: a multiple excitation approach for the frequency domain

In this work, we address the problem of damage diagnosis on the railway pantograph mechanism including nonlinear behaviour and sample-induced uncertainties. In particular, we discuss an experimental campaign in which investigation pursued the analysis of frequency response functions estimated by a dedicated inspection robot that we intentionally developed for vibration tests on pantographs. Special focus is pointed to the inherent nonlinear behaviour of the pantograph for which we estimated the damage index for different levels of the input excitation. The investigation is carried out on a population of pantographs of the same type and studying three kinds of damages. Results highlight the relevance of including several excitation levels and encourage investigation in a real operational scenario.

Hardware-in-the-loop simulations of a railway pantograph with a finite element periodic catenary model

The pantograph-catenary dynamic interaction problem is addressed by Hardware-in-the-Loop (HIL) tests to simulate the dynamic interaction between a numerical model (the catenary) and a physical device (the pantograph). The real-time simulation requires a computationally efficient numerical model and an on time and accurate transference of the response to the pantograph, for which a Periodic Finite Element Model (PFEM) of the catenary is considered. Firstly because of the acceptable computation time required to solve it, makes it suitable for real-time simulations and, secondly, its ability to allow for the delay caused by the transfer of the numerical model response. The catenary PFEM we used considers the non-linear behaviour of the dropper slackening, leading to highly accurate HIL test results, which were validated up to a frequency of 25 Hz.

Damage Caused by Material Defects of Carbon Composites Used on Various Types of Railway Pantographs.

Mainstream materials of the railway pantograph strips are carbon composites. They are subject to wear during use, as well as various types of damage. It is important that their operation time is as long as possible and that they are not damaged, as it may damage the remaining elements of the pantograph and the overhead contact line. As part of the article, three types of pantographs were tested: AKP-4E, 5ZL, and 150 DSA. They had carbon sliding strips made of MY7A2 material. By testing the same material on different types of current collectors, it was possible to check what impact the wear and damage of the sliding strips has on (among others) the method of their installation, i.e., whether the damage to the strips depends on the type of current collector and what is the participation of damage caused by material defects. As a result of the research, it was found that the type of pantograph on which it is used has an undoubted influence on the damage characteristics of the carbon sliding strips, whereas the damage caused by material defects can be classified as a more general group-the group of damage of a sliding strip, which also includes overburning of a carbon sliding strip.

The Electrical Behaviour of Railway Pantograph Arcs

Electric arcing is an unavoidable consequence of the current collection process by sliding contact in railways and metros, and in general in many electrified transportation systems (ETSs). The most relevant consequences in an electrical perspective are: the occurrence of transients triggering resonant behaviour and transient responses, reduction of the energy efficiency of the system, conducted and radiated disturbance, in particular for the new radio systems widely employed for signalling and communication. The involved parameters are many (type of materials, current intensity, DC and AC supply, relative speed, temperature), as well as the studied characteristics (arc instability and lifetime, dynamic behaviour, electrical system response, radiation efficiency and coupling to external radio systems). This work reports the state of the art in arc modelling, arcing experimental characterisation, interaction with the supply system, radiated emissions and disturbance to radio systems, providing a complete description of phenomena and of reference data, critically discussing similarity and differences between sources. Proposed arc models are many with different assumptions and simplifications for various applications, so that a critical review and discussion are a necessity, considering the many different approaches and not-so-obvious applicability. The comparison with experimental results highlights unavoidable discrepancies, also because of intrinsic arc variability and for the many involved parameters and operating conditions. The impact of the arc as embedded in the railway system is then considered, speaking of conducted and radiated phenomena, including interference to radio communication systems and arc detection. The most prominent effect for conducted emissions is the excitation of system resonances, including the LC filters onboard rolling stock and substations in DC railways, with consequences for disturbance and energy efficiency, and this is discussed in detail. Conversely, for high frequency emissions, the attenuation along the line circuit is significant and the effective distance of propagation is limited; nevertheless radiated electromagnetic field emissions are a relevant source of disturbance for radio systems within the ETS premises and outside (e.g., at airports). The published approaches to quantify performance reduction are discussed with emphasis on experimental methods.

Condition Monitoring of Railway Pantograph Using R-CNN and Image Processing

Condition Monitoring of Railway Pantograph Using R-CNN and Image Processing

Modelling a uniaxial inerter in a 2D or 3D environment: Implications of centripetal acceleration

The inerter completes the force-current analogy between mechanical and electrical components, providing the mechanical equivalent to the capacitor. As such, it is a two-terminal passive element that, when implemented ideally, is normally said to generate a force proportional to the relative acceleration between its two terminals. However, this is applicable only if the inerter does not rotate, so the only relative motion between the device's terminals is axial. In many applications, this restriction is acceptable, such as in car suspension systems. However, in this paper, it is shown that the relationship between the terminal accelerations and the generated force is more complex if the inerter is used in a 2-dimensional (2D) or 3-dimensional (3D) environment, such as within a multi-bar mechanism (e.g., robotic arms or railway pantographs). Specifically, the inerter force is not given by simply the relative acceleration between the two terminals. The centripetal acceleration, resulting from the rotation of the inerter, needs to be accounted for to find the second derivative of the inerter length, which defines the generated force. Two case studies are presented to demonstrate the effects of this normally neglected centripetal acceleration term. It is shown that when an inerter is operating in a 2D or 3D environment, significant errors may occur in evaluating the inerter force and also the system response if the centripetal acceleration term is neglected. Equations are provided for both modelling the inerter in different coordinate systems and for incorporating the inerter in 2D and 3D multibody systems.

Microstructure and properties of C/C-CuNi composites fabricated by carbothermal reduction of hydrothermal co-deposited oxides

A novel hydrothermal co-deposition method was proposed to fabricate C/C-CuNi composites as high-speed railway pantograph strip. The bulk density of composites reached 1.83 g/cm3 with 5 cycles of co-deposition. The effect of Ni addition on the microstructure and properties of the composites was investigated. The Ni addition not only improves the graphitic degree of the carbon matrix but also enhances the fiber/matrix interface bonding. The composites presented outstanding properties when the Ni/Cu molar ratio was 0.6. It possesses high flexural strength (92.4 MPa) and low electrical resistivity (10.78 μΩ m). The friction coefficient was stabilized at 0.223 and wear rate was just 0.45 g h−1 under 10 N applied load. The outstanding tribological performance resulted from the micro-spall fatigue wear and the formation of self-lubricating film owing to the Ni addition. The C/C-CuNi composite provides an attractive high-speed railway pantograph strip material, and the hydrothermal co-deposition method is a feasible strategy to improve the interfacial bonding of Cu-based carbon fiber reinforced composites.

Multi-domain approach to modeling pantograph-catenary interaction

When a railway pantograph interacts with a catenary during the movement of a rail vehicle, several physical phenomena, both mechanical and electrical, occur in the system. These phenomena affect the quality of power supply of a train from traction devices. The unfavourable arcing occurring when there are disturbances of contact between the pantograph’s slider and the catenary contact wire. In turn, it results in energy loss and increased wear of the components of the system. When designing new solutions, computational models are helpful to predict the quality of interaction between the components of the pantograph-contact line system already at the virtual prototyping stage. In this paper, the authors comprehensively present a multi-domain (multiphysics) model, which takes into account necessary conditions for interaction between pantograph elements and a catenary. Finally, the impact of the individual physical domains are analysed and the ones which have a significant impact on the simulation of the operation results are identified.

Analytics of Waveform Distortion Variations in Railway Pantograph Measurements by Deep Learning

Waveform distortion in general represent a widespread problem in electrified transports due to interference, service disruption, increased losses and ageing of components. Given the multitude of moving sources and the extremely variable operating conditions, short time records must be considered for analysis, and this increases in turn its complexity, from which the need for effective automated processing, as offered by a deep learning (DL) approach. This paper proposes an application of unsupervised DL to measurements of railway pantograph quantities to identify waveform distortion patterns. Data consists of pantograph current from a Swiss 15 kV 16.7 Hz railway system. Three DL input types are considered: waveforms, harmonic spectra, and supraharmonic spectra. The applied DL method applied is the deep autoencoder (DAE) followed by feature clustering, using techniques to define a suitable number of clusters. Short-term distortion is evaluated over sub-10 min intervals of harmonic and supraharmonic spectra down to sub-second intervals. Results are explained among others by connecting the distribution of the clusters (determined by self-supervised method) to the dynamic operating conditions of the rolling stock. Resulting DAE performance are superior in terms of accuracy and comprehensiveness of spectral components compared to a more traditional principal component analysis (PCA) that was chosen as reference for comparison.

Crosswind Effects on Current Collection Quality of Railway Pantograph–Catenary: A Case Study in Chengdu–Chongqing Passenger Special Line

As a common disturbance to the railway pantograph–catenary system, the crosswind usually deteriorates the current collection quality and threats to operational safety. The main topic of this article is to evaluate the effect of crosswind on the interaction performance of pantograph–catenary considering the aerodynamic forces acting on both the pantograph and catenary. The pantograph–catenary system of the Chengdu–Chongqing passenger special line is adopted as the analysis object. The absolute nodal coordinate formulation (ANCF) is employed to model the catenary. The numerical accuracy is validated via the comparison with the field measurement data collected from an inspection vehicle operating at 378 km/h. According to the quasi-steady theory, the wind load acting on the catenary is derived. Computational fluid dynamics (CFD) is employed to calculate the lift and drag forces acting on each component of the pantograph, which are used to derive the equivalent aerodynamic force that can be applied in the lumped-mass model. A special spatial grid is defined for the pantograph–catenary system to generate the fluctuating wind field based on the empirical spectrum. The simulation results indicate that the pantograph–catenary system of Chengdu–Chongqing passenger special railway has an acceptable performance with a crosswind speed of 20 m/s. However, when the crosswind increases up to 30 m/s, some contact force statistics exceed the safety threshold with a turbulence intensity of more than 17%. Through the analysis of the operational safety, it is found that the contact wire always works within the safety range of the pantograph head with a crosswind speed of 30 m/s. However, some safety issues can be seen from the maximum uplift of the pantograph head with a turbulence intensity of more than 21%.

Pantograph Spark Fault Detection using YOLO

Pantograph-catenary is now the dominant form of current collection for modern electric trains because they can be used for higher voltages. Faults in pantograph-catenary systems threaten the operation and safety of railway transportation. They need to be continuously monitored and controlled to maintain safe transport. Pantograph may be damaged as a result of extreme weather conditions which can affect its normal operation, leading to failure of pantograph and overhead contact line systems. Poor contact between pantograph and overhead contact line causes thermal erosion to the wire. When the pantographs are exposed to air, they could deteriorate due to electrochemical reaction with the environment since they are made of metals. Movement of catenary lines and pantograph in high crosswinds has been found to cause the wire to be trapped in the pantograph. There is a serious issue regarding the quality of images generated by pantograph video monitoring system on high-speed railway trains which often shows inconsistencies of catenary faults. The application of traditional image processing and deep learning techniques have been unable to meet the requirements of spark detection. In this paper, a modern deep learning algorithm is proposed to detect sparks in the pantograph. Specifically, the YOLOv3 model is used to counter this problem that traditional image processing algorithms have been unable to. The results on a very large sample of data show the efficiency and real-time performance of the proposed method, which meets the requirements of pantograph spark detection in high-speed railway. Keywords : High-speed railway pantograph; Spark detection; Deep learning; YOLOv3; DOI: 10.7176/ISDE/12-3-02 Publication date: September 30 th 2021