Pantograph-catenary Contact Force Research Articles

A Reinforcement Learning-Based Pantograph Control Strategy for Improving Current Collection Quality in High-Speed Railways.

In high-speed railways, the pantograph-catenary system (PCS) is a critical subsystem of the train power supply system. In particular, when the double-PCS (DPCS) is in operation, the passing of the leading pantograph (LP) causes the contact force of the trailing pantograph (TP) to fluctuate violently, affecting the power collection quality of the electric multiple units (EMUs). The actively controlled pantograph is the most promising technique for reducing the pantograph-catenary contact force (PCCF) fluctuation and improving the current collection quality. Based on the Nash equilibrium framework, this study proposes a multiagent reinforcement learning (MARL) algorithm for active pantograph control called cooperative proximity policy optimization (Coo-PPO). In the algorithm implementation, the heterogeneous agents play a unique role in a cooperative environment guided by the global value function. Then, a novel reward propagation channel is proposed to reveal implicit associations between agents. Furthermore, a curriculum learning approach is adopted to strike a balance between reward maximization and rational movement patterns. An existing MARL algorithm and a traditional control strategy are compared in the same scenario to validate the proposed control strategy's performance. The experimental results show that the Coo-PPO algorithm obtains more rewards, significantly suppresses the fluctuation in PCCF (up to 41.55%), and dramatically decreases the TP's offline rate (up to 10.77%). This study adopts MARL technology for the first time to address the coordinated control of double pantographs in DPCS.

Non-contact detection method for pantograph-catenary contact force based on image processing

This paper introduces a non-contact method for detecting contact force between pantograph and catenary (PAC), based on image processing and Kalman filter. A non-contact method for detecting contact force of PAC, which only utilizes the vertical displacement of the collector head, is proposed. First, the images of the collector head area are collected by adding an image acquisition system on the roof of the vehicle. Second, combined with target tracking and template matching, the vertical displacement of the pantograph’s collector head is identified. Finally, based on the Kalman filter considering least squares method and the PAC dynamics model, a method for detecting contact force is constructed. The estimation of the PAC’s dynamic contact force is realized only by using the vertical displacement of the collector head obtained from the image identification. The results of simulation and test-bed results show that the Kalman filter considering least squares significantly has higher accuracy and better robustness compared with the traditional Kalman filter.

Pantograph–Catenary Interaction Prediction Model Based on SCSA-RBF Network

As a traditional numerical simulation method for pantograph–catenary interaction research, the pantograph–catenary finite element model cannot be applied to the real-time monitoring of pantograph–catenary contact force, and the computational cost required for the multi-parameter joint optimization of the pantograph–catenary system with the finite element model is very high. In this paper, based on the selective crow search algorithm–radial basis function (SCSA-RBF) network, the time-domain signal of the panhead acceleration, which can be obtained in real-time through non-contact test technology, is taken as the boundary condition to directly solve the pantograph dynamic equation and a data-physics coupling model that can quickly predict the pantograph–catenary interaction is proposed. The prediction model is trained and verified using the dataset generated through the finite element model. Furthermore, the prediction model is applied to the multi-parameter joint optimization of six pantograph dynamic parameters and nine pantograph dynamic parameters, considering nonlinear panhead stiffness, and optimization suggestions under various speeds and filtering frequencies are given.

Dynamic Parameter Optimization of High-Speed Pantograph Based on Swarm Intelligence and Machine Learning

Good pantograph–catenary interaction quality is a fundamental premise for ensuring stable and reliable current collection of high-speed trains, and the optimization of dynamic parameters of high-speed pantographs provides an effective approach to improve the current collection quality of the pantograph–catenary system. In this paper, with the objective of minimizing the standard deviation of the pantograph–catenary contact force, the multi-parameter joint optimization for pantograph at different filtering frequencies and running speeds was carried out by using swarm intelligence optimization algorithm and artificial neural network method. First, the selection operator in genetic algorithm (GA) was introduced into crow search algorithm (CSA), and the selective CSA was proposed, which can effectively improve the solution accuracy and convergence rate of multi-parameter optimization. Second, a radial basis function (RBF) neural network was used to construct a surrogate model of the standard deviation of contact force with respect to the running speed and pantograph dynamic parameters, and a method for optimizing the upper limit of mapping interval of the decision variables by the selective crow search algorithm (SCSA) was proposed, which effectively improves the generalization ability of the surrogate model. Finally, by combining the surrogate model and SCSA, optimization iterations for a total of 630 combined conditions such as cut-off frequency, running speed and pantograph dynamic parameters were conducted, and an optimization method for high-speed pantograph dynamic parameters with universal applicability was proposed.

Active pantograph in high-speed railway: Review, challenges, and applications

The pantograph–catenary system (PCS) vibration causes the pantograph–catenary contact force (PCCF) to fluctuate, deteriorating current collection quality and damaging the electrical equipment. The active pantograph is one of the most promising methods for suppressing PCS coupling vibration and improving the current collection quality of high-speed trains. This paper first summarizes the research progress of five critical links in the active pantograph, including PCS modeling, control algorithm, hardware support, and HIL test verification. Then, the impact of the PCS model on numerical simulation accuracy and calculation time, the pros and cons of different control algorithms, and the execution mechanism selection are discussed. Finally, the active pantograph’s future development trend and research direction are prospected, such as model optimization, algorithm design, and signal correction. The analysis results show that establishing the PCS model should consider the representation of system dynamics and calculation efficiency. Control targets need to reflect the current collection quality comprehensively, and the measurement system needs to minimize the effect of locomotive disturbances on the observation results. The actuator structure needs to execute the control commands efficiently and quickly without affecting the operation of the raising mechanism. These factors, together with the real-time control algorithm, determine the practical effectiveness of the active pantograph.

1D CNN Based Detection and Localisation of Defective Droppers in Railway Catenary

Defective droppers pose a significant threat to the performance of the contact between the train pantograph and railway catenary. In this paper, the impact of damaged droppers on the performance of pantograph–catenary interaction behaviour is analysed, and the impact of varying degrees of damage to each dropper is labelled. To improve the classification accuracy when both the damage degree and position are considered, a model integrating multiple 1D CNNs is proposed. Approaches including randomly searching the optimal hyper-parameters and K-fold cross-validation are used to prevent overfitting and to ensure model performance regardless of the training data subset selected. Compared with a conventional 1D CNN, the classification performance of the integrated method is demonstrated using the metrics accuracy, F1-score, precision and recall. It is concluded that, through the use of the integrated 1D CNN, damaged droppers can be detected and localised based on the pantograph–catenary contact force. Hence, intelligent catenary inspection can be enhanced.

Surrogate modelling of railway pantograph-catenary interaction using deep Long-Short-Term-Memory neural networks

The interaction performance of the pantograph-catenary is of great importance as it directly determines the current collection quality and operational safety of trains. The finite element method (FEM) is dominantly used for simulating pantograph-catenary interaction, which is normally computationally heavy. In this work, addressing the tremendous computational cost of FEM models, a surrogate model for fast simulations of pantograph-catenary interaction is proposed using deep learning. A dataset containing 30,000 cases of pantograph-catenary interaction is generated by a validated FEM model. A Long-Short-Term-Memory (LSTM) neural network is proposed to learn the inherent nonlinearity between the input model parameters and the output pantograph-catenary contact force from data. The resulting prediction performance indicates that contact forces predicted by the surrogate model are consistent with those simulated by FEM, while the computational efforts of the surrogate model are negligible compared with FEM. Prediction performances using different network architectures and configurations are compared to determine the optimal setting for a pantograph-catenary system. The LSTM-based surrogate model shows high efficiency for simulating pantograph-catenary interactions and promising practicability in optimising catenary structural parameters for design or upgrade.

Pantograph Catenary Contact Force Regulation Based on Modified Takagi-Sugeno Fuzzy Models

In this paper, a new contact force control technique, based on the modified Takagi-Sugeno model and the parallel distributed compensation concept is developed to suppress vibrations between the pantograph and the catenary by regulating the contact force to a reference value, thereby achieving stable current collection. The proposed method uses simple and standard PID and modified Takagi-Sugeno fuzzy controllers. The two controllers guarantee the designed system's robust stability. Furthermore, based on a simplified pantograph–catenary system model, the comparative simulation results show that variations of the contact force can be almost attenuated. As a result, the system stability is guaranteed, and the performance robustness is verified.

Disturbance Observer-Based Sliding Mode Controller for Regulating Pantograph–Catenary Contact Force

For most electrified railways, pantographs play a vital role in transmitting energy from overhead line to vehicles, and therefore a stable and continuous contact behavior is required. This paper proposes a disturbance observer-based sliding mode controller (DO-SMC) for the problem of pantograph–catenary contact force regulation. The simulation results show that the DO-SMC with a chattering alleviation approach can effectively reduce contact force fluctuation through a reasonable control input.

Deep Reinforcement Learning Based Active Pantograph Control Strategy in High-Speed Railway

The pantograph-catenary system (PCS) is the essential power supply system in the high-speed railway, but its coupling performance is influenced significantly by the rapidly increasing train speed. The actively controlled pantograph is one of the promising technologies to suppress the fluctuation of the pantograph-catenary contact force (PCCF). In this paper, we propose a novel pantograph control strategy based on deep reinforcement learning (DRL) to overcome the complex time-varying characteristic of PCS, which distorts the system identification of the classical control methods. First, a non-linear pantograph-catenary system model is established based on the finite element and multi-body dynamics theory as the simulation environment in DRL. Then, the state space, action space, and reward in DRL are redesigned to train the agent, which is suitable for PCS. Finally, the effectiveness and robustness of our proposed method are verified under various working conditions and parameter disturbances. The experiment results show that our control strategy can reduce the PCCF fluctuation up to 40% and reject parametric perturbation while achieving state-of-the-art performance on the benchmarks.

LQR Active Control of Fractional-Order Pantograph-Catenary System Based on Feedback Linearization

Fractional-order calculus has exclusive advantages in modeling the viscoelastic components with obvious fractional-order characteristics such as air springs and metal rubbers in the pantograph structure. In this paper, the air spring is tested, and fractional-order calculus is applied to the modeling of pantograph-catenary system of the high-speed train. The parameter identification method of fractional-order derivative is analytically derived. The traditional lumped mass model is improved and a coupling two-degree-of-freedom model of the fractional-order pantograph-catenary system is established. The fractional-order derivative term in the pantograph-catenary model is approximately calculated by the Oustaloup filter algorithm. Taking the time-varying nature into consideration, the catenary is treated as an extended variable to obtain an augmented model. On this basis, the system is linearized based on differential geometry theory, and an LQR controller is designed to control the pantograph-catenary system. The feedback linearized LQR control and PID control are used to control the same type of traditional pantograph, and the results are compared. Meanwhile, the control effects of feedback linearized LQR control under different pantograph parameters and at different train speeds are analyzed. The results show that the feedback linearized LQR control can present a much better control performance than PID control, and the pantograph-catenary contact force and pantograph head vibration amplitude are both reduced obviously. Even at different train speeds or under different pantograph parameters, it can also effectively reduce these control indexes and provide more robust control performance. These results help to put forward new control ideas and theoretical basis for the vibration control of the pantograph-catenary or similar dynamical system.

Study of Time-Frequency Characteristics of Contact Force Signal and Parameter Sensitivity of Catenary of High-Speed Railway

With the increasing train speed, catenary fluctuation and pantograph vibration are intensified, the pantograph–catenary contact force (PCCF) at the dropper point increases, and the current collection quality of pantograph–catenary contact deteriorates. This study performs the location analysis of the PCCF characteristics based on the simulation method to reduce the PCCF value at the dropper point. First, the key wavelength component and the corresponding amplitude component (ac) of the PCCF at the dropper point were located using the time-frequency representation, which is the continuous wavelet transform (CWT). It was found that the PCCF signal at each dropper point considered the dropper spacing wavelength (DW) and span wavelength (SW) as the time-frequency characteristics (TFC) components; however, its contribution to the current collection quality for each dropper point was different. Second, the ac change rule of the DW and SW was analyzed by changing the tension and linear density of the catenary. Third, the sensitivity analysis method was used to quantitatively analyze the relationship between the catenary design parameters and the ac of the PCCF at the dropper point. Moreover, the quantitative analysis of PCCF was conducted based on the positioning analysis. It is concluded that the influence of catenary tension and linear density of messenger wire on the key ac is significant. Finally, the catenary structure was optimized via the parameter sensitivity coefficient when the train was running at 450 km/h speed. The results show that the current collecting quality of pantograph–catenary is improved effectively.

An Investigation on the Current Collection Quality of Railway Pantograph-Catenary Systems With Contact Wire Wear Degradations

In railway pantograph-catenary systems, the contact surfaces undergo wear in long-term operations, directly affecting interaction performance and potentially deteriorating the current collection quality. The effect of contact wire wear (CWW) on the current collection quality should be evaluated to understand the system’s health status in operations. This article presents a stochastic analysis of the pantograph–catenary interaction performance with different levels of CWW based on four years of measurement data. The power spectral density (PSD) estimation is carried out on the measured CWW to obtain their frequency representations. The random time histories of CWW are generated based on the PSDs. A nonlinear finite element model of catenary with a lumped-mass pantograph is built. Using the Monte Carlo method, the stochastic analysis of pantograph-catenary contact force is carried out to investigate the distribution and dispersion of assessment indices with different levels of CWW. The results indicate that the CWW mainly affects the maximum and minimum contact forces instead of the contact force standard deviation. The optimal pantograph–catenary interaction performance is observed certain years after CWW is formed, depending on the traffic density of the railway line, which is at the second year in the presented case study. Then, the performance declines with an increase in service time. Also, higher operating speed causes a more significant dispersion in assessment indices representing a lower current collection quality, particularly at the maximum operating speed (70% of the catenary wave propagation speed).

A Bayesian Network Approach for Condition Monitoring of High-Speed Railway Catenaries

The growing variety of data from condition monitoring of high-speed railways offer unprecedented opportunities to improve railway infrastructure maintenance. For condition monitoring of railway catenaries, this paper proposes a data-driven approach that uses a Bayesian network (BN) to integrate the inspection data from catenaries into a key performance indicator (KPI). The BN topology is structured based on the physical relationships among data types, including train speed, dynamic stagger and height of the contact wire, pantograph head acceleration, and pantograph-catenary contact force. The tailored performance indicators are individually defined and extracted from the five types of data as the BN input. As the output of the BN, the KPI is defined as the overall condition level of the catenary considering all defects that can be reflected by the data types. Finally, using historical inspection data and maintenance records from a section of the Beijing-Guangzhou high-speed line in China, the BN parameters are estimated to establish a probabilistic relationship between the input and output. An approach that applies the estimated BN to catenary condition monitoring is proposed. Testing of the BN-based approach using new inspection data shows that the output KPI can adequately represent the catenary condition, leading to a nearly 66.2% reduction in the false alarm rate of defect detection compared with current practice. It is also tested that when the input data quality is not ideal, the approach can still work acceptably on noisy data with a signal-to-noise ratio greater than 3 dB or with one type of data missing.

Study on Characteristics Location of Pantograph–Catenary Contact Force Signal Based on Wavelet Transform

With rising of the running speed of the train, the variation of pantograph–catenary contact force (PCCF) signal increases and the current collection quality between pantograph and catenary becomes worse. In order to explore the ways to optimize the PCCF signal, localization analysis of the value and the change of PCCF signal at the dropper-point are carried out using the method of simulation research in this paper. First, the continuous wavelet transform is adopted, and the variation of the PCCF signal of each dropper-point at the critical frequency is analyzed based on the time–frequency characteristics. It is obtained that the PCCF signal at the dropper-point is characterized by the amplitudes of the wavelength of dropper-spacing and span, in which the contribution degrees are different. Second, the methods of wavelet ridge and the Lipschitz exponents are adopted to analyze the change rate of PCCF signal based on the singularity. It is obtained that the declining rate of PCCF signal on the right side at the dropper-point is greater than the rising rate on the left side when the pantograph runs from the left of the dropper to the right. Finally, the relationship between the amplitude and the change rate of the PCCF signal and the catenary tension is discussed. The results show that increasing the contact wire tension and decreasing the messenger wire tension can reduce the value and the change rate of the PCCF signal at the dropper-points so that the current collection quality between pantograph and catenary is improved.

Wavelength Component Analysis of the Pantograph-catenary Contact Force Based on EEMD-SPWVD

The contact force between pantograph and catenary in high-speed railways is an important index to characterize the quality of current receiving. In this paper, the EEMD-SPWVD analytic method was proposed to analyze the inherent and abnormal wavelength components of pantograph-catenary contact force (PCCF). Catenary structure Wavelength (CSW) was analyzed as SS400+ pantograph matches with the catenary mentioned in this paper, and the results show that CSW is mainly related to the parameters of the catenary. Then the DSA380 pantograph is used to make a comparative analysis, and the same conclusion is obtained. Finally, taking the irregularity of the contact wire as an example, the abnormal wavelength components are detected. The Non-CSWresidual detection method proposed in this paper is more accurate and effective than the single SPWVD method.

Design and testing of fibre Bragg grating force transducers for the measurement of pantograph–catenary contact force

This paper deals with the design, development and testing of a novel force transducer based on fibre-optic technology, for the measurement of contact force between a pantograph and an overhead line. Due to the particular application, in which part of the measurement chain is at high voltage and part is at ground potential, fibre-optic technology has the advantage of making the set-up easier to install and to manage with respect to the adoption of classical electrical-based transducers. Fibre Bragg grating is used as detectors in strain-based force transducers developed for this purpose. Considering that the force transducers become part of the connection between each collector of the pan head and the suspension, a proper design matching many conflicting requirements, such as encumbrance, mass, static and fatigue strength and sensitivity, is necessary. Laboratory tests and in-line tests proved the suitability of the optical force transducers. In particular, tests demonstrated that optical transducers represent an alternative to the classical electrical-based transducers for pantograph–catenary force measurement, reducing the complexity of the complete measurement set-up.

A temperature-compensated fiber Bragg grating sensor system based on digital filtering for monitoring the pantograph–catenary contact force

Optical sensors based on fiber Bragg gratings have become an important type of sensing element for strain measurements. In this study, fiber Bragg grating strain sensors and corresponding reference temperature sensors were integrated into a pantograph strip. The results of an online test indicated that the temperature of the pantograph strip impacting the strain measurement reaches about 80 ℃ while the vehicle was running. In addition, Fourier analysis showed that the energies of the temperature measurement signals dominated the relatively low-frequency band (less than 0.02 Hz), whereas the strain signals prevailed in the relatively high-frequency band. Thus, a novel method based on a digital filtering technique was proposed for temperature compensation in fiber Bragg grating sensor systems for monitoring the conditions in electrified pantograph–catenary systems. A Butterworth high-pass filter was designed to reject the temperature-related signal component with a stopband and to capture the real strain in the passband in frequency domain. To achieve this filtering, the cutoff frequencies and the filter order were calculated adaptively according to the frequency-domain characteristics of the measured temperature signal. With the designed filter, the temperature effect to the strain signals can be eliminated so that the strain can be estimated accurately. In comparison with the traditional temperature compensation technique, the proposed method is more effective in terms of estimating the real strain of the pantograph strip in practical applications. Compensated by the proposed method, the time-domain and frequency-domain analyses of the contact force denote the frequencies corresponding to the support span, and the dropper can be distinguished. Further, the first-order (4 Hz) and second-order (8.3 Hz) natural frequencies of the pantograph are visible in the measurements from catenary sections, which demonstrates the sufficiency and rationality of the proposed temperature compensation method for fiber Bragg grating sensor systems.

Influence of typical faults over the dynamic behavior of pantograph-catenary contact force in electric rail transport

The quality of electric energy capture and also the equipment operational safety depend essentially of the technical state of the contact line (CL). The present method for determining the technical state of CL based on advance programming is no longer efficient, due to the faults which can occur into the not programmed areas. Therefore, they cannot be remediated. It is expected another management method for the repairing and maintenance of CL based on its real state which must be very well known. In this paper a new method for determining the faults in CL is described. It is based on the analysis of the variation of pantograph-CL contact force in dynamical regime. Using mathematical modelling and also experimental tests, it was established that each type of fault is able to generate ‘signatures’ into the contact force diagram. The identification of these signatures can be accomplished by an informatics system which will provide the fault location, its type and also in the future, the probable evolution of the CL technical state. The measuring of the contact force is realized in optical manner using a railway inspection trolley which has appropriate equipment. The analysis of the desired parameters can be accomplished in real time by a data acquisition system, based on dedicated software.

Sliding Mode Control with PD Sliding Surface for High-Speed Railway Pantograph-Catenary Contact Force under Strong Stochastic Wind Field

As is well known, the external disturbance (especially the stochastic wind load) has nonnegligible effect on the operation of pantograph-catenary system, which may cause the strong fluctuation in contact force as well as the increased occurrence of contact loss. In order to improve the current collection quality of a high-speed railway pantograph-catenary system under a strong stochastic wind field, a sliding mode controller with a proportional-derivative (PD) sliding surface for a high-speed active pantograph is proposed. The nonlinear finite element procedure is employed to establish the catenary model. The fluctuating wind speeds along catenary are simulated using empirical spectrums. The buffeting forces exerted on contact and messenger wires are derived to construct the stochastic wind field along the catenary. A PD sliding surface is properly determined to guarantee that the mechanical impedance of pantograph head at the dominant frequencies of contact force decreases when the sliding surface approaches zero. Through several numerical simulations with different wind velocities and wind angles, the control performance of two popular control laws (proportional switching law and constant switching law) is evaluated.