High-speed Train Research Articles

Unseen Rail Damages Diagnosis Framework Using Mechanism Embedded Generative Network

Abstract Rail damages can pose tremendous hazards for high-speed trains, making damage diagnosis critical in the field of engineering. Currently, deep learning enables an end-to-end approach for rail damage diagnosis. However, the training and test data in real applications are often out of distribution, or even the test data represent fault categories that are previously unseen. To address this situation, an unseen damages diagnosis framework (UDDF) that effectively embeds the mechanism damage features from the simulation signals of all possible damage categories has been proposed. In particular, the mechanism- embedded generative adversarial networks in the UDDF utilize a hierarchical embedding technique to ensure the stability of the mechanism embedding process. In addition, a k-means clustering discriminator uses an unsupervised method to guarantee the minimum intra-category sample spacing of the generated unseen categories. After the generation of all types of damage categories, the generated and existing original data are included as a new dataset for the training of a diagnostic model. The trained diagnostic model can perform classification tasks without acquiring all the types of damage signals in real situations. Finally, the effectiveness of our proposed diagnostic framework is validated through comparative and ablation studies on a dataset that contains finite element simulation and experimental data of ultrasonic guided waves signals with damages at different locations and depths of rails.

Aerodynamic energy consumption analysis of divided evacuated tube transportation system

Evacuated Tube Transportation (ETT) reduces aerodynamic drag and energy consumption by lowering gas pressure around high-speed trains (HSTs). To optimise this effect, integrating the ETT system into high-speed cruise segments is a practical approach, though it may introduce vacuum potential energy losses. To address this, the paper put forward a Divided Evacuated Tube Transportation (D-ETT) system to seamlessly connect open-line and tube operation of HST then the regulations of aerodynamic energy consumption were studied. Theoretical discussions into reasonable parameter range including tube design and HST operation manners were conducted and then formed system-designing strategy. The spatial and temporal distribution law of tube gas circumstances were examined through model testing and numerical simulation. Three-dimensional, unsteady and compressible fluid models were established using Large Eddy Simulation (LES) to analyse tube fluid characteristics. Relative results indicated that under reasonable D-ETT designing strategies with larger blockage ratios, higher HST speeds, larger total mileage and mileage ratio of the mid-section, the aerodynamic energy saving effect is more impressive. The mixing of the adjacent tube gases with differential pressure induced gas-mixing fluctuations then changed the fluid circumstances inside the tube. The positional relationship between HST and gas waves infected aerodynamic energy consumption. By figuring out the spatiotemporal variation of tube gas, the theoretical energy estimation scheme for aerodynamic energy consumption with various cases was put forward, then the rationality and accuracy of which was verified by numerical simulation with prediction error less than 8%. The saving ratio of aerodynamic drag energy consumption of a 10 km tube could be 39.9% compared to traditional tunnels, which will be higher under ultra-long mileage, thus realising the overall aerodynamic energy saving effect. High-amplitude pressure waves intensified the pressure changes around HSTs, making it necessary to use HST capsules with superior sealing performance to ensure eardrum comfort.

Dynamic Performance Assessment of MSE Walls under High-Speed Train Loads

Dynamic Performance Assessment of MSE Walls under High-Speed Train Loads

Comprehensive optimization of dynamic pricing and passenger flow assignment for differentiated high-speed train products

Comprehensive optimization of dynamic pricing and passenger flow assignment for differentiated high-speed train products

Experimental and Numerical Investigation into the Formation Mechanism of Wheel Polygonal Wear of High-Speed Trains with Wheel Flat Excitation

Experimental and Numerical Investigation into the Formation Mechanism of Wheel Polygonal Wear of High-Speed Trains with Wheel Flat Excitation

A tracker pose optimization method for robotic measuring system based on spatial distance constraints

In large-scale metrology (LSM), the transformation of the tracker base frame (TBF) is a predominant method to enlarge the field of view (FOV) of the tracking sensor for full-field 3D measurements. Nevertheless, such a process will introduce cumulative errors and significantly diminish the global point cloud alignment accuracy. To address this problem, we propose a novel tracker pose optimization method for TBF transformation. A pose graph optimization (PGO) model based on spatial distance constraints is implemented to improve the tracker pose accuracy. We also adopt a robust coefficient and a damping factor to simplify the experimental process and stabilize the convergence results. Simulations and experiments on high-speed train surfaces are conducted to validate our method’s accuracy and effectiveness. The results indicate that our optimization method outperforms two existing methods in spatial positioning accuracy and point cloud alignment accuracy, which showcases its practical applicability and superiority in manufacturing scenarios.

Numerical simulation of snow accumulation in bogie area of high-speed trains in CFD-DEM method

Numerical simulation of snow accumulation in bogie area of high-speed trains in CFD-DEM method

Quantitative Evolution of Tribo-Layers in Copper Based Friction Materials for High-Speed Trains Operating at 400 km/h Equivalent Energy Density: Ratio of Formation to Damage

The quantitative Evolution of the braking properties and tribo-layer of copper based friction materials (CBFM) at 400km/h equivalent energy density was investigated. The braking properties of CBFM were determined, with two significant degradations at the 1st and 12th cycles. The ratio of formation to damage of the tribo-layer, t, based on the thickness of the sub-surface of CBFM and wear debris, was defined. The variation of t showed an excellent correlation with the decline in the coefficient of friction. The mechanically mixed layer (MML) deteriorates after the first cycle, evolving into a mixed MML-PDL (plastic deformation layer) structure. The deformed substrate gradually loses hard particles, resulting in a tribo-layer predominantly composed of severely deformed copper, with minimal iron content and numerous defects.

Experimental study on particle deposition behavior in air supply ducts of a high-speed train

Experimental study on particle deposition behavior in air supply ducts of a high-speed train

Robust cooperative tracking control of multiple high-speed trains with nonlinear inherent resistance and disturbance

Robust cooperative tracking control of multiple high-speed trains with nonlinear inherent resistance and disturbance

Fatigue Life Prediction of Wheels for CRH2 High-speed Train Due to Flexible Tracks

Fatigue Life Prediction of Wheels for CRH2 High-speed Train Due to Flexible Tracks

Study on semi-active damping control strategies to improve dynamic behavior of high-speed trains subject to strong crosswinds

The aerodynamic loads on high-speed trains (HSTs) increase as the running speed increases. Particularly, strong crosswinds can significantly increase these loads and generate a safety risk to trains. This paper focuses on the application of semi-active control strategies based on secondary lateral suspension for HST operating in crosswinds, aiming to enhance the running safety of HST. First, a vehicle nonlinear dynamics model with 50 degrees of freedom (DOFs) is established. The aerodynamic loads caused by crosswinds are simulated using Simiu wind spectra, and the track irregularities are acquired through field tests of the high-speed railway line. Second, a semi-active control model is set up using Matlab/Simulink to replace the secondary lateral damper, and the co-simulation for vehicle dynamics and semi-active control is undertaken. Then, the vibration characteristic analysis of the vehicle system caused by aerodynamic loads under crosswind conditions is conducted in both time and frequency domains, while a conventional semi-active control strategy is employed to attenuate the vibrations. Moreover, a single coefficient mixed skyhook and groundhook control strategy (SMSG) regulated by a single mixing coefficient β, and mixed skyhook and acceleration driven damper control strategy (MSA) is proposed. The simulation results demonstrate that the proposed mixed skyhook and groundhook control strategy not only enhances the running safety of the trains in crosswind environments by adjusting the mixing coefficients but also improves ride performance compared to passive suspensions. While the suggested mixed skyhook and ADD control strategy can apparently reduce the vibration of the carbody.

Stochastic Seismic Responses of High-Speed Train–Bridge Systems with Ground Motion Correlation

Stochastic Seismic Responses of High-Speed Train–Bridge Systems with Ground Motion Correlation

UAV selection for high-speed train communication using OTFS modulation

Providing continuous wireless connectivity for high-speed trains (HSTs) is challenging due to their high speeds, making installing numerous ground base stations (BSs) along the HST route an expensive solution, particularly in rural and wilderness areas. This paper proposes using multiple unmanned aerial vehicles (UAVs) to deliver high data rate wireless connectivity for HSTs, taking advantage of their ability to fly, hover, and maneuver at low altitudes. However, autonomously selecting the optimal UAV by the HST is challenging. The chosen UAV should maximize the HST’s achievable data rate and provide an extended HST coverage period to minimize frequent UAV handovers constrained by the UAV’s limited battery capacity. The optimization challenge arises from accurately estimating each UAV’s expected coverage period for the HST, given both are moving at high speeds and the UAV’s flying altitude is unknown to the HST. This paper utilizes the estimated HST-UAV channel parameters in the delay-doppler (DD) domain, employing orthogonal time frequency space (OTFS) modulation, to estimate the relative speeds between the HST and UAVs, as well as the UAVs’ flying altitudes. Based on these estimates, HST can predict the maximum coverage period each UAV provides, allowing for selecting the best UAV while considering their remaining battery capacities. Numerical analysis demonstrates the effectiveness of the proposed approach compared to other benchmarks in various scenarios.

Research on the rapid diagnosis method for hunting of high-speed trains

PurposeHigh-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.Design/methodology/approachFirst, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.FindingsUnder continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.Originality/valueThe research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

Global sensitivity analysis of high-speed train dynamics system with high-dimensional inputs and multiple outputs

A high-speed train dynamics system involves numerous uncertainty parameters, and there are multiple evaluation indices for its dynamic performance. In this paper, we conduct high-dimensional and multi-output global sensitivity analysis for the dynamic performance of high-speed trains by comprehensively considering these dynamics parameters and indices. Firstly, the dynamics simulation model of the high-speed train is established and six dynamics indices for evaluating the safety and comfort of the train are obtained under operating conditions. Subsequently, considering the multi-output and high-dimensional characteristics of train sensitivity analysis, we propose a multi-output global sensitivity analysis method based on the correlation-analysis-guided Kriging model (CA-K). Finally, global sensitivity analysis of 96 uncertainty parameters on six dynamics indices is conducted under three scenarios utilising the proposed method. The results show that (1) CA-K achieves higher accuracy in approximating high-dimensional train dynamics indices than existing conventional surrogate models. (2) The multi-output global sensitivity analysis method can simultaneously identify all important dynamics parameters and exclude unimportant parameters.

Crack detection based on GMM-Wasserstein distance under variable temperature environment

Abstract Abstract: The operation of high-speed trains in dynamic temperature environments presents significant challenges for crack detection in critical aluminum alloy components. It has been demonstrated that temperature fluctuations significantly impact the performance of Lamb wave-based structural health monitoring (SHM) systems, thereby compromising the reliability of damage detection protocols. In response to these challenges, a novel crack detection methodology is introduced, leveraging GMM-Wasserstein distance metrics to address variable temperature conditions. Two innovative information entropy measures are developed: Energy Singular spectral entropy (ESE) and Power Singular spectral entropy (PSE), which are utilized to characterize the complex interactions between Lamb wave signals and crack propagation under thermal variations. To enhance feature extraction robustness, an integrated approach combining Ensemble Empirical Mode Decomposition (EEMD) and Singular Spectrum Analysis (SSA) has been implemented, effectively mitigating temperature-induced signal perturbations. Additionally, a sophisticated GMM-based probability migration analysis framework incorporating Wasserstein distance metrics has been developed to quantify structural damage state evolution. The efficacy of the proposed methodology has been rigorously validated through comprehensive experimentation on Al6061 aluminum plates subjected to temperatures ranging from -40°C to 80°C. Experimental results indicate that the proposed method achieves a classification accuracy of 95.83% in crack detection, representing a significant improvement over conventional approaches.

Dynamic analysis of a new high-speed train model

Dynamic analysis of a new high-speed train model

Investigation into the reduction of aerodynamic drag via external windshields on high-speed trains

As train speeds increase, aerodynamic drag becomes a significant factor in train resistance. The geometric profile of the train’s end connection changes abruptly, enhancing this aerodynamic resistance. Implementing an external windshield effectively mitigates this resistance, particularly for middle- and rear-train cars. This study utilizes three-dimensional, steady Navier–Stokes (N-S) equations for open line conditions and three-dimensional, unsteady N-S equations for tunnel environments to analyze the drag reduction effects of trains with and without external windshields in both scenarios. The findings indicate that external windshields have minimal impact on the flow and pressure fields surrounding the entire train, whether operating on open lines or in tunnels. However, the installation of an external windshield creates a positive pressure zone on its surface, with varying pressure levels depending on whether the train is in open air or a tunnel. Additionally, a high-velocity airflow occurs in the gap between the external and internal windshields, reaching speeds up to 90 m/s. In open-line conditions, the external windshield decreases the train’s overall aerodynamic resistance by approximately 14.46%, while in tunnels, it achieves a reduction of about 24.48%. Furthermore, the pressure surrounding the windshield is higher during tunnel operations compared to open-line conditions.

Numerical research on two typical flow structures and aerodynamic drag characteristics of blunt-nosed trains

Purpose This study aims to provide new insights into aerodynamic drag reduction for increasingly faster blunt-nosed trains, such as urban and freight trains. Specifically, this work investigates two distinctly different wake structures and associated aerodynamic drag of blunt-nosed trains. Design/methodology/approach Three typical cases of blunt-nosed trains with 1-, 2- and 3-m nose lengths are selected. The time-averaged and unsteady flow structures around the trains are analyzed using the improved delayed detached eddy simulation model and proper orthogonal decomposition method. Findings The simulation results indicate that for 2- and 3-m nose lengths, the flow separates at first and then reattaches to the slanted surface of the tail, with a pair of longitudinal vortices dominating the wake. In contrast, for the 1-m nose length case, the wake structure is characterized by complete separation, attributed to the larger curvature of the slanted tail surface. Consequently, the total time-averaged drag coefficient is reduced by 27.2% and 19.2% for the 1-m nose length case compared to the 2- and 3-m cases, respectively. Moreover, the predominant unsteady structures with Strouhal numbers St = 0.30 and St = 0.28 are detected in the near-wake of the 2- and 3-m nose length cases, respectively. These structures result from periodic vortex shedding at the lower slanted tail surface. In contrast, for the 1-m nose length case, the predominant unsteady structure with St = 0.19 is induced by the nearly periodic expansion and contraction of the upper bubbles. Originality/value Two distinctly different wake structures in blunt-nosed trains are identified. Unlike high-speed trains with longer, streamlined noses, for blunt-nosed trains, shorter nose lengths result in lower aerodynamic drag. Insights for reducing energy consumption in blunt-nosed trains are provided.