The bogie serves as a pivotal structural and functional unit within the rail vehicle system, and any failure in its performance can critically affect the safety and reliability of railway operations. This paper aims to develop a bogie structural health monitoring system based on the transfer function. In this study, the rigid-flexible coupling model of the bogie system will be established through the parameters and data of a real vehicle system. Propose a method for calculating the transfer function through the cross spectral density and auto spectral density. In this study, the system is constructed with the 3-axial acceleration data of the axle box and the stress of a cowcatcher. Then, calculate the transfer function of the 3-input single output system. And the system error is corrected through the sliding window method. Subsequently, the transfer function is used to predict the stress of the cowcatcher. Finally, based on the Dirlik frequency domain fatigue life estimation method, the damage and remaining life of the cowcatcher were calculated by using the measured stress and the predicted stress by transfer function. The results show that the stress results of the two methods have good consistency in both time and frequency domains, with a maximum error of only 6.5 %. It illustrates that the method can reproduce the stress state of the bogie system well. Based on this method, structural health monitoring of the bogie system can be realized.

Magnetic components play a critical role in Wireless Power Transfer (WPT) systems by enhancing the coupling coefficient, thereby improving efficiency and power transfer capacity. In high-power WPT systems for electric vehicles and battery-electric locomotives, Ferrite Blocks/Bars (FBs) and Magnetic Composite Particle Materials (MCPMs) are commonly used to fabricate magnetic components, both demonstrating notable performance. However, limited comparative studies have examined their effects on WPT systems. This paper presents a comparative analysis of FB and MCPM in WPT systems, focusing on the coupling coefficient and system efficiency. First, the magnetic reluctance circuit of the WPT coupler is analyzed. Based on this analysis, MCPM couplers without grooves, MCPM couplers with Grooves (MCPM/G), and FB couplers are designed and optimized using finite element analysis to maximize the coupling coefficient under constrained conditions. The optimized couplers are then fabricated and integrated into a prototype WPT system, and their performance is validated through testing. Compared to the coil-only coupler without magnetic components, the simulated and experimental coupling coefficients show that the MCPM coupler improves by 35.36 % and 25.25 %, the MCPM/G coupler improves by 44.96 % and 27.00 %, and the FB coupler improves by 58.82 % and 41.81 %. Regarding maximum efficiency, the MCPM, MCPM/G, and FB couplers achieve increases of 1.22 %, 1.55 %, and 2.39 %, respectively. These results demonstrate the effectiveness of magnetic components and the differences among various materials in enhancing the performance of WPT systems.

This paper tackles the critical challenge of catastrophic forgetting and inefficient learning in artificial intelligence models processing continuous, non-stationary data streams. Inspired by neurobiological mechanisms, specifically the Complementary Learning Systems (CLSs) theory involving the hippocampus and neocortex, we propose a novel brain-inspired biomimetic memory system. The core innovation integrates dimensionality reduction techniques—covariance decomposition and low-dimensional mapping—for efficient feature extraction from long spatiotemporal-scale information flows, with a biomimetic learning/forgetting mechanism grounded in CLS principles. Evaluated on real-world power plant operational data, the proposed system demonstrates robust performance against noise and fluctuations, validating the effectiveness of the bionic learning/forgetting mechanism.

This paper addresses the challenge of weak discharge characteristics being masked by strong background noise in the acoustic detection of partial discharges in high-speed train high-voltage cable terminals. It innovatively introduces the Minimum Entropy Deconvolution (MED) method for fault diagnosis. Traditional detection methods are difficult to apply rapidly in vehicle maintenance due to equipment complexity and environmental constraints. The proposed method collects acoustic signals from cable terminals using portable devices and leverages the core advantage of the MED algorithm—designing an optimal inverse filter to maximize the enhancement of periodic impulse components within the signal. This effectively extracts the pulse sequences associated with partial discharges from heavy noise. Combined with a 2000 Hz high-pass filter to suppress low-frequency interference, the method clearly identifies discharge signals characterized by 50 Hz and its harmonics in both the time-domain waveform and frequency spectrum. Experimental and field verification demonstrate that this method can accurately distinguish faulty cables. Furthermore, an integrated graphical user interface analysis program was developed based on this approach, automating and streamlining the detection process. This provides a novel, low-cost, and efficient on-site solution for the operation and maintenance of high-voltage cables in rail transit.

The Pantograph-Catenary System (PCS) is a critical interface for stable power acquisition in high-speed railways, and its dynamic interaction performance directly dictates the safety and reliability of train operation. As operating speeds increase, traditional passive pantographs experience severe fluctuations in contact force, leading to electrical arcing and mechanical wear, becoming a key bottleneck to further speed advancements. Active control technology, which integrates sensors, controllers, and actuators to regulate the pantograph’s behavior dynamically, is a core solution for addressing these challenges and ensuring superior current collection quality. This review aims to systematically survey and summarize the state of the art and future trends in active control for the pantograph-catenary system. Firstly, the core dynamic challenges and the necessity of active control are discussed before detailing the key modeling techniques required for simulation and real-time control design. Secondly, existing active control strategies are meticulously classified and reviewed. Subsequently, the essential hardware implementation platforms, including actuators, sensor technologies, real-time controllers, and Hardware-In-the-Loop (HIL) testing rigs, are systematically outlined, thereby bridging theory and practical verification. Additionally, the emerging concept of active catenary control is also explored. Finally, present an in-depth discussion and outlook on the current status and limitations. This review is intended to provide a comprehensive and insightful reference for researchers and engineers in the relevant fields.

The guideway girder is a key supporting component that ensures the safe and stable operation of high-speed maglev systems. Taking the Shanghai high-speed maglev demonstration line as the background, this paper conducts a comprehensive experimental and numerical investigation on the dynamic characteristics of the guideway girder. Dynamic response tests were carried out under an operational load corresponding to 300 km/h, and by employing the Eigensystem Realization Algorithm (ERA) together with deflection curves derived from the conjugate beam method, a complete set of dynamic properties of the guideway girder was simultaneously identified using field test data. The identified parameters were then used to calibrate a highly reliable vehicle-guideway coupled dynamic model, which showed excellent agreement with the measured data in both the time and frequency domains, thereby undergoing rigorous validation. Numerical simulations based on this model revealed a fundamental transition in the governing dynamic mechanisms of the system: the system response shifted from being primarily resonance-driven to being dominated by inertial forces and dynamic amplification due to moving loads, leading to an acceleration growth rate far exceeding that of quasi-static deflection. This study provides the maglev system with a validated model and new insights into its speed-dependent dynamics, while also pointing out directions for future research focused on mitigating high-frequency vibrations.

For variable-section high-speed railway bridges, such as continuous girders and rigid-frame bridges, tapered 3D beam elements are frequently utilized to model bridge components. However, current high-speed railway design software and vehicle-bridge coupling analysis software tend to use prismatic beams instead, which leads to insufficient accuracy. In this paper, the cross-sectional stiffness matrix and flexibility matrix without rigid body displacement are established utilizing a generalized coordinate system with cantilever beam constraint and force interpolation function based on the equilibrium relation. Based on the force-based finite element method in combination with the virtual work principle, the shape function matrices for the cases with and without considering the shear effect are deduced, respectively. Then, the tapered 3D beam element consistent mass matrix is derived. To verify the accuracy of the proposed force-based finite element method, the derived matrix is degenerated into a prismatic beam to obtain the prismatic 3D beam element consistent mass matrix. Furthermore, compared with the commercial software Midas, the maximum natural frequency error for a linearly varying simply supported beam is less than 0.16 %. Both the theoretical degenerate solution and the numerical verification case prove that the stiffness matrix and consistent mass matrix of the tapered 3D beam element derived in this paper are highly accurate. Moreover, the force-based derivation method is proven to be reliable for deriving the tapered 3D beam element dynamic property matrix.

This paper reviews the innovative international development practices promoted by High-speed Railway (HSPR), a journal launched under the “High-Starting-Point New Journals” subprogram of the Excellence Action Plan for Chinese Scientific Journals. With the goal of establishing a world-class journal in the traffic and transportation field, this study explores a model for developing a leading science and technology journal aligned with the goals of the “Double First-Class” initiative (China’s program for developing world-class universities and disciplines). Using statistical data analysis, the study conducts a comparative analysis of global high-speed railway development and high-impact traffic and transportation journals. It examines the consolidation of the sponsor university resources, the composition of the editorial board, and its regional distribution. Furthermore, this paper explains how the editor-in-chief team, editorial board, and Young editorial board collaboratively guide the journal’s focus based on disciplinary trends and establish a targeted editorial scope. The team’s efforts in developing professional publishing capabilities are summarized, as is the strong support provided by the sponsor university’s existing publishing journals. Finally, the journal of High-speed Railway’s achievements are discussed to provide a reference for the future novel established international journals in traffic and transportation and other related fields.