An improved methodology for identifying the dynamic coupling loads at the carbody-hanging equipment interface is proposed, aiming to enhance structural dynamic behaviour across a range of operational scenarios. The mathematical model is established to simulate the carbody and hanging equipment interactions through Euler-Bernoulli beam theory and the vehicle vertical coupled dynamics simulation approach. The load identification model is constructed through integration of compressed sensing (CS) technology with a weighted sparse regularisation strategy, while an improved Akaike Information Criterion (AIC) is employed for optimisation of regularisation parameters. It is demonstrated that the proposed method effectively accounts for both structural coupled vibrations and the influence of different excitation sources from the equipment. Furthermore, a CS framework combined with a redundant dictionary is constructed to achieve sparse signal decomposition, thereby resolving the conflict in simultaneous identification of harmonic loads and impulse components. At the core of the proposed iterative algorithm is a strategy founded on weighted sparse regularisation augmented by an improved AIC, dedicated to the optimal selection of the regularisation parameter, leading to superior accuracy and robustness against noise. Validation results from both simulation and roller rig experiments verify the proposed method and confirm its effectiveness and practical value.

Axle box bearings are critical for the operational safety of high-speed trains. During service, external loads induce thermo-mechanical coupling, leading to pronounced non-stationarity in dynamic responses. This paper incorporates thermo-mechanical coupling effects into the bearing dynamic response analysis. Based on a bearing dynamic model, a localized heat generation method is employed to calculate the temperature distribution of the axle box system. The influence of temperature-induced thermal expansion on the internal contact state of the bearing is analyzed. A thermo-mechanical coupling model for the axle box bearing is developed to investigate its effects on the dynamic response characteristics. Model responses are validated against monitoring signals from high-speed train operation, providing insights into the correlation between bearing operational states and thermo-vibration characteristics.

To address the heavy computational burden and the complex vehicle-tube coupled vibration characteristics in modeling ultra-long tube dynamics for ultra-high-speed evacuated-tube maglev systems, this paper proposes a vehicle-tube coupled dynamical modeling method based on an Arbitrary Lagrangian-Eulerian (ALE) moving-region method (MRM). A three-dimensional tube dynamical model was established using Donnell-Mushtari thin shell theory; and a maglev vehicle dynamical model was developed based on the Newton-Euler method. A localized moving-region technique was introduced to efficiently compute dynamic responses of ultra-long evacuated tubes. Subsequent analyses investigated tube modal characteristics, localized vibration behavior under moving loads, and vehicle-tube coupled dynamic responses. Analysis results indicate that the low-order modal frequencies of tubes are significantly affected by their wall thickness, whereas the influence of internal pressure is relatively limited. Vibrations induced by moving loads are mainly concentrated near the load region. Moreover, the proposed moving-region method effectively reduces computational workloads for ultra-long tube dynamical modeling while accurately capturing the vehicle-tube coupled dynamic characteristics of ultra-high-speed evacuated-tube maglev systems.

High-temperature superconducting (HTS) magnetic levitation (maglev) offers a promising solution for urban and high-speed transport due to its self-stabilizing levitation and negligible magnetic drag. This paper introduces a novel V-shaped permanent magnet guideway (PMG) that achieves stronger magnetic-flux concentration than conventional flat PMGs, enabling reduced rare-earth magnet usage while enhancing both lift and lateral guidance performance. A validated finite element model is used to characterize the electromagnetic forces, which are then incorporated into a dynamic model of an HTS maglev vehicle, including a carbody, five bogies, ten air springs, and sixty cryostat-mounted HTS bulk modules. Dynamic simulations across speeds of 60-160 km/h show enhanced levitation efficiency, improved lateral stability, and acceptable ride comfort and vibration. These results demonstrate the feasibility of the V-shaped PMG concept and provide both theoretical guidance and engineering evidence for its application in future HTS pinning maglev transportation systems.

In practical research of high-temperature superconducting (HTS) maglev, a compulsory centering alignment operation between the superconducting levitator and permanent magnet guideway (PMG) is completed before field cooling (FC) process. However, errors in installation, positioning, and machining may lead to an eccentric state between the superconducting levitator and PMG before the FC process, which essentially means the geometric center of the internal HTS bulks is eccentric from that of the PMG. Therefore, this study investigates the effects of eccentric field cooling (EFC) on the levitation and guidance performance of HTS maglev. Specifically, a Halbach-type PMG is employed, and the eccentric displacement (ED) of bulks is set before FC process. Then during the levitation process, lateral displacement (LD) between bulks and PMG is applied to generate the guidance force. Results show that the EFC can adversely affect the levitation force, and this detrimental effect intensifies with increasing ED. During the LD process, when LD and ED are in the same direction, the reduction in levitation force increases with higher LD; conversely, when LD and ED are in opposite directions, the reduction decreases with increasing LD. Regarding the guidance force, at the initial of LD, appropriate EFC can enhance it, but excessive ED or LD values will negatively impact guidance force. These findings suggest that, in applications requiring high levitation performance, strict centering alignment operation before FC is essential. In contrast, for systems prioritizing guidance performance, appropriate applied EFC may be an effective optimization strategy.

In the supercritical speed range, the pantograph-catenary system exhibits clear advantages, including reduced fluctuations in dynamic contact force and limited vertical displacement of the pantograph head, making it highly suitable for train operations above 400 km/h. However, ensuring a stable transition from subcritical conditions (speed ratio < 0.7) to supercritical operation (speed ratio > 1) presents a major challenge, as resonance risks emerge near the critical speed ratio of approximately 1. This study proposes a hybrid-tension catenary configuration strategy to enable supercritical operation. Targeting an operational speed of 500 km/h, the analysis considers acceleration processes and dynamic performance through overlap sections. The results show that increasing the contact-wire tension to approximately 40 kN during acceleration and maintaining the maximum operational speed ratio below 0.8 allow the pantograph-catenary system to reach the supercritical regime. Moreover, optimizing the number of stitch wires and the crossing-point height in overlap sections further improves dynamic performance. The proposed configuration strategy provides a significant step toward achieving supercritical operation and offers essential guidance for the development of next-generation, higher-speed pantograph-catenary systems.

The abnormal wear of the pantograph and catenary system (PCS) has caused significant economic losses, and understanding the relationship between the wear performance of contact pairs and dynamic interaction has become a widely recognized research issue. This study presents a numerical model for exploring the correlation between the wear and dynamic performance of the PCS, integrating the contact strip wear model with the PCS dynamic model. Firstly, a wear model for the pantograph contact strip was established based on the Archard model, taking into account the multi-parameter impact and dynamic interaction of the PCS. Subsequently, the wear performance of the contact strip was analyzed under different PCS dynamic parameters based on multibody dynamics theory. The results indicate that the parameters of the PCS have varying degrees of influence on the wear performance of the contact strip. Specifically, the equivalent stiffnesses of the three pantograph components significantly affect the wear performance, and some of these parameters were validated through experiments. However, the density of the bolts and channel steel in the catenary suspension mechanism has almost no influence on the wear performance. Finally, the wear performance was significantly improved by selecting the optimal parameter combinations. This research provides important guidance for improving the wear and dynamic performance of the PCS.

The accurate identification of abnormal impact loads generated by under-vehicle equipment is recognized as critical for assessing structural integrity in high-speed trains. This inverse problem is addressed through a novel load identification approach, which leverages sparse regularization principles. The precision of impact load identification is enhanced through a weighted l1-norm regularization framework, aimed at mitigating solution ill-posedness and minimizing peak force errors. This framework is efficiently solved by an optimized TwIST algorithm, into which an iterative reweighting technique is incorporated. Furthermore, an improved AIC is employed for optimal regularization parameter selection, and an analysis of sample size selection is complemented. The method proved accurate and robust, as verified by comprehensive simulations and scaled carbody experiments. The proposed method is demonstrated to significantly outperform classical l1-norm regularization in identifying impact loads, with superior accuracy and increased robustness exhibited with respect to measurement point selection and noise contamination.

ObjectiveThe structural safety of pantograph has a significant impact on the operational reliability of trains. Fatigue cracks are prone to occur at the elbow joints of pantograph on high-speed trains. Therefore, it is necessary to utilize their vibration characteristics to accurately identify the hardly detectable small cracks in their early-stage initiation and to analyze their characteristics. MethodThe damage identification theory based on strain mode is introduced. Taking the upper frame of a certain type of pantograph as the research object, a finite element model is established to perform modal simulation analysis. The accuracy of the simulated modal frequency results is verified through a physical modal test. The displacement mode and strain mode shapes of the pantograph upper frame are calculated and analyzed. The first two strain mode orders are selected, and the mean value of the strain mode change rate is adopted as the damage index to identify cracks. The influence of different crack sizes correspond to strain modes is calculated. Result & Conclusion The occurrence of cracks has no significant effect on mode shape or frequency. At the crack location, the strain mode exhibits a pronounced mutation, whereas the displacement mode does not change. The strain mode is more sensitive to damage than the displacement mode. The strain mode of upper frame shows a distinct mutation at the crack damage location, with the effect being most evident in the lower-order modes, while the changes caused by higher-order mode damage may be concealed. As the crack size increases, the mutation of the strain mode at the crack location becomes more significant. The damage index value increases with the increase in crack depth; when the crack length is less than 10.00 mm, the difference in damage index value is small, and when the crack length exceeds 10.00 mm, the damage index value will increase with the crack length.

Abstract With the continuous increase in train speed, braking noise has emerged as a critical issue. To investigate and mitigate this problem, this study applies complex modal analysis based on modal coupling theory to evaluate the noise response of brake discs under specific operating conditions. The influence of key parameters, namely friction coefficient and the elastic moduli of both the brake disc and pad, on noise generation is examined. Results indicate that the friction coefficient is positively correlated with braking noise tendency, while the elastic modulus of the brake disc has a negligible effect. Using orthogonal experimental design combined with range and variance analysis, the sensitivity of various design parameters to braking noise is assessed. The parameters, in descending order of influence, are friction coefficient, brake disc thickness, brake pad elastic modulus, friction block chamfer, brake disc elastic modulus, and brake pad thickness. Among these, friction coefficient, brake disc thickness, and brake pad elastic modulus significantly affect noise generation, while the chamfer of the friction block also shows a notable influence. Subsequently, response surface methodology is employed to optimize the friction block chamfer, brake disc thickness, and brake pad thickness. After-optimization complex modal analysis reveals a substantial reduction in braking noise response, with the system instability tendency coefficient decreasing by 50.12%, demonstrating the effectiveness of the proposed optimization approach.

Transient repetitive impulses are a typical feature of localized damage to rolling element bearings. Enhancing the damage-induced impulse components hidden in collected vibration signals is an important issue for local defect recognition in bearings. Blind deconvolution (BD) is a typical approach for enhancing bearing impact impulses, which focuses on utilizing a filter to highlight the fault features in the filtered signal. Minimum entropy deconvolution is the most classic BD approach that solves the filter by maximizing the kurtosis value of the filtered signal. Inspired by this, various BD methods have been proposed. However, these methods are all applicable for extracting fault features from a single signal. Therefore, this article extends existing BD methods to multiple signals and proposes a multiple signal blind deconvolution (MSBD) guided by the weighted sum of multiple kurtosis for repetitive transient enhancement. The core of this new method is to utilize a filter to recover the fault impulse components in multiple signals simultaneously. An iterative solution strategy is devised to filter multiple signals by maximizing the weighted sum of their kurtosis values. The efficacy of MSBD was validated in comparison with existing BD methods using numerically synthesized and experimental bearing signals. The results showcase that, compared to typical BD methods, the proposed MSBD has more advantages in extracting bearing fault features by utilizing multiple signals.

The rotating machinery system consists of several key components such as bearings and gears. The operating condition of the bearings directly affects equipment safety and production efficiency. However, traditional bearing fault diagnosis methods face challenges in complex operating conditions, including insufficient local feature extraction, severe noise interference, and difficulty in integrating global information due to the heterogeneity of multi-sensor data. To address these issues, this paper proposes a multi-sensor and multi-task fault diagnosis method based on the multi-scale hidden state interaction network (MHSNet). In terms of feature extraction, MHSNet integrates deep separable convolutions with hidden state-space models. By introducing multi-scale convolution units, it captures local details under different receptive fields. Additionally, the selective hidden state modeling mechanism of the Mamba module overcomes the limitations of conventional convolution networks’ local receptive fields, enabling the modeling of periodic impulses and long-range dependencies in signals. In the data fusion layer, a dynamic state space fusion module is designed to achieve parameterized interaction and adaptive alignment of multi-sensor data within the hidden state space, effectively alleviating the distribution differences and redundancy issues between multi-source information. Through the collaborative extraction of complementary features between tasks, the model further enhances robustness and discriminative accuracy under conditions of data imbalance and noise interference. Extensive experiments conducted on real bearing data and multi-condition testing platforms demonstrate that MHSNet consistently achieves high diagnostic accuracy and condition classification performance. It outperforms traditional single-modal and heterogeneous multi-sensor signal-based diagnostic networks, highlighting its significant advantages in multi-sensor collaborative representation, global and local feature fusion, and noise suppression.

Studies have focused on the significant impact of contact wire damage on the abnormal wear of pantograph contact strips. Initially, on the basis of field data analysis, the most common types of contact wire damage were identified. The experiments and wear performance analysis of contact strips in contact with damaged contact wires were subsequently conducted at high and low humidities. Finally, correlation analysis was employed to explore the influence of various factors on strip wear performance. The results indicate that excessive wear occurs on the contact strip with the pitted contact (PC) wire, particularly under low humidity, where the strip wear rate is 2.2 times greater than that of the contact strip with the normal contact (NC) wire. While in contact with a PC, the primary wear mechanisms of the contact strip include material transfer and arcing ablation under high humidity but involve material transfer, arcing ablation, and microcutting under low humidity. Correlation analysis revealed that under low humidity, the parameters related to PC had the greatest impact on the wear rate of the contact strips, with a significant increase in the mechanical wear proportion. On the basis of these findings, both contact wire damage and reduced humidity contribute to more severe abnormal wear of the contact strip, with the influence of PC conditions being more excessive than that of reduced humidity on wear performance.

It is crucial to investigate the evolution of wear performance and its impact on the PCS dynamic behavior following contact surface damage. Firstly, through experiments, the variation in wear and dynamic performance parameters with the progression of contact strip damage were analyzed. Additionally, the mapping relationship between wear and dynamic performance was analyzed. Building upon these findings, a pantograph and catenary system (PCS) dynamic interaction model incorporating strip damage model was developed using multibody dynamics theory, which was utilized to investigate the variation of wear and dynamic performance and proposes performance change thresholds. The results indicate that strip profile damage leads to a synergistic degradation of both wear and dynamic performance. Specifically, an increase in contact resistance, arcing energy, and the percentage of arcing. Simultaneously, arcing ablation traces in the groove become more pronounced, with significant accumulation of wear debris, indicating that this thermal accumulation significantly increases the proportion of electrical wear, ultimately driving a nonlinear increase in wear rate. Furthermore, when the contact point passes through the groove, the vibration amplitude of contact pair, arcing energy, and the magnitude and fluctuation of contact force increase compared to a smooth surface, which results in a higher contact force standard deviation and leads to the degradation of dynamic performance. This process simultaneously accelerates both mechanical and electrical wear, exacerbating material transfer and arcing ablation in the groove region. Moreover, both wear and dynamic performance are positively correlated with the aspect ratio (7) of the groove. To maintain system stability, 7 should be strictly controlled below the critical threshold of 0.15.

Superconducting Pinning Maglev (SPM) and Permanent Magnet Maglev (PMM) systems generate levitation force using permanent magnet tracks, offering advantages such as simple structure and low energy consumption. However, accurate measurement of key state parameters-namely the levitation gap and lateral deviation-remains challenging due to strong magnetic fields, non-magnetic protective layers, and environmental disturbances near the track surface. To address this issue, this paper proposes a non-contact measurement method based on magnetic-field inversion for real-time estimation of levitation gap and lateral deviation. A magnetic field-displacement conversion model is established using a surface-current approach, and a multi-point Hall sensor array is employed to acquire magnetic field signals above a Halbach-type permanent magnet track. An error-minimization inversion algorithm is then used to infer the corresponding displacement parameters. Static calibration experiments demonstrate that, under the tested conditions, the proposed method achieves a maximum measurement error of 0.11 mm, with an average error of approximately 0.04 mm, satisfying typical engineering accuracy requirements. Dynamic running tests conducted at speeds ranging from 10 km/h to 25 km/ h further verify that the method can stably track levitation gap and lateral deviation variations in real time within the validated speed range. The results indicate that the proposed approach provides an effective and practical solution for non-contact state monitoring of maglev systems employing permanent magnet tracks.

High-temperature superconducting (HTS) pinning maglev technology is considered promising for high-speed transportation due to its self-stabilizing characteristics, and it has been widely studied worldwide. In high-speed engineering applications, safety is a primary concern, largely dependent on the reliable flux-pinning capability of the onboard superconductors. This article proposes a noncontact, nondestructive, and easy-to-implement real-time monitoring method for assessing the flux-pinning state of HTS bulks onboard maglev vehicles, based on the antisymmetric property of null-flux coils. The configuration, working principle, and mathematical model of the method are established, along with a coil geometry optimization strategy and a tailored low-frequency, narrowband filtering circuit. An experimental setup is then built based on the optimized parameters, and a series of tests are performed to the method's feasibility. Furthermore, the effectiveness of the resonance-frequency-based filtering circuit in enhancing signal extraction is analyzed, and theoretical predictions of the relationship between the voltage signal and factors such as displacement, working height (WH), and degradation level are validated experimentally. This study provides a comprehensive investigation from concept to validation and demonstrates strong potential for real-time safety monitoring in HTS maglev systems. It can also offer useful insights for other superconducting or maglev monitoring applications.

This study addresses key challenges for hyperloop trains, such as high surface temperatures and pressures on the carbody; shock wave effects and airflow choking inside the tubes. Based on the three-dimensional compressible Navier-Stokes equations coupled with the SST k-ω turbulence model, and employing the Roe spatial discretization scheme along with hybrid meshing techniques, a numerical computational model for aerodynamics of hyperloop trains was established to systematically investigate the evolution of flow fields, aerodynamic forces and aerothermal characteristics on the carbody surface and inside the tubes, under operating speeds ranging from 400 km/h to 2 500 km/h and in-tube pressures from 1 atm (101 325 Pa) down to 0.005 atm (506.625 Pa). Results show that the largest positive pressure zones on the carbody surface occur at the nose tip and the leading edge of the bottom mover plate of the head car; the mover region experiences strong compression, resulting in local pressure increases of 12% to 17% compared to the stagnation point on the head car. At a fixed blockage ratio of 0.057 42, a clear Kantrowitz limit appears when the Mach number ranges from 0.793 to 1.370 (corresponding to train speeds of approximately 971 km/h to 1 677 km/h), potentially triggering airflow choking and causing nonlinear jumps in the aerodynamic drag coefficient. Furthermore, increasing the vacuum level in the tubes significantly reduces shock wave intensity and aerothermal loads; at extremely low pressures between 0.05 atm (5 066.25 Pa) and 0.005 atm (506.625 Pa), aerodynamic drag falls to 5%–0.5% of that under atmospheric conditions. Therefore, a high-acceleration operating strategy is recommended to rapidly traverse choking speed ranges, and targeted thermal protection for the underside of the head car is emphasized for the design. These findings provide theoretical support for selecting optimal vacuum levels, optimizing vehicle contours, and ensuring safe operation of Hyperloop systems.

Abnormal wear in pantograph-catenary systems (PCS) is becoming increasingly frequent in rail transportation, leading not only to accelerated wear of the contact materials but also to substantial economic losses and significant operational and maintenance pressures. As a result, the exploration of abnormal wear mechanisms and optimization measures has emerged as a critical issue that needs to be addressed in the operation and maintenance of rail transport systems. Firstly, this study conducts a correlation analysis between wear performance and high-current operational conditions based on theoretical analysis and statistical data, revealing the mechanisms of abnormal wear under high-current excitation. Based on these findings, targeted wear optimization measures are proposed and validated with field data. Finally, using multi-body dynamics theory and wear models, the study systematically analyzes the evolution of the PCS dynamic interaction and wear performance throughout its lifecycle. The results show that, a strong correlation between high-current conditions and abnormal wear in PCS. In particular, under high-current conditions, contact strip primarily experience material transfer and arcing ablation as the main wear mechanisms. Material transfer occurs predominantly in the arcing ablation area, where over 40% of the transferred material on the contact wire surface is carbon, which is identified as the primary cause of the high wear rate of the strips. By implementing current reduction measures, the wear rate can be reduced by 17.11%, and this improvement has been validated through field measurements. The simulation results show that after applying these measures, the dynamic performance of the PCS over its entire lifecycle is improved by 5%, and the overall service life of the strip is extended by 29.63%. The results of this study provide a theoretical basis and data support for the management of abnormal wear in PCS and the optimization of operational parameters.

The longitudinal impulse poses a significant threat to safe operation of the heavy-haul trains (HHTs). The primary factor contributing to excessive longitudinal impulse is the poor synchronization of the pneumatic braking system. The segmented electronically controlled pneumatic braking system (SECPB) has been widely adopted due to its capacity to achieve synchronous transmission of braking signals. However, the specific SECPB configurations and their impact mechanisms on train dynamic behavior remain inadequately clarified. Therefore, this article aims to elucidate the influence mechanisms of SECPB configurations on train dynamic behavior. To this end, an SECPB model based on fluid mechanics principles was established, together with a HHT longitudinal-vertical coupled dynamics model, and joint simulations were conducted. A systematic analysis was subsequently performed on the HHT dynamic behavior under various SECPB configurations during a single cyclic braking. The analysis indicates that the SECPB can significantly mitigate the HHT longitudinal impulse, exhibiting a more pronounced effect during release. Although SECPB reduces the overall vibration level of HHTs, it aggravates vibrations in specific directions of the bogies and wheelsets during both braking and release. Furthermore, the transition process of the coupler force state emerges as a key factor contributing to severe train vibrations.