Search Results (73)

The service status of rail, fasteners and track slabs is the key determinant of whether the ballastless track is ready for traffic after a fire. The track slab rail support bolt anchoring performance and the shoulder service performance damaged by fire were tested. Experiments of ballastless track slab concrete burned at different high temperatures were carried out to compare macro- and microstructural properties of the concrete under high-temperature burning to study the microstructure of hydration products after high-temperature burning and reveal the damage mechanism of the track slab concrete after a fire. The results show that the fire damage to the rail and fastener is mainly deformations, fractures and strength reduction. The degree of the fire damage of the mortar layer and base slab is much lower than that of the track slab. The main fire damage to the concrete is track and base slab cracks, spalling and gaps. The degree of the fire damage to the mortar layer and base slab is much lower than that of the track slab. The fire damage of the track slab concrete is mainly bursts, and the concrete cracks, spalling and deterioration occur layer by layer from the outside to inside. The shoulder injury is the most serious, the shear resistance is greatly reduced, the rail support is protected by the rail and fastener, the impact of the fire damage is small and the bolt anchoring performance was not decreased. The position of the track slab’s inside damage corresponds to the surface damage position. The steel bar inside the track slab is in good condition, and there is no obvious damage. The bulk expansion of the ballastless track concrete was caused by the expansion of aggregates under fire. When the expansion of aggregates is constrained by the shrinkage of hydration products, greater internal stress is generated, which is the main reason for the cracking or bursting of the ballastless track slab concrete under high temperatures. Full article

This study addresses the gap in the experimental validation of the tilt-rotor vertical take-off and landing (VTOL) UAVs by developing a novel prototype that integrates fixed-wing and multi-rotor advantages. A dynamic model based on the “X” quadrotor configuration was established, and Euler parameters were employed to derive the attitude transformation matrix. Structural optimization using hybrid meshing and inertia release methods revealed a maximum deformation of 57.1 mm (2.82% of half-wingspan) and stress concentrations below material limits (379.21 MPa on fasteners). The landing gear was optimized using the unified objective method, and the stress was reduced by 32.63 MPa compared to the pre-optimization stress. Vibration analysis identified hazardous frequencies (11–12 Hz) to avoid resonance. Stable motor speed tracking (±5 RPM) and rolling attitude control (less than 10% error) are achieved using a dual-serial PID control system based on the DSP28377D master. Experimental validation in low-altitude flights confirmed the prototype’s feasibility, though ground effects impacted pitch/yaw performance. This work provides critical experimental data for future tilt-rotor UAV development. Full article

This study develops a quantitative framework to assess performance degradation and damage evolution in CRTS I ballastless track slabs. Based on the impact-echo method, the internal void distribution characteristics of the new and old track slabs were obtained. The track slabs were sampled separately by drilling cores to verify the distribution of voids, and uniaxial compression tests were conducted simultaneously to quantify the attenuation of bearing capacity. The on-site wheel–rail force and temperature field data were monitored, based on the established three-dimensional finite element model of CRTS I ballastless track, and the damage distribution characteristics of the track slab under different load combinations after performance degradation were studied. The results show the following: (1) As the performance of the track slabs gradually deteriorated, it was reflected in the increasing internal void distribution area from 0.5% to 3.6%, corresponding to a 22.4% decrease in core strength. (2) The on-site monitoring results showed that the average wheel–rail force was 84.5 kN. The temperature gradient range varied from −50.4 °C/m to 100.0 °C/m, exceeding the allowable value of the design specifications. (3) The actual damage distribution of the track slab after performance degradation under different load combinations significantly increased at key stress locations such as near fasteners, convex abutments, and anchor holes of prestressed steel bars, which required special attention in actual maintenance and repair. Full article

During the maintenance of railway fasteners, there are issues with the current nut disassembly and assembly operation, including low efficiency, heavy reliance on manual labor, and high physical strain. A mechanical device has been designed to move along the railway track while identifying and locating the center of the nut to perform disassembly and assembly operations. First, based on the nut disassembly and assembly process and the operating environment, the structure of the equipment was designed. This machine can simultaneously disassemble and assemble all the nuts on a single rail tie and accommodate position errors and deviations of spiral spikes. Secondly, to verify the structural reliability of the designed machine, a static simulation analysis was conducted on the key load-bearing structures under extreme operating conditions. Based on the simulation results, a lightweight design was applied to the machine’s carrier platform. The performance of the nut assembly and disassembly mechanism was optimized based on the Kriging model and the Non-dominated Sorting Genetic Algorithm (NSGA-II). The optimized machine reduced its mass by 21.7% and increased its strength by more than 30%. A transient analysis was also conducted on the optimized machine structure, further validating its strength. Finally, based on the design and optimization results, a physical prototype of the nut disassembly machine was constructed and tested. The results show that the device can efficiently perform nut disassembly and assembly tasks on the railway track. Both the mechanical structure’s reliability and functionality meet the design objectives and requirements, demonstrating significant application value for promoting the intelligent maintenance of railways. Full article

With the development of the railway industry and the progression of deep learning technology, object detection algorithms have been gradually applied to track defect detection. To address the issues of low detection efficiency and inadequate accuracy, we developed an improved orbital defect detection algorithm utilizing the YOLO11 model. First, the conventional convolutional layers in the YOLO (You Only Look Once) 11backbone network were substituted with the SPD-Conv (Spatial Pyramid Dilation Convolution) module to enhance the model’s detection performance on low-resolution images and small objects. Secondly, the EffectiveSE (Effective Squeeze-Excitation) attention mechanism was integrated into the backbone network to enhance the model’s utilization of feature information across various layers, thereby improving its feature representation capability. Finally, a small target detection head was added to the neck network to capture targets of different scales. These improvements help the model identify targets in more difficult tasks and ensure that the neural network allocates more attention to each target instance, thus improving the model’s performance and accuracy. In order to verify the effectiveness of this model in track defect detection tasks, we created a track fastener dataset and a track surface dataset and conducted experiments. The mean Average Precision (mAP@0.5) of the improved algorithm on track fastener dataset and track surface dataset reached 95.9% and 89.5%, respectively, which not only surpasses the original YOLO11 model but also outperforms other widely used object detection algorithms. Our method effectively improves the efficiency and accuracy of track defect detection. Full article

Based on the dynamic receptance method, a vehicle–track–bridge interaction model was developed to calculate the wheel–rail interaction forces and the forces transmitted to the bridge in an elevated urban rail transit system. A prediction model integrating the finite element method–boundary element method (FEM-BEM) and the statistical energy analysis (SEA) method was established to obtain the noise from the main girder, track slab, and wheel–rail system for elevated urban rail transit. The calculated results agree well with the measured data. Thereafter, the noise radiation characteristics of a single source and the total noise of elevated urban rail transit systems with resilient fasteners, trapezoidal sleepers, and steel spring floating slabs were investigated. The results demonstrate that the noise prediction model for elevated urban rail transit that was developed in this study is effective. The diversity of track forms altered the noise radiation field of elevated urban rail transit systems significantly. Compared to monolithic track beds, where the fastener stiffness is assumed to be 60 × 10⁶ N/m (MTB_60), steel spring floating slab tracks (FSTs), trapezoidal sleeper tracks (TSTs), and resilient fasteners with a stiffness of 40 × 10⁶ N/m (MTB_40) and 20 × 10⁶ N/m (MTB_20) can reduce bridge-borne noise by 24.6 dB, 8.8 dB, 2.1 dB, and 4.2 dB, respectively. These vibration-mitigating tracks can decrease the radiated noise from the track slab by −0.7 dB, −0.6 dB, 2.5 dB, and 2.6 dB, but increase wheel–rail noise by 0.4 dB, 0.8 dB, 1.3 dB, and 2.4 dB, respectively. The noise emanating from the main girder and the track slab was dominant in the linear weighting of the total noise of the elevated section with MTBs. For the TST and FST, the radiated noise from the track slab contributed most to the total noise. Full article

This study aims to explore the dynamic response of ballastless tracks under various temperatures of the cement-emulsified asphalt (CA) mortar layer and other environmental factors. CA mortar is the key material in the ballastless track structure, exhibiting notably temperature-dependent viscoelastic properties. It can be damaged or even fail due to the continuous loads from trains. However, the dynamic behaviors of ballastless tracks considering the temperature-dependent viscoelasticity of CA mortar have been insufficiently studied. This paper captures the temperature-dependent viscoelastic characteristics of CA mortar by employing the fractional Maxwell model and applying it to finite element simulations through a Prony series. A vehicle–track–subgrade (VTS) coupled CRTS I ballastless track model, encompassing Hertz nonlinear contact and track irregularity, is established. The model is constrained symmetrically on both of the longitudinal sides, and the bottom is fixed on the infinite element boundary, which can reduce the effects of reflected waves. After the simulation outcomes in this study are validated, variations in the dynamic responses under different environmental factors are analyzed, offering a theoretical foundation for maintaining the ballastless tracks. The results show that the responses in the track subsystem will undergo significant changes as the temperature rises; a notable effect is caused by the increase in speed and fastener stiffness on the entire system; the CA mortar layer experiences the maximum stress at its edge, which makes it highly susceptible to damage in this area. The original contribution of this work is the establishment of a temperature-dependent vehicle–track–subgrade coupled model that incorporates the viscoelasticity of the CA mortar, enabling the investigation of dynamic responses in ballastless tracks. Full article

The unit slab track structure in high-speed railways exhibits multiple periodic characteristics, which result in bandgaps of elastic wave propagation within the track structure. Moreover, local defects inevitably occur in the ballastless track structure, disrupting its periodicity and leading to the generation of defect states. An analytical model for infinite periodic slab track structure was established using the Floquet transform and supercell method, accounting for local defects, to clarify the propagation of flexural waves in slab tracks. The formation mechanism of elastic wave bandgaps in periodic slab tracks can be explained by Bragg scattering and local resonance. In the low-frequency below 200 Hz, the local resonances of the slab interact with the flexural waves in the rail, forming an approximately broad coupling bandgap. The bandgaps expand significantly with the increasing fastening stiffness. Besides, when the stiffness of the isolating layer beneath the slab is within the range of 0.9 to 1.0 × 10⁹ N/m³, a broad coupled bandgap is generated in the frequency range of 180–230 Hz. Local damage caused by contact loss between the composite slab and baseplate leads to defect states, and the frequencies of the defect states correspond to unique wave modes, demonstrating the localization of elastic waves near the defect location. The formation mechanism of defect states can be elucidated by the local resonance of the structure at the defect. The frequency of the first-order defect state is significantly affected by the defect size, the second-order defect state exhibits unidirectional propagation characteristics, and the third-order defect state shows localized vibration characteristics, which can provide a reference for defect identification. Full article

This paper presents an experimental study on the elastic support in a discrete rail fastening system used in a ballastless tram track structure. The study focuses on the elastic support of the anchor element, specifically the Pm49 baseplate. These elements significantly influence environmental pollution along tram routes, such as vibration (at low frequencies) or noise (at high frequencies), as well as static and dynamic rail deflections. The authors outline a methodology for identifying the static and dynamic characteristics of the discrete elastic support in laboratory conditions. The procedure follows the European standard EN 13146-9 for track category A (tramway), as classified according to the European standard EN 13481-5. The study analyzes how the thickness and density of the tested materials affect stiffness. Additionally, it examines the correlation between parameters identified easily on-site (thickness, Shore hardness and density) and laboratory-determined parameters (static and dynamic stiffness), which are costly and time-consuming to measure. The research confirms that prototype prefabricated vibration isolation baseplate pads made of styrene butadiene rubber (SBR) granules, recycled from end-of-life car tires, can achieve equivalent basic static and dynamic parameters, compared to underlays made of two-component polyurethane (PU) resin. This aligns with the strategy of promoting sustainable materials in construction. The innovative and prefabricated SBR rubber baseplate pads can also be used in repair and maintenance works (regardless of weather conditions), as they enable the quick launch of tram traffic. The results of the research included in this article can be used by other scientists, recycled rubber producers, tram track designers or construction site engineers. Full article

With the widespread construction of the subway in the Chinese mainland, the environmental vibration caused by subway operation has attracted increasing attention. Train-induced environmental vibrations can cause structural deformation, uneven settlement of line foundations, and tunnel leakage, affecting the structural safety of lines and foundations. This research focuses on a segment of the Nanchang Metro Line 3, which has been chosen as the subject of investigation. A numerical model was developed to analyze the subway train-induced environmental vibration, employing the finite element method (FEM). Utilizing a numerical model, an investigation was conducted to examine the impact of train speed on the subway train-induced environmental vibration, the train-induced environmental vibration transmission characteristics were analyzed, and the control effects of vibration reduction tracks on train-induced environmental vibration were discussed. Train-induced vibration tests were also conducted on Nanchang Metro Line 3 to verify the control effects of various vibration reduction tracks. The results indicate that the subway train-induced environmental vibration rises as the train speed goes up, and the vibration peaks always appear around 63 Hz. When the train speed doubles, the Z-vibration level increases from about 5.1 dB to 5.9 dB. Subway train-induced environmental vibration shows a fluctuating decreasing trend with increasing distance from the centerline of the tunnel. The Z-vibration level reaches its maximum 4 m away from the centerline of the tunnel. Compared with the embedded sleeper, the vibration-damping fastener exhibits a vibration reduction effect of about 9 dB to 18 dB, the rubber vibration-damping pad exhibits a better vibration reduction effect of about 16 dB to 24 dB, and the steel spring floating plate exhibits the best vibration-damping effect of about 18 dB to 28 dB. The calculated Z-vibration levels are basically consistent with the measured values, indicating the accuracy of the calculated results of the control effects of the vibration reduction tracks. Full article

To address the issues of the Real-Time DEtection TRansformer (RT-DETR) object detection model, including poor defect feature extraction in the task of rail fastener defect detection, inefficient use of computational resources, and suboptimal channel attention in the self-attention mechanism, the following improvements were made. Firstly, a Super-Resolution Convolutional Module (SRConv) was designed as a separate component and integrated into the Backbone network, which enhances the image details and clarity while preserving the original image structure and semantic content. This integration improves the model’s ability to extract defect features. Secondly, a channel attention mechanism was integrated into the self-attention module of RT-DETR to enhance the focus on feature map channels, addressing the problem of sparse attention maps caused by the lack of channel attention while saving computational resources. Finally, the experimental results show that compared to the original model, the improved RT-DETR-based rail fastener defect detection algorithm, with an additional 0.4 MB of parameters, achieved a higher accuracy, with a 2.8 percentage point increase in the Mean Average Precision (mAP) across IoU thresholds from 0.5 to 0.9 and a 1.7 percentage point increase in the Average Recall (AR) across the same thresholds. Full article

The automation of rail track inspection addresses key issues in railway transportation, notably reducing maintenance costs and improving safety. However, it presents numerous technical challenges, including sensor selection, calibration, data acquisition, defect detection, and storage. This paper introduces a compression method tailored for laser triangulation scanners, which are crucial for scanning the entire rail track, including the rails, rail fasteners, sleepers, and ballast, and capturing rail profiles for geometry measurement. The compression technique capitalizes on the regularity of rail track data and the sensors’ limited measurement range and resolution. By transforming scans, they can be stored using widely available image compression formats, such as PNG. This method achieved a compression ratio of 7.5 for rail scans used in the rail geometry computation and maintained rail gauge reproducibility. For the scans employed in defect detection, a compression ratio of 5.6 was attained without visibly compromising the scan quality. Lossless compression resulted in compression ratios of 5.1 for the rail geometry computation scans and 3.8 for the rail track inspection scans. Full article

In an ever expanding railway network all around the world, the need for track maintenance grows steadily. Traditionally, one major part of track maintenance is ramming large vibrating steel picks into the gravel between and under railway sleepers to compress the gravel and generate a safe substructure. Even today, maintenance personnel still have to manually locate the sleepers if they cannot be detected by computer vision systems or visually by the operator. Here we developed a first of its kind magnetic sleeper detector, even able to find sleepers, buried in gravel, undetectable by vision based systems. Our approach of magnetic detection is based on a DC magnetic field excitation and a detector moving with respect to the rail system, including the sleepers and fasteners for mounting the rails. Due to railway application constraints a large air gap between the sensor and the sleeper structure is required, which significantly complicates the magnetic sensing task for robust sleeper detection. The design and optimization of the magnetic circuit was based on extensive 3D simulation studies to ensure highest possible variation in magnetic flux density at the sensor locations for absence and presence of a sleeper. Furthermore, a low noise and high sensitivity electronic circuit has been realized to cope with sensor signal offsets from unknown or changing sensor orientations with respect to the earth’s magnetic field, or magnetic interferences from other trains potentially passing by during active measurements. Since we only want to detect sleepers in close vicinity of the moving sensor system, digital signal processing of the acquired signals can easily compensate for disturbing slowly changing or static field components within real world application scenarios. We demonstrate that magnetic detection of even buried sleepers on railway tracks is possible for distances of up to 172 mm between the sensor and the sleeper. This enables an even higher level of railway maintenance automation previously impossible in certain scenarios. Full article

Railway track defects pose significant safety risks and can lead to accidents, economic losses, and loss of life. Traditional manual inspection methods are either time-consuming, costly, or prone to human error. This paper proposes RailTrack-DaViT, a novel vision transformer-based approach for railway track defect classification. By leveraging the Dual Attention Vision Transformer (DaViT) architecture, RailTrack-DaViT effectively captures both global and local information, enabling accurate defect detection. The model is trained and evaluated on multiple datasets including rail, fastener and fishplate, multi-faults, and ThaiRailTrack. A comprehensive analysis of the model’s performance is provided including confusion matrices, training visualizations, and classification metrics. RailTrack-DaViT demonstrates superior performance compared to state-of-the-art CNN-based methods, achieving the highest accuracies: 96.9% on the rail dataset, 98.9% on the fastener and fishplate dataset, and 98.8% on the multi-faults dataset. Moreover, RailTrack-DaViT outperforms baselines on the ThaiRailTrack dataset with 99.2% accuracy, quickly adapts to unseen images, and shows better model stability during fine-tuning. This capability can significantly reduce time consumption when applying the model to novel datasets in practical applications. Full article

While the effect of ballast degradation on lateral resistance is noteworthy, limited research has delved into the specific aspect of ballast breakage in this context. This study is dedicated to assessing the influence of breakage on sleeper lateral resistance. For simplicity, it is assumed that ballast breakage has already occurred. Accordingly, nine granularity variations finer than No. 24 were chosen for simulation, with No. 24 as the assumed initial particle size distribution. Initially, a DEM model was validated for this purpose using experimental outcomes. Subsequently, employing this model, the lateral resistance of different particle size distributions was examined for a 3.5 mm displacement. The track was replaced by a reinforced concrete sleeper in the models, and no rails or rail fasteners were considered. The sleeper had a simplified model with clumps, the type of which was the so-called B70 and was applied in Western Europe. The sleeper was taken into consideration as a rigid body. The crushed stone ballast was considered as spherical grains with the addition that they were divided into fractions (sieves) in weight proportions (based on the particle distribution curve) and randomly generated in the 3D model. The complete 3D model was a 4.84 × 0.6 × 0.57 m trapezoidal prism with the sleeper at the longitudinal axis centered and at the top of the model. Compaction was performed with gravity and slope walls, with the latter being deleted before running the simulation. During the simulation, the sleeper was moved horizontally parallel to its longitudinal axis and laterally up to 3.5 mm in static load in the compacted ballast. The study successfully established a relationship between lateral resistance and ballast breakage. The current study’s findings indicate that lateral resistance decreases as ballast breakage increases. Moreover, it was observed that the rate of lateral resistance decrease becomes zero when the ballast breakage index reaches 0.6. Full article