As a critical factor in the degradation of rails and wheels, wheel-rail contact heat has been investigated with various analytical and numerical methods. However, the predicted temperature distributions and thermal loads have not been directly validated through measurements due to the challenges associated with accurate measurements. This study employs an infrared camera to measure the temperature variation at the wheel-rail contact under various slip ratio conditions in an in-house wheel-rail dynamic contact test rig. Wheel braking is replicated, and a wheel flat is generated. The temperature field of the contact interface is measured and analyzed, revealing the heating and cooling processes before and after the formation of the wheel flat. The results demonstrate that the contact temperature between the wheel and rail progressively increases with increasing slip ratio until a flat is formed. Notably, at a slip ratio of 8.3%, the observed contact temperature reaches 337.2 ℃ and then rises to 432.8 ℃ at a higher slip ratio of 15.9%. When the wheel flat is generated at a slip ratio of 20.4%, the observed contact temperature between the wheel and rail reaches 652.4 ℃. After the formation of the flat, the contact temperature initially decreases due to more wheel material of lower temperature entering into the contact and rises again with the increase of slip ratio. These measurement findings are valuable for calibrating and validating simulation models and investigating thermal damage related to wheel-rail interactions.@en

Railway transition zones connecting conventional embankments and rigid struc-tures, such as bridges and tunnels, usually degrade much faster than other railway sections. Efficient health condition monitoring of transition zones is important for preventative track maintenance. In this paper, a methodology for monitoring rail-way transition zones using acceleration measurements on multiple axle boxes (multi-ABA) of a passing train is presented. To showcase its capability, the measurements in the Netherlands, Sweden, and Norway are analyzed and dis-cussed. It is found that different bridges and transition zones exhibit unique char-acteristics including dominant wavelengths and energy distribution. Based on these unique characteristics, the geometry and support conditions at different lo-cations of a transition zone can be evaluated. Higher train speed makes the char-acteristics more pronounced. The results demonstrate that the multi-ABA meas-urement has the potential to evaluate and thus monitor the health conditions of various transition zones.@en

This study presents a measuring framework for railway transition zones using a case study on the Swedish line between Boden and Murjek. The final goal is to better understand the vertical dynamics of transition zones using hammer tests, falling weight measurements, and axle box acceleration (ABA) measurements. Frequency response functions (FRFs) from hammer tests indicate two track resonances, for which the FRF magnitudes on the plain track are at least 30% lower than those at the abutment. The falling weight measurements indicate that the track on the bridge has a much higher deflection than the track on the embankment. Two features from ABA signals, the dominant spatial frequency and the scale average wavelet power, show variation along the transition zone. These variations indicate differences in track conditions per location. Finally, the ABA features in the range of 1.05–2.86 m⁻¹ are found to be related to the track resonance in the range of 30–60 Hz. The findings in this paper provide additional support for physically interpreting train-borne measurements for monitoring transition zones.

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Wheel-rail high-frequency interaction is closely related to the formation of railway short-wave defects. Finite element (FE) method has been widely used to simulate wheel-rail dynamic systems, but its validity in modelling high-frequency interaction has not been fully demonstrated in three dimensions (3D). This work aims at comprehensively validating the 3D FE modelling of wheel-rail high-frequency interaction using a downscale V-Track test rig. First, the FE model of the V-Track is developed that comprehensively includes the 3D track elasticity. The simulated track dynamic behaviours are validated against hammer tests, and the major vibration modes are analyzed employing modal analysis. Afterwards, the simulate wheel-rail dynamic responses are comprehensively compared with measurement results up to 10 kHz. Their characteristic frequencies are identified and correlated to the eigenmodes of the vehicle-track system. The results indicate that the proposed 3D FE model is capable of comprehensively and accurately simulating the 3D track dynamics and wheel-rail dynamic interaction of the V-Track up to 10 kHz. Rail vibrations dominate the wheel-rail dynamic contact within 10 kHz, while the wheel vibrations play an increasingly important role at higher frequencies and become decisive near the wheel eigenmode frequencies. The V-Track overall achieves dynamic similarity to the real vehicle-track system.

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A transfer function (TF) is an effective representation of the load-response relationship of railway track structures. To fill the gap in measuring track structure TFs over a wide frequency range from a moving vehicle, we develop a TF measurement system and the associated TF estimation methodology. Accelerometers are utilized to estimate the dynamic vehicle load to track structures, and a laser Doppler vibrometer (LDV) is used to scan track structures and measure their vibration response. First, operational modal analysis is applied to vehicle impact response over joints to identify its modal parameters, which support the estimation of dynamic wheel-rail forces from vehicle vibrations. This combination eliminates the need to pre-define the vehicle stiffness, vehicle damping, and vehicle body mass and enables the vehicle parameters to be updated under operational conditions. Meanwhile, a signal processing method is applied to LDV signals to reduce speckle noise and compensate for the effect of vehicle vibration. Then, a continuous track structure is segmented into distributed sections, and a TF is estimated for each track section using the estimated wheel-rail force as input and the extracted track vibration as output. We validate the methodology in a vehicle-track test rig on different track sections (with or without joints) and at different speeds (from 8 km/h to 16 km/h). The results are further compared with trackside measurements and hammer tests. We demonstrate that the track vibrations extracted from the LDV signals are consistent with those measured by trackside accelerometers. The shapes and resonance frequencies of the estimated TFs are in good agreement with those measured from the hammer tests in the frequency range of 200–800 Hz. The developed system captures differences in the TFs between different track sections, suggesting its potential to be used for structural health monitoring of railway tracks.

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Polygonal wear is a type of damage commonly observed on the railway wheel tread. It induces wheel-rail impacts and consequent train/track components failure. This study presents a finite element (FE) thermomechanical wheel-rail contact model, which is able to cope with the three possible generation and development mechanisms of polygonal wear: initial defects, thermal effect, and structural dynamics. The polygonal wear-induced impact contact and further development of wear are simulated. The simulated elastic contact solutions are verified against the program CONTACT. Different material properties (elastic, elasto-plastic and elasto-plastic-thermo, i.e. with thermal softening) and initial polygonal profiles are then applied to the FE model to investigate the influence of wheel/rail material and wear amplitude on wheel-rail contact stress and wear development. The simulations indicate that the wheel-rail impact-induced temperature may reach up to 362 ℃ at the contact interface, and the high temperature at the contact area influences wheel-rail contact stress and wear depth.

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This article develops and tests a self-contained railway track monitoring system that fits in existing vehicles without the need for speed and load control. Combining a train-borne laser Doppler vibrometer and axle box accelerometers enables synchronized measurements of train-track response under operational conditions. Utilizing a GPS antenna and video camera, we propose the multisignal processing method to obtain train-track vibrations with train position and speed. Then, we fuse the multiple signals to extract an impact index and a resonance index and further propose an interpretable anomaly detection strategy. We test the system on an operational line at 20-60 km/h under different working conditions and verify the detection results using information from conventional technologies. The impact index peaks near joints and welds, and the resonance index yields a good correlation with the measured track geometry. The developed solution achieves the detection, localization, and quantification of surface and support anomalies in railway tracks.

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Various models for simulating rail ratcheting behaviour were developed to study rolling contact fatigue (RCF) damage in rails. However, limitations remain in terms of the accuracy of wheel–rail contact modelling and computational efficiency of the cyclic loading simulation. This study developed an efficient 3D finite element (FE) procedure to simulate ratcheting in rails subjected to numerous load cycles. The procedure simulates a wheel rolling repeatedly over a rail section with updated stress–strain states, enabling automatically executed cyclic loading simulation given a predefined number of cycles. To ensure the accuracy of the contact modelling, the effect of meshing schemes on subsurface stress distribution was examined. In addition, the FE contact model with the selected meshing scheme, which balances accuracy and computational efficiency, was verified against the widely accepted CONTACT program. Subsequently, a non-linear kinematic hardening (NLKH) steel material was used in the FE model for ratcheting simulations with up to 100 wheel-loading cycles. The rail surface and subsurface stress states were replicated under partial-slip wheel–rail rolling contact conditions with traction coefficients of 0.10, 0.20 and 0.35, respectively. The ratcheting behaviour was extensively analysed in terms of plastic deformation, contact patch evolution, and ratcheting rates. The simulated plastic deformation was found to alter the contact geometry and thus contact stresses, which in turn affect further accumulation of plastic deformation and subsequent ratcheting strains. These findings highlighted the importance of considering the interplay between the rail ratcheting behaviour of the rail and evolving contact conditions for predicting ratcheting and RCF damage in rails.

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Friction/adhesion management in railway networks is a challenge for infrastructure managers and railway operators. Friction/adhesion at the wheel–rail interface influences the braking and traction performance of railway vehicles and the formation of wheel and rail defects. A minimum level of friction/adhesion must be guaranteed to ensure appropriate braking and traction of vehicles, whereas high friction/adhesion increases wear and rolling contact fatigue (RCF) of wheels and rails, noise emissions and carbon footprint (transportation energy consumption). A crucial part of friction/adhesion management is to reliably measure the wheel–rail friction levels and creepage. A train-borne tribometer is desired because the wheelrail friction level depends on, among others, the normal contact load and speed.

A light vehicle will thus experience adhesion different from a heavy train, and the accuracy of hand-pushed tribometers is adversely affected by scaling and low speed. Aiming to contribute to the development of a train-borne tribometer for friction/adhesion management, this study conducted a comprehensive lab test in the V-Track in the Railway lab of TU Delft. The V-Track is a downscaled wheel-rail contact test rig consisting of a 4-meterdiameter ring track and 1~4 wheel assemblies running over it with well-controlled and measurable normal load and friction forces. The coefficient of friction (COF) was measured with two schemes: 1. Increase the angle of attack (AoA) to get friction saturation in the lateral direction and 2. Increase the traction/braking torque of the wheel to get friction saturation in the longitudinal direction. The wheel-rail contact forces in the three directions, AoA, wheel rolling speed and rotational/circumferential speed, and traction/braking torques were measured and analysed to obtain the COF of the V-Track.@en

Excessive underground train-induced building vibration is an environmental concern resulting in human distress. Wheel polygon is probably one of the main vibration sources. In the present work, an explicit-integration time-domain, fully coupled 3D dynamic train-track-tunnel-soil-building FE model is developed and employed to investigate the effects of wheel polygon on the building vibration. Measured wheel polygon data is analyzed and input into the developed FE model. Based on the simulation results, it is found that the contribution of the wheel polygon to the building vibration is considerable in the frequency range from 30 to 180 Hz. Wheel polygon makes the building vibration more pronounced at the P2 resonance frequency and the passing frequencies (f = v/λ) of wheel polygon. From the foundation to a high floor in the building, the effect of the P2 resonance-related wheel polygon attenuates the slowest while the effects of the other orders of wheel polygon attenuate fast.

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This work presents the results of a measurement campaign to demonstrate the effectiveness of the axle box acceleration (ABA) technology for detecting rail defects. The measurements were conducted along the Iron Ore line between Sweden and Norway for the IN2TRACK3 project. This line is mostly single-track with passenger-freight mixed traffic and heavy axle load. Historical data and track information data were not considered in this study. By analyzing data acquired from the accelerometers in vertical and longitudinal directions, rail defects were detected in near real-time using big-data analytics. For our validated sections, 100% of rail defects (including squats) were detected using time-frequency analysis and an outlier detection approach. The methodology also allows for identifying priority locations, e.g., defective welds, joints, transition zones, etc., and its use for prescriptive maintenance recommendations is being explored in the framework of the IAM4RAIL project.@en

Vibrations resulting from dynamic vehicle-track interactions (VTI) offer valuable insights into track conditions. This paper presents an approach for track condition monitoring by detecting and quantifying multiple track degradations using a digital twin of the VTI system. Unlike existing techniques that focus on a specific degradation type at a single track component, our proposed method provides a generic and integrated framework. By combining a physics-based VTI model with a data-driven model, we dynamically update the digital twin’s state based on measured axle-box accelerations (ABA). We introduce a local ABA feature extracted from its spectrogram and demonstrate its effectiveness in distinguishing various degradations at different track positions. The implementation and capability of the proposed approach were demonstrated in a case study conducted on a transition zone of a railway bridge. The simultaneous track stiffness variations in the railpad/fastening and ballast layers were successfully detected, confirming the effectiveness of our approach. The case study also showcases the generality, interpretability, efficiency, and robustness of the proposed approach in identifying concurrent degradation. Our proposed framework opens new possibilities for cost-effective continuous track monitoring for railway infrastructure management.@en

The Coefficient of Friction (CoF) is an important parameter affecting acceleration and braking behavior of trains, and consequently the inter-train distance and utilization of track. To optimize operation schedules, maximize railway capacity, and realize automatic train operations, reliable measurements of the CoFs experienced by in-service trains are desirable. In this study, a train-borne measurement approach is proposed based on a torque modulation concept. It involves superimposing a small-amplitude sinusoidal signal on the motor torque. Because the wheel-rail friction force acts as variable damping, it causes a phase difference between the angular velocity response of the wheelset and the input modulated torque signal. This phase difference can be used to determine the creep coefficient, i.e., the slope of the creep curve, and then to estimate the CoF in combination with the measured Coefficient of Adhesion (CoA), i.e., the ratio between the wheel-rail friction force and normal load. Simulations of torque modulation with VI-Rail are conducted. Variation of phase difference with the increase of the modulated torque is derived theoretically and compared with numerically obtained results using the VI-Rail multibody dynamics model under different CoF conditions. The good agreement between the results indicates the effectiveness of the proposed measurement concept.@en

The conventional vertical track quality index (TQI) based on the standard deviation of longitudinal levels yields standardized railway track condition assessment. Nevertheless, its capability to identify problems is limited, particularly in the ballast and substructure layers when abrupt changes affect train-track interaction. Previous research shows that dynamic responses from moving trains via axle box acceleration (ABA) measurements can quantify abrupt changes in the vertical dynamic responses. Thus, this paper proposes a framework to design an enhanced vertical TQI, called EnVTQI, by integrating track longitudinal levels and dynamic responses from ABA measurements. First, measured ABA signals are processed to mitigate the influence of variation in measurement speed. Then, substructure and ballast-related features are extracted, including scale average wavelet power (SAWP) in the ranges 0.04 m^-1 to 0.33 m^-1 (substructure) and 1.25 m^-1 to 2.50 m^-1 (ballast). This enables identifying track conditions at different track layers. Finally, EnVTQI is determined by weight averaging between the conventional vertical TQI and the ABA features from moving trains. The performance of EnVTQI is evaluated based on 48 segments of a 200-m track on a Dutch railway line. The results indicate that EnVTQI helps to distinguish track segments that cause poor train-track interaction, which the conventional TQI does not indicate. EnVTQI can supplement the conventional TQI, improving the effectiveness of track maintenance decision-making.

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A train-borne laser Doppler vibrometer (LDV) directly measures the dynamic response of railway track components from a moving train, which has the potential to complement existing train-borne technologies for railway track monitoring. This paper proposes a holistic methodology to characterize train-borne LDV measurements by combining computer-aided approaches and real-life measurements. The focus is on the speed-dependent characteristics because the train speed affects the intensity of railway sleeper vibrations and the intensity of speckle noise, which further affects the quality and usability of the measured signals. First, numerical models are established and validated to simulate sleeper vibrations and speckle noise separately. Then, a vibration–noise separation method is proposed to effectively extract speckle noise and structural vibrations from LDV signals measured at different speeds. The parameters of the separation method are tuned using simulation signals. The method is then validated using laboratory measurements in a vehicle-track test rig and applied to field measurements on a railway track in Rotterdam, the Netherlands. Further, the speed-dependent characteristics of train-borne LDV measurement are determined by analyzing the competition between sleeper vibrations and speckle noise at different speeds. Simulation and measurement results show that an optimal speed range yields the highest signal-to-noise ratio, which varies for different track structures, measurement configurations, and operational conditions. The findings demonstrate the potential of train-borne LDV for large-scale rail infrastructure monitoring.

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Railway track stiffness is an important property closely related to track condition and maintenance. Track stiffness variations occur over time and space due to dynamic train loading and aging of track components. Track stiffness variations may further lead to geometry deteriorations and vibration problems. It is therefore essential to continuously monitor track stiffness variations, as well as related track component degradations, over time and space, so that preventive and targeted maintenance can be performed to reduce the life-cycle cost of rail infrastructures.

Various techniques exist for evaluating track stiffness from dynamic responses of the train– track system, including track-side and train-borne measurements. The track-side measurement uses sensors mounted on sleepers to measure the track stiffness at each sleeper support. Nonetheless, because of the cost of sensor deployment, the track-side measurement is more suited for discrete locations in the rail network of special interest, such as transition zones. To scan for track stiffness over a long distance, specialised measurement vehicles were developed. However, they can only measure at low speeds and require track occupation, thus not suitable for frequent measurements. In comparison, train-borne measurements using in-service vehicles are more cost-effective and allow for more frequent surveys of the entire rail network. However, existing techniques are not able to measure the respective stiffness of different track layers, such as the ballast and railpad stiffness. In addition, existing train-borne techniques using in-service vehicles have seldom been validated by field measurement data.@en

Short pitch corrugation has been a problem for railways worldwide over one century. In this paper, a parametric investigation of fastenings is conducted to understand the corrugation formation mechanism and gain insights into corrugation mitigation. A three-dimensional finite element vehicle–track dynamic interaction model is employed, which considers the coupling between the structural dynamics and the contact mechanics, while the damage mechanism is assumed to be differential wear. Various fastening models with different configurations, boundary conditions, and parameters of stiffness and damping are built up and analysed. These models may represent different service stages of fastenings in the field. Besides, the effect of train speeds on corrugation features is studied. The results indicate: (1) Fastening parameters and modelling play an important role in corrugation formation. (2) The fastening longitudinal constraint to the rail is the major factor that determines the corrugation formation. The fastening vertical and lateral constraints influence corrugation features in terms of spatial distribution and wavelength components. (3) The strengthening of fastening constraints in the longitudinal dimension helps to mitigate corrugation. Meanwhile, the inner fastening constraint in the lateral direction is necessary for corrugation alleviation. (4) The increase in fastening longitudinal stiffness and damping can reduce the vibration amplitudes of longitudinal compression modes and thus reduce the track corrugation propensity. The simulation in this work can well explain the field corrugation in terms of the occurrence possibility and major wavelength components. It can also explain the field data with respect to the small variation between the corrugation wavelength and train speed, which is caused by frequency selection and jump between rail longitudinal compression modes.

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Short pitch corrugation is a typical defect on rail surfaces that induces high level of noise and increases maintenance costs. Despite numerous research efforts, corrugation development mechanism has not yet been fully understood and root-cause solutions have not been developed. This work numerally simulates the rail corrugation in the V-Track test rig, aiming to better understand corrugation mechanism and also link the scaled laboratory tests to the full-scale reality. A three-dimensional finite element model of the V-Track is established to simulate the vehicle-track dynamic interaction. The fastening and ballast parameters are calibrated by fitting the simulated track receptances to hammer tests. Rail corrugation with a major wavelength of 5.7 mm is successfully reproduced using the FE model, which shares features similar to the experimentally produced corrugation in the V-Track. The numerical simulation demonstrates that a rail longitudinal compression mode at 790 Hz is the ‘wavelength-fixing’ mechanism of corrugation in the V-Track, agreeing with the experimental results. This work numerically verifies the dominance of the rail longitudinal vibration modes on corrugation formation.

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Excessive underground train-induced vibration becomes a serious environmental problem in cities. To investigate the vibration transfer from an underground train to a building nearby, an explicit-integration time-domain, three-dimensional finite element model is developed. The underground train, track, tunnel, soil layers and a typical multi-story building nearby are all fully coupled in this model. The complex geometries involving the track components and the building are all modelled in detail, which makes the simulation of vibration transfer more realistic from the underground train to the building. The model is validated with in-situ tests data and good agreements have been achieved between the numerical results and the experimental results both in time domain and frequency domain. The proposed model is applied to investigate the vibration transfer along the floors in the building and the influences of the soil stiffness on the vibration characteristics of the track-tunnel-soil-building system. It is found that the building vibration induced by an underground train is dominant at the frequency determined by the P2 resonance and influenced by the vibration modes of the building. The vertical vibration in the building decreases in a fluctuant pattern from the foundation to the top floor due to loss of high frequency contents and local modes. The vibration levels in different rooms at a same floor can be different due to the different local stiffness. A room with larger space thus smaller local stiffness usually has higher vibration level. Softer soil layers make the tunnel lining and the building have more low frequency vibration. The influence of the soil stiffness on the amplification scale along the floors of the building is found to be nonlinear and frequency-dependent, which needs to be further investigated.

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Inefficient management of rail surface defects can increase maintenance costs, safety hazards, service disruptions, and catastrophic failures like rail breaks. To achieve adequate management, having effective technology capable of timely detecting and frequently monitoring rail defects is of utmost importance. The aim is early detection of defects to maintain safety levels and prevent the re-appearance due to residual damages.

Various measurement technologies, such as visual inspections, geometry profile measurements, and other measurement techniques, have been used for the detection of rail defects. While these methods provide insights, they often lack the capability for early-stage defect detection. Thus, most of these technologies are suitable for reactive maintenance since they detect defects when they reach a certain severity level. Axle box acceleration (ABA) technology provides a solution capable of frequent monitoring, mounted on trains in operation without dedicated measurement vehicles (see figure 71-1). Its basic principle is to use a train as a moving load that excites the infrastructure and to detect defects by evaluating the time-frequency characteristics of the dynamic response measured by accelerometers installed on axle boxes of the train. ABA systems have shown promise in detecting defects in the early stages. However, its widespread application and need for robustness require further validation and development. This work presents the results of detecting and monitoring rail surface defects using ABA technology.@en