Axle Box Acceleration Research Articles

Smart technology solutions for the NeTIRail-INFRA case study lines: Axle box acceleration and ultra-low cost smartphones

In this paper, we present preliminary results on the development of smart technology solutions for lower density railway lines. The goal is to reach a cost effective inspection and asset management to minimize maintenance interventions time/cost without dedicated inspection vehicles. The proposed methods include axle box acceleration measurements and ultra-low cost smartphones. The collected data will be further used to increase knowledge of the condition of the railway track and to estimate the comfort of passengers. In order to make use of the data, the data is interpreted and converted from monitoring information into management information. Feasibility and preliminary studies were conducted in the railway lines of Romania. The results presented in this paper were obtained in the framework of the H2020 project NeTIRail-INFRA, Work Package 4: Monitoring and Smart Technology.

Fatigue prediction of rail welded joints

A multiaxial fatigue criterion recently developed by the authors for 2D conditions is extended here to 3D situations and applied to predict fatigue damage in rail welded joints with the help of an explicit finite element model. Contact theory and axle box acceleration response in frequency domain are used to validate the finite element model. The influence of depth and length of the welded joints is analyzed. It is found that fatigue damage is more severe with shorter and deeper welded joints. When the length of the welded joints is less than 150 mm, fatigue damage is greatly increased with the increasing of the depth. When the depth is less than 0.1 mm, fatigue damage is not relevant, regardless of the length. When the depth is greater than 0.3 mm, fatigue damage increases significantly with the decreasing of the joint length, especially when the length is less than 150 mm. When the welded joints are long enough, the depth restriction can be relaxed. This work can provide guidance and theoretical support for maintenance and repair of rail welded joints.

Feasibility in assessing the dipped rail joint defects through dynamic response of heavy haul locomotive

The feasibility of monitoring the dipped rail joint defects has been theoretically investigated by simulating a locomotive-mounted acceleration system negotiating several types of dipped rail defects. Initially, a comprehensive locomotive-track model was developed using the multi-body dynamics approach. In this model, the locomotive car-body, bogie frames, wheelsets and driving motors are considered as rigid bodies; track modelling was also taken into account. A quantitative relationship between the characteristics (peak–peak values) of the axle box accelerations and the rail defects was determined through simulations. Therefore, the proposed approach, which combines defect analysis and comparisons with theoretical results, will enhance the ability for long-term monitoring and assessment of track systems and provides more informed preventative track maintenance strategies.

Dynamic responses of a high-speed railway car due to wheel polygonalisation

ABSTRACTThe polygonal wear around the wheel circumference could pose highly adverse influences on the wheel/rail interactions and thereby the performance of the vehicle system. In this study, the effects of wheel polygonalisation on the dynamic responses of a high-speed rail vehicle are investigated through development and simulations of a comprehensive coupled vehicle/track dynamic model. The model integrates flexible slab track, wheelsets and axle boxes subsystem models so as to account for elastic deformations caused by impact loads induced by the wheel polygonalisation. A field-test programme was undertaken to acquire the polygonal wear profile and axle box acceleration response of a high-speed train, and the data are used to demonstrate the validity of the coupled vehicle/track system model. Subsequently, the effects of wheel polygonalisation are evaluated in terms of wheel/rail impact forces, axle box vertical acceleration and dynamic stress developed in the axle considering different amplitudes and harmonic orders of the polygonal wear. The results suggest that the high-order wheel polygonalisation can give rise to high-frequency impact loads at the wheel/rail interface, and excite some of the vibration modes of the wheelset and the axle box leading to high-magnitude axle box acceleration and dynamic stress in the wheelset axle.

Observation and Simulation of Axle Box Acceleration in the Presence of Rail Weld in High-Speed Railway

Rail welds are widely used in high-speed railways and short-wave irregularities usually appear due to limitations in welding technology. These irregularities can excite a high wheel/rail force and are regarded as the main cause of deterioration in track structures. To measure this fierce force (or deterioration of the rail weld), axle box acceleration is treated as an effective and economic measure, though an exact quantitative relation between these two quantities remains elusive. This paper aims to develop such a relation in order to provide a new theoretical basis and an analysis method for monitoring and controlling weld geometry irregularity. To better understand the characteristics of axle box acceleration, the paper consists of two parts: an observation and a numerical simulation of axle box acceleration by rail welds. Based on measured data from field tests, axle box acceleration at rail welds was found to have high-frequency vibrations in two frequency bands (i.e., 350–500 Hz and 1000–1200 Hz). Upon analyzing the vibration characteristics in time–frequency domains, the exact location of the rail weld irregularity could be identified. Subsequently, a 3D high-speed wheel/rail rolling contact finite element model was employed to investigate the effect of rail weld geometry on axle box acceleration, and led to the discovery that the weld length and depth determine the vibration frequency and amplitude of the axle box acceleration, respectively. A quantitative relation between axle box acceleration and wheel/rail force has also been determined. Finally, we propose an approach for real-time health detection of rail welds and discuss the influence of other defects and rail welds on the acceleration signal of the axle box.

Correlation of track irregularities and vehicle responses based on measured data

ABSTRACTTrack geometry quality and dynamic vehicle response are closely related, but do not always correspond with each other in terms of maximum values and standard deviations. This can often be seen to give poor results in analyses with correlation coefficients or regression analysis. Measured data from both the EU project DynoTRAIN and the Swedish Green Train (Gröna Tåget) research programme is used in this paper to evaluate track–vehicle response for three vehicles. A single degree of freedom model is used as an inspiration to divide track–vehicle interaction into three parts, which are analysed in terms of correlation. One part, the vertical axle box acceleration divided by vehicle speed squared () and the second spatial derivative of the vertical track irregularities (), is shown to be the weak link with lower correlation coefficients than the other parts. Future efforts should therefore be directed towards investigating the relation between axle box accelerations and track irregularity second derivatives.

Evaluating Degradation at Railway Crossings Using Axle Box Acceleration Measurements.

In this paper, we investigate the capability of an axle box acceleration (ABA) system to evaluate the degradation at railway crossings. For this purpose, information from multiple sensors, namely, ABA signals, 3D rail profiles, Global Positioning System (GPS) and tachometer recordings, was collected from both nominal and degraded crossings. By proper correlation of the gathered data, an algorithm was proposed to distinguish the characteristic ABA related to the degradation and then to evaluate the health condition of crossings. The algorithm was then demonstrated on a crossing with an unknown degradation status, and its capability was verified via a 3D profile measurement. The results indicate that the ABA system is effective at monitoring two types of degradations. The first type is uneven deformation between the wing rail and crossing nose, corresponding to characteristic ABA frequencies of 230–350 and 460–650 Hz. The second type is local irregularity in the longitudinal slope of the crossing nose, corresponding to characteristic ABA frequencies of 460–650 Hz. The types and severity of the degradation can be evaluated by the spatial distribution and energy concentration of the characteristic frequencies of the ABA signals.

Robust and Predictive Fuzzy Key Performance Indicators for Condition-Based Treatment of Squats in Railway Infrastructures

This paper presents a condition-based treatment methodology for a type of rail surface defect called squat. The proposed methodology is based on a set of robust and predictive fuzzy key performance indicators. A fuzzy Takagi-Sugeno interval model is used to predict squat evolution for different scenarios over a time horizon. Models including the effects of maintenance to treat squats, via either grinding or replacement of the rail, are also described. A railway track may contain a huge number of squats distributed in the rail surface with different levels of severity. This paper proposes to aggregate the local squat interval models into track-level performance indicators including the number and density of squats per track partition. To facilitate the analysis of the overall condition, a single fuzzy global performance indicator per track partition is proposed based on a fuzzy expert system that combines all the scenarios and predictions over time. The proposed methodology relies on the early detection of squats using axle box acceleration measurements. Real-life measurements from the Meppel-Leeuwarden track in the Dutch railway network are used to show the benefits of the proposed methodology. The use of robust and predictive fuzzy performance indicators facilitates the visualization of the track health condition and eases the maintenance decision process.

Wheel–Rail Impact at Crossings: Relating Dynamic Frictional Contact to Degradation

Irregularities in the geometry and flexibility of railway crossings cause large impact forces, leading to rapid degradation of crossings. Precise stress and strain analysis is essential for understanding the behavior of dynamic frictional contact and the related failures at crossings. In this research, the wear and plastic deformation because of wheel–rail impact at railway crossings was investigated using the finite-element (FE) method. The simulated dynamic response was verified through comparisons with in situ axle box acceleration (ABA) measurements. Our focus was on the contact solution, taking account not only of the dynamic contact force but also the adhesion–slip regions, shear traction, and microslip. The contact solution was then used to calculate the plastic deformation and frictional work. The results suggest that the normal and tangential contact forces on the wing rail and crossing nose are out-of-sync during the impact, and that the maximum values of both the plastic deformation and frictional work at the crossing nose occur during two-point contact stage rather than, as widely believed, at the moment of maximum normal contact force. These findings could contribute to the analysis of nonproportional loading in the materials and lead to a deeper understanding of the damage mechanisms. The model provides a tool for both damage analysis and structure optimization of crossings.

Dynamic Response of Wheel-Rail Interaction at Rail Weld in High-Speed Railway

As a main part of continuously welded rail track, rail weld widely exists in high-speed railway. However, short-wave irregularities can easily initiate and develop in rail weld due to the limitation of welding technology and thus rail weld has been a main high-frequency excitation and is responsible for deterioration of track components. This work reports a 3D finite element model of wheel-rail rolling contact which can simulate dynamic wheel-rail interaction at arbitrary contact geometry up to 400 km/h. This model is employed to investigate dynamic response of wheel-rail interaction at theoretical and measured rail weld, including wheel-rail force and axle-box acceleration. These simulation results, combined with Quality Index (QI) method, are used to develop a quantitative expression, which can be easily applied for evaluating rail weld deterioration based on measured rail profiles and axle-box acceleration.

Study on application of axle-box acceleration measured on track inspection car for rail corrugation management on railway track

Study on application of axle-box acceleration measured on track inspection car for rail corrugation management on railway track

Health condition monitoring of insulated joints based on axle box acceleration measurements

This paper presents a health condition monitoring system for insulated rail joints (IRJs) based on axle box acceleration (ABA) measurements. The ABA signals from all the wheels of the measuring train are processed to extract those characteristics that better represent the quality of the IRJ. Then, different indicators are used for damage assessment, the most relevant being a set of frequency bands in the ABA power spectrum. A detection algorithm is proposed based on the derived frequency characteristics of the ABA signal. We compared the responses of IRJs in good condition with those in poor condition. Track inspections were performed to validate the health condition monitoring methodology in different IRJs of the Dutch railway network. The hit rate of IRJs detection was 84% for two validated tracks. The damage assessment procedure allowed to prioritize the IRJs that require maintenance. This information is useful for the railway inframanagers as it allows to predict where safety compromises will be faced.

Monitoring bolt tightness of rail joints using axle box acceleration measurements

Rail joints are a weak component in railway tracks because of the large impact and wheel-rail contact forces. Every train passage contributes to the deterioration of rail joints, causing visible (e.g. battered rails) and invisible (e.g. loose bolts) damages. The invisible damage cannot be detected by the commonly performed visual inspection, which is labor intensive, unreliable, intrusive and unsafe. In this paper, a vehicle-borne monitoring system is used to automatically detect and assess the tightness condition of bolts at rail joints. The monitoring method is developed based on field Axle Box Acceleration (ABA) measurements using different bolt tightness conditions. The suitability of the method is assessed by bolt tightness prediction and verification of a set of rail joints in the tram network of Sheffield, United Kingdom. The results show that ABA system can be employed to monitor bolt tightness conditions at rail joints.With this information better planning for selective preventive maintenance actions can be taken over rail joints.

Axlebox accelerations: Their acquisition and time–frequency characterisation for railway track monitoring purposes

Railway track maintenance is becoming a real challenge for Railway Engineers due to the need of meeting increasingly high quality requirements by means of cost-effective procedures. Frequently, this can be only achieved by implementing some technological developments from other fields into the railway sector, such as Digital Signal Processing. Indeed, the present work delves into data acquisition and processing techniques in order to enhance track surveying processes. For this purpose, run tests on the Metropolitan Rail Network of Valencia (Spain) were carried out, and axlebox accelerations were gathered and analysed in different ways. The results determined the optimal sampling and filtering frequencies as well as the location of accelerometers along the train. Furthermore, by means of spectral analysis and time–frequency representations, diverse track defects, track singularities and vibration modes can be clearly identified. It is shown how, with a Hamming time window of 0.5s and an overlapping of 95%, a wide set of track defects can be detected, without the need of complementary analyses. These values yield the best results as they are a good compromise between time and frequency resolution and allow for appropriate pattern recognition of the corresponding track singularities and resonant frequencies.

鉄道車両の台車で測定した加速度によるレール波状摩耗の発生機構の推定

In this study, we examined the rail corrugation generated on the high rail of railway track, and measured acceleration of axle-box of the bogie of railway vehicle for clarification of the generation mechanism of rail corrugation. We tried to grasp the dynamic interaction between the vehicle and the track structure where the rail corrugation had been generated on the high rail by analyzing the data of the axle-box acceleration. As a result, we confirmed that the track supporting stiffness had a great influence on the generation of the high rail corrugation. Then, it is estimated that the high rail side wheel of leading axle of bogie resonated remarkably at about 60Hz with the track of which the sleeper was not elastically supported, and the high rail corrugation was caused by this vibration.

Improvements in Axle Box Acceleration Measurements for the Detection of Light Squats in Railway Infrastructure

Squats are a type of short-wave rolling contact fatigue defect whose early detection can contribute to cost reductions in the railway industry. This paper demonstrates how the early detection of squats is possible via enhanced instrumentation based on axle box acceleration (ABA) and adequate postprocessing. Three improvements are discussed. The first corresponds to the use of longitudinal ABA to enhance measurement sensitivity to light squats. Compared to vertical ABA, longitudinal ABA does not contain the vibrations of the rail, fastening, sleepers, and ballast, and thus, the impact-related vibration is considerably stronger in the signal. The second improvement considers the use of multiple sensors, noise-reduction techniques, and repeated measurements. Due to hunting, the wheels of a measuring train do not always pass over small squats; thus, light squats are more likely to be detected using multiple sensors and multiple measurement runs. The third improvement concerns the signal-processing solution for the reduction of disturbances from wheel defects. Extensive field measurements show that these improvements make the characteristics of squats more visible in signals and allow the squats to be distinguished from vibrations of other origins.

Time–frequency processing of track irregularities in high-speed train

Track irregularities are the main source of vehicle vibration. With the increase in the speed, the track irregularities have become a more significant issue of concerned. The axle box acceleration signals can be obtained for analyzing the track irregularities, but the signals are usually non-stationary and signal processing results are not normally satisfied with the ordinary way. Thus, time–frequency distribution analysis is proposed to use in this study. To minimize the cross-terms, a new method based on Empirical Mode Decomposition (EMD) and Cohen׳s class distribution has been developed and advanced. This approach has been tested with three typical simulation signals and then applied to analyze the track irregularities. The result is consistent with the result from track inspection cars. This indicates this new algorithm is suitable for analyzing the track irregularities. It can be applied in rail irregularity measurement to compensate some shortages of the track inspection cars.

Dynamic Wheel–Rail Interaction Over Rail Squat Defects

Dynamic interaction between wheel and rail generates vibration and acoustic radiations transmitted through other media such as structural track systems, air, and rolling stock. Noteworthy, both wheel and rail irregularities often induce additional impact vibration and noise along the rail corridor. Rail squats and studs are typically classified as the development of any cracks that have grown longitudinally and laterally through the subsurface and become a laminated crack resulting in a depression of the rail surface. The rail defects are commonly referred to as ‘squats’ when they are initiated from rolling contact fatigue cracks, and as ‘studs’ when they are associated with a white etching layer due to wheel slips or excessive tractive effort. Interestingly, recent research shows that rail squats can be found almost everywhere, and every type of track structures, gradients and geometries in either light passenger or heavy freight traffics and for low, medium or high speed trains all over the world. A more pronounced issue appears when the crack grows and finally flakes off the rail. This paper highlights the monitoring of wheel–rail interaction over rail squat defects. Using the axle box acceleration data obtained from the calibrated track recording vehicle, the frequency spectra can be analysed. The results demonstrate an apparent influence of squats on the wheel–rail interaction over the defective sections and increased acoustic radiation at the high frequency range. The practical understanding will also enhance the development of acoustic- and vibration-based monitoring systems of rail surface defects.

Time-frequency analysis of wheel-rail shock in the presence of wheel flat

Abstract: Against the deficiencies of traditional time domain and frequency domain analysis in detecting wheel-rail (W-R) system hidden risks which wheel flats generate, the time-frequency characteristics of W-R shock caused by wheel flat are analyzed and the vehicle-rail dynamic model with wheel flat is investigated. The 10 degrees of freedom (DOF) vehicle model is built up. 90-DOF rail model is constructed. The wheel flat excitation model is built up. The vehicle-track coupling dynamic model including wheel flat excitation is set up through nonlinear Hertzian contact theory. The vertical accelerations of axle box are calculated at different speeds and flat sizes based on the vehicle-track coupling dynamic model with wheel flat. Frequency slice wavelet transform (FSWT) is employed to analyze time-frequency characteristics of axle box accelerations to detect the W-R noncontact risks s which the traditional time domain or frequency domain method does not analyze. The results show that the small flat size and high running speed lead to high frequency W-R impact. Large flat size and high running speed result in momentary loss of W-R contact, and there exist security risks between wheel and rail. The conclusion that the phase of axle box accelerations is same to W-R forces lays a theoretical foundation of monitoring W-R contact safety from axle box acceleration instead of traditional W-R force detection.

Automatic Detection of Squats in Railway Infrastructure

This paper presents an automatic method for detecting railway surface defects called “squats” using axle box acceleration (ABA) measurements on trains. The method is based on a series of research results from our group in the field of railway engineering that includes numerical simulations, the design of the ABA prototype, real-life implementation, and extensive field tests.We enhance the ABA signal by identifying the characteristic squat frequencies, using improved instrumentation for making measurements, and using advanced signal processing. The automatic detection algorithm for squats is based on wavelet spectrum analysis and determines the squat locations. The method was validated on the Groningen–Assen track in The Netherlands and accurately detected moderate and severe squats with a hit rate of 100%, with no false alarms. The methodology is also sensitive to small rail surface defects and enables the detection of squats at their earliest stage. The hit rate for small rail surface defects was 78%.