Broken Rail Research Articles

Imaging localisation of damages on switch rail foot based on laser ultrasonic testing

ABSTRACT The corrosion on the switch rail’s foot may easily lead to rail breakage. Laser ultrasound detection is often used to assess the integrity of rails. Nevertheless, the inadequate photoacoustic conversion efficiency and vulnerability to surface interference of the entirely non-contact laser ultrasound result in a diminished signal-to-noise ratio (SNR), hence impeding the efficient detection and analysis of minor damages in the rail. This work demonstrates piezoceramic material lead zirconate titanate (PZT) wafers in conjunction with a pulsed laser to create a sensor array capable of accurate array image inspections. The PZT sensor arrays are manufactured in a flexible format that may be easily installed and altered to complicated geometries. Pulsed lasers are used to achieve dense and high-frequency array excitation. This study proposes a novel probabilistic picture location identification strategy by merging the variable mode decomposition algorithm based on parameter optimization (PVMD) and the principle component analysis (PCA) algorithm. The aim is to enhance the SNR and increase the accuracy of damage findings. Simulation and experimental tests have demonstrated the accuracy of the suggested mechanisms and algorithms in identifying damaged regions.

Quantifying the effect of fixed structures on rail stress management: A numerical investigation

From 2012 to 2021, FRA accident data indicate that there have been 132 derailments caused by track buckles. Out of the 132 total derailments, 59 (or 45 %) occurred within 152 m (500 ft.) of a fixed structure. Therefore, this paper presents, validates, and applies a 3D finite element-based model to study the effect of the fixed structure on the rail gap size given a rail break. Specifically, the model was used to quantify the effect of the: 1) temperature differential between the rail neutral temperature (RNT) and the actual rail temperature (dT), 2) distance of the cut to the fixed structure, and 3) fixed structure length and anchoring patterns (ETA and EOTA). Model results indicated that at low dTs (e.g., <13.9ºC (25ºF)) the effect of the fixed structure can be considered if the cut occurred at the edge of the fixed structure with EOTA anchoring pattern and the fixed structure length of at least 18.3 m (60 ft.). At a dT of 22.2ºC (40ºF), the fixed structure should be accounted for when there is an edge cut. At extreme dTs (e.g., > 44.4ºC (80°F)) the fixed structure should be considered if the cut occurs within 152.3 m (500 ft.). Therefore, it is recommended that railroads refrain from strictly following open track guidelines for CWR (continuous welded rail) management and rather, consider the influence of fixed structures in relevant situations.

Natural rail fracture defect calibration using infrared thermography and edge detection

Rail breakage can cause train derailment that leads to catastrophic consequences, prevention of which is worthy of a significant amount of investment in finance and time. Non-destructive evaluation can provide qualitative and quantitative inspection of rail tracks in-situ to detect dangerous faults, even though these defects are primarily invisible or hardly noticed from the surface of the rail. To make it efficient and convenient, infrared thermography technique offers a remote operation without interfering with rail transportation. The image processing for edge detection can further quantify the defect deterioration by depicting the contour of the defect. Moreover, the optimal parameters for various edge operators provide reliable detection for natural fracture defects.

Damage behaviour of rail flash-butt welding joints under controlled impact kinetic energy

Rail welded joints are a critical component of seamless railway tracks, and they are essential for maintaining the continuity and smoothness of the tracks. However, they also represent weak points in the entire track, which makes these areas susceptible to frequent damage and rail breaks. This study employs an impact wear testing platform with controlled energy to compare and analyse the impact wear characteristics of three different locations (i.e., weld zone, heat-affected zone and base material) on the U75VG flash-butt welding joint. Results indicate significant differences in material properties, such as hardness and microstructure, within different zones of the flash welded rail joints, which leads to varying impact damage behaviours. The heat-affected zones, which are located on both sides of the weld zone, exhibit the weakest ability to resist impact deformation. Thus, these areas are the most vulnerable in the entire welded rail joint and are prone to damages, such as squat. In general, damage in different zones of the welded joint gradually evolves from plastic deformation and local pitting into fatigue wear with delamination as the main failure mechanism, while the surface of the heat-affected zone tends to develop an oxide debris layer. The distinct damages observed in different zones of the welded joint pose challenges to the problem of track irregularities. This study offers a theoretical framework for predicting the evolution of damage in welded joints.

Rail Structural Health Monitoring using ultrasonic guided waves: system design and deployment

Railways are a central industrial infrastructure enabling people and goods transportation all across the globe and their use is due to increase in the forthcoming years to reduce the overall carbon footprint of our modern societies. Hence the need to ensure their reliable use, as traffic interruptions or accidents can have dire social, economic and environmental impacts. In particular, rail breaks can produce such incidents and need to be monitored and prevented if possible. Ultrasonic guided waves are a promising physical phenomenon to monitor rails as they can enable the monitoring of long portions with a limited number of sensors. This talk will present a SHM system relying on such waves for rail monitoring which has been deployed for industrial tests on a subway line. The electronics, the sensors and their coupling to the rail were optimized to ensure the measurement of guided waves after a long-range propagation throughout the life of the system. Indeed, specific couplings are needed to enable long-time coupling, and so ultrasound sensitivity of the system, while the rails are bearing high loads or dilating due to temperature changes. An experimental campaign was carried out to evaluate the sensitivity of the system to rail breaks, and to demonstrate its detection under representative, uncontrolled environmental conditions. Particular considerations linked to pulse-echo inspections, inducing a sensitivity to cut-off frequencies and zero-group velocity modes, will be presented.

Automated Identification and Localization of Rail Internal Defects Based on Object Detection Networks

The timely identification of rail internal defects and the application of corresponding preventive measures would greatly reduce catastrophic failures, such as rail breakage. Ultrasonic rail defect detection is the current mainstream rail defect detection method thanks to its advantages of strong penetration, high accuracy, and ease to deploy. The 2D B-scan image output by ultrasonic detectors contains rich features of defects; however, rail engineers manually identify and localize the defect image, which can be time-consuming, and the image may be subject to missing identification or mistakes. This paper adopted state-of-the-art deep learning algorithms for novel B-scan images for the automatic identification and localization of rail internal tracks. First, through image pre-processing of classification, denoising, and augmentation, four categories of defect image datasets were established, namely crescent-shaped fatigue cracks, fishbolt hole cracks, rail web cracks, and rail base transverse cracks; then, four representatives of deep learning object detection networks, YOLOv8, YOLOv5, DETR, and Faster R-CNN, were trained with the defects dataset and further applied to the testing dataset for defect identification; finally, the performances of the three detection networks were compared and evaluated at the data level, the network structure level, and the interference adaptability level, respectively. The results show that the YOLOv8 network can effectively classify and localize four categories of internal rail defects in B-scan images with a 93.3% mean average precision at three images per second, and the detection time is 58.9%, 376.8%, and 123.2% faster than YOLO v5, DETR, and Faster R-CNN, respectively. The proposed approach could ensure the real-time, accurate, and efficient detection and analysis of internal defects to a rail.

Wayside Railway Switch and Crossing Monitoring Using Isolation Forest Anomaly Scores

Railway switch and crossing (S&amp;C) systems have complicated moving structures compared with regular rail. They require multiple components that vary in complexity. The complexity of railway S&amp;C, together with the fact that they are discontinuous points of the system, makes them vulnerable to defects such as squats. A squat on the switching rail could potentially cause rail breakage and lead to catastrophic results, such as derailment. In this study, a method based on anomaly scoring was investigated to estimate the status of an S&amp;C system with respect to squat defects. The proposed method was tested in a real environment under controlled measurement sequences. The results show that the methods can differ between an S&amp;C with squats and another one without them.

Effect of Critical Factors Influencing Longitudinal Track Resistance Leveraging Field Experimentation

As extreme temperatures increase, there is an increased need to ensure that continuous welded rail (CWR) stresses are more accurately set and better maintained. Therefore, to improve the management of CWR rail stresses and to increase safety through the reduction of buckled track derailments this paper documents the results from a field experimentation program of controlled single rail breaks (SRBs). SRBs were conducted at multiple field site locations to quantify the longitudinal resistance on both timber and concrete sleeper track. Accurate longitudinal resistance values are critical, because if the wrong value is selected, the rail neutral temperature could easily be set to a low value, increasing the probability of a track buckle or rail pull-apart, further compounding the impact of extreme temperatures. The results presented quantify the effect of sleeper and fastener type as well as ballast consolidation, and compare them with relevant results from the literature. From this, it was found that well-maintained concrete sleeper track exhibited a longitudinal resistance greater than the currently recommended value. Further, well-maintained timber sleeper track with anchors on every other sleeper exhibited a longitudinal resistance 44% lower than concrete sleeper track and 30% lower than timber track with anchors installed on every sleeper. Additionally, disturbing the ballast reduced the longitudinal resistance by 15%. Finally, the results indicated that slip was primarily occurring at the rail–sleeper interface for unanchored timber sleepers and at the sleeper–ballast interface for anchored timber sleepers and concrete sleepers.

Efficient Railway Turnout Design: Leveraging TRIZ-Based Approaches

This study focuses on the design and improvement of railway turnouts, which are critical yet complex parts of the railway infrastructure. As they are responsible for track discontinuity and potential derailments, turnouts pose significant challenges in terms of slack, misalignment and rail breakage. A new concept related to the design of turnouts, including switches and crossings, is presented in this paper. The application of TRIZ (Theory of Inventive Problem Solving) principles, specifically the use of the contradiction matrix, was instrumental to achieving these innovative designs for railway systems and represents the main contribution of the paper. Based on the systematic use of the TRIZ principles, the proposed design addresses the problems associated with switches and crossings by replacing the classic frog with a movable element that sits in the crossing gap and reduces the existing gap, thus minimising the length of the rail gap and, consequently, providing greater contact with the rail, minimising wheel impacts on the rail gap and, consequently, decreasing the risk of derailment. By reducing rail contact forces, which are a major contributor to derailments, the risk of derailment is reduced. This study also introduces a new design for the switch rail system using a piston mechanism with an up and down stroke, which is accompanied by a rotating motor at the top for controlled movement. Finally, numerical simulations were performed to validate the proposed designs.

Probability of rail break caused by out-of-round wheel loads

A simulation procedure to predict the probability of rail break due to a measured wheel load spectrum is presented. The load distribution includes a representative proportion of high-magnitude dynamic loads generated by out-of-round wheels. Linear elastic fracture mechanics is applied to determine the stress intensities of pre-existing rail head cracks in a continuously welded rail subjected to combined bending and temperature loading. Rail bending moments are evaluated using a validated time-domain model of dynamic vehicle–track interaction. The considered multi-dimensional stochastic parameter space includes field test data of dynamic loads from a wheel impact load detector and crack depths from eddy current data. Meta-models based on poly-harmonic splines are applied to reduce the computational cost of the analysis. Supported by the extensive field test data, the simulation procedure is demonstrated by investigating the influences of freight traffic type, track support stiffness and rail temperature on the probability of a rail break initiated at a pre-existing rail head crack.

Review of Critical Factors Influencing Longitudinal Track Resistance

Longitudinal track resistance is one of the most critical parameters required to accurately analyze longitudinal load propagation and refine rail neutral temperature (i.e., stress-free temperature) maintenance practices. However, longitudinal track resistance has not been consistently defined and has been quantified using multiple methods that should not be conflated. This paper documents common definitions of longitudinal track resistance and the two methods regularly used for its quantification: track panel pull test (TPPT) and single rail break (SRB). Further, this paper documents the differences in mechanics between these methods, summarizes and discusses the critical factors influencing the longitudinal track resistance values found in the literature, and adds novel TPPT longitudinal track resistance values for timber sleeper track to address the current scarcity of data found in the literature. In summary, TPPT values provide insight into the mechanics of load propagation and pre-buckle analysis while the SRB values aid in the maintenance and restoration of rail neutral temperature after a rail break or destress. Additionally, the TPPT longitudinal track resistance values reported in the literature were independent of panel length, were influenced most by the presence of a vertical load, and were reduced by 25% when the ballast was disturbed. Finally, novel TPPT results indicated the longitudinal resistance of timber sleeper track was 19% lower than concrete sleeper track and that unfastened sleepers still transferred longitudinal load when the cribs were full and ballast was compacted.

The Effectiveness of Distributed Acoustic Sensing (DAS) for Broken Rail Detection

Broken rails remain one of the main causes of railway accidents despite improved rail quality and inspections. Today, signalling system with track circuits are often used to detect broken rails, however new signalling systems such as the European Train Control System (ETCS) with axle counters are replacing track circuits and therefore new methods are needed to detect broken rails. One promising technology is distributed acoustic sensing (DAS). The best DAS analytical techniques to show the position of the rail break are gradient analysis, convolution using the train consist and 2 D sinusoidal convolution. This paper describes field tests carried out on DAS to evaluate its ability to detect broken rails and the moment when rails break. The testing showed that DAS has good potential for detecting broken rails in both scenarios. Especially helpful is the ability of DAS to identify the moment of rail breakage and its potential for determining the break’s location on open lines. Recommendations for further research include testing these qualities in more detail and considering how DAS could be efficiently combined with new signalling systems.

Study of Melting Methods by Electric Resistance Welding of Rails

An analysis of the results of rail operation shows that up to a third of all rail breaks in the railway line and up to 12.9% of all withdrawn acute defective rails are associated with welded joints. This is largely explained by the formation of structures with martensite sections in the welded joints of rails and the formation of burns. This work presents the results of studying welded joints, obtained under three welding modes (continuous flash welding, pulsating flash welding and combined flash welding). The conducted studies have shown that the flash welding mode significantly influences both the cooling rate value and the very nature of the thermal cycle of the welded joint as a whole. Changes in the cooling rate under different modes exert a significant influence on the structure and properties of the weld. Resistance welding of rails from the steel grade E76HGF by pulsating flash welding can result in the appearance of needle martensite areas, which is the reason for increased embrittlement of the weld and a decrease in its properties. The conducted field experiments have reliably shown that in the conditions of the combined welding mode it becomes possible to avoid these problems. Moreover, a slight increase in the mechanical properties of the weld in the range of 2–4% has been experimentally recorded, and the destructive load of the welded joint of the rail increases by 2–3% at high values of the bending deflection. In turn, these factors allow a significant reduction in the number of cases of rail welded-joint failures in real conditions of their operation.

Development of rails of a new category for use in particularly harsh operating conditions

Introduction. In the conditions of an annual increase in load stress on the roads of the Eastern Polygon, an effective technical solution to the problem of an increased number of rolling stock derailments due to rail breakage is the creation of rails for cold climate conditions with increased hardness to increase wear resistance and contact endurance with simultaneously high values of impact strength. Such a set of properties can be achieved by using separate heating for quenching and cooling with a quenching medium with a high cooling capacity. Rails manufactured using this technology will belong to a new category. In this regard, the purpose of this work was to create a new category of rails for their use in particularly harsh operating conditions.Materials and methods. In this paper the effect of separate induction heating before differentiated quenching with compressed air of controlled humidity on the microstructure and mechanical properties (hardness, mechanical properties during tensile and impact tests, endurance limit, cyclic crack resistance) of rails of type R65 was investigated.The results of the study. A comparative analysis of the results obtained with similar indicators for rails of the DT350, DT350NN and DT370IK categories according to GOST R 51685-2013 was carried out. Studies of the chemical composition, mechanical properties, hardness on the rolling surface of the rail head and cross-section, as well as the microstructure of the rails of the experimental batch showed compliance with the requirements of GOST R 51685-2013 for rails of categories DT350, DT370IK, DT350NN.Discussion and conclusion. It is shown that as a result of the application of differentiated thermal hardening of the rail using compressed air of controlled humidity as a quenching medium, a new category of DTO350NN rails was obtained, characterized by a favorable combination of strength properties, plasticity characteristics and brittle fracture resistance indicators. Rails of the new category can be recommended for use in particularly severe operating conditions (in curved sections of the track of a small radius at low temperatures), including on the roads of the Eastern Polygon.

Automatic Control over Rail Breakage in Sections with AC Electric Traction

Automatic Control over Rail Breakage in Sections with AC Electric Traction

Research on Coded Excitation Using Kasami Sequence in the Long Rail Detection Based on UGW

For a broken rail detection system based on ultrasonic guided waves (UGW), the multimodal and dispersion characteristics of UGW degrade signal-to-noise ratio (SNR) and range resolution. To improve the SNR of the received signals and range resolution, the coded excitation based on Kasami sequences is presented in this work. Utilizing a PSpice model of piezoelectric ultrasonic transducers, as well as conducting field tests based on the pitch–catch mechanism, it is shown that encoded UGW signals can increase the SNRG (the gain of SNR) by 6.29 dB. The main lobe width of the coded excitation is mainly determined by the number of carrier cycles and the carrier waveform, and the size of the side lobes is mainly determined by the number of coding bits. To quickly identify the corresponding transmissions at the receivers, a peak detection algorithm is shown. It is based on bandpass filter, triangle filter and Hilbert transform. Its accuracy and effectiveness are validated by using some field tests under different distances. It can be concluded that the shown adaptive peak algorithm has strong robustness and immunity to noise.

Rail temperature variation under heavy haul operations

There currently does not exist in industry a reliable method for the detection of rail foot flaws. Like their head-based counterparts, foot flaws result in broken rail with potentially catastrophic consequences. A proposed area of research for the detection of these flaws is thermography, a non-contact method of measuring and analysing infrared emissions from an object under test. In industry, active excitation thermography is the most common, requiring an excitation source. This paper will present a temperature measurement system and a method of transient temperature extraction from the running rails for the effects of a passing train to evaluate heat transfer in the practical rail environment. The outcomes of these results will provide future direction in the development of a rail heat transfer model and determine if train passage provides enough active excitation for a thermography-based detection technique.

Rail Break Prediction and Cause Analysis Using Imbalanced In-Service Train Data

Timely detection and identification of rail breaks are crucial for safety and reliability of railway networks. This article proposes a new deep learning-based approach using the daily monitoring data from in-service trains. A time-series generative adversarial network (TimeGAN) is employed to mitigate the problem of data imbalance and preserve the temporal dynamics for generating synthetic rail breaks. A feature-level attention-based bidirectional recurrent neural network (AM-BRNN) is proposed to enhance feature extraction and capture two-direction dependencies in sequential data for accurate prediction. The proposed approach is implemented on a three-year dataset collected from a section of railroads (up to 350 km) in Australia. A real-life validation is carried out to evaluate the prediction performance of the proposed model, where historical data are used to train the model and future “unseen” rail breaks along the whole track section are used for testing. The results show that the model can successfully predict nine out of 11 rail breaks three months ahead of time with a false prediction of nonbreak of 8.2%. Predicting rail breaks three months ahead of time will provide railroads enough time for maintenance planning. Given the prediction results, a Shapley additive explanations (SHAP) method is employed to perform a cause analysis for individual rail break. The results of cause analysis can assist railroads to plan appropriate maintenance to prevent rail breaks.

Automatic control of rail breakage in sections with AC electric traction

Automatic control of rail breakage in sections with AC electric traction

Thermal non-destructive characterization of rail networks by using Infrared Thermography and FEM simulation

Because of the repeated passage of trains, anomalies are created inside the rails in the form of cracks of different shapes and position. These are due essentially to the wheel – rail contact. They present a hazard causing at the final stage rail failure, train derailment and accidents. Detecting track anomalies has become a major issue for the entire rail industry around the world. This paper focuses on the degradation of rails in urban railways in terms of cracks. The purpose is to develop an approach to detect and predict rail breaks, which will optimize maintenance task. Infrared thermography was used in order to characterise the effect of a defect on the acquired thermogram. Different defects were considered by varying their size, depth and inclination angle with respect to the rail surface.