Search Results (556)

Periodic visual inspections are currently conducted to maintain the condition of railway bridges. These inspections rely on direct visual assessments by human inspectors, often requiring specialized equipment such as aerial ladders. However, this method is not only time-consuming and costly but also involves significant safety risks. Therefore, there is a growing need for a more efficient and reliable alternative to traditional visual inspections of railway bridges. In this study, we evaluated and compared the performance of damage detection using U-Net-based deep learning models on images captured by unmanned aerial vehicles (UAVs). The target damage types include cracks, concrete spalling and delamination, water leakage, exposed reinforcement, and paint peeling. To enable multi-class segmentation, the U-Net model was trained using three different loss functions: Cross-Entropy Loss, Focal Loss, and Intersection over Union (IoU) Loss. We compared these methods to determine their ability to distinguish actual structural damage from environmental factors and surface contamination, particularly under real-world site conditions. The results showed that the U-Net model trained with IoU Loss outperformed the others in terms of detection accuracy. When applied to field inspection scenarios, this approach demonstrates strong potential for objective and precise damage detection. Furthermore, the use of UAVs in the inspection process is expected to significantly reduce both time and cost in railway infrastructure maintenance. Future research will focus on extending the detection capabilities to additional damage types such as efflorescence and corrosion, aiming to ultimately replace manual visual inspections of railway bridge surfaces with deep-learning-based methods. Full article

The structural design of rail vehicle bodies significantly influences rail vehicle performance, passenger comfort, and operational efficiency. This study presents a comparative analysis of three key concepts of a rail vehicle body, namely a differential, an integral, and a hybrid structure, with a focus on their structural principles, material utilization, and implications for manufacturability and maintenance. Three rail vehicle body variants were developed, each incorporating a low-floor configuration to enhance accessibility and interior layout flexibility. The research explores the suitable placement of technical components such as a power unit and an air-conditioning system, and it evaluates interior layouts aimed at maximizing both passenger capacity and their travelling comfort. Key features, including door and window technologies, thermal comfort solutions, and seating arrangements, are also analyzed. The study emphasizes the importance of compromises between structural stiffness, reparability, production complexity, and passenger-oriented design considerations. A part of the research includes a proposal of three variants of a rail vehicle body frame, together with their strength analysis by means of the finite element method. These analyses identified that the maximal permissible stresses for the individual versions of the frame were not exceeded. Findings contribute to the development of more efficient, accessible, and sustainable regional passenger rail vehicles. Full article

To overcome the limitations of current train positioning systems, including low positioning accuracy and heavy reliance on track transponders or GNSS signals, this paper proposes a novel LiDAR-inertial and visual landmark fusion framework. Firstly, an IMU preintegration factor considering the Earth’s rotation and a LiDAR-inertial odometry factor accounting for degenerate states are constructed to adapt to railway train operating environments. Subsequently, a lightweight network based on YOLO improvement is used for recognizing reflective kilometer posts, while PaddleOCR extracts numerical codes. High-precision vertex coordinates of kilometer posts are obtained by jointly using LiDAR point cloud and an image detection box. Next, a kilometer post factor is constructed, and multi-source information is optimized within a factor graph framework. Finally, onboard experiments conducted on real railway vehicles demonstrate high-precision landmark detection at 35 FPS with 94.8% average precision. The proposed method delivers robust positioning within 5 m RMSE accuracy for high-speed, long-distance train travel, establishing a novel framework for intelligent railway development. Full article

Accurate diagnostics of the railway track axis are crucial for enabling higher operational speeds of rail vehicles. Consequently, assessment methods are under continuous refinement. The precision of mobile GNSS-based measurements is influenced by external factors such as terrain obstructions and satellite geometry. This study presents an innovative approach that continuously monitors a predefined multi-receiver GNSS configuration in real time to enhance positioning accuracy. Field experiments on operational railway lines demonstrate that the proposed method significantly improves measurement reliability and reduces uncertainty compared to the conventional CQ-based quality assessment. The algorithm underlying the proposed method is formulated through analytical equations, allowing it to be implemented in any programming environment. The method’s effectiveness is demonstrated by comparing the expanded uncertainty calculated using GNSS-provided data with that obtained through the proposed approach. Full article

From the point of view of the intelligent operation and maintenance of high-speed train tracks, this paper examines the research status of high-speed train rail damage detection technology in the field of high-speed train track operation and maintenance detection in recent years, summarizes the damage detection methods for high-speed trains, and compares and analyzes different detection technologies and application research results. The analysis results show that the detection methods for high-speed train rail damage mainly focus on the research and application of non-destructive testing technology and methods, as well as testing platform equipment. Detection platforms and equipment include a new type of vortex meter, integrated track recording vehicles, laser rangefinders, thermal sensors, laser vision systems, LiDAR, new ultrasonic detectors, rail detection vehicles, rail detection robots, laser on-board rail detection systems, track recorders, self-moving trolleys, etc. The main research and application methods include electromagnetic detection, optical detection, ultrasonic guided wave detection, acoustic emission detection, ray detection, vortex detection, and vibration detection. In recent years, the most widely studied and applied methods have been rail detection based on LiDAR detection, ultrasonic detection, eddy current detection, and optical detection. The most important optical detection method is machine vision detection. Ultrasonic detection can detect internal damage of the rail. LiDAR detection can detect dirt around the rail and the surface, but the cost of this kind of equipment is very high. And the application cost is also very high. In the future, for high-speed railway rail damage detection, the damage standards must be followed first. In terms of rail geometric parameters, the domestic standard (TB 10754-2018) requires a gauge deviation of ±1 mm, a track direction deviation of 0.3 mm/10 m, and a height deviation of 0.5 mm/10 m, and some indicators are stricter than European standard EN-13848. In terms of damage detection, domestic flaw detection vehicles have achieved millimeter-level accuracy in crack detection in rail heads, rail waists, and other parts, with a damage detection rate of over 85%. The accuracy of identifying track components by the drone detection system is 93.6%, and the identification rate of potential safety hazards is 81.8%. There is a certain gap with international standards, and standards such as EN 13848 have stricter requirements for testing cycles and data storage, especially in quantifying damage detection requirements, real-time damage data, and safety, which will be the key research and development contents and directions in the future. Full article

Urban public transport represents a fundamental pillar of a sustainable transport system and a key subsystem within the broader mobility framework in urban environments. This paper focuses on the analysis and optimization of the public transport system in the city of Prievidza and the nearby town of Bojnice in Slovakia, which currently face challenges such as low system attractiveness, operational inefficiency, and weak integration with regional railway transport. This study presents the results of a comprehensive analysis of existing public transport services in Prievidza and Bojnice, including an assessment of passenger flows, line network structure, transfer connections, and operational parameters. Based on the identified deficiencies, a new urban public transport network system is proposed, emphasizing direct links to the railway network. This methodology is developed in the context of an integrated timed-transfer timetable, with defined system time slots at the main transfer hub and a newly designed line network with standardized paths and regular intervals. The proposed system ensures significantly improved connectivity between urban transport and rail services, reduces deadhead kilometres, lowers the number of required vehicles, and leads to a reduction in operational costs by up to 20%. The resulting model serves as a transferable example of efficient service planning in medium-sized cities, with a focus on functional integration, operational efficiency, and sustainable urban development. Full article

Non-active current in the time domain is considered for application to the diagnostics and classification of loads in power grids based on waveform-distortion characteristics, taking as a working example several recordings of the pantograph current in an AC railway system. Data are processed with a deep autoencoder for feature extraction and then clustered via k-means to allow identification of patterns in the latent space. Clustering enables the evaluation of the relationship between the physical meaning and operation of the system and the distortion phenomena emerging in the waveforms during operation. Euclidean distance (ED) is used to measure the diversity and pertinence of observations within pattern groups and to identify anomalies (abnormal distortion, transients, …). This approach allows the classification of new data by assigning data to clusters based on proximity to centroids. This unsupervised method exploiting non-active current is novel and has proven useful for providing data with labels for later supervised learning performed with the 1D-CNN, which achieved a balanced accuracy of 96.46% under normal conditions. ED and 1D-CNN methods were tested on an additional unlabeled dataset and achieved 89.56% agreement in identifying normal states. Additionally, Grad-CAM, when applied to the 1D-CNN, quantitatively identifies the waveform parts that influence the model predictions, significantly enhancing the interpretability of the classification results. This is particularly useful for obtaining a better understanding of load operation, including anomalies that affect grid stability and energy efficiency. Finally, the method has been also successfully further validated for general applicability with data from a different scenario (charging of electric vehicles). The method can be applied to load identification and classification for non-intrusive load monitoring, with the aim of implementing automatic and unsupervised assessment of load behavior, including transient detection, power-quality issues and improvement in energy efficiency. Full article

In the context of global environmental pollution and energy shortages, the use of lightweight designs of railway vehicles has become a key technological approach to improve energy efficiency and reduce carbon emissions. The use of lightweight and high-strength materials such as carbon-fiber-reinforced composites to replace traditional metal vehicle structures holds great application potential. In this study, random track loads and ballast impact loads that may occur during service were considered, and a finite-element model of the electric locomotive coupling protective cover was established. The impact resistance of CFRP, GFRP, and their interlayer hybrid configurations (C/G/C and G/C/G) against structural and ballast impacts were investigated. The calculation results showed that the CFRP protective cover exhibited the best structural impact resistance (with the lowest Tsai–Wu strength failure values), but it also had the largest maximum deformation displacement (2.36 mm) under ballast impact conditions. In contrast, the GFRP protective cover had a higher Tsai–Wu strength failure value, indicating that it had worse structural impact resistance, but it had a lower maximum deformation displacement (2.20 mm) under ballast impact conditions, demonstrating superior ballast impact resistance. The impact resistances of the hybrid-layered protective covers fell between those of the CFRP and GFRP in terms of the structural impact, while their ballast-impact resistance surpassed those of single-fiber configurations. Full article

This study investigates the dynamic interaction between railway vehicles and tracks, focusing on the effects of elastic–viscous properties of spring suspensions and track inertia. This research examines vertical oscillations of a railway car moving on a non-uniformly elastic track, modeled as a system with lumped parameters. Analytical and numerical methods are employed to derive track parameters by comparing frequency characteristics of continuous and discrete models. Key findings reveal that adjacent wheelsets influence interaction forces and bending moments by approximately 10%, while rail deflections are affected by up to 20% within the speed range of 60–180 km/h and for disturbances up to 20 Hz. Experimental validation using a roller test rig confirms the theoretical predictions, demonstrating the significance of track inertia and damping in dynamic analyses. This study provides practical recommendations for improving railway vehicle design and track maintenance, emphasizing the need to account for nonlinearities and inertial effects in high-speed scenarios. Full article

The article explores the capacity of zero-emission urban public transport (PT) and proposes a standardised method for calculating it across different PT corridors (bus, tram, metro and urban railway). As the European Union (EU) tightens regulations on emissions, targeting also PT, cities are increasingly shifting to electric and hydrogen-powered vehicles. A significant challenge was the lack of a unified methodology to calculate the capacity of zero-emission vehicles, e.g., battery-powered buses carry fewer passengers than diesel ones due to weight restrictions. The article addresses this gap by creating capacity matrices for various vehicle types based on standardised assumptions. Vehicle capacity is calculated based on seating and standing space, with standing passenger space standardised to 0.2 m²/person (E Level of Service). A detailed rolling stock analysis shows how modern designs and floor layouts impact passenger space. Matrices were developed for each mode of transport, showing the number of transported passengers per hour depending on vehicle type and service frequency. The highest capacity is achieved by metro and urban railway systems (up to 95,000+ passengers/hour/direction), while buses offer the lowest (up to 7800 passengers/hour/direction). The authors recommend standardising calculation methods and integrating matrices into planning tools for urban PT corridors. Full article

Magnetic levitation (maglev) technology offers significant advantages for rail transport, including frictionless propulsion, reduced noise, and lower maintenance costs. However, its widespread adoption has been limited due to the need for a dedicated infrastructure incompatible with conventional rail networks. The MaDe4Rail project, funded by Europe’s Rail Joint Undertaking (ERJU), explores Maglev-Derived Systems (MDSs) as means to integrate maglev-inspired solutions into existing railway corridors with minimal modifications. This paper focuses on the so-called “hybrid MDS” configuration, which refers to levitating systems that can operate on existing rail infrastructure. Unlike current maglev systems, which require dedicated tracks, the proposed MDS system is designed to operate on conventional rail tracks, allowing for its compatibility with traditional trains and ensuring the interoperability of lines. In order to identify the most viable solution, two different configurations have been analysed. The evaluated scenario could benefit from the introduction of hybrid MDSs based on magnetic levitation, where a group of single vehicles, also called pods, is used in a virtual coupling configuration. The objective of this case study is to increase the capacity of traffic on the existing railway line by significantly reducing travel time, while maintaining a similar energy consumption to that of the current conventional trains operating on this line. Simulation results indicate that the hybrid MDS can optimise railway operations by taking advantage of virtual coupling to improve traffic flow, reducing travel times and energy consumption with the optimisation of the aerodynamic drag. The system achieves a balance between increased speed and energy efficiency, making it a viable alternative for future rail transport. An initial cost–benefit analysis suggests that the hybrid MDS could deliver substantial economic advantages, positioning it as a promising solution for enhancing European railway networks with minimal infrastructure investment. Full article

This document comprehensively analyses the literature on accelerometers used in monitoring systems designed for rail vehicle applications. It reviews the current research on this topic and highlights key findings, methodologies, and trends in the field. Additionally, it discusses the role of accelerometers in enhancing safety and performance within rail vehicle systems. This review is structured into several sections: Introduction, Fundamentals of Accelerometer Data, Signal-Processing Techniques, Examples of Accelerometers Used in Railway Monitoring Systems, and a Guide for Choosing the Right Accelerometer. One of the primary contributions of this paper is recommending the best accelerometer in terms of cost and performance for use in the rail vehicle industry. Future work will consider using an online detection tool for the acceleration of the frame of the railway coach and signalization of the peak values using the train intercom to the driver and static diagnosis systems. This approach aims to facilitate the detection of track irregularities, wind influence, and failures of the coach suspensions, which can be easily detected. Full article

The dislocation of the active fault zone altered the stress distribution and geometry of the track structure in the tunnel, which in turn affected the safety and stability of the train operation. Polyurethane-solidified track bed (PSTB) is suitable for sections crossing through active fault zones due to its excellent serviceability and adaptability to deformation. In this study, the stress and deformation response induced by active fault dislocation are investigated for this novel track structure. The corresponding deformation of track structure is subsequently introduced into a vehicle-track dynamics model to calculate the train operation safety index. The study examines the impact of fault displacement on railway track structures, revealing significant vertical deformation in rails that corresponds to the displacement magnitude. The effects are mainly confined to the active fault zone and its immediate surroundings, with variations depending on the fault zone’s structural characteristics. Key factors such as larger displacements, steeper fault angles, and narrower fault zones increase stress on track components, particularly the wide sleeper, which is prone to cracking and represents a structural vulnerability. Higher fault displacement, narrower zones, steeper angles, and increased train speeds elevate derailment risks and wheel load reduction rates, potentially exceeding safety limits. To ensure safety under typical fault conditions, train speeds should not exceed 250 km/h for PSTB with a 40 mm displacement and a 60° fault angle. These findings provide critical guidance for railway construction in fault-prone areas. Full article

One of the main challenges in the operation of electric traction vehicles is ensuring safety and operational reliability. To ensure the safety of railway traffic, vehicles must undergo a series of tests related to the investigation of disturbances generated, among others, in the return current to the mains. This problem is further complicated by the inability to perform such measurements under laboratory conditions. The implementation of tests under real conditions determines the appearance of additional potential interference sources, from power sources to improper interactions between current collectors and the overhead contact system, and it requires strict compliance with regulatory standards and the implementation of standardized testing procedures. This article presents issues related to the investigation and analysis of the electromagnetic compatibility of rolling stock with train detection systems using track circuits. The aim of these tests is to determine the harmonic components in the traction current in relation to the permissible levels specified in the latest editions of the European Railway Agency—ERA/ERTMS/033281 version 5.0 documents and Annex S-02 to the List of the President of the Office of Rail Transport. The measurement methodology and test procedures are presented in detail with respect to current legal requirements. Full article

The current technical condition of facilities designated for the technical–hygienic maintenance of railway rolling stock is unsatisfactory, as they are neither technologically nor technically equipped to meet the required quality standards. Maintenance is often carried out in open spaces or directly on the tracks of major railway junctions, which prevents year-round execution of these services and causes operational limitations. This article analyses and proposes solutions for the technical–hygienic maintenance center (THU) of railway rolling stock at the Nové Zámky railway station in Slovakia, focusing on improving the efficiency and quality of the provided services. The analysis includes an assessment of technological procedures, identification of operational deficiencies, and a comparison of current maintenance standards with the requirements for contemporary railway systems, such as automated diagnostic platforms, predictive maintenance modules, and modular cleaning infrastructure. The optimization of THU services considers the average time norms for selected technological procedures and the characteristics of train sets passing through the center. The proposed solution involves a more efficient scheduling of operations in line with the valid railway traffic timetable and train set circulation, utilizing a graphical planning method for modelling and optimizing the facility’s service processes. The implementation of optimization measures can lead to increased capacity and efficiency of maintenance, reduced time required for individual procedures, and lower operational costs. The study’s results provide practical recommendations for improving the quality of technical–hygienic maintenance at railway junction stations, contributing to greater railway transport reliability and an overall improvement in passenger comfort. Additionally, the findings offer a transferable framework that may inform the planning and modernization of maintenance facilities at other regional railway stations facing similar infrastructural and operational challenges. Full article