Railway Field Research Articles

Research on Intelligent Identification Method for Pantograph Positioning and Skateboard Structural Anomalies Based on Improved YOLO v8 Algorithm

The abnormal structural state of the pantograph skateboard is a significant and highly concerning issue that has a significant impact on the safety of high-speed railway operation. In order to obtain real-time information on the abnormal state of the skateboard in advance, an intelligent defect identification model suitable to be used as a monitoring device for the pantograph skateboard was designed using a computer vision-based intelligent detection technology for pantograph skateboard defects, combined with an improved YOLO v8 model and traditional image processing algorithms such as edge extraction. The results show that the anomaly detection algorithm for the pantograph sliding plate structure has good robustness, maintaining recognition accuracy of 90% or above in complex scenes, and the average runtime is 12.32 ms. Railway field experiments have proven that the intelligent recognition model meets the actual detection requirements of railway sites and has strong practical application value.

Swiss railway field laboratory: analysis of two years' data collection

Since May 2022, a 1 km long section of the regular train network of Switzerland between Lucerne and Olten has been equipped with a variety of sensors and microphones. The superstructure of this test track was renewed in December 2019 and consists of ballasted track with concrete sleepers, in part with and without stiff under sleeper pads, respectively. Since June 2022 the sensors and microphones have continuously recorded pass-by data for sound, vibration and track dynamics for every passing train. This long-term measurement installation allows studying different environmental influences on noise and vibration. The very large amount of data enables both statistical analysis and building statistical models. Furthermore, the railway field lab can be used determine the influence of different track components. In this paper, we report on our statistical analysis of the data gathered since June 2022 including statistical models of the influence of the environment and of different rolling stock on sound and vibration. Furthermore, we present the results of a novel high damping rail pad tested at the railway field lab. Based on these results, we present a proposal and discuss our thoughts on the best practice for measuring acoustic quantities.

MODERN TRENDS AND INNOVATIONS IN THE MODERNIZATION OF RAILWAY LINES BASED ON EXPERIENCE IN THE REPUBLIC OF BULGARIA

The modernization of the Bulgarian railways has been underway for over 20 years. Hundreds of kilometres have been rehabilitated with funds from the European Union. The aim is to join the main Trans-European network, according to Regulation No. 1315/2013 [1] of the EU. Given the complex mountainous relief, the specific engineering objects are now the design and construction of a large number of tunnels (in the SofiaPlovdiv section alone, over 16 tunnels are planned, the longest of which is 6 km long); the design and construction of railway bridges, some of which have unique dimensions; the rehabilitation of bridges; and the construction of drainage facilities, including drains, ditches, and culverts (some of the culverts have a unique length of about 80 m). The report analyses the main railway projects with a critical analysis of strengths and weaknesses, according to the EU cost-benefit analysis methodology. The analysis presented in this report is unique for Bulgarian railways, as it includes a large volume of projects in the field of designing and building railway infrastructure according to European and world rules, which have not been used in Bulgaria until now. This is only the first stage of scientific research, which involves collecting data, examining the data, and building a working hypothesis. After the completion of the construction (supposedly by around 2029), there will be measurements of the railway and a diagnosis of its condition. At this time, data will be collected again, and the credibility of the presented hypotheses will be verified. The conclusions will serve for the more adequate preparation of the technical assignments for future infrastructure projects in the field of railways.

Experimental investigation and fluid-structure interaction modelling of the casting of self-compacting concrete for CRTS III slab track in the curved segments

Ensuring the casting quality of self-compacting concrete (SCC) is crucial for the operational safety and durability of China railway track system (CRTS) III slab track. However, the mechanisms of key factors influencing flow behaviors of SCC and structural responses remain insufficiently understood, nor is the relationship between flow behaviors and structural responses during casting. In this study, fluid-structure interaction (FSI) models of SCC casting were developed and verified by full-scale physical tests, comprising slump flow, L-box flow and casting of SCC in an actual track at the field of Laixi-Rongcheng high-speed railway. Through in-depth analysis on the casting process of SCC in curved segments with a super elevation of 80 mm, the relationship between flow behaviors and structural responses was established. Furthermore, the influence mechanisms of key factors on flow behaviors and structural responses were investigated systematically. Results show that during gravity-fed SCC casting, its flow velocity diminishes, thus increasing the static pressure and the forces exerted on the slab by SCC. These vertical and lateral forces increase to 147.16 and 7.83 kN through three stages of development, acceleration and stabilization, resulting in commensurate structural responses. At the end of casting process, the central region of the slab exhibits maximum vertical deformation of 0.95 mm and tensile stress of 1.07 MPa. The tension rods at the side with lower elevation bear greater vertical and lateral forces than the ones at the side with higher elevation. The rise of funnel height from 1.05 to 1.35 m accelerates the casting process but increases the forces exerted by SCC by up to 26 % and augments the associated response of entire structures, whereas the funnel diameter shows little effect. Increasing yield stress of SCC from 9.3 to 49.3 Pa produces a more uniform flow morphology and thus higher static pressure and force by SCC in the middle region of the slab, impacting the structural responses by up to 15 %. The growth of plastic viscosity from 59 to 99 Pa⋅s significantly affects the volume rate and casting time by up to 66 % but has little effect on the flow morphology, fluid pressure and structural responses. In order to ensure high quality casting of SCC, five clamping beams are suggested with two beams positioned at either side of the slab and the other three evenly placed along the middle region of the slab.

A Survey on Multi-Sensor Fusion Perimeter Intrusion Detection in High-Speed Railways.

In recent years, the safety issues of high-speed railways have remained severe. The intrusion of personnel or obstacles into the perimeter has often occurred in the past, causing derailment or parking, especially in the case of bad weather such as fog, haze, rain, etc. According to previous research, it is difficult for a single sensor to meet the application needs of all scenario, all weather, and all time domains. Due to the complementary advantages of multi-sensor data such as images and point clouds, multi-sensor fusion detection technology for high-speed railway perimeter intrusion is becoming a research hotspot. To the best of our knowledge, there has been no review of research on multi-sensor fusion detection technology for high-speed railway perimeter intrusion. To make up for this deficiency and stimulate future research, this article first analyzes the situation of high-speed railway technical defense measures and summarizes the research status of single sensor detection. Secondly, based on the analysis of typical intrusion scenarios in high-speed railways, we introduce the research status of multi-sensor data fusion detection algorithms and data. Then, we discuss risk assessment of railway safety. Finally, the trends and challenges of multi-sensor fusion detection algorithms in the railway field are discussed. This provides effective theoretical support and technical guidance for high-speed rail perimeter intrusion monitoring.

Effect of shaft voltage on electric damage of GCr15 bearing material

Electrical erosion pit is a fundamental manifestation of electrical bearing damage. As the shaft voltage increased, the degree of electrical damage became more severe, and the residual compressive stress and hardness of bearing surface decreased. The transition of martensite into ferrite induced by high discharge temperature was found at the edge of the erosion pit using a transmission electron microscopy. This phenomenon has not been observed below the mechanically rolled surface under the same conditions. Electrical penetration harmed the bearing through surface erosion, lubrication deterioration and martensite decomposition. The electrical pit could be observed when current density exceeded 0.95 A/mm2. The results can help understand bearing failure in the fields of railways, wind turbines, and new-energy vehicles.

Transport statutes in the system of sources of law of Ukraine

The article is devoted to the issues of transport statutes as sources of transport law of Ukraine, their validity and ability to effectively regulate social relations in the field of railway, road, and inland water transport, taking into account the changes that have occurred in social, political and socio-economic life over the past time on the restoration of Ukraine’s independence in 1991. The author analyzes the formal preservation of the validity of the relevant legislative acts of the Soviet era, taking into account the normative legal acts adopted in 1991 on a legal succession of Ukraine. The author emphasizes that from a formal and legal point of view, the transport statutes of the Soviet era remain valid, however, due to the contradiction of a significant part of their norms with the legislation adopted later, these normative legal acts are increasingly losing their legal influence on social legal relations and are subject to the action of such a phenomenon as “forgetting the rules of law”. At the same time, it was noted that proposals to abandon transport statutes in favor of a cumbersome codification of transport law norms (by raising the norms of statutes to the level of law) are irrational since an overly detailed Transport Code of Ukraine or codes of laws in the fields of road, rail or inland water transport will not be simple in use and will not meet the technical and legal requirements to the law. As a result, the author concludes that transport statutes in general are necessary regulatory legal acts. Still, their current editions are to a large extent morally outdated and such that they urgently need a radical revision to bring them into line with the changed norms of the legislation of Ukraine and take into account the need for adaptation of the national legal system to the law of the European Union. Thus, the application of their current editions in practical activities should be carried out after a thorough legal examination for the relevance of certain provisions.

The impact of vlogs on travellers’ intentions to use semi-high speed trains: A study on Vande Bharat Express

Recently, there has been a lot of buzz on social media, particularly in the form of vlogs, about newly launched semi-high speed trains in India popularly known as Vande Bharat Express. However, no information is available about the extent to which people trust the vlogs promoting the trains and the trains themselves. Therefore, this research aims to investigate the impact of watching vlogs about semi-high speed trains on the trust and attitude towards them, and how they perceive the risks associated. This study is guided by the trust transfer theory to investigate how trust transference can lead to a traveler’s intent to use semi-high speed trains. This study involved 338 participants. The relationship between variables was examined using SmartPLS 4 software. The findings indicate that trust in semi-high speed trains can be established through vlogs leading to intention to use. On the theoretical side, it provides insight into how trust, attitude, and perceived risk can affect the adoption of new technology, while on the practical side, it helps to understand how vlog coverage can be used as a tool to increase trust and ultimately drive adoption. Vlog coverage, trust in vlog content, trust in semi-high speed trains and behavioural intention altogether are not well understood in current literature despite the important implication for managers, academicians and consumers alike. This study contributes to the field of transportation and railways, social media and communication, and hospitality and tourism research. The study helps policy makers to understand users’ characteristics regarding the latest social media tools and adopt them accordingly to provide a better governance policy.

Research on the Correlation of Safety Risk of Railway Bridge Construction Based on Meta-Analysis

China has emerged as a prominent global player in the field of railways, with numerous railway construction projects spanning across diverse locations. Railway bridges, as a crucial component of railway construction, warrant significant attention. Meta-analysis, a statistical method that systematically synthesizes research findings, has been utilized to summarize and compare the results of safety risk management studies pertaining to railway bridge construction in China. By integrating social network analysis and evidence-based assessment of the literature, this study explores the interrelationships among risk factors. Within a specific railway bridge construction project, various safety risk factors may originate from common sources, including environmental factors, material and equipment factors, technical factors, management factors, personnel factors, and bridge-specific factors. Notably, there exists coupling among these security risk factors, whereby the presence or occurrence of one factor can influence the probability or severity of consequences associated with other factors. The results reveal that safety risk factors in railway bridge construction accumulate and propagate, thereby impacting the efficacy of safety risk management. Moreover, these factors are significantly influenced by the complexities inherent in the geo-meteorological and social-technical systems. This finding provides valuable insights for innovations in security risk management practices and offers suggestions for future innovation pathways.

Event-driven piezoelectric energy harvesting for railway field applications

Piezoelectric energy harvesters (PEHs) hold promises for revolutionizing railway structural health monitoring (SHM). However, the challenges of designing high-robust PEHs for handling complex and ever-shifting vibrations in practical railway scenarios remain formidable. Unlike conventional methods that align the fundamental frequency of the PEH with the dominant frequency of the vibration source, this study employs an event-driven enhancement method. This study commences by employing a high-fidelity dynamic model of the PEH and an advanced vehicle-track coupled dynamic model to evaluate energy harvesting efficiency across various railway scenarios. The vehicle-induced track vibrations are predicted across various train speeds, track structures, and track irregularities, considering 12 distinct vehicle-track conditions and totaling 3600 simulation datasets, each representing a specific event. We employ the particle swarm optimization (PSO) algorithm to identify optimal PEH designs for different events. To streamline this process, instead of offering one optimal solution for each event, we employ the K-means algorithm to cluster similar events. Subsequently, we choose the centroid design for each cluster as the representative solution for events within that cluster. This approach allows us to use a limited number of representative PEHs to effectively address most events across different clusters. Finally, we thoroughly examine and evaluate the dynamic responses of these representative designs to demonstrate their robust performance. This study explores PEH design optimization from a fresh perspective, bridging the gap between theoretical design and practical implementation in rail transportation systems.

Thermal stress simulation analysis of aerospace optical fibers and connectors and related extensions to high-speed railway area

Aerospace optical cables and fiber-optic connectors have numerous advantages (e.g., low loss, wide transmission frequency band, large capacity, light weight, and excellent resistance to electromagnetic interference). They can achieve optical communication interconnections and high-speed bidirectional data transmission between optical terminals and photodetectors in space, ensuring the stability and reliability of data transmission during spacecraft operations in orbit. They have become essential components in high-speed networking and optically interconnected communications for spacecrafts. Thermal stress simulation analysis is important for evaluating the temperature stress concentration phenomenon resulting from temperature fluctuations, temperature gradients, and other factors in aerospace optical cables and connectors under the combined effects of extreme temperatures and vacuum environments. Considering this, advanced optical communication technology has been widely used in high-speed railway communication networks to transmit safe, stable and reliable signals, as high-speed railway optical communication in special areas with extreme climates, such as cold and high-temperature regions, requires high-reliability optical cables and connectors. Therefore, based on the finite element method, comprehensive comparisons were made between the thermal distributions of aerospace optical cables and J599III fiber optic connectors under different conditions, providing a theoretical basis for evaluating the performance of aerospace optical cables and connectors in space environments and meanwhile building a technical foundation for potential optical communication applications in the field of high-speed railways.

The Application of New Technologies to Promote the Dissemination of Training Content in the Railway Field in the Context of Informational Economy

The Application of New Technologies to Promote the Dissemination of Training Content in the Railway Field in the Context of Informational Economy

Макроэкономические тенденции развития Дальнего Востока России в первой половине 2024 г.

Based on operational statistical, analytical and expert information, an analysis of the economic and social situation in the Far Eastern Federal District in the first half of 2024 is carried out in comparison with 2022–2023. It is shown that while instability and contradictory development trends in certain sectors of the economy persist, a sharp decline in the macroeconomic context is not observed. The output index of basic economic activities shows positive dynamics, but the active growth rate has slowed down. This does not currently allow us to talk about a stable phase of economic growth. The formation of growth rates in the industry of the Far Eastern Federal District was positively influenced by an increase in mining production for the main raw materials, an increase in the production of aviation and engineering products, certain types of non-metallic mineral products, and prefabricated wooden building structures. The positive dynamics and growth of investments in fixed assets were associated with the implementation of large investment projects in the field of railway and port infrastructure, mining, and manufacturing. There is a high level of inflation despite tight monetary policy. Consumer demand continues to expand in certain categories due to the growth of real incomes of the population

A LiDAR based obstacle detection framework for railway

Obstacle detection on the railway, a crucial operational safety concern, is a complex task that encompasses a multitude of challenges. While Machine Learning (ML) algorithms are commonly employed in analogous applications such as autonomous car driving [1] [2], the railway field faces a significant barrier due to the scarcity of available data (particularly images), rendering conventional ML approaches impractical. In response to this challenge, this study proposes and evaluates a framework which uses LiDAR (Light Detection and Ranging) data for obstacle detection on the railways. The framework aims to address the limitations posed by image data scarcity while enhancing operational safety in railway environments. The developed methodology combines the use of a long-range LiDAR capable of detecting obstacles at distances of up to 500 meters, with the train’s GPS (Global Positioning System) coordinates to accurately determine its position relative to detected obstacles. The LiDAR data is processed using a data fusion approach, where pre-existing knowledge regarding the track topography is combined with a clustering algorithm, specifically DBSCAN (Density-based spatial clustering of applications with noise), to identify and classify potential obstacles at a pre-defined distance. Tests of the proposed framework were conducted within the confines of a moving locomotive, specifically the CP 2600-2620 series, along a designated section of the Contumil-Leixões line. These tests served to validate the effectiveness and feasibility of the approach under real-world operating conditions. Overall, the utilization of LiDAR data coupled with advanced algorithms presents a promising avenue for enhancing obstacle detection capabilities in railway operations. By overcoming the challenges associated with data scarcity, this framework holds the potential to significantly improve operational safety and efficiency within railway networks. Further research and testing are warranted to validate the framework’s performance across diverse railway environments and operating conditions.

<b>Trend on Research and Development Relating to Information and Communication Technology in Railway Fields</b>

<b>Trend on Research and Development Relating to Information and Communication Technology in Railway Fields</b>

Research on Low-Frequency Stability under Emergency Power Supply Scheme of Photovoltaic and Battery Access Railway Traction Power Supply System

Photovoltaics and batteries can be connected to a traction power supply system through a railway power conditioner (RPC) to switch between different control strategies. This can address power quality issues or provide emergency traction for locomotives that unexpectedly lose power and even break through traditional energy barriers in the railway field, achieving a low-carbon power supply for railway energy, and a mutual backup with substations. However, methods to coordinate the control strategies of PV and the battery locomotive traction have not been clearly revealed, nor has the actual stability of the system. In this study, to address the above issues, an emergency power supply scheme is proposed for the first time that utilizes a dual-mode RPC inverter combined with a coordinated control strategy for the PV and battery, achieving the traction of locomotives. In addition, a one-dimensional impedance model was established for the PV system, battery system, locomotive (CRH3), and RPC projected onto the dq coordinate system, and the critical amplitude margin (CAM) was defined to quantitatively analyze the sensitivity and laws of different parameters concerning the low-frequency stability of the system. At the same time, impedance ratios and passive criteria were used to reveal the stability mechanism, and parameter adjustment criteria and design suggestions were put forward. Finally, the feasibility of the emergency power supply scheme of the “PV–battery locomotive network” coupling system and the correctness of the low-frequency stability study were verified using the Starsim semi-physical experiment platform.

Real‐Time Crossing‐Gate Rod Breakage Detection Based on Sequential‐Dataset Classification for the Railway‐Telemeter System

In our previous studies, we proposed crossing‐gate rod breakage detection methods based on machine learning techniques for the telemeter system installed by the Shikoku Railway Company (JR Shikoku) on railway lines in the Shikoku area to collect real‐time equipment data. However, these methods involve batch processing of many training data over several days, making them unsuitable for real‐time detection because of the long computation time. Therefore, this study improves these methods by performing sequential processing for real‐time detection for installation in the railway field. A one‐class support vector machine‐based detection method was applied to sequential processing to perform detection at each sampling period every few seconds. The proposed method is evaluated and its effectiveness is demonstrated in two representative cases of crossing‐gate rod breakage. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Thermodynamic models of the air spring on the high-speed pantograph

ABSTRACT The modelling method of the air spring and its additional pneumatic system has been studied more frequently in recent years. As for the railway field, the study of the secondary suspension system of the bogie is the most popular, while little focus is on the air spring of the pantograph. In this paper, the modelling method of the air spring on the pantograph is investigated and developed. Four thermodynamic models are derived step by step, which can roughly be separated into two types. The first two models are established to express the relationship between the inner pressure and the vertical displacement of the air spring, and the effect of a regulator is illustrated and discussed. The latter two models that are developed from the first two models are set up to express the relationship between the vertical force and the vertical displacement of the air spring, where the effect of air spring material is illustrated and discussed. All four models are validated by comparing the simulation results with experimental results for frequency characteristics. Finally, the characteristics of the four proposed models are illustrated and discussed.

Scattered Train Bolt Point Cloud Segmentation Based on Hierarchical Multi-Scale Feature Learning.

In view of the difficulty of using raw 3D point clouds for component detection in the railway field, this paper designs a point cloud segmentation model based on deep learning together with a point cloud preprocessing mechanism. First, a special preprocessing algorithm is designed to resolve the problems of noise points, acquisition errors, and large data volume in the actual point cloud model of the bolt. The algorithm uses the point cloud adaptive weighted guided filtering for noise smoothing according to the noise characteristics. Then retaining the key points of the point cloud, this algorithm uses the octree to partition the point cloud and carries out iterative farthest point sampling in each partition for obtaining the standard point cloud model. The standard point cloud model is then subjected to hierarchical multi-scale feature extraction to obtain global features, which are combined with local features through a self-attention mechanism, while linear interpolation is used to further expand the perceptual field of local features of the model as a basis for segmentation, and finally the segmentation is completed. Experiments show that the proposed algorithm could deal with the scattered bolt point cloud well, realize the segmentation of train bolt and background, and could achieve high segmentation accuracy, which has important practical significance for train safety detection.

A Methodology Framework for Modelling a Rail Moving Block System

In the railway field, rigorous development processes contribute to implement safe and efficient systems. Railway safety standards recommend the use of formal modelling and verification techniques to guarantee processes’ correctness and validate safety requirements. ERTMS/ETCS L3 (European Railway Traffic Management System / European Train Control System Level 3) is a European standard for interoperable railways based on the concept of Moving Block signaling systems which allows for substantial capacity gains and reduced costs. In this paper, we explain why the ETCS L3 struggles to be deployed despite the benefits it can bring. Then, we discuss the planned implementations of ETCS L3 at a European-wide scale. Finally, we present a methodology framework using formal models to verify moving block systems. This work is performed in the context of the PERFORMINGRAIL European project.