Safety Of Railway Transportation Research Articles

Enhancing Railway Transportation Safety with Proactive Maintenance Strategies Incorporating Machine Learning

Enhancing Railway Transportation Safety with Proactive Maintenance Strategies Incorporating Machine Learning

APPLICATION OF VIBRATION DIAGNOSTICS OF AXLE BOXES OF FREIGHT CARS TO REDUCE THE RISK OF FAILURES

The research presented in this study advocates for the adoption of vibration diagnostics as a method to mitigate the risk of axle box failures in freight cars, emphasizing its significant impact on enhancing the safety of railway transportation. The authors assert that employing vibration diagnostics for axle boxes in freight cars results in a noteworthy 2.5-fold reduction in risks within the realm of railway transport.The practical implications of the developed diagnostic method extend to its capacity for assessing the safety of railway transport, offering a valuable tool for risk evaluation. Experimental studies conducted as part of this research further validate the effectiveness of the method, revealing a substantial decrease in the risk of axle box failures by a factor ranging from 1.125 to an impressive times. This empirical evidence solidifies the credibility and applicability of vibration diagnostics in averting potential failures in axle boxes.From an economic standpoint, the implementation of vibration diagnostics for axle box units demonstrates a tangible impact, with cost savings ranging from 13 to 44 thousand UAH corresponding to the operational mileage of a freight car. This underscores not only the safety benefits but also the economic advantages associated with the utilization of vibration diagnostics in the maintenance and operation of railway transport.The findings of this research contribute to a more comprehensive understanding of the capabilities of vibration diagnostics as a powerful and effective tool in ensuring the safety of railway transportation. By highlighting the practical applicability of the method and supporting its success through empirical data, the authors advocate for its widespread adoption as a means to bolster the safety and efficiency of freight transportation by rail. In essence, this study provides a robust foundation for the integration of vibration diagnostics into routine maintenance practices, offering a proactive approach to minimizing risks and optimizing the performance of axle box units in freight cars.

Fatigue fracture cross-sections after cyclic tests with a combination of cyclic bending and torsion of samples made of aluminum alloy 6060

The paper presents the results of fatigue tests of the 6060 aluminum alloy. The test material was taken from the profiles used for production of side windows and external doors of the passenger trains by the RAWAG company. The tests were carried out for cyclic loads with pure bending, pure torsion, and two combinations of bending and torsion. Fatigue tests were performed at zero mean values. Using scanning electron microscopy, a fractographic analysis was made, which is a supplementary basis for considerations about the mechanism of initiation and development of fatigue cracks. Based on the appearance of individual zones and the characteristics of cracks, a picture of the behavior of the material under specific conditions was obtained. Finally, the plastic property of fatigue cracks was indicated. The work demonstrates the influence of aluminum alloy processing on the fatigue properties of this alloy during operation in order to obtain maximum reliability and safety of railway transport.

Symmetry-Driven Unsupervised Abnormal Object Detection for Railway Inspection

Vision-based abnormal object detection in railway track inspection images is one of the critical tasks to ensure the safety of railway transportation. Even though many machine learning based methods have been developed, these approaches heavily rely on anomaly supervisions and therefore can not detect unknown anomaly classes. In order to tackle the problem, this paper proposes a novel unsupervised method to detect abnormal objects, which does not require abnormal object training data. Specially, we find that a railway track image is almost symmetrical about the track central line, i.e., normal objects appear repeatedly and symmetrically, while abnormal ones are rare and also significantly different from the corresponding symmetric areas. Motivated by this observation, we propose to train a metric-learning based deep model to learn the similarity between normal objects and the corresponding symmetrical areas. Then for each object proposal in one test image, we measure the distance between the proposal and the corresponding symmetrical regions, and determine whether it is an abnormal object based on the symmetrical metric. Extensive experiments on our collected dataset show that our proposed method achieves competitive performance compared with the state-of-the-art methods.

Повышение качества транспортных услуг на основе развития железнодорожной инфраструктуры Сибирского федерального округа

The article describes the degree of influence of the level of transport infrastructure development on the quality of transportation services provided to the population. It analyzes the state of infrastructure in the Siberian Fed-eral District for all types of transport, and considers a risk-oriented approach to traffic safety in railway transport as an internal control of service quality indicators. According to the results of the factor analysis of train traffic safety risks of the activity of the West Siberian Engineering Structures Division, the problematic risk factors af-fecting the quality level of the indicator “Reliability” are determined. The integral assessment of the quality of services provided for the use of transport infrastructure and the significance of risk factors in relation to the achievement of the reference state of the quality criterion “Safety” are determined. Long-term corrective measures of transport infrastructure development aimed at improving the quality of services in general are examined.

An Overview of Current Challenges and Emerging Technologies to Facilitate Increased Energy Efficiency, Safety, and Sustainability of Railway Transport

This article presents a review of cutting-edge technologies poised to shape the future of railway transportation systems, focusing on enhancing their intelligence, safety, and environmental sustainability. It illustrates key aspects of the energy-transport-information/communication system nexus as a framework for future railway systems development. Initially, we provide a review of the existing challenges within the realm of railway transportation. Subsequently, we delve into the realm of emerging propulsion technologies, which are pivotal for ensuring the sustainability of transportation. These include innovative solutions such as alternative fuel-based systems, hydrogen fuel cells, and energy storage technologies geared towards harnessing kinetic energy and facilitating power transfer. In the following section, we turn our attention to emerging information and telecommunication systems, including Long-Term Evolution (LTE) and fifth generation New Radio (5G NR) networks tailored for railway applications. Additionally, we delve into the integral role played by the Industrial Internet of Things (Industrial IoT) in this evolving landscape. Concluding our analysis, we examine the integration of information and communication technologies and remote sensor networks within the context of Industry 4.0. This leveraging of information pertaining to transportation infrastructure promises to bolster energy efficiency, safety, and resilience in the transportation ecosystem. Furthermore, we examine the significance of the smart grid in the realm of railway transport, along with the indispensable resources required to bring forth the vision of energy-smart railways.

A Review on the Development of a Track Irregularity Measurement Tool

Railway transportation is one of the most vital transportation modes for people and goods. Ensuring railway transportation safety and efficiency is very important. The condition of the track is one of the most vital factors in ensuring railway safety, as irregularities in the track can lead to severe accidents. Thus, it is essential to have proper gauges and methods to measure track irregularities. This paper will discuss different methods to measure track irregularities and their advantages and limitations. Several track irregularity measurement tools will be divided into groups based on different aspects, such as the contact types and their location. Contact methods can measure more detailed irregularities, but have limitations such as injury and equipment damage. Non-contact methods are less invasive and can measure larger rail sections, but are less accurate. The inspection method will be chosen based on the track configuration that must be carefully studied to ensure the most efficient and effective inspection methods for a rail type. Regardless of the method, it is important to keep developing and improving existing track irregularity measurement tools to increase efficiency and reduce measurement errors.

Is the safety index of modern safety integrity level(SIL) truly appropriate for the railway?

Safety is paramount in rail transportation. The International Safety Standard IEC 61508, issued by the International Electrotechnical Commission (IEC) in 2000, describes the modern concept of safety and the specifications for safety evaluation in a systematic manner. On this basis, the EN 50129 railway transportation safety standard and safety integrity level(SIL) are established. Through the above analysis, the relationship between safety-related system reliability, acceptable risk, and safety index is summarized. It is clear that the safety index is based on acceptable risks. Nonetheless, as the economy and society advance, the safety index mandated by the SIL falls behind. Consequently, the principles and methodologies for calculating the safety index are presented. The paper proposes a reference for the Chinese railway safety index based on actual data from the Chinese railways over the past few years.

Visual Fault Detection of Multiscale Key Components in Freight Trains

Fault detection for key components in the braking system of freight trains is critical for ensuring railway transportation safety. Despite the frequently employed methods based on deep learning, these fault detectors are extremely reliant on hardware resources and complex to implement. In addition, no train fault detectors consider the drop in accuracy induced by scale variation of fault parts. This paper proposes a lightweight anchor-free framework to solve the above problems. Specifically, to reduce the amount of computation and model size, we introduce a lightweight backbone and adopt an anchor-free method for localization and regression. To improve detection accuracy for multi-scale parts, we design a feature pyramid network to generate rectangular layers of different sizes to map parts with similar aspect ratios. Experiments on four fault datasets show that our framework achieves 98.44% accuracy while the model size is only 22.5 MB, outperforming state-of-the-art detectors.

Mechanism and Control Scheme of Central Defects in Cross Wedge Rolling of Railway Vehicle Axles

Faced with a great demand for railway axles, the cross wedge rolling (CWR) process has the advantages of high efficiency and material saving, and good forming quality of axles is significant for railway transportation safety. The stress inside the railway axle of CWR was analyzed by the finite element method. It was found that the center of the rolled piece is subjected to tensile stress in transverse and axial directions and compressive stress in radial direction, making it more prone to defects. By simulating the evolution of micro voids in the center of the CWR piece, it was found that the presence of voids makes the strain around them significantly large and concentrated and the material between the voids deforms intensely. When voids expand relative to the rolled piece and the internal necking between voids is significant, void coalescence is easy to occur, and central defects are formed. The influence of process parameters on void evolution was analyzed. The scheme of detaching die was proposed to avoid central defects of the CWR piece and the optimal parameter conditions of CWR of railway axles were determined, which proved that the quality of railway axles formed with optimized parameters meets the technical requirements of railway vehicle axles.

On Certain Areas of Improvement of Control and Supervisory Activities in the field of Ensuring Transport Safety in Railway Transport

Various types of control and supervisory measures provide the anti-terrorist protection of transport (railways included) from potential threats. An important role is assigned to the federal state control (supervision) in the field of transport security, despite the fact that Federal Law No. 17‑FZ of 10.01.2003 «On Railway Transport in the Russian Federation» and the Charter of Railway Transport do not mention this type of transport supervision. The analysis of the subject, objects, participants and the content of administrative and legal relations arising in the implementation of transport supervision on railway transport allows us to attribute this activity to the control and supervisory and identify a number of its features. The peculiarity of risk management to ensure the anti-terrorist security of railways is the attribution of certain types of activities of controlled persons to one category of severity and risk probability group. This provision makes it possible to plan and carry out uniform preventive measures against one controlled person both within the framework of federal state control (supervision) in the field of transport security and within the framework of federal state control (supervision) in the field of railway transport. Amendments have been proposed to the Federal Law «On Railway Transport in the Russian Federation» in terms of supplementing it with norms on transport security and to the Regulation on Federal State Control (Supervision) in the field of Transport Security, approved by Decree of the Government of the Russian Federation No. 1051 of 06/29/2021. The main directions for transport supervision improvement include: carrying out control measures aimed at identifying potential threats to the automated transport security system; expanding the list of situations that can be simulated during the experiment; using a permanent raid as a special mode of transport supervision on the railway; conducting an inspection visit with respect to vehicle owners; developing an information resource for conducting self-examination as a preventive measure.

Development of DMPS-EMAT for Long-Distance Monitoring of Broken Rail

The safety of railway transportation is crucial to social and economic development. Therefore, real-time monitoring of the rail is particularly necessary. The current track circuit structure is complex and costly, posing challenges to monitoring broken tracks using alternative methods. As a non-contact detection technology with a lower environmental impact, electromagnetic ultrasonic transducers (EMATs) have become a concern. However, traditional EMATs have problems such as low conversion efficiency and complex modes, which can limit their effectiveness for long-distance monitoring. Therefore, this study introduces a novel dual-magnet phase-stacked EMAT (DMPS-EMAT) design comprising two magnets and a dual-layer winding coil arrangement. The magnets are positioned at a distance equal to the wavelength of the A0 wave from each other, while the center distance between the two sets of coils beneath the transducer is also equal to the wavelength. After analyzing the dispersion curves of the rail waist, it was determined that the optimal frequency for long-distance rail monitoring is 35 kHz. At this frequency, adjusting the relative positions of the two magnets and the coil directly underneath to be one A0 wavelength can effectively excite a constructive interference A0 wave in the rail waist. The simulation and experimental results show that DMPS-EMAT excited a single-mode A0 wave, resulting in a 1.35-times increase in amplitude.

INJURIES IN RAILWAY TRANSPORT AND WAYS OF REDUCING THE INDUSTRIAL DANGERS IMPACT

The article deals with the problem of the labour protection state in railway transport. The transport sector, in particular the railway, is one of the main country's activity spheres, which significantly affects the level of its social and economic development. The analysis of statistical data shows that the transport industry is one of the leaders in the most trauma-hazardous human activity spheres. Thus, the analysis of injury rates and factors determining the professional reliability of locomotive crews, and the scientific substantiation of measures set aimed at preserving the health of railway transport workers and ensuring the safety of railway transport, are urgent and essential tasks. The article's purpose is a comprehensive analysis of the injury's actual state in railway transport. In the work, it is established that during the performance of their duties, railway transport employees are affected by physical, chemical and biological harmful production factors. The work is carried out under the influence of psychophysiological factors caused by the severity and intensity of the labour process in conditions of hydrodynamic and fixed working posture. It was determined that the influence of adverse factors complex leads to disruption of the cardiovascular, central nervous and endocrine systems activity. The authors assessed the actual state of industrial and non-industrial injuries in railway transport. It has been established that the number of industrial accident victims has been gradually increasing in recent years. This indicates the need to develop and implement in practice a set of measures to improve the working conditions of mainline locomotive crews. It is noted that the key areas of measures to preserve the health and professional capacity of railway transport workers are the improvement of regulatory and legal support, socio-economic motivation of workers, and organizational-technological and sanitary-medical measures. Keywords: injury, accident, railway transport, labour protection.

БЕЗОПАСНАЯ ЭКСПЛУАТАЦИЯ ВАГОНОВ ПРИ НАЛИЧИИ НЕИСПРАВНОСТЕЙ

A study of various types of malfunctions in railway transport is conducted. Their critical impact on the safety of operation is evaluated. The research is aimed at studying statistical data on appearing failures and malfunctions both on rolling stock and on railway tracks. At high loads on mechanical components, the probability of various defects is high, which requires the most thorough study of the reliability of structural elements. Any deviation can lead to significant breakdowns and cause huge damage, especially for rolling stock for passenger transportation or transportation of dangerous goods. It is also necessary to predict the indicators of reliability and stability of the system to various impacts. In this regard, the study is aimed at evaluating the failures of railway systems and their critical impact on traffic safety. Despite such a great interest in the problems of evaluating and ensuring the safety of railway transport, there is still no unambiguous evaluation of the parameters of railway carriages and the track for the maximum stability coefficient, if exceeded, the train is highly likely to derail.

Blockchain enabled zero trust based authentication scheme for railway communication networks

With the introduction of emerging technologies such as cloud computing, the railway communication network has the characteristics of complex structure and blurred boundaries, which leads to a series of security threats including information leakage and malicious access. Specifically, the third-party cloud services are difficult to be supervised, and network traffic is untrustworthy. To ensure system security, we propose a zero-trust security model in this paper. Then, we introduce blockchain and Merkle tree to build a distributed identity storage scheme for guaranteeing reliable, confidential and efficient data updates, and improving authentication efficiency. Furthermore, the proxy was introduced for two-way authentication with cloud servers, so that internal and external threats could be counteracted. Moreover, reputation assessment mechanism has been adopted to reduce the possibility of nodes accessing malicious cloud services. Performance analysis demonstrated that the proposed security model is able to enhance the security, efficiency and stability of the system, and consequently can guarantee the safety and reliability of railway transportation.

SDRC-YOLO: A Novel Foreign Object Intrusion Detection Algorithm in Railway Scenarios

Foreign object intrusion detection is vital to ensure the safety of railway transportation. Recently, object detection algorithms based on deep learning have been applied in a wide range of fields. However, in complex and volatile railway environments, high false detection, missed detection, and poor timeliness still exist in traditional object detection methods. To address these problems, an efficient railway foreign object intrusion detection approach SDRC-YOLO is proposed. First, a hybrid attention mechanism that fuses local representation ability is proposed to improve the identification accuracy of small targets. Second, DW-Decoupled Head is proposed to construct a mixed feature channel to improve localization and classification ability. Third, a large convolution kernel is applied to build a larger receptive field and improve the feature extraction capability of the network. In addition, the lightweight universal upsampling operator CARAFE is employed to sample the size and proportion of the intruding foreign body features in order to accelerate the convergence speed of the network. Experimental results show that, compared with the baseline YOLOv5s algorithm, SDRC-YOLO improved the mean average precision (mAP) by 2.8% and 1.8% on datasets RS and Pascal VOC 2012, respectively.

Gaps in Asset Management Systems to Integrate Railway Companies’ Resilience

Railways and metros are safe, efficient, reliable, and environmentally friendly mass carriers. They are critical cyber-physical systems (CPS) that are attractive targets for cyber and/or physical attacks. SAFETY4RAILS project delivers methods and systems to increase the safety and resilience of track-based inter-city railway and intra-city metro transportation. Asset management plays a fundamental role in resilience management. This study analyses the gaps in asset management systems of rail infrastructure. The objective of the study is to understand the weaknesses and vulnerabilities in an asset management system that impacts resilience. The form of triangulation fashion was used for the analysis of consequences for each threat event. The research conducted included: a systematic literature review; a multiple case study review; and an analysis. The strength of asset inventory, condition inspection methods and decision-making scenarios were analysed, and as an expanded part of this analysis, mitigation actions linked to the vulnerabilities were identified. The study implies that asset management systems are most important in resilience management’s response and recovery phases where the largest sudden economic implications can take place. The results of the gap analysis could be used to provide policy recommendations and standardisation efforts.

An Improved Structural Health Monitoring Method Utilizing Sparse Representation for Acoustic Emission Signals in Rails

The structural health of rails significantly impacts the safety of railway transport, which requires long-term and accurate monitoring. An improved structural health monitoring (SHM) method is proposed to enhance the damage information and construct an adaptive weighted index for evaluating the structural health states of rails. In this method, modified singular value decomposition (SVD) with a double-layer Hankel matrix compensation algorithm enhances the damage information and ensures real-time detection. Based on the inflection point of the inner product gradient, the step size of the sparsity adaptive matching pursuit (SAMP) algorithm is adaptively adjusted to reconstruct damage signals. Subsequently, an innovative index is constructed with adaptive weighting for SHM of rails. Tensile tests are performed to verify the effectiveness of the proposed method. The results show that the proposed method avoids the defects of traditional nondestructive testing (NDT) techniques that rely on a priori information about the damage signal (such as damage frequency acoustic emission (AE) hits rate and waveform characteristics). Furthermore, using the variation in signal energy, the proposed method has the capability to accurately delineate the three structural health stages under complex waveform conditions, which is not possible with conventional detection methods. This method provides guidance for the damage analysis and monitoring techniques of rails.

Hybrid convolution and transformer network for coupler fracture failure pattern segmentation recognition in heavy-haul trains

Couplers are an important component of heavy-haul trains. Effective failure analysis and fracture surface pattern recognition of the fractured coupler are of great significance for improving the safety of railway transportation. An end-to-end hybrid convolution and transformer (HCT) segmentation network for automatic semantic segmentation recognition of fracture surface failure patterns in metal couplers is proposed in this study. To achieve local modeling, the proposed method replaces handcrafted features with a pre-trained convolutional network for automatic feature extraction from the coupler's input image. Further, an HCT module is proposed for feature fusion and global modeling to improve the accuracy of different failure pattern semantic segmentation. A multi-scale loss function (MS-Loss) is proposed to improve the network performance while accelerating the convergence of the network. The experimental results show that the proposed HCT network achieves the highest mean intersection over union (mIoU) on the DJTU-Seg (91.28 %) and DWTT-Seg (86.37 %) datasets and achieves a detection speed of 51 fps on a single GPU. The proposed method can detect in real-time while avoiding contamination from human subjective factors. It provides a new pattern recognition method for the brittle fracture inspection of heavy-haul train couplers and even the whole metal material fracture measurement solution, offering promising applications.

IMPROVING THE PROFESSIONAL TRAINING OF SPECIALISTS TO ENSURE FIRE SAFETY IN RAILWAY TRANSPORT

Purpose. The goal is to reduce the severity of the consequences of fires, it is necessary to intensify the joint efforts of state authorities, local governments, as well as enterprises and, most importantly, citizens, and to ensure the improvement of measures of a legal, organizational, economic, social, scientific and technical nature, which will ensure their more active use in the process of ensuring fire safety.
 The method or methodology of the work. The article notes the traditional elements of the fire safety system and the mechanisms for regulating fire safety in the Russian Federation.
 Results. The fact of the existence of shortcomings in the fire safety regulation system, in particular, an excessive number of inspections, an insufficient level of professional training of personnel responsible for maintaining fire safety in transport, has been established. Directions for improving the mechanisms for regulating the process of ensuring fire safety in the Russian Federation are proposed.
 Scope of the results. The obtained results should be applied in the professional training of specialists to ensure fire safety in railway transport.