Prognostics with autoregressive moving average for railway turnouts

Turnout systems are one of the most critical systems on railway infrastructure. Diagnostics and prognostics on turnout system have ability to increase the reliability & availability and reduce the downtime of the railway infrastructure. Even though diagnostics on railway turnout systems have been reported in the literature, reported studies on prognostics in railway turnout system is very sparse. This paper presents autoregressive moving average model based prognostics on railway turnouts. The model is applied to data collected from real turnout systems. The failure progression is obtained manually using the exponential degradation model. Remaining Useful Life of ten turnout systems have been reported and results are very promising

Importance and applications of robotic and autonomous systems (RAS) in railway maintenance sector: a review

Maintenance, which is critical for safe, reliable, quality, and cost-effective service, plays a dominant role in the railway industry. Therefore, this paper examines the importance and applications of Robotic and Autonomous Systems (RAS) in railway maintenance. More than 70 research publications, which are either in practice or under investigation describing RAS developments in the railway maintenance, are analysed. It has been found that the majority of RAS developed are for rolling-stock maintenance, followed by railway track maintenance. Further, it has been found that there is growing interest and demand for robotics and autonomous systems in the railway maintenance sector, which is largely due to the increased competition, rapid expansion and ever-increasing expense

Learning from accidents : machine learning for safety at railway stations

In railway systems, station safety is a critical aspect of the overall structure, and yet, accidents at stations still occur. It is time to learn from these errors and improve conventional methods by utilizing the latest technology, such as machine learning (ML), to analyse accidents and enhance safety systems. ML has been employed in many fields, including engineering systems, and it interacts with us throughout our daily lives. Thus, we must consider the available technology in general and ML in particular in the context of safety in the railway industry. This paper explores the employment of the decision tree (DT) method in safety classification and the analysis of accidents at railway stations to predict the traits of passengers affected by accidents. The critical contribution of this study is the presentation of ML and an explanation of how this technique is applied for ensuring safety, utilizing automated processes, and gaining benefits from this powerful technology. To apply and explore this method, a case study has been selected that focuses on the fatalities caused by accidents at railway stations. An analysis of some of these fatal accidents as reported by the Rail Safety and Standards Board (RSSB) is performed and presented in this paper to provide a broader summary of the application of supervised ML for improving safety at railway stations. Finally, this research shows the vast potential of the innovative application of ML in safety analysis for the railway industry

The posssibilities of railway transport utilizing as a backbone network of integrated passenger transport systems

The aspects of utilizing of railway transport as a backbone network of integrated passenger transport systems are solved in the contribution. The basic requirements on this railway transport service are specified in the contribution. The main attention is focused on creating of line structure of the integrated transport systems. The location of interchange points is also accented in the contribution. The theoretical presumptions are also illustrated in the way of convenient practical examples

Geocellular railway drainage systems: physical and numerical modelling

The importance of resilient railway infrastructure is paramount when considering the increased likelihood of extreme weather and flash flood events in coming years. One of the main causes of instability of railway tracks is excess water in the trackbed, particularly when it is at or above the interface of the ballast and subgrade. Conventional drainage systems are susceptible to clogging and deterioration. Resilient track drainage systems should therefore have sufficient capacity to allow water to dissipate quickly, but they should also be designed to ensure long-term operation with minimal or easily performed maintenance. This paper presents results from an investigation of a potential new railway drainage system using geocellular components. In the paper, the development of a large scale physical model is described which represents a full scale unit cell of a sleeper-to-sleeper track substructure. The physical model includes ballast and subgrade layers, under-track and lateral drainage systems, rainfall simulation, and instrumentation. Results demonstrate the relative hydraulic response of the drainage system with and without the geocellular components. The paper also describes the development of a numerical model of the track subgrade and drainage system, which was first calibrated and verified using experimental data from the physical model, then extended to study the effect of certain parameters on the hydraulic response of the railway track. Results indicate that the under-track geocellular drainage system offers potential benefits in terms of maintaining a lower water table level within the subgrade as well as in aiding the migration of fines out of the ballast

Overview of Infrastructure Charging, part 4, IMPROVERAIL Project Deliverable 9, “Improved Data Background to Support Current and Future Infrastructure Charging Systems”

Improverail aims are to further support the establishment of railway infrastructure management in accordance with Directive 91/440, as well as the new railway infrastructure directives, by developing the necessary tools for modelling the management of railway infrastructure; by evaluating improved methods for capacity and resources management, which allow the improvement of the Life Cycle Costs (LCC) calculating methods, including elements related to vehicle - infrastructure interaction and external costs; and by improving data background in support of charging for use of railway infrastructure. To achieve these objectives, Improverail is organised along 8 workpackages, with specific objectives, responding to the requirements of the task 2.2.1/10 of the 2nd call made in the 5th RTD Framework Programme in December 1999.This part is the task 7.1 (Review of infrastructure charging systems) to the workpackage 7 (Analysis of the relation between infrastructure cost variation and diversity of infrastructure charging systems).Before explaining the economic characteristics of railway and his basic pricing principles, authors must specify the objectives of railways infrastructure charging.principle of pricing ; rail infrastructure charging ; public service obligation ; rail charging practice ; Europe ; Improverail

Reliability and heterogeneity of railway services

Reliability is one of the key factors in transportation, both for passengers and for cargo. This paper examines reliability in public railway systems. Reliability of railway services is a complex matter, since there are many causes for disruptions and at least as many causes for delays to spread around in space and time. One way to increase the reliability is to reduce the propagation of delays due to the interdependencies between trains. In this paper we attempt to decrease these interdependencies by reducing the running time differences per track section, i.e. by creating more homogeneous timetables. Because of the complexity of railway systems, we use network wide simulation for the analysis of the alternative timetables. We report on both theoretical and practical cases. Besides a comparison of different timetables, also general timetabling principles are deduced.heterogeneity;simulation;reliability;transportation;railways

Precise vehicle location as a fundamental parameter for intelligent selfaware rail-track maintenance systems

The rail industry in the UK is undergoing substantial changes in response to a modernisation vision for 2040. Development and implementation of these will lead to a highly automated and safe railway. Real-time regulation of traffic will optimise the performance of the network, with trains running in succession within an adjacent movable safety zone. Critically, maintenance will use intelligent trainborne and track-based systems. These will provide accurate and timely information for condition based intervention at precise track locations, reducing possession downtime and minimising the presence of workers in operating railways. Clearly, precise knowledge of trains’ real-time location is of paramount importance. The positional accuracy demand of the future railway is less than 2m. A critical consideration of this requirement is the capability to resolve train occupancy in adjacent tracks, with the highest degree of confidence. A finer resolution is required for locating faults such as damage or missing parts, precisely. Location of trains currently relies on track signalling technology. However, these systems mostly provide an indication of the presence of trains within discrete track sections. The standard Global Navigation Satellite Systems (GNSS), cannot precisely and reliably resolve location as required either. Within the context of the needs of the future railway, state of the art location technologies and systems were reviewed and critiqued. It was found that no current technology is able to resolve location as required. Uncertainty is a significant factor. A new integrated approach employing complimentary technologies and more efficient data fusion process, can potentially offer a more accurate and robust solution. Data fusion architectures enabling intelligent self-aware rail-track maintenance systems are proposed

Limits and opportunities of risk analysis application in railway systems

Risk Analysis is a collection of methods widely used in many industrial sectors. In the transport sector it has been particularly used for air transport applications. The reasons for this wide use are well-known: risk analysis allows to approach the safety theme in a stochastic - rather than deterministic - way, it forces to break down the system in sub-components, last but not least it allows a comparison between solutions with different costs, introducing de facto an element of economic feasibility of the project alternatives in the safety field. Apart from the United Kingdom, in Europe the application of this tool in the railway sector is relatively recent. In particular Directive 2004/49/EC (the "railway safety directive") provides for compulsory risk assessment in relation to the activities of railway Infrastructure Managers (IMs) and of Railway Undertakings (RUs). Nevertheless the peculiarity of the railway system - in which human, procedural, environmental and technological components have a continuous interchange and in which human responsibilities and technological functions often overlap - induced the EC to allow wide margins of subjectivity in the interpretation of risk assessment. When enacting Commission Regulation (EC) No 352/2009 which further regulates this subject, a risk assessment is considered positive also if the IM or RU declare to take safety measures widely used in normal practice. The paper shows the results of a structured comparative analysis of the rail sector and other industrial sectors, which illustrate the difficulties, but also the opportunities, of a transfer towards the railway system of the risk analysis methods currently in use for the other systems