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

Advances in fault diagnosis for high-speed railway: A review

The high speed railway (HSR) is a complex system with many subsystems and components. The reliability of its core subsystems is a key consideration in ensuring the safety and operation efficiency of the whole system. As the service time increases, the degradation of these subsystems and components may lead to a range of faults and deteriorate the whole system performance. To ensure the operation safety and to develop reasonable maintenance strategies, fault detection and isolation is an indispensable functionality in high speed railway systems. In this paper, the traction power supply system, bogie system, civil infrastructure system, and control and signaling system of HSR are briefly summarized, and then different fault diagnosis methods for these subsystems are comprehensively reviewed. Finally, some future research topics are discussed

DYNAMIC STRAY CURRENT MEASURING METHODS IN URBAN AREAS

In areas where urban tracks are used as public transportation, dynamic stray currents cause high maintenance costs for the tracks and metal structures near the tracks. Stray currents caused by rail vehicles depend on many factors (traffic density, vehicle speed, acceleration and deceleration, soil and track moisture), so it is very difficult to get a clear picture of the harmfulness of the stray current based on the results of a single field measurement. However, there are several measurement methods that can be used to determine the presence of stray currents and predict appropriate track maintenance actions. Some of these methods are described in this article, namely the use of stray current mapper, measurement of rail potential and rail current, measurement at the stray current collection system, and the use of nondestructive sensors. In track construction, measuring the electrical potential between rail and ground is one of the most common methods of detecting the damaging influence of stray current

Assessment of Railway Train Energy Efficiency and Safety Using Real-time Track Condition Information

This paper presents the use of track condition data from the virtual remote wireless sensor network within a simulation model of a battery-hybrid diesel-electric locomotive-driven freight train for a realistic mountain railway route simulation scenario. Simulation model includes the point-mass model of freight train longitudinal motion dynamics subject to wheel-to-track adhesion and head wind variations, the model of hybrid diesel-electric locomotive energy efficiency, and the model of real-time information provide to the virtual train driver about railway track conditions based on a narrow-band wireless remote sensor network. Simulation results are used to assess the possible benefits remote wireless sensor data for freight train energy-optimal control and to increase the transportation safety, including prediction of possible delays due to changed weather conditions en route

A review of key planning and scheduling in the rail industry in Europe and UK

Planning and scheduling activities within the rail industry have benefited from developments in computer-based simulation and modelling techniques over the last 25 years. Increasingly, the use of computational intelligence in such tasks is featuring more heavily in research publications. This paper examines a number of common rail-based planning and scheduling activities and how they benefit from five broad technology approaches. Summary tables of papers are provided relating to rail planning and scheduling activities and to the use of expert and decision systems in the rail industry.EPSR

Using information engineering to understand the impact of train positioning uncertainties on railway subsystems

Many studies propose new advanced railway subsystems, such as Driver Advisory System (DAS), Automatic Door Operation (ADO) and Traffic Management System (TMS), designed to improve the overall performance of current railway systems. Real time train positioning information is one of the key pieces of input data for most of these new subsystems. Many studies presenting and examining the effectiveness of such subsystems assume the availability of very accurate train positioning data in real time. However, providing and using high accuracy positioning data may not always be the most cost-effective solution, nor is it always available. The accuracy of train position information is varied, based on the technological complexity of the positioning systems and the methods that are used. In reality, different subsystems, henceforth referred to as ‘applications’, need different minimum resolutions of train positioning data to work effectively, and uncertainty or inaccuracy in this data may reduce the effectiveness of the new applications. However, the trade-off between the accuracy of the positioning data and the required effectiveness of the proposed applications is so far not clear. A framework for assessing the impact of uncertainties in train positions against application performance has been developed. The required performance of the application is assessed based on the characteristics of the railway system, consisting of the infrastructure, rolling stock and operational data. The uncertainty in the train positioning data is considered based on the characteristics of the positioning system. The framework is applied to determine the impact of the positioning uncertainty on the application’s outcome. So, in that way, the desired position resolution associated with acceptable application performance can be characterised. In this thesis, the framework described above is implemented for DAS and TMS applications to understand the influence of positioning uncertainty on their fundamental functions compared to base case with high accuracy (actual position). A DAS system is modelled and implemented with uncertainty characteristic of a Global Navigation Satellite System (GNSS). The train energy consumption and journey time are used as performance measures to evaluate the impact of these uncertainties compared to a base case. A TMS is modelled and implemented with the uncertainties of an on-board low-cost low-accuracy positioning system. The impact of positioning uncertainty on the modelled TMS is evaluated in terms of arrival punctuality for different levels of capacity consumption. The implementation of the framework for DAS and TMS applications determines the following: • which of the application functions are influenced by positioning uncertainty; • how positioning uncertainty influences the application output variables; • how the impact of positioning uncertainties can be identified, through the application output variables, whilst considering the impact of other railway uncertainties; • what is the impact of the underperforming application, due to positioning uncertainty, on the whole railway system in terms of energy, punctuality and capacity

Technology transfer: Transportation

The application of NASA derived technology in solving problems related to highways, railroads, and other rapid systems is described. Additional areas/are identified where space technology may be utilized to meet requirements related to waterways, law enforcement agencies, and the trucking and recreational vehicle industries

A Review in Fault Diagnosis and Health Assessment for Railway Traction Drives

During the last decade, due to the increasing importance of reliability and availability, railway industry is making greater use of fault diagnosis approaches for early fault detection, as well as Condition-based maintenance frameworks. Due to the influence of traction drive in the railway system availability, several research works have been focused on Fault Diagnosis for Railway traction drives. Fault diagnosis approaches have been applied to electric machines, sensors and power electronics. Furthermore, Condition-based maintenance framework seems to reduce corrective and Time-based maintenance works in Railway Systems. However, there is not any publication that summarizes all the research works carried out in Fault diagnosis and Condition-based Maintenance frameworks for Railway Traction Drives. Thus, this review presents the development of Health Assessment and Fault Diagnosis in Railway Traction Drives during the last decade