A Survey on Audio-Video based Defect Detection through Deep Learning in Railway Maintenance

Within Artificial Intelligence, Deep Learning (DL) represents a paradigm that has been showing unprecedented performance in image and audio processing by supporting or even replacing humans in defect and anomaly detection. The Railway sector is expected to benefit from DL applications, especially in predictive maintenance applications, where smart audio and video sensors can be leveraged yet kept distinct from safety-critical functions. Such separation is crucial, as it allows for improving system dependability with no impact on its safety certification. This is further supported by the development of DL in other transportation domains, such as automotive and avionics, opening for knowledge transfer opportunities and highlighting the potential of such a paradigm in railways. In order to summarize the recent state-of-the-art while inquiring about future opportunities, this paper reviews DL approaches for the analysis of data generated by acoustic and visual sensors in railway maintenance applications that have been published until August 31st, 2021. In this paper, the current state of the research is investigated and evaluated using a structured and systematic method, in order to highlight promising approaches and successful applications, as well as to identify available datasets, current limitations, open issues, challenges, and recommendations about future research directions

Design analysis of short neutral section through dynamic modelling of performance

PhD ThesisUK railway overhead line electrification employs a feature known as ‘short’ neutral section which uses insulators spliced into the contact wire to separate the electrical phases, and they are known as a cause of reliability problems. This research proposes to develop, validate and apply a hitherto unexplored approach to studying short neutral section behaviour. This research briefly initially examines the experience of British Rail with the introduction of the ceramic bead neutral section and its development during the 80s and 90s, and the subsequent introduction and development of a further proprietary type in the early 2000s, which is then assessed in detail. Using information from Network Rail, the significant failures of the main types of neutral sections are examined over a 10 year period for which adequate data exists. European practice is briefly examined. Current methods for analysing the interaction of pantograph and overhead lines are investigated, and the principles are adopted into a bespoke methodology implemented using proprietary software Ansys, rather than custom code as is current widespread practice. This methodology is constructed using finite element and multi-body principles and is successfully validated against ‘benchmarks’, in accordance with current European practice and standards. Mathematical models of a neutral section are constructed using their physical characteristics and data captured in lab tests, and the behaviour against real UK pantographs is simulated using this method. Findings are again successfully validated against real line test data. Using the result, the sensitivity of the neutral section performance to particular parameters of its construction is tested, allowing opportunities for optimisation to be identified, and improvements proposed, successfully demonstrating a (previously untried) validated methodology for examining the neutral section problem. This work has answered all its research questions

Kinematic morphology of space systems

This thesis considers the robustness to faults of mechanical kinematic systems typical of the type applied to the locomotion sub-systems of planetary exploration vehicles. It is argued that, whereas the electronic, software and control methodologies for such kinematic systems have received extensive attention, the development of the theory supporting the corresponding mechanical architectures has not received the same level of attention. An introduction to the space systems context of the topic is provided, and used to illustrate the nature of the requirements that evolve for such missions, concentrating on aspects of'terrainability' - the suitability of a vehicle to manoeuvre on rough planetary surfaces. An approach is investigated which takes concepts from graph theory and linear algebra, and uses these to establish a means for representing kinematic topologies, and, in particular, the 'fault graph' structures, and 'fault classes' that result from the progressive application of faults to nominal kinematic system configurations. Ways whereby the eigenvalues and eigenvectors of the characteristic polynomials of the interchange graph adjacency matrices of various kinematic systems can be applied to represent such systems under nominal and fault conditions are investigated, including development of the 'constraints matrix'. Additionally, the relevance of entropy within a fault graph context is considered, and also techniques suggested for analysing systems in a way which allows a richer representation of the underlying kinematic structure. Various metrics are considered and a means is established whereby a selection of parameters representing some aspects of kinematic systems' behaviour is used in conjunction with these to provide a means of comparing system configurations with each other, in terms of several 'intersystem distance' measures. Some success was achieved - 'inter-system distances' were derived for a selection of systems exhibiting different topologies and showed that these can usefully be used to represent some aspects of kinematic system topologies. Some evidence was obtained that it is possible to discriminate between tree-based and looped systems using this method

An internet of things enabled system for real-time monitoring and predictive maintenance of railway infrastructure

The railway industry plays a pivotal role in the socioeconomic landscape of many countries. However, its operation poses considerable challenges in terms of safety, environmental impact, and the intricacies of intertwined technical and social structures. Addressing these challenges necessitates the adoption of innovative approaches and advanced technologies. This doctoral research delves into the potential of the Internet of Things (IoT) as an enabler for railway infrastructure monitoring and predictive maintenance, aiming to enhance reliability, efficiency, and safety within the industry. Rooted in a pragmatic modelist philosophical stance, this thesis employs an exploratory sequential mixed-method approach incorporating qualitative and quantitative methodologies. The research process involves engaging with key stakeholders to gain insights into the challenges faced in railway maintenance and the opportunities presented by IoT implementation. Following this, an IoT system is developed, and a comprehensive value-creation framework is proposed for its effective implementation within the railway sector. The findings of this investigation underscore the transformative potential of IoT integration in railway infrastructure monitoring, yielding significant improvements in maintenance processes, safety, and operational efficiency. Furthermore, this doctoral research provides a foundation for future innovation and adaptation in the railway industry, contributing to its ongoing evolution and resilience in an ever-changing technological landscape

Robotic Ultrasound Imaging: State-of-the-Art and Future Perspectives

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques.Comment: Accepted by Medical Image Analysi

MethOds and tools for comprehensive impact Assessment of the CCAM solutions for passengers and goods. D1.1: CCAM solutions review and gaps

Review of the state-of-the-art on Cooperative, Connected and Automated mobility use cases, scenarios, business models, Key Performance Indicators, impact evaluation methods, technologies, and user needs (for organisations & citizens)

Infrastructure Design, Signalling and Security in Railway

Railway transportation has become one of the main technological advances of our society. Since the first railway used to carry coal from a mine in Shropshire (England, 1600), a lot of efforts have been made to improve this transportation concept. One of its milestones was the invention and development of the steam locomotive, but commercial rail travels became practical two hundred years later. From these first attempts, railway infrastructures, signalling and security have evolved and become more complex than those performed in its earlier stages. This book will provide readers a comprehensive technical guide, covering these topics and presenting a brief overview of selected railway systems in the world. The objective of the book is to serve as a valuable reference for students, educators, scientists, faculty members, researchers, and engineers