Prognostics and health management for an overhead contact line system - A review

The railway industry in European countries is standing a significant competition from other modes of transportation, particularly in the field of freight transport. In this competitive context, railway stakeholders need to modernize their products and develop innovative solutions to manage their asset and reduce operational expenditures. As a result, activities such as condition-based and predictive maintenance became a major concern. Under those circumstances, there is a pressing need to implement prognostics and health management (PHM) solutions such as remote monitoring, fault diagnostics techniques, and prognostics technologies. Many studies in the PHM area for railway applications are focused on infrastructure systems such as railway track or turnouts. However, one of the key systems to ensure an efficient operability of the infrastructure is the overhead contact line (OCL). A defect or a failure of an OCL component may cause considerable delays, lead to important financial losses, or affect passengers safety. In addition maintaining this kind of geographically distributed systems is costly and difficult to forecast. This article reviews the state of practice and the state of the art of PHM for overhead contact line system. Key sensors, monitoring parameters, state detection algorithms, diagnostics approaches and prognostics models are reviewed. Also, research challenges and technical needs are highlighted

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

Dynamic Performance of High-Speed Railway Overhead Contact Line Interacting With Pantograph Considering Local Dropper Defect

The local dropper defect is the most common fault in the early service stage of the overhead contact line (OCL) system. The plastic deformation and loose of a dropper may cause the variation of the contact line height, which has a direct effect on the contact performance of the pantograph-OCL system. This paper proposes a methodology to model the OCL with local dropper defect using a nonlinear finite element approach. Employing a developed TCUD (Target Configuration under Dead Load) method, which takes the vertical defective dropper position in the contact line as additional constraints, the local dropper defect is exactly added in the initial configuration of the OCL model. Several simulations of pantograph-OCL interaction are run with different positions of the defective dropper. The effect of local dropper defect on the pantograph-OCL contact forces is analysed. The results show that the increase of the defect degree causes the increment of the contact force peak around the defective dropper point. The defect on the first or last dropper within a span is the most detrimental to the current collection quality, as it directly causes the increase of maximum contact force, which challenges the safe operation of the pantograph-OCL system, and should be strictly restricted. The PSD (Power Spectral Density) analysis of contact force indicates that the dropper defect distorts the frequency characteristics of the contact force. The energy of contact forces decreases at the dropper-interval related frequencies due to the presence of dropper defect. Similarly, a significant `break' of the dropper-interval frequency component can be observed in the time-frequency representation of the contact force. This phenomenon has the potential to be used to identify and locate the defective dropper from the measured contact force