Prognostics and Health Management for an Overhead Contact Line System - A Review

Abstract

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 systemsis 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

Taxonomy of candidate’s selection for prioritized predictive maintenance in maintenance, repairs and overhaul organizations

“…Examples of methods in this group are screening methods that use expert judgment to assess the risk of failure, including using failure mode effects (and criticality) analysis (FMEA and FMECA) models or a fault tree analysis (FTA) and HAZOP (hazard and operability study) (Brahimi et al, 2016, Gouriveau et al, 2016, Avizienis et al, 2004). An equally important part of this group of methods is assessment methods based on various checklists, which allow tracking criteria that cannot be quantified.…”

“…Combined methods include methods that use at least two of the above methods at the same time. In a study, Brahimi et al (2016) uses an integral indicator (criticality index) combining…”

System-level failure prognostics: Literature review and main challenges

“…From this perspective, the system prognostics is simplified to the prognostics of the critical components determined by using risk analysis and reliability methods. 37,45,46 The standard 47 provides a series of methods to support engineers in evaluating the reliability of a given system. These methods can be divided into two main groups, namely qualitative and quantitative techniques.…”

“…These approaches can be physics-based 49 or data-driven. [50][51][52] The critical component identification approach was applied in several cases, such as identifying the contact wire as the most critical and impacting component of the Overhead Contact System of railway infrastructure, 45 bearings in rotating machines, lithium-ion batteries, and turbofan engines in commercial airplanes, 46 etc.…”

Impact of decision horizon on post-prognostics maintenance and missions scheduling: a railways case study

“…In the context of applying PHM methodology on rolling stock, several works have studied condition monitoring [17] and prognostics [18,19]. In this work, we focus on the decision-making process.…”