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Predictive Models for Railway Track Geometry Degradation
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-3266-2434
2019 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Prediktiva modeller för degradering av spårgeometri i järnväg (Swedish)
Abstract [en]

Railways are a vital and effective means of mass transportation and play a vital role in modern transportation and social development. The benefits of the railway compared to other transportation modes are a high capacity, high efficiency and low pollution, and owing to these advantages, railways are nowadays experiencing a higher demand for the transportation of passengers and goods. This is in turn imposing higher demands on the railway capacity and service quality. As a result, infrastructure managers are being driven to develop new strategies and plans to fulfil new requirements, which include a higher level of resilience against failure, a more robust and available infrastructure, and cost reduction. This can be achieved by making efficient and effective maintenance decisions by applying RAMS (reliability, availability, maintainability, and safety) analysis and LCC (life cycle cost) assessment.

A major part of the railway maintenance burden is related to track geometry maintenance. Due to the forces induced on the track by traffic, the railway degrades over time, causing deviations from the designed vertical and horizontal alignment. When the track geometry degrades to an unacceptable level, this can cause catastrophic consequences, such as derailment. Maintenance actions are used to control the degradation of the track and restore the geometry condition of the track sections to an acceptable state.

With the current advancements in the field of technologies for railway track geometry measurement, a large amount of event data and condition monitoring data is available. Such technologies, along with advances in predictive analytics, are providing the possibility of predicting the track geometry condition in support of a predictive maintenance strategy. The aim of the research conducted for this thesis has been to develop methodologies and tools for the prediction of railway track geometry degradation, in order to facilitate and enhance the capability of making effective decisions for inspection and maintenance planning. To achieve the purpose of this research, literature studies, case studies and simulations have been conducted.

Firstly, a literature review was performed to identify the existing knowledge gaps and challenges for track geometry degradation modelling and maintenance planning. Secondly, a case study was conducted to analyse the effect of tamping on the track geometry condition. By considering the track geometry condition before tamping as the predictor, a probabilistic approach was utilised to model the recovery after tamping interventions. Thirdly, a two-level piecewise linear framework was developed to model the track geometry evolution over a spatial and temporal space. This model was implemented in a comprehensive case study. Fourthly, a data-driven analytical model was developed to predict the occurrence of track geometry defects. This model enables infrastructure managers to predict the occurrence of severe isolated geometry defects. Finally, an integrated model was created to investigate the effect of different inspection intervals on the track geometry condition.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2019.
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords [en]
Data-driven models, Degradation, Inspection, Maintenance, Predictive analytics, Tamping, Track geometry, Railway infrastructure, RAMS
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-72811ISBN: 978-91-7790-310-9 (print)ISBN: 978-91-7790-311-6 (electronic)OAI: oai:DiVA.org:ltu-72811DiVA, id: diva2:1286681
Public defence
2019-09-12, F1031, Luleå, 09:30 (English)
Opponent
Supervisors
Available from: 2019-02-07 Created: 2019-02-07 Last updated: 2019-08-21Bibliographically approved
List of papers
1. Track geometry degradation and maintenance modelling: A review
Open this publication in new window or tab >>Track geometry degradation and maintenance modelling: A review
2018 (English)In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 232, no 1, p. 73-102Article in journal (Refereed) Published
Abstract [en]

Increased demand for railway transportation is creating a need for higher train speeds and axle loads. These, in turn,increase the likelihood of track degradation and failures. Modelling the degradation behaviour of track geometry anddevelopment of applicable and effective maintenance strategies has become a challenging concern for railway infrastructuremanagers. During the last three decades, a number of track geometry degradation and maintenance modellingapproaches have been developed to predict and improve the railway track geometry condition. In this paper, existingtrack geometry measures are identified and discussed. Available models for track geometry degradation are reviewedand classified. Tamping recovery models are also reviewed and discussed to identify the issues and challenges of differentavailable methodologies and models. Existing track geometry maintenance models are reviewed and critical observationson each contribution are provided. The most important track maintenance scheduling models are identified and discussed.Finally, the paper provides directions for further research.

Place, publisher, year, edition, pages
Sage Publications, 2018
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-14797 (URN)10.1177/0954409716657849 (DOI)000419833100006 ()2-s2.0-85040348348 (Scopus ID)e3794ef4-cb25-49e0-b55c-a579ff2ea6f5 (Local ID)e3794ef4-cb25-49e0-b55c-a579ff2ea6f5 (Archive number)e3794ef4-cb25-49e0-b55c-a579ff2ea6f5 (OAI)
Note

Validerad;2018;Nivå 2;2018-01-18 (svasva)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2019-08-21Bibliographically approved
2. Evaluation of the effect of tamping on the track geometry condition: a case study
Open this publication in new window or tab >>Evaluation of the effect of tamping on the track geometry condition: a case study
2018 (English)In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 232, no 2, p. 408-420Article in journal (Refereed) Published
Abstract [en]

Tamping is one of the major activities applied by railway maintenance managers to recover track geometry condition. Modelling the tamping effectiveness along with track geometry degradation is essential for long term prediction of track geometry behaviour. The aim of this study is to analyse theeffect of tamping on the different track geometry measures, i.e. longitudinal level, alignment and cant; on the basis of inspection car records from a part of Main Western Line in Sweden. To model recovery after tamping a probabilistic approach is applied. The track geometry condition before tamping was considered as the dominant factor for modelling the model parameters. Correlation analysis has performed to measure the linear relation between the recoveries of the different geometry measures. The results show a moderate correlation between the recovery of the longitudinal level and that of the cant, and a weak correlation between the recovery of the longitudinal level and that of the alignment. Linear regression and Wiener process are also applied to model track geometry degradation and to obtain degradation rates. Theeffect of tamping on degradation rate is analysed. It is observed that the degradation rate was increased after tamping intervention.  

Place, publisher, year, edition, pages
Sage Publications, 2018
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-15883 (URN)10.1177/0954409716671548 (DOI)000424780200006 ()f7391512-a026-4e7c-a4d0-96223a5957dd (Local ID)f7391512-a026-4e7c-a4d0-96223a5957dd (Archive number)f7391512-a026-4e7c-a4d0-96223a5957dd (OAI)
Note

Validerad;2018;Nivå 2;2018-02-12 (svasva)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2019-08-21Bibliographically approved
3. Modelling the evolution of ballasted railway track geometry by a two-level piecewise model
Open this publication in new window or tab >>Modelling the evolution of ballasted railway track geometry by a two-level piecewise model
Show others...
2018 (English)In: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980, Vol. 14, no 1, p. 33-45Article in journal (Refereed) Published
Abstract [en]

Accurate prediction and efficient simulation of the evolution of track geometry condition is a prerequisite for planning effective railway track maintenance. In this regard, the degradation and tamping effect should be equipped with proper and efficient probabilistic models. The possible correlation induced by the spatial structure also needs to be taken into account when modelling the track geometry degradation. To address these issues, a two-level piecewise linear model is proposed to model the degradation path. At the first level, the degradation characteristic of each track section is modelled by a piecewise linear model with known break points at the tamping times. At the second level, Autoregressive Moving Average models are used to capture the spatial dependences between the parameters of the regression lines indexed by their locations. To illustrate the model, a comprehensive case study is presented using data from the Main Western Line in Sweden

Place, publisher, year, edition, pages
Taylor & Francis, 2018
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-63815 (URN)10.1080/15732479.2017.1326946 (DOI)000415674800003 ()2-s2.0-85019663898 (Scopus ID)
Note

Validerad;2017;Nivå 2;2017-11-01 (andbra)

Available from: 2017-06-09 Created: 2017-06-09 Last updated: 2019-08-21Bibliographically approved

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Soleimanmeigouni, Iman

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