Prediction of railway track geometry defects
a case study
Document identifier: oai:DiVA.org:ltu-76538
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10.1080/15732479.2019.1679193Keyword: Engineering and Technology,
Prediction,
Drift och underhållsteknik,
Tamping,
Shock events,
Binary logistic regression,
Linear regression,
Intervention limit,
Degradation,
Civil Engineering,
Geometry defect,
Railway track maintenance,
Annan samhällsbyggnadsteknik,
Samhällsbyggnadsteknik,
Teknik och teknologier,
Other Civil Engineering,
Operation and MaintenancePublication year: 2020Relevant Sustainable Development Goals (SDGs):
The SDG label(s) above have been assigned by OSDG.aiAbstract: The aim of this study has been to develop a data-driven analytical methodology for prediction of isolated track geometry defects, based on the measurement data obtained from a field study. Within the study, a defect-based model has been proposed to identify the degradation pattern of isolated longitudinal level defects. The proposed model considered the occurrence of shock events in the degradation path. Furthermore, the effectiveness of tamping intervention in rectifying the longitudinal level defects was analysed. The results show that the linear model is an appropriate choice for modelling the degradation pattern of longitudinal level defects. In addition, a section-based model has been developed using binary logistic regression to predict the probability of occurrence of isolated defects associated with track sections. The model considered the standard deviation and kurtosis of longitudinal level as explanatory variables. It has been found that the kurtosis of the longitudinal level is a statistically significant predictor of the occurrence of isolated longitudinal level defects in a given track section. The validation results show that the proposed binary logistic regression model can be used to predict the occurrence of isolated defects in a track section.
Authors
Iman Soleimanmeigouni
Luleå tekniska universitet; Drift, underhåll och akustik
Other publications
>>
Alireza Ahmadi
Luleå tekniska universitet; Drift, underhåll och akustik
Other publications
>>
Arne Nissen
Trafikverket, Luleå, Sweden
Other publications
>>
Xun Xiao
School of Fundamental Sciences, Massey University, Palmerston North, New Zealand
Other publications
>>
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identifier: oai:DiVA.org:ltu-76538
datestamp: 2021-04-19T12:44:50Z
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recordCreationDate: 2019-10-28
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10.1080/15732479.2019.1679193
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titleInfo:
@attributes:
lang: eng
title: Prediction of railway track geometry defects
subTitle: a case study
abstract: The aim of this study has been to develop a data-driven analytical methodology for prediction of isolated track geometry defects based on the measurement data obtained from a field study. Within the study a defect-based model has been proposed to identify the degradation pattern of isolated longitudinal level defects. The proposed model considered the occurrence of shock events in the degradation path. Furthermore the effectiveness of tamping intervention in rectifying the longitudinal level defects was analysed. The results show that the linear model is an appropriate choice for modelling the degradation pattern of longitudinal level defects. In addition a section-based model has been developed using binary logistic regression to predict the probability of occurrence of isolated defects associated with track sections. The model considered the standard deviation and kurtosis of longitudinal level as explanatory variables. It has been found that the kurtosis of the longitudinal level is a statistically significant predictor of the occurrence of isolated longitudinal level defects in a given track section. The validation results show that the proposed binary logistic regression model can be used to predict the occurrence of isolated defects in a track section.
subject:
@attributes:
lang: eng
authority: uka.se
topic:
Engineering and Technology
Civil Engineering
Other Civil Engineering
@attributes:
lang: swe
authority: uka.se
topic:
Teknik och teknologier
Samhällsbyggnadsteknik
Annan samhällsbyggnadsteknik
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lang: eng
topic: Railway track maintenance
@attributes:
lang: eng
topic: geometry defect
@attributes:
lang: eng
topic: degradation
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lang: eng
topic: prediction
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lang: eng
topic: intervention limit
@attributes:
lang: eng
topic: linear regression
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lang: eng
topic: binary logistic regression
@attributes:
lang: eng
topic: shock events
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lang: eng
topic: tamping
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lang: swe
authority: ltu
topic: Drift och underhållsteknik
genre: Research subject
@attributes:
lang: eng
authority: ltu
topic: Operation and Maintenance
genre: Research subject
language:
languageTerm: eng
genre:
publication/journal-article
ref
note:
Published
4
Validerad;2020;Nivå 2;2020-06-03 (alebob)
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Soleimanmeigouni
Iman
1988-
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Luleå tekniska universitet
Drift underhåll och akustik
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solmei
0000-0002-3266-2434
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Ahmadi
Alireza
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Luleå tekniska universitet
Drift underhåll och akustik
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@attributes:
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Nissen
Arne
role:
roleTerm: aut
affiliation: Trafikverket Luleå Sweden
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Xiao
Xun
role:
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affiliation: School of Fundamental Sciences Massey University Palmerston North New Zealand
originInfo:
dateIssued: 2020
publisher: Taylor & Francis
relatedItem:
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type: host
titleInfo:
title: Structure and Infrastructure Engineering
identifier:
1573-2479
1744-8980
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type: volume
number: 16
@attributes:
type: issue
number: 7
extent:
start: 987
end: 1001
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url: http://ltu.diva-portal.org/smash/get/diva2:1366253/FULLTEXT01.pdf
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