Prediction of railway track geometry defects

a case study

Document identifier: oai:DiVA.org:ltu-76538
Access full text here:10.1080/15732479.2019.1679193
Keyword: 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 Maintenance
Publication year: 2020
Relevant Sustainable Development Goals (SDGs):
SDG 9 Industry, innovation and infrastructureSDG 3 Good health and wellbeing
The SDG label(s) above have been assigned by OSDG.ai

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.

Authors

Iman Soleimanmeigouni

Luleå tekniska universitet; Drift, underhåll och akustik
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Alireza Ahmadi

Luleå tekniska universitet; Drift, underhåll och akustik
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Arne Nissen

Trafikverket, Luleå, Sweden
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Xun Xiao

School of Fundamental Sciences, Massey University, Palmerston North, New Zealand
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