An adaptive opportunistic maintenance model based on railway track condition prediction

Letot, Christophe; Soleimanmeigouni, Iman; Ahmadi, Alireza; Dehombreux, Pierre

doi:10.1016/j.ifacol.2016.11.021

Cited by 21 publications

(18 citation statements)

References 4 publications

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“…20 A Wiener process-based model is characterized by a drift parameter representing the expected degradation rate and by a Brownian motion term to consider the non-monotonic behaviour. Letot et al 21 used the Wiener process to model track geometry degradation. It should be noted that, in contrast to the gamma process, the Wiener process has both negative and positive increments.…”

Section: Effect Of Tamping On the Track Geometry Degradation Ratementioning

confidence: 99%

Evaluation of the effect of tamping on the track geometry condition: A case study

Soleimanmeigouni

Ahmadi

Khouy

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part F:

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Tamping is one of the major activities undertaken by railway maintenance managers to recover the track geometry condition. Modelling the effectiveness of tamping along with track geometry degradation is essential for long-term prediction of track geometry behaviour. The aim of this study is to analyse the effect of tamping on the different track geometry measurements, i.e. longitudinal level, alignment and cant, based on inspection car records from a part of the 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 was 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 were also applied to model track geometry degradation and to obtain degradation rates. The effect of tamping on degradation rate was analysed. It was observed that degradation rate increased after tamping.

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Section: Effect Of Tamping On the Track Geometry Degradation Ratementioning

confidence: 99%

Evaluation of the effect of tamping on the track geometry condition: A case study

Soleimanmeigouni

Ahmadi

Khouy

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part F:

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“…In addition, in order to capture the uncertainty in the degradation path, stochastic models are used by many researchers, e.g. the gamma process [8], Wiener process [9,10] and Markov chain [11,12]. The aforementioned models can be used to predict the degradation of a track section over time.…”

Section: Introductionmentioning

confidence: 99%

Prediction of track geometry degradation using artificial neural network: a case study

Khajehei

Ahmadi

Soleimanmeigouni

et al. 2021

International Journal of Rail Transportation

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The aim of this study has been to predict the track geometry degradation rate using artificial neural network. Tack geometry measurements, asset information, and maintenance history for five line sections from the Swedish railway network were collected, processed, and prepared to develop the ANN model. The information of track was taken into account and different features of track sections were considered as model input variables. In addition, Garson method was applied to explore the relative importance of the variables affecting geometry degradation rate. By analysing the performance of the model, we found out that the ANN has an acceptable capability in explaining the variability of degradation rates in different locations of the track. In addition, it is found that the maintenance history, the degradation level after tamping, and the frequency of trains passing along the track have the strongest contributions among the considered set of features in prediction of degradation rate.

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“…However, some approaches have been proposed for rail track and railway switches maintenance. (Letot, Soleimanmeigouni, Ahmadi, & Dehombreux, 2016) addressed the problem of rail track tamping interventions scheduling. A cost model has been proposed for the optimization of the maintenance time, for a single track section, based on three thresholds, namely, comfort penalty, speed reduction penalty and track closure (failure).…”

Section: Decision For Predictive Maintenancementioning

confidence: 99%

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

Brahimi

Medjaher

Mohammed

et al. 2020

IJPHM

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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

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An adaptive opportunistic maintenance model based on railway track condition prediction

Cited by 21 publications

References 4 publications

Evaluation of the effect of tamping on the track geometry condition: A case study

Evaluation of the effect of tamping on the track geometry condition: A case study

Prediction of track geometry degradation using artificial neural network: a case study

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

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