A new innovative method for track deflection and track stiffness measurement is described and used on the iron-ore line in Sweden. The method uses two different measurement systems of longitudinal level on one axle, and by comparing them in a new way it is possible to extract the unloaded level and the effect of the loading from the loaded longitudinal level. Displacement due to loading can also be interpreted as a track stiffness value if the wheel load is simulated or measured. With this method, a new approach to condition monitoring of track is created due to the possibility of monitoring stiffness and longitudinal level at the same time using a track recording car. The method has been used in an extensive measurement campaign on the iron-ore line in the north of Sweden. Many examples are given in this paper to illustrate different track defects on ordinary track, mainly on track section (bandel) 118. Hanging sleepers and mudpumping places have been successfully located using the new method. The method has been used in both winter and summer conditions. We have found that the track stiffness/deflection level does not vary considerably with change of season. This result is explained by the design decision in the 1980s to use soft fastener pads, which seems to have been a very good decision.

The objective of this study has been to develop an approach to the allocation of an effective maintenance limit for track geometry maintenance that leads to a minimisation of the total annual maintenance cost. A cost model was developed by considering the cost associated with inspection, preventive maintenance, normal corrective maintenance and emergency corrective maintenance. The standard deviation and extreme values of isolated defects of the longitudinal level were used as quality indicators for preventive and corrective maintenance activities. The Monte Carlo technique was used to simulate the track geometry behaviour under different maintenance limit scenarios and the effective limit was determined which minimises the total maintenance cost. The applicability of the model was tested in a case study on the Main Western Line in Sweden. Finally, a sensitivity analysis was carried out on the inspection intervals, the emergency corrective maintenance cost and the maintenance response time. The results show that there is an optimal region for selecting an effective limit. However, by considering the safety aspects in track geometry maintenance planning, it is suggested that the lower bound of the optimal region should be selected.

This study has been dedicated to the optimization of opportunistic tamping scheduling. The aim of this study has been to schedule tamping activities in such a way that the total maintenance costs and the number of unplanned tamping activities are minimized. To achieve this, the track geometry tamping scheduling problem was defined and formulated as a mixed integer linear programming (MILP) model and a genetic algorithm was used to solve the problem. Both the standard deviation of the longitudinal level and the extreme values of isolated defects were used to characterize the track geometry quality and to plan maintenance activities. The performance of the proposed model was tested on data collected from the Main Western Line in Sweden. The results show that different scenarios for controlling and managing isolated defects will result in optimal scheduling plan. It is also found that to achieve more realistic results, the speed of the tamping machine and the unused life of the track sections should be considered in the model. Moreover, the results show that prediction of geometry condition without considering the destructive effect of tamping will lead to an underestimation of the maintenance needs by 2%.

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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.