A wheel impact load detector is used to assess the condition of a railway wheel by measuring the dynamic forces generated by defects. This system normally measures the impact force at multiple points by exploiting multiple sensors to collect samples from different portions of the wheel circumference. The outputs of the sensors are used to estimate the dynamic force as the main indicator for detecting the presence of the defect. This method fails to identify the defect type and its severity. Recently, a data fusion method has been developed to reconstruct the wheel defect signal from the wheel–rail contact signals measured by multiple wayside sensors. The reconstructed defect signal can be influenced by different parameters such as train velocity, axle load, number of sensors, and wheel diameter. This paper aims to carry out a parametric study to investigate the influence of these parameters. For this purpose, VI-Rail is used to simulate the wheel–rail interaction and provide the required data. Then, the developed fusion method is exploited to reconstruct the defect signal from the simulated data. This study provides a detailed insight into the effects of the influential parameters by investigating the variation of the reconstructed defect signals.

The train rescheduling problem is quite a popular topic in the railway research community. Many approaches are available to reschedule traffic in a network partition, but very few works address the coordination of these partitions. In railway systems with very dense traffic, e.g. the Swiss one, it is not always possible to partition the network such that local rescheduling algorithms can work completely independently one from another. This paper proposes a coordination approach for adjacent local rescheduling algorithms. These algorithms are based on the Resource Conflict Graph model, which enables the representation of the interlocking system at a very fine granularity. Simulations on data from the Swiss Federal Railways show the validity of this approach to improve the consistency of decisions at the common boundaries of adjacent local rescheduling algorithms.