**4. Experiments**

The scaled-down experimental railcar (**Figure 6**) was mounted on a closed-circuit track (**Figure 7**). The track has curves that make the railcar rotate clock and counterclockwise. The railcar has two bogies, with a suspension and a platform that can be loaded with different weights and containers. One of the bogies is powered by a servomotor that can vary the railcar speed, and it is remotely controlled.

The railcar is instrumented with an encoder (for measuring the wheel's speed) with 500 PPR (pulses per revolution), three orthogonal accelerometers, and three gyroscopes (MEMs LSM6DS3) with a resolution of 4 g and the gyroscopes 143 DPS (degrees per second). As the railcar moved, a light sensor TCRT5000 counted the sleepers and determined the speed. The system had a data acquisition system with a 1000 Hz sampling rate.

The railcar ran freely around the track, but only the data from a segment was considered for the analysis. **Figure 8** shows the trajectory considered for the study.

The gyroscope data were used to locate the curvature changes within the data vectors. The Recurrence Plots can be built with any acceleration data; nevertheless, it was decided to use the vertical acceleration since it contains the higher dynamic responses and is more sensitive to tracking defects.

The following section describes the analysis of the measured data and the corresponding Recurrence Plots.

**Figure 6.** *Experimental railcar.*

**Figure 7.** *Railcar mounted on the track.*

*Perspective Chapter: Predicting Vehicle-Track Interaction with Recurrence Plots DOI: http://dx.doi.org/10.5772/intechopen.105752*

**Figure 8.** *Trajectory for data analysis.*
