# In-Motion, Non-Contact Detection of Ties and Ballasts on Railroad Tracks
## 4 Experiments
### Laboratory Testing  
The system was tested on a 40 ft track panel (\(\sim\)12 m) at the Railway Technologies Laboratory (RTL). The robotic rail cart, equipped with all the mentioned sensors, ran over a small section of the track with ties and ballasts to collect data. As shown in Figure 4, the left distance LiDAR sensor was put on an unballasted section with only ties to establish reference measurements for the ties. These measurements were used as the \"ground truth\" for another sensor on the right with both ties and ballasts. In parallel with the LiDAR sensors, an inductive proximity sensor was used to detect the ties. This sensor was used for two purposes: first, to evaluate its applicability for differentiating between ties and ballasts; second, to verify the accuracy of the LiDAR measurements in distinguishing between the ties and ballasts.  
The tests were intended to evaluate the system's general capability and the applicability of the sensors in tie/ballast detection at low speeds in a controlled environment. Unless the LiDAR's measurements are sufficiently consistent and repeatable, its success for field measurements will be doubtful because of the uncontrolled environment common in track measurements.  
Figure 5a shows the measured distances from LiDAR sensors to their target surface (tie, ballast, or ground) and an inductive proximity sensor. Note that the left distance LiDAR measurement is used as the ground truth. The terms \"activated\" and \"null\" for the inductive proximity sensor are used to indicate when the sensor is detecting a tie plate (hence, a magnetic field is generated) and when no tie plate is detected and a magnetic field is not generated. As shown in Figure 5a, the system accurately captured the surface profile of the traversed track, down to its finest details. The recorded variations are highly tangible and clear, allowing one to easily visualize the track layout. This level of precision stands in contrast to other similar instruments mentioned before, which often suffer from low resolution or slow sampling rates, whereas the LiDAR sensors used in this system demonstrate superior accuracy and agility. The data in Figure 5a show irregular and noisy measurements over ballast sections (unshaded areas) with more significant and frequent variations. In contrast, the tie sections (orange-shaded areas) exhibit smoother and relatively flat measurements compared to the ballast sections. The measurements also show the surface height differences between ties and ballasts, which agree with a visual inspection of the track. The variations observed in the inductive proximity sensor measurements are attributed to the surfaceregulates of the tie plates, as verified by visual observations.  
Figure 4: Laboratory evaluation of LiDAR sensors on a 40 ft track panel for differentiating between ties and ballasts.  
Figure 5a shows that the inductive proximity sensor does not detect the first half of the second tie. The reason for this is illustrated in Figure 5b, which shows that the first half of the left tie plate is sunk into the tie, making it out of the inductive proximity sensor's range. In contrast, the right tie plate is not sunk and remains in the sensor's measurement range; therefore, it is detected. Inductive proximity sensors tend to have a small working range that requires putting the sensor as close as possible to the tie plate (maximum: 15 mm), increasing the likelihood of interference with objects that may be present on a track. Although there are inductive proximity sensors with more extensive working ranges, their magnetic fields could get diverted to the rail, significantly increasing the rate of false positives. At the conclusion of the laboratory tests, we deemed the inductive proximity sensors unsuitable for revenue-service testing despite their success in the controlled laboratory tests.