Analyzing the Dynamic Response of Frauscher Wheel Sensors: Correlations Between Electromagnetic Signals and Train Speed

This thesis focuses on the analysis and simulation of Frauscher wheel sensors used in railway monitoring systems. By leveraging both synthetic data generation and real-world data collection, we developed models to replicate the sensor's magnetic field response and currents under various wheel speeds and diameters. A detailed examination was conducted on signal processing techniques, including down-sampling, advanced filtering, and Kalman filters, to enhance data quality and accuracy. The study also explored methods for wireless data transmission to facilitate remote monitoring and calibration of the sensors. The findings provide a robust framework for optimizing sensor sensitivity and improving railway safety and efficiency through reliable, real-time data analysis.