Multiphysics simulation of Eddy current sensor and Railway track interaction

Developing a comprehensive Multiphysics model simulating the interaction between an eddy current sensor and railway tracks, enabling the detection and differentiation of various track defects.

Goal

To develop a comprehensive Multiphysics model simulating the interaction between an eddy current sensor and railway tracks, enabling the detection and differentiation of various track defects.

Background

The purpose of the project is to enhance railway infrastructure management by developing a novel approach for detecting critical track components through Multiphysics simulation and data-driven models. The goal is to develop an automated monitoring system using a train-based differential eddy current sensor to continuously monitor multiple track components, improving operational capacity, service quality, and safety while minimizing downtime and delays.

Methodology

The project employs a multidisciplinary approach combining experimentation, simulation, and data analysis. In this project, robotic measurements are used to quantify the magnetic flux and evaluate the sensor coil configuration. 3D Multiphysics simulations are developed to simulate both healthy states and defects under operational conditions. In the next stage, a database generated from these simulations will undergo data processing, enabling machine learning models to detect anomalies and classify track component states. In addition, validation will be performed through laboratory and field tests, including train-based measurements. Using these real-world datasets will help refining numerical models, ensuring accurate defect detection and system reliability, ultimately enhancing railway maintenance efficiency and safety standards.

Status and Results

A Multiphysics model has been developed to differentiate various defects by analysing the voltage output generated by the eddy current sensor. The baseline model of a defective track, created in COMSOL, is illustrated in Figure 1, where a rail breakage is represented as a small gap. As the sensor moves along the rail, it records voltage output, displayed in Figure 2. A voltage spike is observed as the sensor approaches the defect, followed by a decline once the sensor passes away from the defect.

Additionally, the corresponding IQ plot demonstrates unique patterns for different defect types, facilitating their identification and classification. Figure 3 presents the current density distribution along the track, contrasting a defect-free track with one containing a defect.