Railway Track Safety Using VSWR Based Fault Detection System

Authors: Deepti Gore, Shravani Bagayatkar, Samiksha Chopade, S. M. Hambarde

Abstract: Railway infrastructure is critical, and track faults pose significant safety and operational risks. This research presents a novel, real-time Voltage Standing Wave Ratio (VSWR)-based fault detection system for continuous railway track integrity monitoring. The system leverages the principles of Time-Domain Reflectometry (TDR), where changes in the rail's characteristic electrical impedance due to faults (like cracks, rail breaks, or joint degradation) are detected as significant spikes in the measured VSWR. A dedicated hardware module continuously injects a signal and monitors the reflected energy. A Machine Learning (ML) classifier (e.g., Support Vector Machine or Random Forest) is then employed to analyze the VSWR waveform, categorize the fault type, and accurately estimate its location. This approach offers a non-intrusive, continuous, and low-latency alternative to traditional, periodic inspection methods. The proposed system aims to significantly enhance railway safety, minimize operational maintenance costs, and prevent catastrophic failures.