Distributed fiber optic sensors (DFOSs) for structural health monitoring (SHM) of railway infrastructure: a critical review

Distributed fiber optic sensing (DFOS) has emerged as a transformative technology for structural health monitoring (SHM) of railway infrastructure, offering continuous, high-resolution measurements along extended optical fiber lengths, capabilities that conventional point sensors such as strain gauges and accelerometers cannot match. This review critically examines DFOS technology and its railway SHM applications, covering system components, interrogator units, optical fiber cables, and data acquisition systems, alongside the three principal scattering mechanisms: Rayleigh, Brillouin, and Raman, each offering distinct trade-offs in spatial resolution, sensing range, and measurand sensitivity. Field applications across track and sleeper monitoring, bridge health evaluation, tunnel lining assessment, and embankment stability are reviewed and critically compared. The integration of artificial intelligence (AI) and machine learning (ML) with DFOS data streams is discussed, demonstrating detection accuracy exceeding 97% in recent studies. Its main application rail embankment monitoring is discussed. Key challenges are identified, including high interrogator costs, large data volumes, installation complexity in retrofit scenarios, and environmental noise under operational train speeds. Future research priorities include lower-cost interrogation hardware, automated signal processing pipelines, digital twin integration, and standardized performance frameworks to accelerate large-scale adoption across railway networks worldwide.