  We propose a composite diagnostics solution for railway infrastructure
monitoring. In particular, we address the issue of soft-fault detection in
underground railway cables. We first demonstrate the feasibility of an
orthogonal multitone time domain reflectometry based fault detection and
location method for railway cabling infrastructure by implementing it using
software defined radios. Our practical implementation, comprehensive
measurement campaign, and our measurement results guide the design of our
overall composite solution. With several diagnostics solutions available in the
literature, our conglomerated method presents a technique to consolidate
results from multiple diagnostics methods to provide an accurate assessment of
underground cable health. We present a Bayesian framework based cable health
index computation technique that indicates the extent of degradation that a
cable is subject to at any stage during its lifespan. We present the
performance results of our proposed solution using real-world measurements to
demonstrate its effectiveness.
