This paper presents a novel wayside rail monitoring system for real-time detection and quantification of rail surface cracks with sub-millimeter precision. The core innovation lies in mounting piezoelectric transducers on the web of the rail—an unconventional and practical location that avoids interference with wheel passages while enabling continuous monitoring in real-world conditions. Moreover, to directly quantify crack depth, a customized signal processing pipeline is developed, employing surface acoustic waves (SAWs) and incorporating a parallel reference transducer pair mounted on an undamaged rail section for calibration. This auxiliary pair provides a real-time calibration baseline, improving measurement robustness and accuracy. The method is experimentally validated on rail samples and verified through metallographic analysis. This approach enables condition-based maintenance by improving detection accuracy and offers the potential to reduce operational costs and enhance railway safety.

Residual stresses play a crucial role in the maintenance and longevity of engineering structures. However, continuous monitoring of these stresses remains a challenge due to cost, implementation complexity, and reliability concerns. The present contribution proposes a novel method for continuous long-term residual stress monitoring by tracking the effect of residual stress changes on the propagation velocity of surface acoustic waves (SAWs) due to the acoustoelastic effect via a fixed setup of piezoelectric patch transducers (PETs). The applicability of patch transducers to stress measurement using SAW was experimentally validated using tensile and bending tests on 25CrMo4 (1.7218) steel specimens. The tensile tests exhibited a consistent decrease in wave velocity with increasing stress, enabling straightforward determination of the acoustoelastic coefficient (AEC). The bending tests confirmed the method’s applicability, highlighting the need for multiple excitation frequencies to improve reliability and detect inconsistencies. Finally, it is briefly outlined how to separate residual and load stresses during long-term measurements. The results demonstrate that this approach provides a cost-effective solution for continuous monitoring of residual stresses in metallic materials, offering potential applications in structural health monitoring and predictive maintenance.