Integrated Time- and Frequency-Domain Reflectometry for Non-Invasive Moisture Monitoring in Historic Masonry Materials

Moisture monitoring in historic masonry requires non-destructive solutions that can be adapted to the characteristics and value of the asset, the spatial extent of the phenomenon, and the need for repeated measurements over time. This work presents an integrated reflectometric methodology that combines accurate Frequency-Domain Reflectometry (FDR) characterization with the development and validation of a custom-developed, compact, portable, low-cost, and potentially scalable Time-Domain Reflectometry (TDR) prototype. Resonant patch antennas operating at different frequencies were used with a Vector Network Analyzer (VNA) to characterize Lecce stone, Carparo, and plaster applied to Carparo during controlled drying. This configuration provides localized moisture information based on sensor–material-specific calibration and is particularly suitable for valuable architectural, monumental, or decorative surfaces, where measurement accuracy and detailed spectral analysis are essential. The proposed TDR prototype extends the same reflectometric approach toward more accessible, low-cost, repeated, distributed, and potentially remotely managed monitoring. Its performance was assessed against a reference PicoVNA using a microstrip probe, selected as a representative application for monitoring broader masonry regions and phenomena such as rising damp. The reflectograms acquired with the prototype were processed to reconstruct the corresponding complex S11(f) responses, allowing the two measurement systems to be compared on a common frequency-domain basis. The results showed a consistent moisture-dependent resonance evolution and demonstrated that the prototype preserves the principal temporal and spectral information observed with the reference instrument. The proposed methodology therefore brings together complementary measurement capabilities within a unified framework, enabling the sensing configuration to be selected according to the required accuracy, spatial coverage, portability, cost, scalability, and monitoring frequency.