Resumen
Structural Health Monitoring allows an automated performance assessment of buildings and infrastructures, both during their service lives and after critical events, such as earthquakes or landslides. The strength of this technology is in the diffuse nature of the sensing outputs that can be achieved for a full-scale structure. Traditional sensors adopted for monitoring purposes possess peculiar drawbacks related to placement and maintenance issues. Smart construction materials, which are able to monitor their states of strain and stress, represent a possible solution to these issues, increasing the durability and reliability of the monitoring system through embedding or the bulk fabrication of smart structures. The potentialities of such novel sensors and systems are based on their reliability and flexibility. Indeed, due to their peculiar characteristics, they can combine mechanical and sensing properties. We present a study on the optimization and the characterization of construction materials doped with different types of fillers for developing a novel class of sensors able to correlate variations of external strains to variations of electrical signals. This paper presents the results of an experimental investigation of composite samples at small and medium scales, made of cementitious materials with carbon-based inclusions. Different from a previous work by the authors, different carbon-based filler composite sensors are first compared at a small cubic sample scale and then tailored for larger plate specimens. Possible applications are in the strain/stress monitoring, damage detection, and load monitoring of concrete buildings and infrastructures.