The electrical conductivity of carbon-reinforced thermoplastics can serve as an indicator of damage, enabling structural health monitoring (SHM) without external sensors. However, their application to components with complex geometries and realistic loading scenarios remains limited, raising questions about their feasibility. This study presents the development and validation of a self-sensing SHM for an automotive component made of short carbon and glass fiber-reinforced polyamide. The topology of the SHM network was defined from failure analysis of preliminary tests and stress distribution estimated with a multiscale numerical model. Prototypes made of the self-sensing composite were manufactured, instrumented, and tested under quasi-static and alternating loads, with continuous monitoring of electrical resistance. Under quasi-static loading, electrical signals showed strong correlation with local deformation, with a sharp increase before failure. Fatigue damage led to a gradual resistance drift followed by a sharp increase near the failure location. Two damage detection algorithms were evaluated: a threshold-based and a data-driven method. Both achieved accuracy above 90% for static tests but struggled to anticipate fatigue failure due to the different damage mechanisms involved. The results demonstrate that a robust SHM system can be developed using self-sensing composites, highlighting their potential for real-time monitoring without external sensors.
Ciampaglia et al. (Thu,) studied this question.