Structural Health and Load Monitoring with Material-embedded Sensor Networks and Self-organizing Multi-agent Systems

One of the major challenges in Structural Health Monitoring and load monitoring of mechanical structures is the derivation of meaningful information from sensor data. This work investigates a hybrid data processing approach for material-integrated SHM and LM systems by using self-organizing mobile multi-agent systems (MAS), with agent processing platforms scaled to microchip level which offer material-integrated real-time sensor systems, and inverse numerical methods providing the spatial resolved load information from a set of sensors embedded in the technical structure. Inverse numerical approaches usually require a large amount of computational power and storage resources, not suitable for resource constrained sensor node implementations. Instead, off-line computation is performed, with on-line sensor processing by the agent system.