Structural Health and Load Monitoring with Material-embedded Sensor Networks and Self-organizing Multi-agent Systems
Klaus-Dieter Thoben; Matthias Busse; Berend Denkena; Jürgen Gausemeier (Hrsg). 2nd International Conference on System-Integrated Intelligence: Challenges for Product and Production Engineering. Amsterdam: Elsevier 2014 S. 668 - 690
Erscheinungsjahr: 2014
Publikationstyp: Diverses (Konferenzbeitrag)
Sprache: Englisch
Doi/URN: 10.1016/j.protcy.2014.09.039
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Inhaltszusammenfassung
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 res...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.» weiterlesen» einklappen