Abstract—Long-term deterioration of civil engineering structures is a serious problem of crucial societal and economical relevance. In these years, civil engineering structures such as bridges or wind turbines are reaching or exceeding their original anticipated lifespan. Consequently, there is an urgent need for applying modern structural health monitoring systems to ensure serviceability and structural safety through efficient as well as cost-effective monitoring. In this contribution, a novel generation of biologically-inspired structural health monitoring systems is introduced, synergistically coupling sophisticated engineering concepts and technologies stemming from artificial intelligence research. To exemplify the proposed concepts in more detail, the design and the implementation of a biologically-inspired and self-managing (i.e. self-configuring, self-optimizing, self-protecting and self-healing) structural health monitoring system prototype is presented. Practicability, reliability and performance of the prototype are corroborated by means of structural and environmental data taken from different engineering structures in tandem with intensive laboratory tests.

Index Terms—Biologically-Inspired Structural Health Monitoring, Computational and Artificial Intelligence,Multi-Agent Technology, Sensor Networks, Emergent Computing.

Cite: Kay Smarsly,"Biologically-Inspired Condition Monitoring of Civil Engineering Structures," International Journal of Computer and Electrical Engineering vol. 2, no. 4, pp. 770-777, 2010.