Soft Computing Applications in Structural Dynamic Monitoring

Soft computing based tools and methodologies are attracting growing interest in the field of structural dynamic monitoring. Within this framework, neural networks, evolutionary computation,metaheuristic and swarm intelligence are becoming very popular in sensor network design, signal processing, system identification, model updating and structural diagnostic. Current research also shows increasing use of fuzzy logic for damage detection and structural diagnostic. The paper provides a short state-of-the-art review about the most recent research on soft computing theories and techniques for structural dynamic monitoring, with the focus on optimal sensor placement, mechanical system identification and health monitoring. Finally, some experimental applications are included to highlight how soft computing methods can be employed effectively in this field. They are concerned with the experimental parametric identification of nonlinear passive devices for seismic protection using differential evolution and particle swarm optimization.