Time series methods for SHM applications and multiple coherence computations: assessment in real and laboratory conditions

Abstract

This doctoral thesis studies times series methods for different industrial applications in two fields: i) Structural Health Monitoring (SHM): the aim is to develop methods to assess the health of a structure (if it has damage or not, location of the damage) including some extensions to changing environmental conditions and identification/localization of the damage. Several methods parametric and non–parametric have been analyzed. The proposed methods have been validated in lab–scale wind turbine structures (tower and blades). ii) Multiple Coherence Method (MCM): the ultimate goal in this line is to identify the predominant sources of noise in different situations considering non–stationary signals. Again several parametric and non–parametric techniques are presented and compared. The developed methods have been validated on experimental data: measurements in semi–anechoic chamber with a moving source and measurements in the shaft and cabin of an elevator.