Structural Damage Detection Via Nonlinear System Identification and Structural Intensity Methods.

During the past decade, the development of Structural Health Monitoring (SHM) systems has attracted considerable interest from several engineering fields. The possibility of monitoring the status (often referred to as "health") of a structure under operational conditions could result in a drastic change in the current maintenance approach. The introduction of SHM systems would allow transitioning the maintenance strategy from a scheduled (i.e. Time Based) basis to a Condition Based approach. The development of SHM systems relies on availability of reliable techniques to extract the characteristic features of damage from experimental measurements. The research presented in this dissertation consists of an investigation of two new SHM methodologies. The first technique is based on the use of the Higher order Harmonic Response Signal (HHRS) typical of cracked structures. A theoretical formulation which exploits the nonlinear harmonics in cracked rods is presented. The HHRS provides an effective way to localize nonlinear fatigue cracks without requiring a baseline signal or a finite element model of the healthy structure. The HHRS method is first evaluated through a series of numerical simulations. The HHRS method is then validated through laboratory experiments specifically designed to induce and measure the nonlinear harmonic response in a one-dimensional cracked rod. Experimental results proved that this technique can achieve high accuracy (error lower than 1%). Useful guidelines for the selection of a proper sensory system for HHRS measurements are provided. Finally, the HHRS technique is extended to a two-dimensional plate structure. The characteristic dispersive nature of the dynamic response of plates increases the complexity in the post-processing phase. A new feature extraction approach, particularly suitable for dispersive system, is presented. Numerical results proved the theoretical approach and provided guidelines for the selection of an appropriate sensory system for data acquisition. The second technique presented in this work is based on the use of Structural Intensity (SI) as a damage detection tool. Although SI has been used in the past for structural vibrations and noise control systems, applications to damage detection are still very limited. A numerical study exploring the relationship between several structural (loss factors, damage size) and experimental (frequency resolution, sensor size and placements) parameters and the SI field is presented. The changes in SI at discrete structural locations are used as the damage metric. In order to improve performance and adaptability of the SI based system over a wide spectrum of structures, the concept of Active Energy Sink (AES) is introduced. A feedback control system is used to realize the absorption device. The AES design is presented, and validated through experimental testing. An increase in the closed loop loss factors up to eta=29% was measured for the low frequency modes. Finally, the concept of Nonlinear Structural Surface Intensity (NSSI) is presented. The SI-based SHM was initially developed by relying on the availability of a baseline for the healthy structure. In order to develop a baseline-free technique, the HHRS is integrated into the SI concept. This approach results in a single technique which benefits from the localization capabilities from the HHRS approach and of the sizing capabilities proper of the SI approach.