Structural Health Monitoring (SHM) through adequate damage detection and prediction of the remaining useful life of structures is a major area of interest in the aerospace community, where the growing maintenance costs can reduce the operational life of flight vehicles. The objective of a SHM system with an advanced diagnostic capability is to gradually replace current schedule-based maintenance tasks, where components are inspected following a pre-established number of cycles using condition-based maintenance, or are maintained prior to attaining an insufficient remaining useful life, based on specified confidence bounds. The research challenge is to obtain a reliable method for determining damage existence and respective location during its initial growth state as a component of an early warning system.

In this thesis, an SHM system based on Lamb waves is proposed. A damage detection algorithm based on the comparison between the damaged structural state and a reference state has been developed. The detection algorithm, based on discrete signals correlation, was tested and improved by incorporating statistical methods and domain division techniques. Two SHM system architectures, namely the sensor network and phased array system were designed, implemented and tested.

A visualization method based on the superposition of solutions obtained from a test set was implemented. Tests executed with multiple damage, representing surface and through-the-thickness holes and cracks were performed. The proposed SHM systems using Lamb waves were able to reliably detect holes of 1 mm holes in aluminum and 1.5 mm in composite plates with great confidence.