Structural Health Monitoring in Composites Based on Probabilistic Reconstruction Techniques

Structural Health Monitoring (SHM) based on guided waves (GWs) is responsive to damage occurrences allowing the assessment of composites integrity. However, online monitoring is quite complex due to a wide range of parameters affecting wave propagation and consequently diagnostic outputs. A useful implementation of a GW-based condition monitoring requires an accurate analysis of reconstruction algorithm and collected data as well. In view of a more effective detection of impact induced damages in composites using a sparse array of sensors, several methods are explored in this paper as a first step towards a comprehensive capability assessment of a system permanently installed on aircraft structures. Various probabilistic reconstruction methods and signal transformation techniques are developed and used to detect hidden flaws with a multiple analysis. From a wide number of simulation carried out it appears that, although a single procedure for the estimation of the structural health is a fast solution for flaw detection, a multiple analysis based on different reconstruction techniques and/or several damage parameters could provide more detailed information about the location and the severity of possible failures if the parameters affecting diagnostics are completely addressed.