Structural health monitoring (SHM) based on guided waves allows assessing the health of a structure due to the sensitivity to the occurrence of delamination. However, wave propagation presents several complexities for effective damage identification in composite structures. An efficient implementation of a guided wave-based SHM system requires an accurate analysis of collected data to obtain a useful detection. This paper is concerned with the identification of small emerging delaminations in composite structural components using a sparse array of surface ultrasonic transducers. An ultrasonic-guided wave tomography technique focused on impact damage detection in composite plate-like structures is presented. A statistical damage index approach is adopted to interpret the recorded signals, and a subsequent graphic interpolation is implemented to reconstruct the damage appearance. Experimental tests carried out on a typical composite structure demonstrated the effectiveness of the developed technique with the aim to investigate the presence and location of damage using simple imaging reports and a limited number of measurements. A traditional ultrasonic inspection (C-scan) is used to assess the methodology.

Aerospace vehicles are demanded to withstand harsh conditions with a low weight impact. Composites have been increasingly adopted to meet such performances but they are affected by sudden and barely visible failures when subjected to low velocity impacts. The design criteria and the maintenance tasks in a damage tolerant approach are unavoidably compromised. Structural Health Monitoring is expected to avoid typical accommodations employed during design and lifetime management by achieving a cost-effective and on condition maintenance. This paper describes the use of guided ultrasonic waves excited and sensed by permanently attached piezoelectric transducers for detection and localization of unforeseen and hidden flaws in composite structures. A composite stiffened structures designed for real scale components is investigated to test a multi-parameter detection technique capable of predicting different wave features affected by hidden failures to detect any possible change in the structure. Usually, propagation behavior is exploited to detect changes in the waveguide focusing on the analysis of an intrinsic feature of the propagating wave. Numerical simulations and measurements carried out on a real-scale aircraft structure demonstrate that increasing the observed characteristics improves the result making efficient the diagnosis. Furthermore, it is shown that accounting a multi-parameter analysis of ultrasonic data enhances the localization reliability making use of the same reconstruction algorithm with data fusion approach while facing with different kind of damages.