RESUMO
A frequently investigated paradigm for monitoring the integrity of plate-like structures is a spatially-distributed array of piezoelectric transducers, with each array element capable of both transmitting and receiving ultrasonic guided waves. This configuration is relatively inexpensive and allows interrogation of defects from multiple directions over a relatively large area. Typically, full sets of pairwise transducer signals are acquired by exciting one transducer at a time in a round-robin fashion. Many algorithms that operate on such data use differential signals that are created by subtracting prerecorded baseline signals, leaving only signal differences introduced by scatterers. Analysis methods such as delay-and-sum imaging operate on these signals to detect and locate point-like defects, but such algorithms have limited performance and suffer when potential scatterers have high directionality or unknown phase-shifting behavior. Signal envelopes are commonly used to mitigate the effects of unknown phase shifts, but this further reduces performance. The blocksparse technique presented here uses a different principle to locate damage: each pixel is assumed to have a corresponding multidimensional linear scattering model, allowing any possible amplitude and phase shift for each transducer pair should a scatterer be present. By assuming that the differential signals are linear combinations of a sparse subset of these models, it is possible to split such signals into location-based components. Results are presented here for three experiments using aluminum and composite plates, each with a different type of scatterer. The scatterers in these images have smaller spot sizes than delay-and-sum imaging, and the images themselves have fewer artifacts. Although a propagation model is required, block-sparse imaging performs well even with a small number of transducers or without access to dispersion curves.
RESUMO
Ultrasonic guided waves are gaining acceptance for structural health monitoring and nondestructive evaluation of plate-like structures. One configuration of interest is a spatially distributed array of fixed piezoelectric devices. Typical operation consists of recording signals from all transmit-receive pairs and subtracting pre-recorded baselines to detect changes, possibly due to damage or other effects. While techniques such as delay-and-sum imaging as applied to differential signals are both simple and capable of detecting flaws, their performance is limited, particularly when there are multiple damage sites. Here a very different approach to imaging is considered that exploits the expected sparsity of structural damage; i.e., the structure is mostly damage-free. Differential signals are decomposed into a sparse linear combination of location-based components, which are pre-computed from a simple propagation model. The sparse reconstruction techniques of basis pursuit denoising and orthogonal matching pursuit are applied to achieve this decomposition, and a hybrid reconstruction method is also proposed and evaluated. Noisy simulated data and experimental data recorded on an aluminum plate with artificial damage are considered. Results demonstrate the efficacy of all three methods by producing very sparse indications of damage at the correct locations even in the presence of model mismatch and significant noise.
