title: Model-based imaging of damage with Lamb waves via sparse reconstruction.
abstract: 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.
authors: School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0250, USA.
authors: Ross M
authors: RM
authors: Levine
authors: Jennifer E
authors: JE
authors: Michaels
mesh_terms: D000465:Algorithms; D000535:Aluminum; D003198:Computer Simulation; D003252:Construction Materials; D004867:Equipment Design; D008422:Materials Testing; D008962:Models, Theoretical; D009038:Motion; D009716:Numerical Analysis, Computer-Assisted; D012542:Scattering, Radiation; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D013016:Sound; D014159:Transducers; D014465:Ultrasonics / Q000295:instrumentation
chemical_list: D000535:Aluminum