Compressive Sensing and Imaging of Guided Ultrasonic Wavefields

Keshmiri Esfandabadi, Yasamin (2020) Compressive Sensing and Imaging of Guided Ultrasonic Wavefields, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Ingegneria elettronica, telecomunicazioni e tecnologie dell'informazione, 32 Ciclo.
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Abstract

Structural health monitoring (SHM) and Nondestructive Evaluation (NDE) technologies can be used to predict the structural remaining useful life through appropriate diagnosis and prognosis methodologies. The main goal is the detection and characterization of defects that may compromise the integrity and the operability of a structure. The use of Lamb waves, which are ultrasonic guided waves (GW), have shown potential for detecting damage in specimens as a part of SHM or NDT systems. These methods can play a significant role in monitoring and tracking the integrity of structures by estimating the presence, location, severity, and type of damage. One of the advantages of GW is their capacity to propagate over large areas with excellent sensitivity to a variety of damage types while guaranteeing a short wavelength, such that the detectability of large structural damages is guaranteed. The Guided ultrasonic wavefield imaging (GWI) is an advanced technique for Damage localization and identification on a structure. GWI is generally referred to as the analysis of a series of images representing the time evolution of propagating waves and, possibly, their interaction with defects. This technique can provide useful insights into the structural conditions. Nowadays, high-resolution wavefield imaging has been widely studied and applied in damage identification. However, full wavefield imaging techniques have some limitations, including slow data acquisition and lack of accuracy. The objectives of this dissertation are to develop novel and high resolution Guided Wavefield Imaging techniques able to detect defects in metals and composite materials while reducing the acquisition time without losing in detection accuracy.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Keshmiri Esfandabadi, Yasamin
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
32
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Compressive sensing, Super-resolution, Wavefield imaging, Non-destructive testing, Structural health monitoring
URN:NBN
Data di discussione
16 Marzo 2020
URI

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