Ultrasonic guided waves-based Structural Health Monitoring (SHM) is a promising solution to perform damage diagnosis in plate-like structures. In this field, the Reconstruction Algorithm for Probabilistic Inspection (RAPID) is one of the most widely used tomographic algorithms to perform active damage detection and localisation. Even though this algorithm is easily implementable, very versatile and satisfactorily accurate, it presents some disadvantages, such as the production of artefacts determined by non-uniform distributions of the sensing network density. In the present article, a processing and spatial filtering technique is proposed, which strongly mitigates the aforementioned problem. The proposed methodology is validated using a numerical database created for a large carbon fibre reinforced polymer (CFRP) with a through-the-thickness hole.
On the mitigation of the RAPID algorithm uneven sensing network issue employing averaging and Gaussian blur filtering techniques
GONZÁLEZ JIMÉNEZ Á.;Lomazzi L.;Cadini F.;Beligni A.;Sbarufatti C.;Giglio M.;Manes A.
2021-01-01
Abstract
Ultrasonic guided waves-based Structural Health Monitoring (SHM) is a promising solution to perform damage diagnosis in plate-like structures. In this field, the Reconstruction Algorithm for Probabilistic Inspection (RAPID) is one of the most widely used tomographic algorithms to perform active damage detection and localisation. Even though this algorithm is easily implementable, very versatile and satisfactorily accurate, it presents some disadvantages, such as the production of artefacts determined by non-uniform distributions of the sensing network density. In the present article, a processing and spatial filtering technique is proposed, which strongly mitigates the aforementioned problem. The proposed methodology is validated using a numerical database created for a large carbon fibre reinforced polymer (CFRP) with a through-the-thickness hole.File | Dimensione | Formato | |
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