Beam structures are widely used in modern engineering applications and must guarantee high standards of reliability. Monitoring their condition in real time allows maintenance operations to be optimized, ensuring safety and operational continuity. In this context, Structural Health Monitoring (SHM) systems provide continuous information on the be- havior of structures in operation. Among the shape sensing techniques used in SHM, the inverse finite element method (iFEM) allows the reconstruction of the displacement field from strain measurements. Collected through a network of sensors, these measurements are combined with the geometry of the structure and the boundary conditions for the correct application of the method, which does not require knowledge of external loads or material properties. The objective of this thesis is to implement iFEM in order to validate the real time reconstruction of the displacement field on a scaled beam-bridge model, instrumented with an FBG-based sensor network and subjected to static and dy- namic loads. For this purpose, a framework was developed in MATLAB that performs data acquisition, pre-processing, numerical processing, and visual rendering of the recon- struction. The results confirm the accuracy of the iFEM framework in reconstructing the deformed shape in real time, ensuring long-term stability. The approach has proven to be highly effective in both spatial and temporal accuracy, with a maximum deviation of 8% with respect to laser reference values. The development and testing of the framework on a dedicated laboratory model allows this work to contribute to demonstrating the feasibility of using iFEM for real-time SHM on real structures.
Le strutture di tipo trave sono ampiamente utilizzate nelle moderne applicazioni ingegner- istiche e devono garantire elevati standard di affidabilità. Monitorare in tempo reale le loro condizioni permette di ottimizzare le operazioni di manutenzione, garantendo sicurezza e continuità operativa. In questo contesto i sistemi di Structural Health Monitoring (SHM) forniscono informazioni continue sul comportamento delle strutture in esercizio. Tra le tecniche di rilevamento della forma utilizzate nell’SHM, il Metodo ad Elementi Finiti in- verso (iFEM) consente la ricostruzione del campo di spostamento a partire da misure di deformazione. Raccolte attraverso una rete di sensori, queste misurazioni vengono combi- nate insieme alla geometria della struttura e alle condizioni al contorno per una corretta applicazione del metodo che non necessita di conoscere i carichi esterni o le proprietà dei materiali. L’obbiettivo di questa tesi è implementare l’iFEM al fine di convalidare la ricostruzione in tempo reale del campo di spostamento su un modello in scala di un ponte a travi, strumentato con una rete di sensori basata su FBG e sottoposto a carichi statici e dinamici. Per questo scopo è stato sviluppato un framework in ambiente MATLAB che compie operazioni di acquisizione dati, pre processamento, elaborazione numerica e resa visiva della ricostruzione. I risultati confermano l’accuratezza del framework iFEM nel ri- costruire la deformata in tempo reale, garantendo stabilità nel lungo periodo. L’approccio ha dimostrato un’ottima efficacia sia in termini di precisione spaziale che temporale, con una deviazione massima dell’8% rispetto ai valori di riferimento laser. Lo sviluppo e il collaudo del framework su un modello di laboratorio dedicato, permettono a questo la- voro di contribuire nel dimostrare la fattibilità dell’uso dell’iFEM per applicazioni SHM in tempo reale su strutture reali.
Development and experimental validation of a real-time inverse finite element framework for shape sensing
OGGIONNI, STEFANO
2024/2025
Abstract
Beam structures are widely used in modern engineering applications and must guarantee high standards of reliability. Monitoring their condition in real time allows maintenance operations to be optimized, ensuring safety and operational continuity. In this context, Structural Health Monitoring (SHM) systems provide continuous information on the be- havior of structures in operation. Among the shape sensing techniques used in SHM, the inverse finite element method (iFEM) allows the reconstruction of the displacement field from strain measurements. Collected through a network of sensors, these measurements are combined with the geometry of the structure and the boundary conditions for the correct application of the method, which does not require knowledge of external loads or material properties. The objective of this thesis is to implement iFEM in order to validate the real time reconstruction of the displacement field on a scaled beam-bridge model, instrumented with an FBG-based sensor network and subjected to static and dy- namic loads. For this purpose, a framework was developed in MATLAB that performs data acquisition, pre-processing, numerical processing, and visual rendering of the recon- struction. The results confirm the accuracy of the iFEM framework in reconstructing the deformed shape in real time, ensuring long-term stability. The approach has proven to be highly effective in both spatial and temporal accuracy, with a maximum deviation of 8% with respect to laser reference values. The development and testing of the framework on a dedicated laboratory model allows this work to contribute to demonstrating the feasibility of using iFEM for real-time SHM on real structures.| File | Dimensione | Formato | |
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2025_12_Oggionni_Executive Summary.pdf
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2025_12_Oggionni_Thesis.pdf
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Descrizione: Thesis text
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https://hdl.handle.net/10589/247207