A novel Augmented Reality (AR) tool for structural health monitoring is illustrated in this work. It provides maintenance operators with the results of an impact detection methodology. It interacts with an eyepiece allowing the inspector to see the estimated impact position on the structure. Electric signals are collected by a network of piezosensors bonded on the structure to be monitored. Dispersive propagation compensation is performed to improve estimation robustness. Hyperbolic beamforming is exploited to locate the impact. Real-time impact data are finally fed to the AR eyepiece. The proposed approach is tested on a Cessna 150 engine cowling. Experimental results confirm the feasibility of the method and its exploitability in maintenance practice.

De Marchi, L., Ceruti, A., Testoni, N., Marzani, A., Liverani, A. (2016). Augmented reality tools for structural health monitoring applications. Springer Verlag [10.1007/978-3-319-20227-3_15].

Augmented reality tools for structural health monitoring applications

DE MARCHI, LUCA;CERUTI, ALESSANDRO;TESTONI, NICOLA;MARZANI, ALESSANDRO;LIVERANI, ALFREDO
2016

Abstract

A novel Augmented Reality (AR) tool for structural health monitoring is illustrated in this work. It provides maintenance operators with the results of an impact detection methodology. It interacts with an eyepiece allowing the inspector to see the estimated impact position on the structure. Electric signals are collected by a network of piezosensors bonded on the structure to be monitored. Dispersive propagation compensation is performed to improve estimation robustness. Hyperbolic beamforming is exploited to locate the impact. Real-time impact data are finally fed to the AR eyepiece. The proposed approach is tested on a Cessna 150 engine cowling. Experimental results confirm the feasibility of the method and its exploitability in maintenance practice.
2016
Lecture Notes in Electrical Engineering
115
121
De Marchi, L., Ceruti, A., Testoni, N., Marzani, A., Liverani, A. (2016). Augmented reality tools for structural health monitoring applications. Springer Verlag [10.1007/978-3-319-20227-3_15].
De Marchi, L.; Ceruti, A.; Testoni, N.; Marzani, A.; Liverani, A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/539442
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