The detection of internal defects in composite materials, due to anomalies during the production processes, is a big issue especially for the production of large structures in aeronautic contexts. The costs of the repair processes can weigh upon the total costs, and sometimes the repair itself can be unfeasible and cause the material to be rejected. The early detection of anomalies during the production phase can interrupt the production chain and the solution to the detected problems can be soon found. In this paper we propose the use of an appropriate sensorial setup to monitor the production line and of some signal processing method- ologies to detect anomalies in the stratication of composite materials. Gaps and overlaps between adjacent stripes that are beyond or below the allowed ranges are soon detected and automatically highlighted to the human operators.
Disparity Image Analysis for 3D Characterization of Surface Anomalies
R Marani;A Petitti;G Cicirelli;A Milella;T D'Orazio
2019
Abstract
The detection of internal defects in composite materials, due to anomalies during the production processes, is a big issue especially for the production of large structures in aeronautic contexts. The costs of the repair processes can weigh upon the total costs, and sometimes the repair itself can be unfeasible and cause the material to be rejected. The early detection of anomalies during the production phase can interrupt the production chain and the solution to the detected problems can be soon found. In this paper we propose the use of an appropriate sensorial setup to monitor the production line and of some signal processing method- ologies to detect anomalies in the stratication of composite materials. Gaps and overlaps between adjacent stripes that are beyond or below the allowed ranges are soon detected and automatically highlighted to the human operators.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.