Comparison between 3D-reconstruction optical methods applied to bulge-tests through a feed-forward neural network


  • Damiano Alizzio Messina University
  • Marco Bonfanti Catania University
  • Guido Garozzo Zerodivision Systems S.r.l., Pisa (Italy)
  • Fabio Lo Savio Catania University
  • Roberto Montanini Messina University
  • Antonino Quattrocchi Messina University



The mechanical behaviour of rubber-like materials can be investigated through numerous techniques that differ from each other in costs, execution times and parameters described. Bulge test method proved helpful for hyperelastic membranes under plane and equibiaxial stress state. In the present study, bulge tests in force control were carried out on SBR 20% CB-filled specimens. 3D reconstructions of the dome were achieved through two different stereoscopic techniques, the epipolar geometry and the Digital Image Correlation. Through a Feed-Forward Neural Network (FFNN), these reconstructions were compared with the measurements by a laser triangulation sensor taken as reference. 3D-DIC reconstruction was found to be more accurate. Indeed, bias errors of the 3D-DIC and epipolar techniques with respect to the relative reference values, under creep condition, were 0.53 mm and 0.87 mm, respectively.

Author Biographies

Damiano Alizzio, Messina University


Department of Engineering 

Marco Bonfanti, Catania University


Department of Electric, Electronic, Informatics Engineering (DIEEI)

Fabio Lo Savio, Catania University

Assistant Professor;

Department of Civil Engineering and Architecture (DICAr)

Roberto Montanini, Messina University

Full Professor;

Department of Engineering

Antonino Quattrocchi, Messina University


Department of Engineering






Research Papers