An algorithm for Structural Health Monitoring by Digital Image Correlation: Proof of concept and case study

Jordan Curt (1, 2) , Matteo Capaldo (1) , François Hild (2) , Stéphane Roux (2)

1 EDF R&D - EDF R&D
2 LMPS - Laboratoire de Mécanique Paris-Saclay

In the field of structural health monitoring, the use of Digital Image Correlation (DIC) on relevant surfaces offers remarkable advantages. Such a method is presented herein. The statistically stationary nature of usual loads makes it possible to determine, by training with DIC, a reduced kinematic basis (composed of "modes") and a statistical amplitude distribution for each mode. Further, a specific DIC technique is proposed to deal with such particular kinematics by introducing an extractor per mode that operates on images after a filtering step. This per-mode DIC measurement is reduced to a simple scalar product between the image and the corresponding extractor, which allows for very fast and noniterative processing. As an illustration, this methodology is deployed on a test case of fatigue crack propagation.

Domaines: Matériaux et structures en mécanique [physics.class-ph]; Traitement des images [eess.IV]

Jordan Curt, Matteo Capaldo, François Hild, Stéphane Roux. An algorithm for Structural Health Monitoring by Digital Image Correlation: Proof of concept and case study. Optics and Lasers in Engineering, 2022, 151, pp.106842. ⟨10.1016/j.optlaseng.2021.106842⟩. ⟨hal-03490633⟩