An algorithm for structural health monitoring by digital image correlation: Proof of concept and case study

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 reduces to a simple scalar product between the image and the corresponding extractor, which allows for very fast and non-iterative processing. As an illustration, this methodology is deployed on a test case of fatigue crack propagation.

Automated summary

This paper presents the advantages of using Digital Image Correlation (DIC) in the field of structural health monitoring and proposes a specific DIC technique. By training, a reduced kinematic basis and amplitude distribution can be determined, and non-iterative processing is achieved using filtering and extractors.