Shape sensing and damage identification with iFEM on a composite structure subjected to impact damage and non-trivial boundary conditions

The inverse Finite Element Method (iFEM) has recently demonstrated to be a valuable tool, not only for shape sensing, but also for damage identification in a Structural Health Monitoring framework. The algorithm computes the displacement field, and consequently the strain field, based on discrete input strain measures in the structure without any a priori knowledge of the material properties or the loading condition. In particular, the reconstruction is obtained by a least-squares minimization of an error functional defined by comparing the experimental strain measures with their numerical formulation, function of the displacements. Even though the formulation of the method is general for any arbitrary geometry and constraints, the definition of the correct boundary conditions is not trivial for structures subjected to non-ideal constraints. Thus, the work proposes a superimposition of the effects approach to weight the contribution of different basic models to simulate the real behavior of the structure. Once the component displacement and strain fields are correctly reconstructed, the structural assessment is performed by means of a load-independent anomaly index based on the comparison of the numerical strain reconstructions and their experimental counterparts. The discrepancies with respect to a load-independent baseline are highlighted by a Mahalanobis distance index. The procedure is experimentally verified on a CFRP reinforced panel subjected to impact damage and a compressive fatigue test. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

The inverse Finite Element Method (iFEM) is a valuable tool for shape sensing and damage identification in structural health monitoring frameworks. This method calculates displacement fields and strain fields based on discrete strain measurements in the structure without prior knowledge of material properties or loading conditions.