Shape Sensing of Stiffened Plates Using Inverse FEM Aided by Virtual Strain Measurements

The inverse problem of structural deformation reconstruction using experimentally measured strains, known as ‘shape sensing’, is a topic with numerous applications in the field of Structural Health Monitoring (SHM). Existing shape sensing methods are influenced by the number and location of in-situ strain sensors used. A dense strain-sensor array can produce accurate displacement predictions, whereas a sparse strain-sensor distribution leads to inaccurate predictions and possibly a breakdown of the method. In the latter cases, introducing virtual strain sensors can provide additional input strain data for the shape sensing method. This paper provides experimental validation of this coupled shape-sensing approach, using real and virtual strain data, for the displacement reconstruction of a stiffened aluminium plate instrumented with fibre optic sensors. The inverse Finite Element Method (iFEM) is the shape sensing technique employed, and two strategies are compared for producing virtual strain data: the Smoothing Element Analysis (SEA), and modal expansion. The experimental results presented demonstrate the effectiveness of the two strategies investigated.