Linear and Geometrically Nonlinear Structural Shape Sensing from Strain Data

What is it about?

An aircraft’s shape must be measured during flight to implement active flexible motion controls under static conditions. A proposed method for linear as well as geometrically nonlinear structural shape sensing is validated using three sample examples. A large structural deformation of the first example is successfully captured using the proposed method with less than 0.3% prediction error. The candidate shapes' performances are compared using the second sample example. In most cases, the newly proposed candidate shape has a better correlation with the target deformation than the traditional candidate shape. Wing shape sensing with sparse strain data is also demonstrated in this study using the last example. Predicted deformations match reasonably with the target deformations even without sensors on some structural components. The predicted deformations have a good match with the target deformations.

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