Wing Dynamic Shape-Sensing From Fiber-Optic Strain Data Using the Kalman State Estimator

Tsoof Joels, Daniella E. Raveh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel method for shape sensing based on strain data and the use of the Kalman state estimator is presented and studied experimentally. Several recent studies proposed different methods in which strain data, measured in optical fibers, can be used to estimate the deformed shape of a flexible wing. Fiber optic sensors typically provide accurate, high resolution, strain data, yielding detailed prediction of a wing’s deformed shape. However, in real lift applications there could be moments in which the strain data is imperfect (for example, due to saturation), or altogether missing. The current study proposed to use a Kalman state estimator that weighs in strain-data and simulation output of an aeroelastic plant model to estimate the wing deformations. The method is demonstrated with a flexible wing model that is excited by prescribed control surfaces deflection in a wind-tunnel test. Strains over the front and rear wing spars are measured by Fiber Bragg Grating sensors, embedded in two optical fibers, and used to estimate the wing deformations. The latter are compared to wing deformations measured by a motion recovery camera system. Results show the advantageous of the use of the Kalman state estimator when the strain data is corrupted. Additionally, with this approach, wing’s modal velocities are estimated together with the wing deformations, resulting in smooth and accurate modal velocities that are readily usable by the vehicle’s control system.

Original languageEnglish
Title of host publicationAIAA SciTech Forum 2022
DOIs
StatePublished - 2022
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022 - San Diego, United States
Duration: 3 Jan 20227 Jan 2022

Publication series

NameAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022

Conference

ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
Country/TerritoryUnited States
CitySan Diego
Period3/01/227/01/22

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

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