Sensor Fusion for Shape Sensing: Theory and Numerical Results

Cornelis de Mooij, Marcias Martinez

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Shape sensing utilizing an inverse finite element method (iFEM) was considered for obtaining the displacement fields of two cantilever beams. Traditional iFEM techniques make use of only a single type of sensor, which can lead to errors in the strain and/or displacement distributions. This study has reduced these errors by combining data from multiple sensor types. A new iFEM algorithm was developed in order to minimize the error on computed strain profiles. The new iFEM algorithm incorporates Tikhonov smoothing in addition to compensating for the lack of sensors in areas of the structure where no sensors are present. The new iFEM algorithm was demonstrated for cantilever plates under various load cases. The preliminary results showed that the new iFEM algorithm is able to determine the structural deformations of two cantilever plates with greater accuracy than a traditional iFEM implementation that was found in the literature, using fewer sensors.
Original languageEnglish
Title of host publication27th International Conference on Adaptive Structures and Technologies
Subtitle of host publicationLake George, USA
Number of pages13
Publication statusPublished - 2016
Event27th International Conference on Adaptive Structures and Technologies - The Sagamore Resort, Lake George, United States
Duration: 3 Oct 20165 Oct 2016
Conference number: 27
http://www.icast2016.com/

Conference

Conference27th International Conference on Adaptive Structures and Technologies
Abbreviated titleICAST2016
CountryUnited States
CityLake George
Period3/10/165/10/16
Internet address

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