2010
DOI: 10.1088/0964-1726/19/3/035011
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Structural shape reconstruction with consideration of the reliability of distributed strain data from a Brillouin-scattering-based optical fiber sensor

Abstract: In this paper, we constructed a shape reconstruction algorithm using a finite element (FE) model of the target structure, taking advantage of characteristics of the distributed strain data, which was acquired from a Brillouin-scattering-based optical fiber sensor. The remarkable point is that, using not only raw strain data but also information of the non-uniformity of strain distribution profiles, the algorithm appropriately considers the data reliability for accurate shape reconstructions. The constructed al… Show more

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Cited by 37 publications
(23 citation statements)
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References 13 publications
(22 reference statements)
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“…The problem of real-time reconstruction of deflection shapes from position and curvature measurements from sensor networks has been widely studied, with applications to condition assessment, SHM, and shape control [28], [29], [30], [31]. Here, we select the polynomial interpolation method for reconstructing the deflection shapes from a network of curvature data, a technique also used to smoothen data.…”
Section: Sec Signal-strain Modelmentioning
confidence: 99%
“…The problem of real-time reconstruction of deflection shapes from position and curvature measurements from sensor networks has been widely studied, with applications to condition assessment, SHM, and shape control [28], [29], [30], [31]. Here, we select the polynomial interpolation method for reconstructing the deflection shapes from a network of curvature data, a technique also used to smoothen data.…”
Section: Sec Signal-strain Modelmentioning
confidence: 99%
“…Our research group constructed a shape reconstruction algorithm using a finite element (FE) model of the target structure, taking advantage of characteristics of the distributed strain data obtained by PPP-BOTDA [36,37]. The remarkable point is that, using not only raw strain data but also information of the non-uniformity of strain distribution profiles, the algorithm appropriately considers the data reliability for accurate shape reconstruction.…”
Section: Full-field Shape Reconstruction Using Distributed Strain Datamentioning
confidence: 99%
“…Note that the use of fiber sensors in the field of SHM is essential to detect fractures, deformations or disbonding of CFRP structures, being temperature a parameter of lower relevance. Unfortunately, most of fiber sensors suitable for SHM [21][22][23] are sensitive to both temperature and strain, leading in many cases to an unwanted cross-sensitivity between these two physical variables [24,25]. This is especially critical in environments with changeable temperature conditions (e.g.…”
Section: Introductionmentioning
confidence: 99%