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Graphene sensing meshes for densely distributed strain field monitoring

Auteur(s):





Médium: article de revue
Langue(s): anglais
Publié dans: Structural Health Monitoring, , n. 5, v. 19
Page(s): 1323-1339
DOI: 10.1177/1475921719877418
Abstrait:

The objective of this study is to design and validate distributed strain field monitoring using a patterned nanocomposite “sensing mesh” that is coupled with an electrical impedance tomography (EIT) measurement strategy and algorithm. Although EIT has been used in other studies and in conjunction with a piezoresistive thin film for spatial damage detection, different strain components cannot be directly extracted from reconstructed EIT conductivity maps. Therefore, this study seeks to address this issue by patterning piezoresistive graphene-based thin films to form a mesh-like pattern. The high aspect ratio of each nanocomposite grid interconnect acts as a linear distributed strain sensor, capable of resolving strains along the entire length and direction of the element. This study first began with the design, fabrication, and characterization of the strain sensing response of a graphene-based thin film of high strain sensitivity. Second, the strain-sensitive film was spray-coated onto patterned polymer substrates to form the sensing meshes, which were then subjected to load tests. Upon validating distributed strain field monitoring through EIT, its applicability for field implementation and damage characterization was also demonstrated by instrumenting sensing meshes in the column of a seven-story reinforced-concrete building subjected to shaking table earthquake excitations. The large-scale shaking table test results successfully validated distributed damage detection.

Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.1177/1475921719877418.
  • Informations
    sur cette fiche
  • Reference-ID
    10562358
  • Publié(e) le:
    11.02.2021
  • Modifié(e) le:
    19.02.2021
 
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