Crack monitoring on concrete structures with distributed fiber optic sensors—Toward automated data evaluation and assessment

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Abstract

The ability to measure strains quasi-continuously with high spatial resolution makes distributed fiber optic sensing a promising technology for structural health monitoring (SHM) as it allows to locate and measure damages in concrete structures, such as cracks. Depending on whether the distributed fiber optic sensor (DFOS) is embedded into the concrete matrix or bonded to the reinforcement, different approaches for crack width calculation exist. The high spatial resolution of DFOS quickly leads to a large amount of data, especially with time continuous monitoring. Scalable, automated analysis approaches are required to handle such big data and to derive a gain in knowledge from the measurements. Thus, in a first step, the Python framework fosanalysis is presented and made available to other researchers or monitoring specialists as free software. The most important input parameters for crack width calculation are discussed for concrete strain and steel strain DFOS. Accurate crack monitoring for a 4 m long reinforced concrete beam is demonstrated by using fosanalysis. The calculated crack widths are in good agreement with digital image correlation measurements.

Details

OriginalspracheEnglisch
Seiten (von - bis)1465-1480
Seitenumfang16
FachzeitschriftStructural Concrete
Jahrgang25
Ausgabenummer2
Frühes Online-Datum20 Nov. 2023
PublikationsstatusVeröffentlicht - Apr. 2024
Peer-Review-StatusJa

Externe IDs

ORCID /0000-0002-2187-1652/work/147142645
ORCID /0000-0001-8735-1345/work/147142867
ORCID /0000-0002-3833-8424/work/147143061
Scopus 85163965758

Schlagworte

Schlagwörter

  • crack monitoring, fiber optic sensing, automated data assessment, monitoring data, structural health monitoring, distributed fiber optic sensors, DFOS, crack monitoring, fiber optic sensing, automated data assessment, monitoring data, structural health monitoring, distributed fiber optic sensors, DFOS

Bibliotheksschlagworte