Abstract
Fiber optic shape sensing is a promising technology capable of enriching the field of Structural Health Monitoring (SHM), with many potential applications that expand the uses of distributed optical fiber sensors. The operational principle is based on the simultaneous strain acquisition from several optical fiber cores deployed in a single sensing cable (or multicore fiber). The parallel strain traces of these cores can be combined to extract curvature and torsion distributions along the sensing cable, that can be used for the three-dimensional reconstruction of the underlying shape. This study evaluates the reliability of fiber optic shape sensing for damage detection through the use of a model-assisted probability of detection framework specifically developed to simulate a carbon fiber-reinforced polymers specimen under quasi-static loading monitored by distributed optical fiber sensors based on Rayleigh backscattering. Specifically, we compare the performance of a traditional distributed optical fiber strain sensor with the one of a hypothetical distributed shape sensing cable (or multicore fiber). To perform this comparison, we redefine the damage index definition, which is usually based on the measured strain values, to make it compatible with shape sensing, where it can be defined in terms of curvature and torsion. With these preliminary results, we aim to evaluate whether shape sensing technology can be employed for damage detection to detect damage-related deformation, whether we can obtain better results compared to traditional optical fiber sensor applications, and discuss how damage metrics need to be modified. In future activities, these aspects will be further investigated taking into account other case studies and shape sensing configurations.
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
