A curvature based approach in dynamic monitoring using long-gage fiber optic sensors

Kaitlyn Kliewer, Branko Glisic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Drawing upon the numerous advantages of fiber Bragg grating (FBG) strain sensors, this research explores the ways to use a series of long-gage fiber optic sensors for structural analysis and damage detection through dynamic strain measurements and curvature analysis. Dynamic structural monitoring provides useful insight into the state of a structure because any changes or damage to the physical property of a structure will result in a change of the dynamic response of the structure. Typically dynamic structural monitoring relies upon detecting structural anomalies through frequency and acceleration based analysis. However, curvature and strain based analysis may be a more reliable means for structural monitoring as they show more sensitivity to damage compared to modal parameters such as displacement mode shapes and natural frequency. Additionally, long gage FBG strain sensors offer a promising alternative to traditional dynamic measurement methods as the curvature can be computed directly from the FBG strain measurements without the need for numerical differentiation. Small scale experimental testing was performed using an aluminum beam instrumented with a series of FBG optical fiber sensors. Dynamic strain measurements were obtained as the beam was subjected to various support and loading conditions as well as subjecting the beam to several simulated damage conditions. From the dynamic strain measurements, the curvature of the aluminum beam can be determined. From these, a normalized parameter based on the strain and curvature from the dynamic strain measurements has been developed as potential means of damage detection. Both a theoretical analysis and experimental data were compared and carried out. The method provided both detection of damage and an indication of damage intensity. The results demonstrated the potential of FBG long-gage sensors to facilitate dynamic monitoring at both the local and global scale, thus allowing assessment of the structures health.

Original languageEnglish (US)
Title of host publication8th European Workshop on Structural Health Monitoring, EWSHM 2016
Number of pages9
ISBN (Electronic)9781510827936
StatePublished - Jan 1 2016
Event8th European Workshop on Structural Health Monitoring, EWSHM 2016 - Bilbao, Spain
Duration: Jul 5 2016Jul 8 2016


Other8th European Workshop on Structural Health Monitoring, EWSHM 2016

All Science Journal Classification (ASJC) codes

  • Health Information Management
  • Computer Science Applications


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