Strain measurement consistency of distributed fiber optic sensors for monitoring composite structures under various loading

Abstract

This research presents a comprehensive investigation into the measurement consistency of distributed fiber optic sensing in composite structures under diverse test scenarios. The study encompasses fifty-six independent experiments, categorized into six groups, comprising tensile, fatigue, three-point bending, and three sets of temperature experiments. The strain-frequency shift coefficient and temperature-frequency shift coefficient of distributed fiber optic sensing based on Optical Frequency Domain Reflectometry in different test scenarios are visually represented using Cumming plots, and their normality is rigorously assessed utilizing the Kolmogorov-Smirnov test. Furthermore, the coefficients’ consistency is evaluated through Cronbach's alpha, McDonald's omega, and Split-half reliability, predicated on the confirmed normal distribution conclusion. The results demonstrate that the strain-frequency shift coefficient consistently remains around -6.4 //e/GHz across diverse tests, while being subject to ambient temperature variations. The temperature-frequency shift coefficient is notably influenced by the coating material and installation state of single mode fiber sensors, with recorded values of -1.55°C / GHz (acrylate coating, free state), -1.04°C / GHz (acrylate coating, surface mounted), and -1.28°C /GHz (polymer coating, free state), respectively. Remarkably, both strain-frequency shift coefficient and temperature-frequency shift coefficient exhibit high consistency across the entire range of test scenarios. In addition, the standard uncertainty (type A) of frequency shift measurements across the fifty-six independent test scenarios consistently remains below 0.1 GHz, affirming the robustness and reliability of distributed fiber optic sensing for strain and temperature data acquisition in composite structures. These findings underscore the capability of distributed fiber optic sensing in accurately characterizing composite materials under varying environmental conditions and loading.