Optically active nanoparticles-embedded optical fiber for random fiber laser distributed sensor
This paper presents the development of a multifunctional photonic device using nanoparticle (NP)-doped fiber as an optical amplification medium and distributed sensing element simultaneously. The proposed system comprises a linear cavity Random Fiber Laser (RFL) in which the NP-doped fiber is used as an amplification medium due to the erbium ions in the NP composition and a distributed cavity due to the enhanced Rayleigh scattering of the fiber. In this case, the RFL is employed as a distributed sensor by means of localized changes on the optical transmission and reflection signals when temperature and strain are applied along the NP-doped fiber. The proposed RFL is analyzed in terms of stability and configurations. In this case, the RFL demonstrated a maximum output power of around 17 mW with a power stability demonstrated by 0.07 nm variations in wavelength stability tests. The RFL distributed sensor validation, and the sensor system was submitted to simultaneous variation of temperature, strain, and location of the mechanical disturbance, where the Random Forest machine learning method was employed for the simultaneous assessment of all three parameters. The results show high accuracy of the sensor system, where relative errors of 0.02%, 2.0%, and 5.3% were found for temperature, strain, and location of strain application along the laser cavity, respectively. Therefore, the proposed RFL distributed sensor is a feasible solution for dynamic monitoring of different physical parameters, which can close the gap between the distributed optical fiber sensors and applications that require lower cost and high portability.
AI-empowered, low-cost and portable optical fiber sensor system for distributed monitoring and shape reconstruction in UAV structures
This paper presents the development and application of a low-cost distributed optical fiber sensor for the continuous monitoring of force and shape in Unmanned Aerial Vehicles (UAVs) wings. The sensor system includes nanoparticle-doped optical fibers with enhanced backscattering, which lead to higher sensitivity and spatial resolution in transmission–reflection analysis (TRA) systems. The acquired optical signals are
fed into a neural network that provides the force distribution along the wing surface area. The results indicated the feasibility of the proposed system in which the RMSEs of 0.46 N, 13.1 mm and 5.2 mm were found for the estimation of force amplitude, location in x-axis and y-axis, respectively. Then, the distributed displacement sensing for wing shape reconstruction is evaluated and demonstrated a high accuracy in the 3D
shape reconstruction with relative errors as small as 0.21%. Thus, the proposed system is a solution with the combination of low-cost, high resolution and high accuracy for the first time in aircraft monitoring distributed systems. Therefore, the proposed AI-enabled sensor system provides a low-cost distributed optical fiber sensor that can be directly integrated into the control unit of UAV due to the simplicity of the signal acquisition process.
Nanoparticle-doped fibers combined with machine learning methods for 3-dimensional shape reconstruction systems
The development of nanoparticle (NP) doped optical fibers provides new possibilities in distributed sensing and provides important advantages in spatially distributed system due to the tailoring of the backscattering signal, which enables the development of new approaches in shape reconstruction systems. For this reason, this paper presents the application of a distributed sensor system based on optical frequency domain reflectometry (OFDR) using the NP-doped optical fiber as the sensing medium in which there is an increase in sensitivity and spatial resolution due to the increase in backscaterred signal. The fiber is embedded in a rubber strip to increase the measurement range and the sensor robustness due to the nitrile rubber flexibility, since the rubber can provide strain transfer to the optical fiber, leading to higher strain limits, which can withstand the complex 3D loadings for the shape reconstruction. The sensor system is tested under different mechanical loadings conditions and the contribution of this work is a readily available sensing system using specialty optical fiber with high spatial resolution for 3D shape sensing approaches. The results indicate the feasibility of the proposed approach for shape sensing monitoring through a determination coefficient (R2) higher than 0.99 for all cases. In addition, the strain distribution along the fiber was also estimated for all loading conditions as well as the combination of them with an RMSE of around 1 mm considering the amplitude estimation of all loadings. The 3D shape reconstruction resulted in a mean error of around 2.0% considering all 3 axes of the cartesian plane. Therefore, the proposed sensor system is a feasible option for shape sensing with sub-centimeter spatial resolution and high accuracy using the NP-doped optical fiber as enhanced backscattered medium.
Distributed sensing with nanoparticle-doped fibers in standard OTDR systems: Validation and performance analysis
This paper presents the implementation of enhanced backscattering optical fibers in optical time-domain reflectometry (OTDR). The increase in the backscattering is achieved by doping the fiber core with nanoparticles, resulting in the so-called nanoparticle-doped optical fibers (NPFs). The so-called NPF-OTDR sensor system takes advantage of the higher scattering of the NPFs to increase the spatial resolution and strain sensitivity of the distributed sensor system. The wavelength-dependent optical attenuation is measured over a wide range of wavelengths using the cutback method to evaluate the operational wavelength for the OTDR. In this case, the results indicated smaller attenuation in 1310 nm than at the other operational wavelengths of the OTDR system (i.e., 1550 nm and 1625 nm). For this reason, the OTDR is applied at the 1310 nm wavelength for different strains applied along the optical fiber (with 1 m separation between them). The results for strain estimation showed relative errors of around 3%, whereas the strain position estimation is around 0.24 m. These results indicate the feasibility of the proposed system with a potential spatial resolution of around 0.5 m (which can be even lower depending on the OTDR setup). Thus, the advantages of the OTDR using the NPF result in a better sensor system performance when compared with the standard optical fibers, significantly enhancing the conventional OTDR capabilities in terms of resolution with even comparable performance to specialty OTDR systems at a lower cost and with a simpler design.
A Comparison Between Nanoparticle-Doped Fibers and Standard Single-Mode Fibers for Distributed Temperature Sensing
This article presents a comprehensive analysis of the thermal properties and distributed temperature-sensing responses of nanoparticles (NPs)-doped optical fiber using optical frequency-domain reflectometry (OFDR). The thermomechanical analysis (TMA) for the NP-doped fiber is performed to evaluate the thermal expansion coefficient of such fibers and their differences compared with standard telecom optical fibers (SMFs). In addition, the thermo-optical coefficient of such fibers is analyzed as a function of their steady-state temperature responses, whereas the thermal conductivity is assessed from the transient thermal analysis of the NP-doped fiber. The results in distributed temperature measurement indicate better sensing performance of NP-doped fiber, which has 2.6 times higher temperature sensitivity, a smaller response time, and high accuracy estimated from a determination coefficient (R2) of 0.993 and root mean squared error (RMSE) of 1.28 ∘ C. Therefore, the main findings of this work indicate the influence of the NPs composition on the thermal properties of the optical fibers, where the addition of oxide particles (in conjunction with the changes in the glass matrix) presented a positive effect on the distributed temperature sensing capabilities with a thermal expansion coefficient increase of 30% and thermal conductivity increase of 25% when compared with SMF. Thus, this article provides not only the comparison of the temperature sensing performance of an NP-doped fiber but also a straightforward method for the assessment of distributed physical parameters of the fiber that can be used for any specialty optical fiber, which can also be used as a nondestructive method for the assessment of the optical fiber composition.