Model-based position and reflectivity estimation of fiber bragg grating sensor arrays

We propose an efficient model-based signal processing approach for optical fiber sensing with fiber Bragg grating (FBG) arrays. A position estimation based on an estimation of distribution algorithm (EDA) and a reflectivity estimation method using a parametric transfer matrix model (TMM) are outlined in detail. The estimation algorithms are evaluated with Monte Carlo simulations and measurement data from an incoherent optical frequency domain reflectometer (iOFDR). The model-based approach outperforms conventional Fourier transform processing, especially near the spatial resolution limit, saving electrical bandwidth and measurement time. The models provide great flexibility and can be easily expanded in complexity to meet different topologies and to include prior knowledge of the sensors. Systematic errors due to crosstalk between gratings caused by multiple reflections and spectral shadowing could be further considered with the TMM to improve the performance of large-scale FBG array sensor systems

Review and Analysis of Peak Tracking Techniques for Fiber Bragg Grating Sensors

Fiber Bragg Grating (FBG) sensors are among the most popular elements for fiber optic sensor networks used for the direct measurement of temperature and strain. Modern FBG interrogation setups measure the FBG spectrum in real-time, and determine the shift of the Bragg wavelength of the FBG in order to estimate the physical parameters. The problem of determining the peak wavelength of the FBG from a spectral measurement limited in resolution and noise, is referred as the peak-tracking problem. In this work, the several peak-tracking approaches are reviewed and classified, outlining their algorithmic implementations: the methods based on direct estimation, interpolation, correlation, resampling, transforms, and optimization are discussed in all their proposed implementations. Then, a simulation based on coupled-mode theory compares the performance of the main peak-tracking methods, in terms of accuracy and signal to noise ratio resilience

Performance analysis of peak tracking techniques for fiber Bragg grating interrogation systems

In this paper, we propose a spectral correlation-based technique for tracking the wavelength shift of a fiber Bragg grating. We compared this approach, by means of a Monte Carlo numerical simulation, to the typical peak tracking techniques applied in classic interrogation systems. As result, we obtained a considerable gain in terms of noise tolerance (about 20 dB), which can be further incremented by selecting large-bandwidth gratings. This permits to increase the power budget of a fiber Bragg grating interrogator without changing the optical layout, overcoming classical limitations of commercial and custom systems. Penalties due to the non-idealities have been evaluated through the same Monte Carlo approach. Finally, we discuss a practical application of the peak tracking techniques to a fiber Bragg grating-based weight sensor, in which we applied the spectral correlation to track both the Bragg wavelength position, spectral deformations due to high strain, and spectral non-linearity

Optimization of multicore optical fibers with fiber Bragg gratings towards bend and shape sensing

A shape sensor based on fiber Bragg gratings (FBGs) in multicore fibers is a complex device with multiple factors which have to be accounted for a successful measure- ment system. In this dissertation, I considered several aspects of such shape and curvature sensors

Towards inline spatially resolved temperature sensing in thermal ablation with chirped fiber Bragg grating

We investigate the theory and feasibility of an in-line spatially resolved temperature sensor, suitable for thermal ablation monitoring. The sensor is based o a chirped fiber Bragg grating (CFBG). The CFBG is modelled as a chain of Bragg gratings, each sensitive to local temperature variations. By using a combination of iterative and statistical optimization techniques, it is possible to use demodulate the CFBG, in case of a Gaussian-like spatial temperature profile. A feasibility test based on CFBG simulation shows that the CFBG returns error <1 mm on cells damage threshold spatial estimation and good noise resilience

Development of a fiber-based shape sensor for navigating flexible medical tools

Robot-assisted minimally invasive surgical procedure (RAMIS) is a subfield of minimally invasive surgeries with enhanced manual dexterity, manipulability, and intraoperative image guidance. In typical robotic surgeries, it is common to use rigid instruments with functional articulating tips. However, in some operations where no adequate and direct access to target anatomies is available, continuum robots can be more practical, as they provide curvilinear and flexible access. However, their inherent deformable design makes it difficult to accurately estimate their 3D shape during the operation in real-time. Despite extensive model-based research that relies on kinematics and mechanics, accurate shape sensing of continuum robots remains challenging. The state-of-the-art tracking technologies, including optical trackers, EM tracking systems, and intraoperative imaging modalities, are also unsuitable for this task, as they all have shortcomings. Optical fiber shape sensing solutions offer various advantages compared to other tracking modalities and can provide high-resolution shape measurements in real-time. However, commercially available fiber shape sensors are expensive and have limited accuracy. In this thesis, we propose two cost-effective fiber shape sensing solutions based on multiple single-mode fibers with FBG (fiber Bragg grating) arrays and eccentric FBGs. First, we present the fabrication and calibration process of two shape sensing prototypes based on multiple single-mode fibers with semi-rigid and super-elastic substrates. Then, we investigate the sensing mechanism of edge-FBGs, which are eccentric Bragg gratings inscribed off-axis in the fiber's core. Finally, we present a deep learning algorithm to model edge-FBG sensors that can directly predict the sensor's shape from its signal and does not require any calibration or shape reconstruction steps. In general, depending on the target application, each of the presented fiber shape sensing solutions can be used as a suitable tracking device. The developed fiber sensor with the semi-rigid substrate has a working channel in the middle and can accurately measure small deflections with an average tip error of 2.7 mm. The super-elastic sensor is suitable for measuring medium to large deflections, where a centimeter range tip error is still acceptable. The tip error in such super-elastic sensors is higher compared to semi-rigid sensors (9.9-16.2 mm in medium and large deflections, respectively), as there is a trade-off between accuracy and flexibility in substrate-based fiber sensors. Edge-FBG sensor, as the best performing sensing mechanism among the investigated fiber shape sensors, can achieve a tip accuracy of around 2 mm in complex shapes, where the fiber is heavily deflected. The developed edge-FBG shape sensing solution can compete with the state-of-the-art distributed fiber shape sensors that cost 30 times more

In-situ deformation monitoring of aerospace qualified composites with embedded improved draw tower fibre Bragg gratings

Aerospace certified fibre reinforced plastics (FRPs) are extreme performing construction materials, which today are increasingly applied in primary structures of the new generation aircrafts (e.g. Boeing 787, Airbus 350, Bombardier C-Series), such as the fuselage, the wings and the fin. An interesting aspect on the technological point of view of sensing is that airplane manufacturers such as Airbus and Boeing are looking at incorporating health-monitoring systems (such as optical fibre sensors, especially fibre Bragg gratings) that will allow the airplane to self-monitor and report maintenance requirements to ground-based computer systems. However, one has to realize that the mechanical behaviour of anisotropic FRPs is significantly different compared to conventional isotropic construction materials. In this dissertation, the author focuses on monitoring the strain and (permanent) deformation in carbon reinforced plastic laminates with embedded fibre Bragg gratings. The research is divided in two main parts. In the first part of this research, the existing fibre draw tower technology is utilized, to manufacture an improved version of the existing in-line high quality, draw tower fibre Bragg gratings (DTG®s). With respect to accurate measurements and structural integrity, the research focuses on reducing the total diameter of the optical fibre, so the incorporation in the reinforcement fibres is enhanced and the distortion in the composite is reduced. The author elaborates in detail the methods of strain and temperature calibrations and the different setups which are applied. Additionally, with respect to the high temperatures during the composite manufacturing process, the thermal stability of the DTG®s is studied at elevated temperatures (>300°C). In the second part, the author embeds the DTG®s in specific types of thermoset and thermoplastic carbon reinforced plastic laminates. The author applies the embedded DTG®s in several stages of the composite lifetime. Starting with the monitoring of the composite manufacturing process and ending with fatigue testing until failure of the composite laminates. During the different experiments, the sensors are subjected to high temperatures, high pressures, extreme longitudinal strains and transverse strains and in the mean time, they are employed to very accurately measure (multi-axial) strains inside composites at microstrain level (~10 6)