RG

R.M. Groves

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24 records found

Master thesis (2024) - J. Voges, R.M. Groves, Frank Grooteman, J. Sodja, J. Sinke
Safety and reliability of aircraft structures are of main concern within the aerospace industry, preferably without influencing the availability of the aircraft and maintenance and operation costs. As damages in composites can be hard to detect, methods are being developed to detect damages which can potentially lead to a (catastrophic) failure of a (sub)system. Interest in structural health monitoring (SHM) has thus gained a strong interest within aerospace engineering, with the development of new systems or optimising existing ones to contribute to a safe and reliable aircraft. This research focuses on the development of an impact damage detection and quantification method for composite structures. The main research objective of this thesis is to investigate the capabilities of a PZT and a state-of-the-art FBG sensor system for passive impact damage detection and quantification on a simple composite panel and a complex stiffened composite structure. ...
Doctoral thesis (2024) - L. Fazzi, Roger Groves, C.A. Dransfeld
Since the dawn of time, human beings have been always fascinated and envious of the flight of birds and human’s desire to fly has become stronger and stronger over the centuries. What child looking at a bird does not wish that they could take flight to chase it and view the at the landscape from above? The dream to fly is inside the human being since tender age, although the physical possibility does not belong to their nature. Nevertheless, humans have exploited the power of their brain and hands to get closer this dream.

Leonardo Da Vinci (1452-1519)1 was the first one that effectively studied the flight dynamics of the birds, developing several technical drawings and building flying machines between the XV and XVI century. However, for almost 400 years, no tangible developments occurred until the Wright brother’s famous flight (in 1903)2, which is the major milestone of the aeronautical world. From that far away event, enormous technological developments have been made so that a large number of apparatuses able to fly in the atmosphere and travel in Space have been developed.

One of the key technological sectors that has allowed the large growth of the aerospace industry is that of the materials. Specifically, the large use of composites materials and adhesives has allowed the design and building of modern airplanes, spacecraft and devices which are increasingly lighter, faster, stronger and tougher. Nevertheless, at the same time, the increase of aerospace performance by using new materials has raised the necessity to develop a technology which is able to provide information on the health state of the materials that composed the structures. This need is not only linked to the necessity to increase the safety but also to two other factors: to optimize the maintenance schedule of the aircrafts so that to save economical resources, and to increase our knowledge about the mechanical, damage and fracture behavior of the materials.

Although, during the decades, a number of inspection and monitoring technologies have been developed as such as piezoelectric, acoustic and ultrasound sensing, electrical gauges, fibre optic sensors, eddy current, comparative vacuum, interferometry, penetrating liquids, thermography, radiography (x-rays) and others, not one of these has proved to be applicable for the entire life cycle of the material (from the manufacturing, operating phase to the end of life) which provides in real-time enough information to effectively evaluate its health state.
Therefore, the here presented thesis aims to demonstrate the multi-sensing abilities and monitoring benefits of tilted Fibre Bragg gratings sensors (TFBGs) in order to fill a current technological gap in the previous technologies and to improve the state-of-art of the Structural Health Monitoring field. The research focused initially on the fundamentals, mathematical and numerical modelling, methodology and demodulation techniques of the TFBG sensors, successively the treatment is dedicated to the TFBG applications for simultaneous three-parameter monitoring embedded in composite material and silicone adhesive, respectively for aeronautical and space use. This selection of these materials was made from those commonly used in the aerospace industry. The application of TFBGs can be, from the very beginning, have a great impact in the scientific community and, also maybe, in industry.
Therefore, taking into account what was reported previously, the research presented in the following thesis was confronted with the aim to demonstrate that TFBG can be a promising sensor for structural health monitoring of aerospace materials, and are able to provide reliable and simultaneous multi-parameter measurements. The treatment begins with the first introduction chapter where composite materials, silicone adhesive and TFBG sensors are presented fro a historical perspective, and their current state-of-art regarding applications, issues and technological gaps in relation with the working load and environment, are reported. Then, the research questions and reasons that motivated the scientific investigation are introduced in the last part of chapter 1.
The starting point of the research can be considered chapter 2, where, first of all, the realization of a TFBG sensor customized for the desired application is confronted by providing a numerical model to simulate the spectrum based on the values of the parameters of the sensor Bragg structure. This is important to obtain TFBGs with a spectral signal usable for the simultaneous and separated measurements of different parameters before the manufacturing of the same sensor. It can be noted that, the simulation of the TFBG spectrum may bring other several benefits such as production time and costs savings. In fact, the determination, a priori, of the Bragg structure, and hence, the parameters of the TFBG manufacturing setup, allows the TFBG sensor to be obtained with the desired measuring characteristics without the waste of materials, testing and manpower time.
In chapter 3, the demodulation of the TFBG spectrum for refractometric measures was improved by developing a new technique based on the Delaunay triangulation of the datapoints that compose the spectral signal, which was demonstrated to be faster and more accurate than previous techniques. This technique is also compatible with the method to extract the strain-temperature variation from the spectrum, so that the methodology for multi-parameter measurement performed with a single TFBG is completed.
At this point, chapter 4 starts the beginning of the second part of the thesis, where the simultaneous thermomechanical measurements of the TFBG were used to determine the deformation effects of a thermal load profile on a glass-fibre/epoxy composite plate induced by heating lamps. A further step achieved in this chapter, was to compare the TFBG measurements with a classical strain sensing technique based on the use of a TFBG as standard strain gauge thermally compensated by a thermocouple. Furthermore, another comparison was performed between the experimental results and the Finite Element Model (FEM) analysis results obtained by modeling the composite sample with and without the embedded TFBG and applying a Gaussian thermal profile.
These comparisons show that the strains measured with the single TFBG are very close to the values obtained by using the classical approach and the full FEM model. The improvement regarding the single TFBG sensor can be obtained by increasing its thermal resolution which is the weak point of the simultaneous thermomechanical measurements. Nevertheless, it can be further improved by using an interrogation system with a finer wavelength scanning resolution or by designing a TFBG whose resonance peaks move in the spectrum much more with the temperature variation. The comparison of the empirical measured deformations with the strain values extracted by the FEMs analysis have highlighted the importance to model the optical fibre inside the composite to increase the accuracy of the model. In conclusion, the single TFBG sensor was able to monitor the thermomechanical trend inside the composite during the heating lamp exposure with a good accuracy as the values were close to those measured with the classical approach and full FEM simulation.
The conclusions drawn from the first and second part of the thesis are that the investigation on the multi-parameter sensing abilities of the TFBG sensors, also embedded in composite materials for a complete monitoring of their state from their manufacturing to the operating life, has given positive and promising results. Especially regarding the embedding of the sensor, each single TFBG sensor can be used in order to measure simultaneously thermomechanical and refractometric variations of the composite material where the sensor is embedded and in any step of the material life.
The second part of the thesis continues with chapter 5. Here, the TFBG sensors are embedded inside glass-fibre/epoxy resin composite material to monitor simultaneously the strain-temperature variations, the resin refractive index (RI) during the manufacturing process and the application of a thermal load profile. Regarding the TFBG monitoring performed during the composite manufacturing, several samples of different thickness were tested and sensorised. In these samples, the sensors were able to measure, simultaneously, the strain state induced in the material due to the manufacturing steps, the temperature profile, and the resin RI variations due to the crosslinking occurring during the curing. This allowed the evaluation, not only of the possible state of stress in the material during the production, but, even more interesting, the cure degree of the resin. Indeed, as anticipated already in previous research, the resin RI measured with the TFBG can indicate the curing degree matrix of the composites. The TFBGs were able to provide the entire RI profile of the resin during the curing in which three different behavior ranges were identified in combination with the temperature trend. The expected typical plateau was reached in the RI curve when the resin was considered fully cured. Furthermore, the refractometric sensing abilities of the TFBGs were also used to monitor the resin flow and speed during its infusion.
From chapter 6 on, the treatment is focused on the TFBG application study on the space qualified silicone adhesive, which regards the third part of the thesis. Silicones are strategic and widely used materials in many engineering fields, but mainly their use finds great importance in space industries, especially for electronic and structural components. Nevertheless, some parts of the spacecraft where silicone elements and adhesives are used undergo a direct exposure to the space environment, which represents harsh operating conditions and is strongly degrading for any material. In fact, perturbations as severe temperature gradients, ultra-high-vacuum, Ultra-Violet (UV) and ionizing radiations (x-rays, γ-rays, etc…), extreme thermal range and cycles, thermal shock, micro-gravity, atomic oxygen (ATOX), high accelerations, vibrations and space debris are characteristic of the space operating environment. Furthermore, it has to be also considered that these elastomers have to maintain their original mechanical and physical properties during their operational life in space, which is a challenging target. In this context, TFBG sensors embedded inside silicone adhesives, through their simultaneous thermomechanical and refractometric measuring abilities, may offer fundamental information to evaluate the internal mechanical and chemical state of the elastomers during the use in space environment. This would offer the possibility to have a technology able to provide a general view on the degradation state of the adhesive in real-time during the laboratory testing or operational life, which may improve the evaluation of its health and performance trend along the exposure time. Nevertheless, as for the composite, the monitoring technology should be always minimally intrusive, light and not affecting the material performance and properties. Hence, in order to match these requirements, each embedded TFBG sensor has to be able to perform the thermomechanical-refractometric measurements as single sensor without to be affected by the exposure to the space environment. The demonstration of a working TFBG sensor in a simulated space environment may be an interesting and promising starting point for the future development of a sensing technology able to real-time detect degradation and damages in spacecraft structures and components during the space missions.
In chapter 6, since studies in literature about the compatibility of optical fibre sensor layers in vacuum were not found, initially, the waveguide containing the TFBG was subjected to an outgassing test. Once the compatibility was verified, a TFBG was then embedded inside a space qualified silicone used as adhesive to join two micro-sheet cover glasses in order to compose a sandwich. This TFBG sensorised glass sandwich was tested inside a vacuum chamber and exposed to high-vacuum (around 10-6 mbar) and loaded with a thermal cycling profile. Hence, in this first approach, the experiment was planned to simulate the degradation on the silicone adhesive of the TFBG sensorised sample generated by outgassing (due to high-vacuum) and thermal cycling loads, which are perturbations constantly present in space environment.
The measurements of the single multi-parameter TFBG sensor, acquired during the experiment, were compared with the values obtained by using the classical sensing approach consisting in the thermal compensation of the TFBG (used as strain-gauge) through a thermocouple. The comparison highlighted the inaccuracy of the classical sensing method due to the different location of the sensors in the silicone which brings serious mistakes in the measurements. In fact, due to the absence of an atmosphere in the space environment, the transfer of heat inside a body depends only from the thermal conductivity of the material which accentuates the issue of the classical sensing approach linked to the different location of the sensors. While, the self-compensated TFBG can overcome this gap as it is thermally self-compensated. Furthermore, for a complete evaluation of the health state of an organic material such as a silicone adhesive, temperature and deformations may be not sufficient as it is not easy to obtain information on the chemical state of the material, such as the variations of the silicone RI. The embedded TFBG sensor, simultaneously sensitive to temperature and deformations, was able to provide measurements of the silicone RI that was changing due to hardening and chemical evolution induced by the thermal cycles in high vacuum environment. The chemical variations were checked also by testing a sample of pure cured silicone adhesive via the Differential Scanning Calorimetry, which showed chemical variations due to the realising of volatiles during the heating-up and cooling-down phases of the test. These results make the TFBG a promising sensor able to provide a complete evaluation of the silicone state that comprises the thermomechanical and refractometric measurements while working in space environment.
By exploiting the experiences achieved in the previous chapters, chapter 7 treats of the research focused on the detection of the UV effects induced in the silicone adhesive working in space simulated environment. This topic may be interesting for polymers used in a space working environment as long exposure to UV radiation in vacuum can cause severe damages and bring the component to failure together with the structures of a spacecraft. The reason lies in the absorption of these light wavelengths by the silicone, whose organic chemical composition is photochemically susceptible to these light wavelengths. As a consequence, the photochemical reactions cause severe degradation of the material with deterioration of the original properties and efficiency and shorter working life. Then, it is easy to understand that a sensing technology able to monitor the degradation of the silicone working in the previously described conditions, may be really useful to evaluate the state of the material during its use, but also, in the phase of laboratory testing to better detect the material behaviour and its changes. Therefore, several and different TFBG sensorised samples were tested in a high vacuum chamber provided of UV lamps which emitted a high radiation level for a certain exposure time. Hence, the acquired spectra were demodulated and used to measure the thermomechanical and refractometric variations induced by the UV exposure inside the silicone in correlation with the equivalent exposure solar hours. This allowed an analysis of the different degrees of degradation of the silicone based on the sample configuration and exposure time. In conclusion, the achievement of this research was the demonstration of a minimal intrusive sensor as the TFBG is not only compatible with operating in a space environment, but is also able to provide in-situ reliable multi-parameter sensing for the monitoring of the thermomechanical and refractometric state of the material during its operations in space environment.
The conclusions of the thesis are reported in chapter 8 where the outcomes of the conducted researches highlighted the potentiality of the TFBG as a single three-parameter sensor to monitor the state of materials for aerospace industry. As consequence, these results may induce the raising-up of the SHM concept by developing a sensing technology based on the TFBGs that are able to provide an overall view of the material state, from the manufacturing to the operational life, also working in harsh environmental conditions as those in space. ...

An in-depth evaluation on the end-to-end process of developing a data-driven tool

Master thesis (2023) - S.D.F. Schmidt, R.M. Groves
This paper examines the end-to-end development process for a Convolution Neural Network (CNN) based damage classification tool for ultrasonic inspection of aerospace-grade composite structures. The recent advent of Artificial Intelligence (AI) and Machine Learning (ML) has piqued the interest of the aerospace industry since it has the potential to improve performance and alleviate the burden on personnel. The big question in the industry right now is how and where to introduce this technology while assuring the safety and reliability of its implementation. Guidelines drafted by the European Aviation Safety Agency (EASA) for the development of AI showed that maintenance and training were the most accessible points of entry for this technology as it did not have the same stringent requirements that a flying system would have. This paper proposes a research methodology which allows for the cost-effective development of ultrasonic data for the training and testing of data-driven tools. This was partly achieved by using a novel eFlaw technique which has been implemented for the first time in composite structures. The method allows for significant augmentation and generalisation of datasets, resulting in a model with the ability to detect features potentially smaller than one-quarter of a wavelength. This improved performance paves the way for more sensitive low-frequency ultrasonic inspection in thick composites. To evaluate these models, various evaluation techniques were compared and showed that Receiver operator curves and confusion matrix-derived metrics provided comparable results. Explainable methods found that the GradCam and the inspection of feature maps showed the most interpretable results on the features that were being identified. Using the feature maps it was possible to generate a new type of C-scan, called an F-scan (Feature-scan) which provides an inspector with a view of the C-scan from the perspective of a feature map from the model providing an interpretable view of the model’s classifications. In addition to these positive results, this thesis provides readers with a cost-effective methodology for developing data-driven tools for maintenance applications within the aerospace industry. ...
Doctoral thesis (2023) - L. Cheng, M. Veljkovic, R.M. Groves
In the past two decades, offshore wind has emerged as a new source of renewable energy. This highlights the requirement for the utilisation of larger and more efficient offshore wind turbines (OWTs). The connections used in support structures of OWTs are critical to ensure the excellent structural performance of OWFs. An alternative option is the C1 wedge connection (C1-WC) to join virtually all the wind turbine generator (WTG) towers to their foundations. This connection shows promising potential in reducing construction, installation, and maintenance costs by eliminating the ring flange and using smaller diameter bolts.
Till now, C1-WC has undergone three generations of development. A more comprehensive research program is required to explore its implementation in a wind farm. The load transfer mechanism and critical component of C1 wedge connections are different to the conventional bolted ring flange (RF) connections. It is important to understand the mechanical behaviour of this connection. Meanwhile, support structures are exposed to the harsh environment during the service life of the OWTs. Material degradation and local cracks in the connection are inevitable to affect the serviceability of OWTs. A need for a reliable and rigorous structural health monitoring (SHM) system for the connection is evident. As one of the non-destructive techniques (NDT), Acoustic emission (AE) has been extensively used in early damage detection and real-time assessment of steel structures. Despite its successful applications, challenges still exist in using AE technique for monitoring applications, especially in analysing the recorded data. Therefore, the research aims to assist in understanding mechanical behaviour and evaluating the health status of the innovative connection.
An extensive experimental program was conducted to evaluate the static and cyclic behaviour of the C1-WCs. Additionally, a detailed 3D non-linear finite element (FE) model of the C1-WCs has been developed. The incorporation of material non-linearity and ductile damage allows the FE model to model the post-necking and final fracture of the connection. The FE model replicates with a good agreement the experimental tensile static and cyclic tests up to the final damage and reproduces the joint behaviour correctly. Parametric studies investigate the influence of bolt grade, the friction coefficient between contact surfaces, and the preloading force level on mechanical behaviour. Moreover, a quantitative comparison between C1-WC and two types of connections (RF connection and RF connection with defined contacts) is performed to provide practical insights into the selection and application of such connections and further optimization. FE-assisted analyses were performed to examine the effect of applied boundary conditions, bolt pretension level, and steel grade on the behaviour of the connections.
In addition to mechanical behaviour analysis. this research is also focused on developing data processing methods to address the challenges of AE monitoring for the C1-WCs. A hybrid model is proposed to identify the deformation stage of metal material. This method combines a self-adaptive denoising technique and an Artificial neural network (ANN). To reduce noise in the AE signals, a decomposition-based denoising method is proposed based on singular spectral analysis (SSA) and variable mode decomposition (VMD), referred to as SSA-VMD. After denoising, an ANN is constructed to identify the deformation stage of steel materials using features extracted from the filtered AE signals as input.
Fatigue damage of the C1-WCs could result in catastrophic failure of OWTs. Due to space constraints, it can be challenging to detect surface cracks in the lower segment holes of the C1-WC using commercial sensors. Thin PZT sensors are lightweight and small, making them suitable for use in restricted-access areas. However, their poor signal-to-noise ratio can limit their effectiveness in AE monitoring. A criterion for selecting the optimal thin PZT sensors is proposed and a configuration is designed for multiple sensors. Two signal processing methods are then proposed in terms of this issue. Firstly, a data fusion-based method is proposed to enhance the functionality of thin PZT sensors in AE applications. Convolutional neural networks (CNNs) combined with principal component analysis (PCA) are employed for signal processing and data fusion. Secondly, a baseline-based method is proposed to provide early warning of the fatigue damage of C1-WCs using thin PZT sensors. A benchmark model correlating to the damage state is created by breaking pencil leads. Multi-variate feature vectors are extracted and then mapped to the Mahalanois distance for identification.
Based on this research work, an efficient FE method has been developed to further improve the design of C1-WC. By providing an in-depth guideline for evaluating the mechanical performance of connections used in OWTs, this research has the potential to contribute to the development of more robust and reliable wind turbine structures. Moreover, the proposed signal processing methods for identifying the deformation stage and early fatigue damage can be further explored in structures with similar damage mechanisms. This can lead to the development of more accurate and effective methods for monitoring and assessing the health of offshore wind turbines, ultimately contributing to improved safety and reliability in the renewable energy industry. ...
Doctoral thesis (2022) - N. Nazeer, R. Benedictus, R.M. Groves
The aerospace industry is an ever-evolving field that has seen many technological advances over the past decades. The desire for aircraft to be not only efficient and reliable but also cheaper and safer has brought about many proposals across the industry. One of these advances is towards morphing aircraft wings to make wings lighter, more flexible, aerodynamically efficient and structurally stable. One of the key elements of a morphing wing is sensors that monitor the loads and shape of the wing throughout the flight. Within the framework of the SmartX project, the goal and contribution of this study is on the design and development of novel sensing methods for Structural Health Monitoring. This has been performed with a specific focus on shape sensing and load monitoring. This thesis is focussed towards the design and development of a Structural Health Monitoring tool for adaptive aerospace structures and at the same time to reduce the dependency on a high number of sensors. Within the already available fibre optic sensor techniques an identification was made for demonstrating the potential of a higher performing SHM tool involving the combination of FBG spectral sensing and FBG-Pair interferometric sensing. A proposal is made to have a reliable, robust and cost effective sensing methodology for real time monitoring of morphing structures with a simultaneous focus on the SmartX morphing wing demonstrator. The method developed and demonstrated in this thesis is not limited to aerospace (and morphing) structures and can be extended to other engineering structures. Load carrying structures that undergo deformations/deflections can be monitored provided they are properly calibrated. These include, but are not limited to, rotor blades, masts, beam structures and bridges. ...
Master thesis (2021) - R.J. Kruithof, R.M. Groves, C. Anand, Rik Tonnaer
This master thesis focuses on developing an integrated system capable of performing ultrasonic phased array measurement on composite parts in an automated fashion. This could potentially be used in the manufacturing process of fiber laminate composite parts to obtain more accu- rate detection of manufacturing defects. Phased array ultrasonics makes use of an array of ultrasonic elements that will be used to send consecutive pulses with each of the elements which are received with the remaining elements in the array. By taking into account the signal strength of the pulses between each of the elements in the array and their respective timings a two-dimensional image of the area underneath the probe can be reconstructed into an image. This image contains information about the acoustic material properties through the depth of the measured object. By automating this method of inspection and taking consecutive measure- ments of this type it becomes possible to obtain volumetric data of the measured object. This research aims to investigate the feasibility and potential constraints of integrating this type of sensor system with a robotic arm. The benefit of combining this with a robot means it may be used in a repeated fashion, as well as to inspect a large number of possible geometric shapes. The final part of this thesis work will cover the processing of the data that is produced using this method.Since a large amount of data is produced, processing and analysis is needed in order to be able to visualise the data and to be able to draw meaningful conclusions from it. ...

Monitoring drone system for turbulence and noise in the urban environment

Master thesis (2021) - T.M. Akaltun, R.M. Groves, Timo Wassenaar, Dino Spirtovic
Automation has come knocking at the door of the world of aircraft maintenance. The general trend shows that the total aircraft fleet size of the world increases in contrast to the number of technicians, which decreases. Therefore, the Royal Netherlands Aerospace Center (NLR) launched a project and setup called Leading Edge Scanner (LES) to automate technician performed inspections on aircraft for partial or total replacement of this service. Automated three-dimensional (3D) reconstruction of known or unknown objects requires robots and sensors. The LES, a robotic arm, will automatically detect and classify anomalies on aircraft components. As several images from different viewpoints are needed to reconstruct a 3D computerized object, a view planning strategy is required to find the Next-Best-View (NBV). The challenging problem of finding the NBV has been studied since the 1980s. ...

Design of method to simulate an induction heating system of out of autoclave mould to scale to full scale production

Master thesis (2019) - Frank van Duin, Roger Groves
This master thesis is part of research at Fokker Aerostructures to an out of autoclave production method for thermoplastic composites. The objective of the thesis is to simulate the induction heating process of this production method to make it possible to simulate the production method before the mould is produced. The final product is a guideline to the design of an induction heating setup for the specific production method. ...
Master thesis (2018) - Dries Schroyen, Roger Groves, Andrei Anisimov, W. Van Paepegem, D. Garoz Gómez
Digital Image Correlation is a powerful tool with which full-field strains can be extracted from a series of digital images. If applied on the micro-scale of composites, the fiber-matrix interaction can be studied. To do so, different challenges have to be overcome. First, composite specimens have to be prepared for microscopy. Then, a speckle pattern for the DIC algorithm has to be applied, for which different methods are examined and optimized. Next, digital microscopic imaging systems are compared and characterized. Finally, a relation between parameters of the DIC algorithm (such as subset shape and size) and the accuracy is determined. ...
Master thesis (2017) - Willem de Zeeuw, Roger Groves, Hans Poulis, Johan Bijleveld, P van Duin
This report shows that animal glue from porcine skins can be used to make thin films with reproducible properties. It shows that the tensile strength of the film relates linearly to the bloom strength, while the stiffness remains constant for temperatures lower than the glass transition temperature. The report continues to show how Differential Scanning Calorimetry (DSC), Fourier Infra-red Spectroscopy (FTIR), and X-ray Diffraction (XRD) can be used to predict the strength of an animal glue film. The test results show that XRD is the easiest method to obtain a reasonable prediction of the mechanical properties. Meanwhile, DSC holds additional information on the internal stress state of the sample, which may promise better predictions of the mechanical properties once the analysis has been optimized. ...
Master thesis (2017) - Vincent van den Bercken, Roger Groves, S.J. Garcia Espallargas, Eric van Genuchten, S. van Eesbeek
Using Fiber Bragg Grating (FBG) sensors in rolling element bearings is a novel way of monitoring bearings. During prototype testing, differences between sensor readouts were observed, leading to the research question: “What causes the observed differences in the strain distribution from sensor to sensor in a rolling element bearing equipped with FBG sensors?”. Further tests were performed with an interrogator capable of scanning the spectra with a resolution 25 times higher compared to the original measurements, performed with a SmartScan SBI interrogator. These tests showed that in different temperature conditions, sensors may behave differently, resulting in a translation of the strain levels between sensors. Furthermore, it was found that (1) the peak detection method used by the SBI interrogator, (2) the lower resolution of the SBI interrogator and (3) the differences in FWHMs between the sensors and between different load conditions, led to inconsistent strain readings from the sensors. ...