Fiber-optically sensorized composite wing

This paper details some significant findings on the use of the fiber Bragg grating (FBG) sensors for structural health monitoring (SHM) in aerospace fiber reinforced polymer (FRP) structures. A diminutive sensor provides a capability of imbedding inside FRP structures to monitor vital locations of damage. Some practical problems associated with the implementation of FBG based SHM systems in the aerospace FRP structures such as the difficulty of embedding FBG sensors during the manufacturing process and interrelation of distortion to FBG spectra due to internal damage, and other independent effects will be thoroughly studied. An innovative method to interpret FBG signals for identifying damage inside the structures will also be discussed.

Fiber optic sensors (FOS) in long-term structural health monitoring (SHM) have drawn significant attention due to their pivotal role in detecting defects and measuring structural performance in diverse infrastructures. While using FOS, temperature variation due to environmental factors is still considered one of the major challenges to isolating sensing parameters. To address this issue, we reported a machine learning (ML)-augmented multi-parameter sensing system that enables simultaneous detection of strain and temperature effects based on one single fiber Bragg gratings (FBGs) sensor for SHM. The initial phase entailed designing, fabricating, and characterizing a novel FBG sensor in the laboratory, incorporating a set of four FBGs, each distinguished by distinct Bragg wavelengths. In the next phase, ML algorithms are employed to separate temperature effects from strain variations. As a proof of concept, mechanical loading tests are conducted on the sensor, exposing the FBG portion to various temperature conditions. In the final phase, data collected from a post-tensioned concrete bridge embedded with both strain and temperature FBG sensors are utilized, and the developed ML models are applied to observe real-environment outcomes. Despite the limited feature points of collected FBG spectrums, the developed ML models effectively address cross-sensitivity issues induced by temperature perturbations. The long-term benefit of using FOS is that it will enable a better understanding and utilization of aging infrastructure. This will potentially reduce embodied carbon of infrastructure in the future and assist in the global efforts to achieve Net-Zero.

Performance assessment of discrete wavelet transform for de-noising of FBG sensors signals embedded in asphalt pavement

Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.

Structural Health Monitoring (SHM) of aircraft structures, especially composite structures, has assumed increased significance on considerations of safety and costs. With the advent of co-cured structures, wherein bonded joints are replacing bolted joints there is a concern regarding skin-stiffener separation, which might not be detected unless a rigorous non-destructive testing (NDT) is done. It would hence be necessary to be able to detect and assess skin-stiffener separation in composite structures before it reaches the critical size. One of the health monitoring strategies is through strain monitoring using fibre optic strain sensors such as Fibre Bragg Grating (FBG) sensors. The first aspect that needs to be addressed is the characterization of the FBG sensors. Issues of embedment in composites have also to be addressed. Before evolving a damage detection strategy, the sensitivity of the structural strain to skin-stiffener separations must be clearly understood and quantified. This paper presents the analysis and experiments done with a composite test box to study the effect of skin-stiffener separation on the strain behaviour. The box consists of two skins stiffened with spars made of Bi-Directional (BD) glass-epoxy prepreg material. The spars are bolted to the skins and removing suitable number of bolts simulates 'de-bonds'. The strains of the healthy box are compared with the unhealthy box. The strains in the experiments are monitored using both strain gauges and Fibre Bragg Grating (FBG) sensors. The experimental results show that there is significant change in the measured strain near and away from the debond location. The finite element analysis of the box is done using ABAQUS and the analysis is validated with the experimental results. A neural network based methodology is developed here to detect skin-stiffener debonds in structures. A multi-layer perceptron (MLP) neural network with a feed forward back propagation algorithm is used to determine the size/severity of damage. The FE model is used to generate the neural network training data for various sizes of debonds. The results show that the network is able to predict the damage size well. The network is implemented for a specified load. However, it is seen that the damage size predicted is independent of the applied load and the network performance is dependent on the fidelity of the finite element model used to train the network.

Fiber Bragg grating (FBG) sensors are excellent transducers for collecting ultrasonic wave signals for structural health monitoring (SHM). Typically, FBG sensors are directly bonded to the surface of a structure to detect signals. Unfortunately, demodulating relevant information from the collected signal demands a high signal-to-noise ratio because the structural ultrasonic waves have low amplitudes. Our previous experimental work demonstrated that the optical fiber could be bonded at a distance away from the FBG location, referred to here as remote bonding. This remote bonding technique increased the output signal amplitude compared to the direct bonding case, however the mechanism causing the increase was not explored. In this work, we simulate the previous experimental work through transient analysis based on the finite element method, and the output FBG response is calculated through the transfer matrix method. The model is first constructed without an adhesive to assume an ideal bonding condition, investigating the difference in excitation signal coherence along the FBG length between the two bonding configurations. A second model is constructed with an adhesive to investigate the effect of the presence of the adhesive around the FBG. The results demonstrate that the amplitude increase is originated not from the excitation signal coherence, but from the shear lag effect which causes immature signal amplitude development in the direct bonding case compared to the remote bonding case. The results also indicate that depending on the adhesive properties the surface-bonded optical fiber manifests varying resonant frequency, therefore resulting in a peak amplitude response when the input excitation frequency is matched. This work provides beneficial reference for selecting adhesive and calibrating sensing system for maximum ultrasonic detection sensitivity using the FBG sensor.

Embedded fiber Bragg grating (FBG) sensors are attractive for in-situ structural monitoring, especially in fiber reinforced composites. Their implementation in metallic structures is hindered by the thermal limit of the protective coating, typically a polymer material. The purpose of this study is to demonstrate the embedding of FBG sensors into metals with the ultimate objective of using FBG sensors for structural health monitoring of metallic structures. To that end, ultrasonic additive manufacturing (UAM) is utilized. UAM is a solid-state manufacturing process based on ultrasonic metal welding that allows for layered addition of metallic foils without melting. Embedding FBGs through UAM is shown to result in total cross-sectional encapsulation of the sensors within the metal matrix, which encourages uniform strain transfer. Since the UAM process takes place at essentially room temperature, the industry standard acrylate protective coating can be used rather than requiring a new coating applied to the FBGs prior to embedment. Measurements presented in this paper show that UAM-embedded FBG sensors accurately track strain at temperatures higher than 400 °C. The data reveals the conditions under which detrimental wavelength hopping takes place due to non-uniformity of the load transferred to the FBG. Further, optical cross-sectioning of the test specimens shows inhibition of the thermal degradation of the protective coating. It is hypothesized that the lack of an atmosphere around the fully-encapsulated FBGs makes it possible to operate the sensors at temperatures well above what has been possible until now. Embedded FBGs were shown to retain their coatings when subjected to a thermal loading that would result in over 50 percent degradation (by volume and mass) in atmospherically exposed fiber.

Application of FBG sensors for geotechnical health monitoring, a review of sensor design, implementation methods and packaging techniques

As an important factor in-service Structure health monitoring (SHM), predictions of displacement become the basis for determining the decrease of modern aircraft and aerospace structural performance. Optical fiber Bragg grating (FBG) sensors are considered an important tool for SHM , however, FBG sensors are rarely directly applied to monitor the displacement because of the intrinsic fragility. To overcome such a problem, we propose a novel method for design and curving an FBG sensor using auxiliary flexible driving function of the shape memory alloy (SMA) to monitor the displacement. The FBG sensor is curved slowly to an S shape along with SMA wire. Strain gradient of SMA which is applied by displacement loading is obtained by finite element analysis. By analyzing the spectral simulations, bandwidth of spectrum is increased and the central wavelength is changed. Spectral properties of curved FBG sensor are analyzed by stretch experiments, the results shown that its bandwidth, light intensity of peak and central wavelength are increased and the central wavelength change is linear with displacement. A new sensor based on an FBG sensor and SMA Actuators can be used to monitor displacement with displacement sensitivity of 141pm/mm.

The advancement of age and the increased awareness of public health have resulted in increased demand for continuous vital sign monitoring devices. Therefore, we developed a noninvasive vital sign measurement device without physical resistance to the user using a fiber Bragg grating (FBG) sensor. The FBG sensor was fixed on the wrist, and a pulse wave signal was obtained. Additionally, we focused on the similarity between this pulse wave signal and the second derivative of the plethysmogram (SDPTG). Classifying this signal, we found that its shape changed according to the age and blood pressure. We found that the change in the shape of the pulse wave signal and the SDPTG have the same tendency. Therefore, it is feasible to estimate the vascular age and arteriosclerosis with the signal obtained by an FBG sensor. On the basis of these results, the FBG sensor system can measure multiple vital signs and monitor health more comprehensively.

Fiber Bragg grating (FBG) sensors are excellent transducers for ultrasonic signal detection in structural health monitoring (SHM) application. While the FBG sensors are typically bonded directly on the surface of a structure to collect signals, one of the major challenges arises from demodulating relevant information from the low amplitude signal. The authors have experimentally demonstrated that the ultrasonic wave detection sensitivity of FBG sensors can be increased by bonding optical fiber away from the FBG location. This configuration is referred to here as remote bonding. However the mechanism causing this phenomenon has not been explored. In this work, we simulate the previous experimental work through a transient analysis based on the finite element method, and the output FBG response is calculated through the transfer matrix method. We first model an optical fiber bonded on the surface of an aluminum plate with an adhesive. The consistent input signal is excited to the plate, which is detected by the directly and remotely-bonded FBGs. The effect of the presence of the adhesive around the FBG is investigated by analyzing strain and displacement along the length of the FBGs at the locations of direct and remote bonding cases, and the consequent output FBG responses. The result demonstrates that the sensitivity difference between the direct and remote bonding cases is originated from shear lag effect due to adhesive.

Glass fiber reinforced polymer (GFRP) materials are recently widely applied in marine industry, especially for hulls structures. The high popularity of composites and safety requirements result in development of Structural Health Monitoring (SHM) systems. One of the sensors types that can be permanently integrated with a composite structure and used as a part of SHM system are fiber Bragg grating (FBG) sensors. FBG sensors advantages like small size, high corrosion resistance, and absence of electric current are especially important in marine applications. The goal of the paper is to present FBG sensors application to SHM of a composite fast patrol boat. An array of the sensors was embedded into a boat hull structure. Moreover, accelerometer was utilized to determined maximum accelerations during the power boat operations. The analyses were performed during normal exploitation of the boat performed on the Gulf of Gdansk (southeastern bay of the Baltic Sea) under different sea states and wind speeds.

Railway tracks are the direct supporting structures of the trains, which are vulnerable to produce large deformation under the temperature stress or subgrade settlement. The health status of track is critical, and the track should be routinely monitored to improve safety, lower the risk of excess deformation and provide reliable maintenance strategy. In this paper, the distributed optical fiber sensor was proposed to monitor the continuous deformation of the track. In order to validate the feasibility of the monitoring method, two deformation monitoring tests on one steel rail model in laboratory and on one real railway tack in outdoor were conducted respectively. In the model test, the working conditions of simply supported beam and continuous beam in the rail model under several concentrated loads were set to simulate different stress conditions of the real rail, respectively. In order to evaluate the monitoring accuracy, one distributed optical fiber sensor and one fiber Bragg grating (FBG) sensor were installed on the lower surface of the rail model, the strain measured by FBG sensor and the strain calculated from FEA were taken as measurement references. The model test results show that the strain measured by distributed optical fiber sensor has a good agreement with those measured by FBG sensor and FEA. In the outdoor test, the real track suffered from displacement and temperature loads. The distributed optical fiber sensor installed on the rail can monitor the corresponding strain and temperature with a good accuracy.

Structural health monitoring of composite wing structure during durability test

Additive manufacturing (AM) polymers are applied in many branches of the industry due to the possibility of fast and accurate production of elements with various and complex shapes. Fibre Bragg grating sensors (FBG) are widely applied in structural health monitoring (SHM) systems. The main objective of this research is to perform analyses of the influence of embedded FBG sensors on AM polymer elements’ durability. Two polymers (M3 X and M3 Crystal) with different mechanical properties were analysed. The tests were performed on samples with FBG sensors embedded in (different alignment) and attached to the surfaces of the elements. Firstly, the samples were exposed to elevated or sub-zero temperatures under stable relative humidity levels. The strain in the samples was measured using fibre Bragg grating (FBG) sensors. The achieved results allow us to determine the relationships between strain and temperature for both materials and the differences in their mechanical response to the thermal loading. Then, the samples were subjected to a tensile test. A comparison of the tensile strength values was performed for the samples without and with embedded FBG sensors. The samples after the tensile tests were compared, showing differences in the mechanisms of failures related to the polymers and the thermal treatment influence on the material internal structure. Additionally, strain values measured by the FBG sensors were compared to the strain values achieved from the testing machine showing a good agreement (especially for M3 X) and indicating the differences in the materials’ mechanical properties. The achieved results allow us to conclude there is a lack of influence of embedded FBG sensors on the mechanical durability of AM polymers.