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Compliant mechanism finds its application in high precision devices for precise movements attaining positioning accuracy, micro actuation, aerospace, biomedical engineering, etc. A detailed study of compliant mechanisms capable of transferring coplanar motion/ force along with geometric amplification was undertaken and is presented. An iterative approach was undertaken successively to design and develop a displacement amplifying compliant mechanism (DaCM) within a specified design domain with the objective to obtain geometric amplification (GA) of 3. Also, an application of object holding mechanism using topology optimization has been presented. The optimized topology was further iterated for attaining desired objective function and modifications in the geometry are undertaken considering design for manufacturing and design for assembly principles. With the modifications undertaken, a reduction in (GA)T is observed and the volume fraction of the mechanism is increased than the base model resulting into more strength required for object holding. However, the designer needs to balance between stiffness and compliance based on the objective function of specific application.

Chromosomal instability leading to aneuploidy is pervasive in early human embryos1-3 and is considered as a major cause of infertility and pregnancy wastage4,5. Here we provide several lines of evidence that blastocysts containing aneuploid cells are worthy of in vitro fertilization transfer. First, we show clinically that aneuploid embryos can lead to healthy births, suggesting the presence of an in vivo mechanism to eliminate aneuploidy. Second, early development and cell specification modelled in micropatterned human 'gastruloids' grown in confined geometry show that aneuploid cells are depleted from embryonic germ layers, but not from extraembryonic tissue, by apoptosis in a bone morphogenetic protein 4 (BMP4)-dependent manner. Third, a small percentage of euploid cells rescues embryonic tissue in mosaic gastruloids when mixed with aneuploid cells. Finally, single-cell RNA-sequencing analysis of early human embryos revealed a decline of aneuploidy beginning on day 3. Our findings challenge two current dogmas: that a single trophectoderm biopsy at blastocyst stage to perform prenatal genetic testing can accurately determine the chromosomal make-up of a human embryo, and that aneuploid embryos should be withheld from embryo transfer in association with in vitro fertilization.

The use of ultrasonic guided waves (GW) in analyzing structural integrity with Fiber Bragg grating (FBG) sensors is a promising topic to implement more in the industrial world. The paper deals with the GW-based analysis of an isotropic aluminium structure using the numerical finite element method (FEM). A set of hybrid FBG and piezoelectric transducers (PZT) are modelled to check the quick SHM GW process in isotropic structures. The PZTs are used to excite the GW that is sensed by the FBG. Multiple damaged sites with different frequencies are simulated by changing the stiffness matrix at the specified group of 3D elements. The signal processing study involves using cosine distance formulation to identify changes in the signal paths of the GW. The paper highlights the automated process of FEM modeling coupled with Matlab scripting to check FBG/PZT numerical setup effectively and to identify the damage regions in the whole structure for further verification. The FEM work is an extension and verification of the previously proposed experimental study.

Guided waves (GW) allow fast inspection of a large area and hence have received great interest from the structural health monitoring (SHM) community. Fiber Bragg grating (FBG) sensors offer several advantages but their use has been limited for the GW sensing due to its limited sensitivity. FBG sensors in the edge-filtering configuration have overcome this issue with sensitivity and there is a renewed interest in their use. Unfortunately, the FBG sensors and the equipment needed for interrogation is quite expensive and their number is restricted. In the previous work by the authors the number and location of the actuators was optimized for developing a SHM system with single sensor and multiple actuators. But through the use of the phenomenon of acoustic coupling, multiple locations on the structure may be interrogated with a single FBG sensors. As a result, a sensor network with multiple sensing locations and few actuators is feasible and cost effective. Hence this paper develops the optimization problem for designing an SHM network for use with FBG sensors making use of acoustic coupling. The optimization problem is implemented on a simple aluminum plate. The directionality, bond efficiency and the factors influencing the acoustic coupling are taken into consideration for optimizing the sensor network. A multi-objective optimization problem is defined and solved using non-sorting genetic algorithm (NSGA). The results indicate that indeed a multi-objective optimization is necessary and has potential to improve the SHM system performance.

This paper aims to investigate the use of ultrasonic guided wave (GW) propagation mechanism and the assessment of debonding in a sandwich composite structure (SCS) using a multi-step approach. Towards this, a series of GW propagation-based laboratory experiments and numerical simulations have been carried out on the SCS sample. The debonding regions of variable size and locations were assessed using a pre-defined network of piezoelectric lead zirconate transducers (PZT). Besides, several artificial masses were also placed in the SCS to validate the multi-step structural health monitoring (SHM) strategy. The SHM approach uses a proposed quick damage identification matrix maps and an improved elliptical wave processing (EWP) strategy of the registered GW signals to detect the locations of debonding and other damages in the SCS. The benefit of the proposed damage identification map is to locate the damaged area (sectors) quickly. This identification step is followed by applying the damage localization step using the improved EWP only on the previously identified damage sector region. The proposed EWP has shown the potential to effectively locate the hidden multiple debonding regions and damages in the SCS with a reduced number of calculations using a step-wise approach that uses only a selected number of grid points. The paper shows the effectiveness of the proposed approach based on data gathered from numerical simulations and experimental studies. Thus, using the above-mentioned SHM strategy debondings and damages present within and outside the sensor network are localized. The results were cross verified with nondestructive testing (NDT) methods such as infrared thermography and laser Doppler vibrometry.

Structural Health Monitoring (SHM) systems allow maintenance planning which reduces maintenance costs. These systems may also allow lifetime extension of structures which allows reduction in lifecycle costs of structures. As a result, SHM systems have been of interest to researchers in civil and mechanical engineering sectors. The SHM system should be ideally low cost, suitable for continuous monitoring, and able to detect small levels of damage. The sensitivity to small levels of damage is even more important for composite structures as composites have low damage tolerance. Electromechanical Impedance (EMI)-based techniques have been proposed due to their sensitivity to low levels of damage. Furthermore, due to their high frequency of operation they are immune to ambient noise. Most of the studies using the EMI technique were limited to damage detection only. Recently some studies have used a network of sensors for EMI measurements and used them for damage localization. This paper follows on this trend of using a network of sensors for damage localization using EMI technique. A novel inverse algorithm is proposed for the damage localization. For the inverse technique, an analytical model for the correlation of distance and angle with the damage index (DI) is developed. This model is then used to generate a database of the DIs for a large number of damage scenarios. The measured DIs from the structure are then compared with this database and the scenario with the least mean error in the DIs is the predicted damage scenario. The algorithm takes into consideration the modeling errors and the measurement errors through regularization and in turn allows more accurate damage localization. The method is applied on different damage scenarios on an unidirectional composite sample. Some sensitivity studies such as the performance of the method using different fits have been carried out. In addition, the accuracy of damage localization of the proposed technique has been compared to a localization technique found in literature. The results show that indeed the proposed algorithm works and improves the damage localization using the EMI technique.

The paper emphasizes an effective quantification of hidden damage in composite structures using ultrasonic guided wave (GW) propagation-based structural health monitoring (SHM) and an artificial neural network (ANN) based active infrared thermography (IRT) analysis. In recent years, there has been increased interest in using a global-local approach for damage localization purposes. The global approach is mainly used in identifying the damage, while the local approach is quantifying. This paper presents a proof-of-study to use such a global-local approach in damage localization and quantification. The main novelties in this paper are the implementation of an improved SHM GW algorithm to localize the damages, a new pixel-based confusion matrix to quantify the size of the damage threshold, and a newly developed IRT-ANN algorithm to validate the damage quantification. From the SHM methodology, it is realized that only three sensors are sufficient to localize the damage, and an ANN- IRT imaging algorithm with only five hidden neurons in quantifying the damage. The robust SHM methods effectively identified, localized, and quantified the different damage dimensions against the non-destructive testing-IRT method in different composite structures.

Data from guided wave propagation in structures, produced by piezoelectric elements, can offer valuable information regarding the possible existence of flaws. Numerical models can be used to complement the attained data for refining the potential for flaw characterization. Unfortunately, evaluation of these models remains computationally expensive, especially for small defects, due to the short wavelength required for detection and, the in turn fine discretization in time and space. This renders real–time simulation infeasible, rendering GW–approaches less attractive for inverse problem formulations, where the forward problem needs to be solved several times. We propose an accelerated computation method, which exploits the properties of guided waves interacting with defects, where an extra band of waves is created, whose phase is differentiated, depending on the location of the flaw (e.g. notch) within the medium. To expedite the actual simulation for the inverse problem, the system is parametrized in terms of the location of the flaw and, in an offline phase, is repeatedly solved to produce snapshots of the system’s response. The snapshots are used to create a physics–informed interpolation of the solution of the wave propagation problem for different flaw locations. The gained information is then used in an inverse setting for localising the defect using an evolution strategy as a means to stochastic, derivative-free numerical optimization. The method is demonstrated in simulations of a 2D slice of a thin plate., Structural Health Monitoring 2021: Enabling Next Generation SHM for Cyber-Physical Systems, ISBN:978-1-60595-687-9

Recent advancements in fiber optic methods have enabled their use for guided wave sensing. It opens up new possibilities for Structural Health Monitoring. The aim of this paper is to provide insight for the physics related to guided wave propagation and coupling between the optical fiber and solid structure. For this purpose, a new approach for non-matching interface based on Lagrange multipliers and the time domain spectral element method was developed. A parallelized code has been implemented in order to simulate the guided wave propagation in the structure, its coupling into the optical fiber and the propagation in the fiber in a computationally efficient way. The paper presents four studies showing the efficacy of the modeling approach. The paper first shows the improvement in the computation speed through the use of parallelization and a more efficient implementation. Then the results of the simulation of wave propagation in the fiber are compared with results from previous simulation studies using commercially available software. The third study shows that the spectral element method is able to capture the directional sensitivity of optical fiber based sensors. Lastly, the simulation is used for detection of simulated damage using the spectral element method based simulation. The results indicate that indeed the spectral element implementation is able to recreate the wave coupling phenomena, capture the physics of the system including directional sensitivity and reflections from damage.

Guided waves (GW) and acoustic emission (AE) -based structural health monitoring (SHM) have widespread applications in structures, as the monitoring of an entire structure is possible with a limited number of sensors. Optical fiber-based sensors offer several advantages, such as their low weight, small size, ability to be embedded, and immunity to electro-magnetic interference. Therefore, they have long been regarded as an ideal sensing solution for SHM. In this review, the different optical fiber technologies used for ultrasonic sensing are discussed in detail. Special attention has been given to the new developments in the use of FBG sensors for ultrasonic measurements, as they are the most promising and widely used of the sensors. The paper highlights the physics of the wave coupling to the optical fiber and explains the different phenomena such as directional sensitivity and directional coupling of the wave. Applications of the different sensors in real SHM applications have also been discussed. Finally, the review identifies the encouraging trends and future areas where the field is expected to develop.

Guided waves (GW) allow fast inspection of a large area and hence have received great interest from the structural health monitoring (SHM) community. Fiber Bragg grating (FBG) sensors offer several advantages but their use for GW sensing has been limited due to their limited sensitivity. FBG sensors in the edge-filtering configuration have overcome this issue with sensitivity and there is a renewed interest in their use. It has been seen that depending on the ratio of the wavelength of the propagating wave to the gauge length of the FBG, the mechanism of the transduction of the wave measurement is different. A large ratio leads to a more uniform strain over the FBG leading to a shift in the frequency, while a non-uniform strain due to a short wavelength, leads to the peak widening. The present paper studies this phenomena and develops a signal processing technique for the filtering of the modes.

Guided waves (GW) are one of the most promising tools for structural health monitoring (SHM). They allow fast inspection of a large area. Thus GW based SHM is finding applications in several fields like aerospace, automotive, wind energy, etc. Recently, the use of optical fiber sensors and more specifically fiber Bragg grating (FBG) sensors are getting increasing attention from researchers for GW sensing. The FBG sensors are deployed in the edge-filtering configuration for the sensing. The FBG sensors offer several advantages such as light weight and small size. They also offer the chance to be embedded, and multiplexed. Unfortunately, they are passive sensors and show directional sensitivity. Also they are relatively expensive. Thus there is a need to optimize the usage of the sensors to obtain maximum information with minimum cost. Several different optimization strategies have been proposed in the literature including gradient based as well as evolutionary algorithms. For a non-linear, non-differentiable cost function evolutionary algorithms (EA) such as genetic algorithm, particle swarm optimization, etc. have shown a lot of promise. In this paper the Covariance-Matrix Adaptation Evolution Strategy (CMAES) has been employed for the sensor network optimization for GW based SHM. First, the ability of the algorithm to obtain the global optima is investigated and then the results are compared with the genetic algorithm (GA) which is the most commonly used EA. 3 different criteria for the optimization are used namely, the coverage with 3 actuator-sensor (AS) pairs (cov3), coverage with 1 AS pair (cov1), and the scalarized combination of cov3 and cov1. The results indicate that indeed CMAES is a powerful optimization tool for the sensor placement optimization problem.

Guided waves (GW) allow fast inspection of a large area and hence have received great interest from the structural health monitoring (SHM) community. Fiber Bragg grating (FBG) sensors offer several advantages but their use has been limited for the GW sensing due to their limited sensitivity. FBG sensors in the edge-filtering configuration have overcome the issue with sensitivity and there is a renewed interest in their use. The FBG sensors have directional sensitivity and are passive in nature. This makes it difficult to apply the existing signal processing and damage detection techniques such as tomography, phased array approach etc. As a result, there is a need to develop novel damage detection techniques which take into consideration the specific limitations of the use of FBG sensors. This paper applies the ellipse and hyperbola based techniques for a FBG sensor based network. The paper identifies the specific challenges and applies solutions to overcome those challenges. A comparative assessment of the two methods is presented with the help of experimental data.

Structural Health Monitoring (SHM) systems have a potential to reduce lifecycle costs of structures. As a result, there is a lot of active research in the area for SHM of civil and mechanical structures. Guided waves (GW) based SHM techniques allow monitoring of large plate-like structures with a few sensors and have been identified as the most promising of techniques for SHM. Fibre Bragg grating (FBG) sensors due to their low weight, and ability to be multiplexed have been long thought to be ideal sensors for SHM. The recent development of the edge filtering approach has increased their sensitivity to GW sensing and made them ideal sensors. Unfortunately the FBG sensors are passive sensors and show directional sensitivity. These operational constraints make extension of the earlier developed GW based SHM techniques for FBG sensors difficult. Recently the authors developed a technique for damage detection specifically designed for a network with FBG sensors. This paper builds on the past work by the authors and develops a methodology for a design of an actuator–sensor (AS) network for improving the damage assessment capability of the previously proposed method. The paper develops a multi objective optimization technique for the joint optimization of actuator and sensor placement for a network with FBG sensors. The joint optimization of the actuators and sensors is necessary due to the passive nature of the FBG sensors and also incorporates the directional nature of the FBG sensors. The paper develops an integer encoded NSGA-II for the optimization of the AS network. The objectives for the optimization are derived from the specific damage detection technique tailored for the use of FBG sensors. The objective are: coverage with at least 2 AS pairs, coverage with at least 1 edge reflected path and the cost of the deployed network. The results indicate that the encoding of the objectives of the optimization is valid and indeed the damage detection capabilities of the AS network are as predicted analytically. The paper for the first time develops a joint optimization of network for FBG sensors. It is also the first attempt at a truly multi-objective optimization of the AS network and promises to have applications on real structures.

Fiber Bragg grating (FBG) sensors have long been thought of as the ideal sensors for structural health monitoring (SHM) due to their small size, light weight, ability to be embedded and ability to be multiplexed. So, FBG sensors have been commonly used for strain based SHM. Their use for ultrasonic guided wave (GW) measurements in the traditional wavelength division multiplexing approach was tried as well, but did not get accepted widely due to the low sensitivity. In the recent times, a renewed interest is seen in the use of FBG sensors for GW measurements using the edge reflection approach which increases the sensitivity several folds. This paper reports a very interesting phenomena, shown by the FBG sensors. The mechanism of the measurement of the incident GW is different based on the relative ratio of the wavelength of the incident GW ( λ G W ) and the grating length (L) of the FBG sensor. For λ G W / L ≫ 1 the propagating wave leads to uniform strain over the FBG resulting in the shift of the Bragg wavelength. For the λ G W / L ≈ 1 the FBG experiences non-uniform strain over the FBG which results in the distortion of the spectrum (widening or narrowing) of the peak. By separating these effects on the FBG, mode filtering may be achieved. The mode-filtered data is then used for damage detection and damage localization. Modifications have been proposed to the elliptical approach which makes use of the filtered modes and removes the unwanted peaks in the signal stemming from the other mode. The methodology is validated on a simple aluminum plate with simulated damage scenarios (added mass). The results indicate that indeed the mode-filtered signals improve the damage localization performance of the actuator-sensor network.

Structural health monitoring (SHM) systems help in reducing maintenance cost and avoiding catastrophic failure of the structure. As a result, they have been a focus of research for the past few decades. Ideally, the methods employed should be low cost and able to detect and localize small levels of damage reliably and accurately. This paper describes a guided waves (GW) based two-step technique for damage detection and localization using fiber Bragg grating (FBG) sensors. The FBG sensors offer benefits such as the ability to be embedded and multiplexed as well as being lightweight and insensitive to electric and magnetic fields, and they have long been seen as a promising solution for the GW measurements in structures. Unfortunately, in the conventional wavelength-based interrogation they have very low signal to noise ratio and as a result low sensitivity. Therefore, the FBG sensor is incorporated in the edge filtering configuration. The major challenges in the use of FBG sensors for GW-based detection are their directional sensitivity and passive nature. The passive nature leads to the reduction in the available actuator&ndash, sensor (AS) pairs while the directionality makes the signal processing a challenge. The proposed two-step methodology overcomes these shortcomings of FBG sensors. In the first step the amplitude weighted elliptical approach is used to identify the hotspots due to the inadequate number of AS pairs, the elliptical approach is not sufficient for damage localization. Therefore, in order to further localize the damage the edge reflection based ray-tracing approach is implemented in the second step. Through the two step method, the damage is accurately located. The paper provides the proof of concept of the proposed methodology on an aluminum plate with simulated damage. The results indicate, that indeed the two-step methodology allows accurate damage localization and overcomes the possibility of false detections.

This paper presents a natural frequency-based method for concentrated mass localization in beam-like structures. The localization of a concentrated mass is achieved by developing a novel index using relative natural frequency change (RNFC) curves and measured RNFCs. The index shows the exact location of the concentrated mass for asymmetrical beams and shows general locations of the concentrated mass including the actual location and its fake counterpart at the symmetrical position for symmetrical beams. With the general locations known, some local inspection methods can be used to identify the specific location. The effectiveness of the proposed method is confirmed by experimental investigation of a simply-supported beam and a clamped-free beam carrying a concentrated mass. In the experiment, the natural frequencies of the beam before and after adding a concentrated mass are measured by non-contact measurement using a scanning laser Doppler vibrometer.

The deployment cost of the structural health monitoring (SHM) system is the major argument against the more widespread use of the structural health monitoring techniques. Optimization of sensor placement offers an opportunity to reduce the cost of the SHM system without compromising on the quality of the monitoring approach. Several studies in the area of optimization of sensor placement for SHM applications have been undertaken but the approach has been rather application specific. This article is an attempt to present an unbiased state of the art of the work carried out in the area. The article is targeted towards researchers working in the field of structural health monitoring and optimization of sensor placement as well as practising engineers. This article reviews the work in the area of optimization of sensor placement. It first presents the definition of the optimization problem and then describes each step of the optimization. The current state of the art is then classified based on the techniques for which the optimization of sensor placement has been optimized. The article covers vibration-based monitoring, strain monitoring and elastic wave-based monitoring, as in the eyes of the authors these three techniques are most commonly used and accepted in the SHM community. The article later discusses the different optimization algorithms that have been applied in the literature. The article highlights the different pitfalls of the optimization algorithms and the countermeasures different researchers have proposed to overcome the known shortcomings. In the later section, the multi-objective optimization or the problem definition, keeping in mind the structural as well as executional demands, is discussed. A section has also been developed to showcase the use of optimization of sensor placement techniques’ data fusion–based systems.

Guided waves (GW) allow fast inspection of a large area and hence have received great interest from the structural health monitoring (SHM) community. Fiber Bragg grating (FBG) sensors offer several advantage but their use has been limited for the GW sensing due to their limited sensitivity. But the use of the edge-filtering approach in the remote bonded configuration has enhanced their sensitivity and allows use of these sensors for GW measurement. Although these sensors are light in weight and need no additional wiring there is still significant motivation to reduce the number of sensors while maintaining the quality and reliability of the assessment due to their high cost. In addition, for the safety and reliability of the structures it is of utmost importance that the entire structure can be investigated. Hence it is necessary to optimize the locations of the sensors in order to maximize the coverage while limiting the number of sensors used. The problem posed for the optimization of the FBG sensors for GW is different from any other work in this area due to the directional sensitivity shown by these sensors. Hence a novel optimization problem is developed for the application of FBG sensors for the GW based SHM. This paper develops a genetic algorithm based optimization methodology to incorporate the directional sensitivity. The methodology is shown analytically, using inputs from experimental investigations.

Structural Health Monitoring (SHM) systems allow early detection of damage which allows maintenance planning and reduces the maintenance cost.Several researchers have proposed use of Neutral Axis (NA) location as a damage sensitive feature. It has been shown that through proper signal processing, NA location is insensitive to measurement noise and ambient temperature changes. This paper presents a methodology for successful NA tracking under changing axial loading conditions. The novel methodology is validated using numerical data as well as experimental results. This paper demonstrates the development of a Kalman Filter (KF) based NA tracking strategy under different loading conditions. The methodology was employed on a composite beam instrumented with fiber optic strain sensors. The stable NA tracking under changing loading conditions allows the application of the NA as a damage sensitive feature. The change in NA location is used to detect delamination in the beam. The method has been validated through a numerical model and experiments. The results show that the novel formulation of the KF for NA tracking allows more robust use of NA location as a damage sensitive feature in a wider range of applications.

The paper presents a proof of concept of a two-step methodology for the damage detection and localization in a scaled model of an offshore support structure. Two damage scenarios have been simulated for validating the methodology. The first damage scenario investigated is deterioration of the support condition which is simulated by removing the attachment of a leg of a tripod to the table and the second scenario is simulated by unbolting the flange to create an artificial circumferential crack in the upper brace of the tripod structure. The strain measurements have been obtained from a network of Fibre Bragg Grating (FBG) sensors bonded to the model. The damage detection is carried out in the first step using the root mean square deviation (RMSD) estimator. If the RMSD value is above a certain threshold, damage is said to be detected. Experimental results show that additional peaks appear in some frequency regions revealing vibration modes which are associated with damage in the structure. Applying the RMSD estimator to the regions where new peak has emerged it is possible to detect the damage. Once the damage is detected the damage isolation factor (DIF) is used for the damage isolation (level II damage detection). The DIF is based on the RMSD as well, and involves normalization using the rosette set values. Based on the results, it is seen that the DIF shows good localization performance. This good performance can be attributed to the ability of the parameter to overcome biases due to higher relative amplitude of vibration of some rosettes.

The paper presents multiple impact damage detections and characterization in a multi-layered carbon fiber reinforced polymer structure using a multi-step combination of the global area and local area damage detection methods. A global area analysis using laser Doppler vibrometer (LDV) with piezoelectric lead zirconate titanate (PZT) actuator-based guided waves (GW) excitation was used to detect and locate the damage. The GW full wavefield (FWF) mode conversion and root mean square (RMS) based LDV studies helped to visualize the impact crack damage (ICD) when tested at varying excitation frequencies. The experimental results were cross-verified numerically using the spectral element method (SEM). The implemented structural health monitoring (SHM) based sectorial elliptical code (SEC) reduced the overall calculation time in damage localization and accurately identified the damage from experimental and numerical data. An infrared thermography (IRT)-based crack identification algorithm was developed in pinpointing the ICD shape. The automatic method removes the influence of high heat sources and highlights the damage zones easily. The accuracy of the localization strategy was successfully verified with non-contact active IRT analysis. The crack size and damage severity were quantified using the ultraviolet radiation (UVR) method with a solution mixture based organic dye. The global area method allows detecting possible damage, validated and quantified with the non-destructive testing (NDT) techniques.

This paper presents a two-step method for the identification of additional masses in beam structures. In the first step, relative natural frequency change (RNFC) curves are developed as an indicator for identifying the possible locations of additional masses at the global level. The RNFC curves based method allows detection of possible mass locations using natural frequencies alone and as such is a significant improvement over the state of the art. To further identify the precise locations of the masses, guided wavefield imaging is used for local mass detection in the second step. The two-step method is successfully applied for the precise localization of additional masses on a simply-supported beam. The paper firstly shows that additional mass-induced RNFC curves are different from those caused by cracks in beams. As a result, a theoretical formulation and validation of additional mass identification is needed and is the main novelty of the paper.

Structural health monitoring (SHM) systems have a potential to reduce lifecycle costs of structures. They may be used for maintenance planning which reduces the maintenance cost as well as for lifetime extension. As a result, there is a lot of active research in the area for SHM of civil and mechanical structures. The SHM system should be low cost, suitable for continuous monitoring, able to detect small levels of damage. Guided waves (GW) based SHM techniques allow monitoring of large plate-like structures with few sensors and have been identified as the most promising of techniques for SHM. Several different actuators and sensors have been developed and used for the GW based SHM. FBG sensors due to their low weight, and ability to be multiplexed have been long thought to be an ideal sensors for SHM. The recent development of the edge filtering approach has increased their sensitivity to GW sensing and made them ideal sensors. Unfortunately the FBG sensors are passive sensors and show directional sensitivity. These operational constraints make extension of the earlier developed GW based SHM techniques for FBG sensors difficult. Recently the authors developed a technique for damage detection specifically designed for a network with FBG sensors. This paper develops a methodology for a design of an actuator-sensor (AS) network for improving the damage assessment capability using the developed method. The paper develops a two-step methodology for the optimization of actuator placement for an AS network with FBG sensors. In the first step the number of actuators needed for the optimization are determined based on actuator densities. Once the number of actuators is known, a genetic algorithm (GA) is developed for the optimization of the their positions. The cost function is developed based on two new metrics (namely coverage2—coverage with at least 2 AS pairs and coverageR—radial coverage based on edge reflections) which are defined by the application demand. The optimized placement is then used to successfully detect and localize the damage. The study also shows the merit in the use of the specific metrics and the sufficiency of the metrics developed for improving the damage detection capability of the specific method.

Structural Health Monitoring (SHM) systems allow early detection of damage which allows maintenance planning and reduces the maintenance cost. The SHM system should be low cost, suitable for continuous monitoring, able to detect small levels of damage, and insensitive to ambient loading, changes in ambient temperature, and measurement noise. Neutral Axis (NA) location is a function of the condition of the structure alone and may be used as a damage sensitive feature. It has been shown that through proper signal processing, NA location is insensitive to measurement noise and ambient temperature changes. This paper aims at validating the use of NA as a damage sensitive feature through experimental study. This paper demonstrates the use of multi-rate Kalman Filter (KF) for accurate estimation of NA under different loading conditions. The methodology was employed on a composite beam instrumented with fiber optic strain sensors. Delamination was introduced in the beam and then progressively increased. The beam was subjected to different loading and temperature conditions for the different damage scenarios. The measured strains were then used for NA tracking. The results show that indeed the NA location may be used as a damage sensitive feature. Some of the loading scenarios were difficult to realise in the laboratory, so these loading scenarios were applied on a validated Finite Element (FE) model of the composite beam. The results indicate that under these dynamic loading scenarios, NA may be used for SHM. Based on the results it can be concluded that KF based NA tracking may be applied to structures for in-service SHM.

Structural Health Monitoring (SHM) and Non Destructive Evaluation (NDE) is considered a necessity for optimized lightweight structures. Thus several SHM strategies have been suggested for assessing the condition of such structures. The key aspect of any SHM method is the choice of the damage sensing feature. Ideally the damage sensing feature should be sensitive to small levels of damage, insensitive to measurements noise and ambient condition changes, like loading conditions, temperature, moisture etc. For beam structures the Neutral Axis (NA) is known as a very informative damage sensing feature. The NA position depends on the condition of the structure alone and it is insensitive to the load level. Through the use of advanced data processing tools like the Kalman Filter (KF), the NA estimation can be made robust in the presence of measurement noise and changing ambient conditions. In this paper, the use of a KF based NA estimation technique is investigated for determining the size of a damage. The methodology is employed in experiments on a thin-walled beam with rectangular cross-section under 4-point bending. Cracks of different lengths are introduced in the beam and based on the strain measurements the NA is estimated. The estimated position of the NA is then correlated with the size of the damage.

Guided waves (GW) allow fast inspection of a large area and hence have attracted research interest from the structural health monitoring (SHM) community. Thus, GW-based SHM is ideal for thin structures such as plates, pipes, etc., and is finding applications in several fields like aerospace, automotive, wind energy, etc. The GW propagate along the surface of the sample and get reflected from discontinuities in the structure in the form of boundaries and damage. Through proper signal processing of the reflected waves based on their time of arrival, the damage can be detected and isolated. For complex structures, a higher number of sensors may be required, which increases the cost of the equipment, as well as the mass. Thus, there is an effort to reduce the number of sensors without compromising the quality of the monitoring achieved. It is of utmost importance that the entire structure can be investigated. Hence, it is necessary to optimize the locations of the sensors in order to maximize the coverage while limiting the number of sensors used. A genetic algorithm (GA)-based optimization strategy was proposed by the authors for use in a simple aluminum plate. This paper extends the optimization methodology for other shape plates and presents experimental, analytical, and numerical studies. The sensitivity studies have been carried out by changing the relative weights of the application demands and presented in the form of a Pareto front. The Pareto front allows comparison of the relative importance of the different application demands, and an appropriate choice can be made based on the information provided.

Guided waves (GW) are one of the most promising tools for structural health monitoring (SHM). They allow fast inspection of a large area. Thus GW based SHM is finding applications in several fields like aerospace, automotive, wind energy, etc. The GW propagate along the surface of the sample and get reflected from the boundaries and damage. Through proper signal processing of the reflected waves based on their time of arrival, the damage can be detected and isolated. For complex structures a higher number of sensors may be required which increases the cost of the equipment as well as the mass. The mass increase is detrimental in aerospace applications where the mass leads to increase in operation cost. Thus there is an effort to reduce the number of sensors. In addition, for the safety and reliability of the aircraft it is of utmost importance that the entire structure can be investigated. Hence it is necessary to optimize the locations of the sensors in order to maximise the coverage while limiting the number of sensors used. A genetic algorithm (GA) based optimization strategy was previously proposed by the authors for the use in a simple aluminium plate. This paper extends the optimization methodology for a composite plate with additional structural elements. The work starts with extension of the optimization strategy and the implementation of the anisotropic properties and structural elements in the optimization problem.