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Heung Soo Kim - One of the best experts on this subject based on the ideXlab platform.
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Classification and prediction of multidamages in Smart Composite laminates using discriminant analysis
Mechanics of Advanced Materials and Structures, 2020Co-Authors: Asif Khan, Heung Soo KimAbstract:A supervised machine learning framework is proposed for local assessments of delamination and transducer debonding in Smart Composite laminates while using their low-frequency structural vibrations...
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Damage detection in Smart Composite structures using low frequency structural vibration
Nano- Bio- Info-Tech Sensors and 3D Systems IV, 2020Co-Authors: Asif Khan, Heung Soo Kim, Jung Woo SohnAbstract:Output-only based damage assessment of delaminated Smart Composite structures is increasingly appealing due to its easy availability in real engineering applications. In this work, structural vibration responses of the pristine and delaminated Composite structures are processed via Fast Fourier Transform (FFT) and Convolutional Neural Network (CNN) for the classification of healthy and various damaged cases. The dynamic model for the healthy and delaminated Smart Composite laminates is developed by incorporating of improved layerwise theory, higher-order electric potential field, and finite element method. Structural vibration responses are obtained through a surface bonded piezoelectric sensor by solving the electromechanically coupled dynamic model in the time domain. FFT is used to construct vibration-based images from the transient responses of the sensor and CCN is used to classify those images into healthy and damaged classes. The confusion matrix of CNN showed physically consistent results and an overall classification accuracy of 90% was obtained. The pre-trained CNN was also tested to predict labels for new cases of delaminations in the Smart Composite laminates. The essence of the proposed method is that it requires only low-frequency structural vibration responses for the detection and localization of delamination in Smart Composite laminates.
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Damage assessment of Smart Composite structures via machine learning: a review
JMST Advances, 2019Co-Authors: Asif Khan, Jae Kyong Shin, Heung Soo Kim, Nayeon Kim, Byeng Dong YounAbstract:Composite materials are heterogeneous in nature and suffer from complex non-linear modes of failure, such as delamination, matrix crack, fiber-breakage, and voids, among others. The early detection of damage in Composite structures, such as airplanes, is imperative to avoid catastrophic failure and tragic consequences. This paper reports on the use of machine learning techniques for the damage assessment (i.e., detection, quantification, and localization) of Smart Composite structures. The success of the machine learning paradigm for damage assessment depends on the representational capability of the discriminative features for the problems of interest. However, from a practical standpoint, it is not possible to define a global or superset of discriminative features that could discriminate between damaged and undamaged states of the structures, and simultaneously make a distinction between various modes of failures. In addition, one machine learning algorithm may show optimum performance for the discriminative features of a particular problem but fails for others. This article focuses on a review of discriminative features and the corresponding machine learning algorithms (both supervised and unsupervised), for various types of damage in Smart Composite structures.
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structural vibration based classification and prediction of delamination in Smart Composite laminates using deep learning neural network
Composites Part B-engineering, 2019Co-Authors: Asif Khan, Soochul Lim, Heung Soo KimAbstract:Abstract This paper proposes a Convolutional Neural Network (CNN) based approach for the classification and prediction of various types of in-plane and through-the-thickness delamination in Smart Composite laminates using low-frequency structural vibration outputs. An electromechanically coupled mathematical model is developed for the healthy and delaminated Smart Composite laminates, and their structural vibration responses are obtained in the time domain. Short Time Fourier Transform (STFT) is employed to transform the transient responses into two-dimensional spectral frame representation. A convolutional neural network is incorporated to distinguish between the damaged and undamaged states, as well as various types of damage of the laminated Composites, by automatically extracting discriminative features from the vibration-based spectrograms. The CNN showed a classification accuracy of 90.1% on one healthy and 12 delaminated cases. The study of the confusion matrix of CNN provided further insights into the physics of the problem. The predictive performance of a pre-trained CNN classifier was also evaluated on unseen cases of delamination, and physically consistent results were obtained.
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Assessment of delaminated Smart Composite laminates via system identification and supervised learning
Composite Structures, 2018Co-Authors: Asif Khan, Heung Soo KimAbstract:Abstract This paper proposes the synergetic integration of system identification and artificial intelligence for the detection and assessment of delamination damages in Smart Composite laminates . An electromechanically coupled mathematical model is developed for the healthy and delaminated Smart Composite laminates on the basis of improved layerwise theory, higher order electric potential field and finite element method . A discriminative feature space is constructed for the healthy and delaminated structures via system identification from their structural vibration responses. The discriminative features are used for the training and cross-validation of various supervised machine learning classifiers and an optimal classifier is identified. The optimal classifier is employed to make predictions on unseen test delamination cases, and its predictions are validated via a dimensionality reduction tool. The obtained results show that the proposed technique could be employed as a reliable tool for nondestructive evaluation of Smart Composite laminates.
Asif Khan - One of the best experts on this subject based on the ideXlab platform.
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Classification and prediction of multidamages in Smart Composite laminates using discriminant analysis
Mechanics of Advanced Materials and Structures, 2020Co-Authors: Asif Khan, Heung Soo KimAbstract:A supervised machine learning framework is proposed for local assessments of delamination and transducer debonding in Smart Composite laminates while using their low-frequency structural vibrations...
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Damage detection in Smart Composite structures using low frequency structural vibration
Nano- Bio- Info-Tech Sensors and 3D Systems IV, 2020Co-Authors: Asif Khan, Heung Soo Kim, Jung Woo SohnAbstract:Output-only based damage assessment of delaminated Smart Composite structures is increasingly appealing due to its easy availability in real engineering applications. In this work, structural vibration responses of the pristine and delaminated Composite structures are processed via Fast Fourier Transform (FFT) and Convolutional Neural Network (CNN) for the classification of healthy and various damaged cases. The dynamic model for the healthy and delaminated Smart Composite laminates is developed by incorporating of improved layerwise theory, higher-order electric potential field, and finite element method. Structural vibration responses are obtained through a surface bonded piezoelectric sensor by solving the electromechanically coupled dynamic model in the time domain. FFT is used to construct vibration-based images from the transient responses of the sensor and CCN is used to classify those images into healthy and damaged classes. The confusion matrix of CNN showed physically consistent results and an overall classification accuracy of 90% was obtained. The pre-trained CNN was also tested to predict labels for new cases of delaminations in the Smart Composite laminates. The essence of the proposed method is that it requires only low-frequency structural vibration responses for the detection and localization of delamination in Smart Composite laminates.
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Damage assessment of Smart Composite structures via machine learning: a review
JMST Advances, 2019Co-Authors: Asif Khan, Jae Kyong Shin, Heung Soo Kim, Nayeon Kim, Byeng Dong YounAbstract:Composite materials are heterogeneous in nature and suffer from complex non-linear modes of failure, such as delamination, matrix crack, fiber-breakage, and voids, among others. The early detection of damage in Composite structures, such as airplanes, is imperative to avoid catastrophic failure and tragic consequences. This paper reports on the use of machine learning techniques for the damage assessment (i.e., detection, quantification, and localization) of Smart Composite structures. The success of the machine learning paradigm for damage assessment depends on the representational capability of the discriminative features for the problems of interest. However, from a practical standpoint, it is not possible to define a global or superset of discriminative features that could discriminate between damaged and undamaged states of the structures, and simultaneously make a distinction between various modes of failures. In addition, one machine learning algorithm may show optimum performance for the discriminative features of a particular problem but fails for others. This article focuses on a review of discriminative features and the corresponding machine learning algorithms (both supervised and unsupervised), for various types of damage in Smart Composite structures.
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structural vibration based classification and prediction of delamination in Smart Composite laminates using deep learning neural network
Composites Part B-engineering, 2019Co-Authors: Asif Khan, Soochul Lim, Heung Soo KimAbstract:Abstract This paper proposes a Convolutional Neural Network (CNN) based approach for the classification and prediction of various types of in-plane and through-the-thickness delamination in Smart Composite laminates using low-frequency structural vibration outputs. An electromechanically coupled mathematical model is developed for the healthy and delaminated Smart Composite laminates, and their structural vibration responses are obtained in the time domain. Short Time Fourier Transform (STFT) is employed to transform the transient responses into two-dimensional spectral frame representation. A convolutional neural network is incorporated to distinguish between the damaged and undamaged states, as well as various types of damage of the laminated Composites, by automatically extracting discriminative features from the vibration-based spectrograms. The CNN showed a classification accuracy of 90.1% on one healthy and 12 delaminated cases. The study of the confusion matrix of CNN provided further insights into the physics of the problem. The predictive performance of a pre-trained CNN classifier was also evaluated on unseen cases of delamination, and physically consistent results were obtained.
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Assessment of delaminated Smart Composite laminates via system identification and supervised learning
Composite Structures, 2018Co-Authors: Asif Khan, Heung Soo KimAbstract:Abstract This paper proposes the synergetic integration of system identification and artificial intelligence for the detection and assessment of delamination damages in Smart Composite laminates . An electromechanically coupled mathematical model is developed for the healthy and delaminated Smart Composite laminates on the basis of improved layerwise theory, higher order electric potential field and finite element method . A discriminative feature space is constructed for the healthy and delaminated structures via system identification from their structural vibration responses. The discriminative features are used for the training and cross-validation of various supervised machine learning classifiers and an optimal classifier is identified. The optimal classifier is employed to make predictions on unseen test delamination cases, and its predictions are validated via a dimensionality reduction tool. The obtained results show that the proposed technique could be employed as a reliable tool for nondestructive evaluation of Smart Composite laminates.
Morvan Ouisse - One of the best experts on this subject based on the ideXlab platform.
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A new method for Poisson’s ratio measurement with time-of-flight technique: application to the preliminary design of Smart Composite structures
2019Co-Authors: Xianlong Chen, Rémy Lachat, Yann Meyer, Morvan OuisseAbstract:Smart Composite structures, which are able to modify their mechanical properties with respect to their environment (e.g. active vibration control), to interact with other structures (e.g. mechatronic) or with human beings (e.g. Human-Machine Interaction), are widely used in the modern industrial fields (e.g. aerospace), due to the intensification of the operational dynamic environment and an increase of durability requirements from the customers. Conventionally, the piezoelectric transducers are glued on the surface of the structure and the power and control electronics are away. To protect the transducer elements and their connections and develop some industrially products in "plug and play" mode, a Smart Composite structure is designed and manufactured in our lab, a wide distributed network of piezo ceramics elements has been integrated into the heart of the Composite during the manufacturing process of Composite structures. To meet the technical specifications of Smart Composite structures, in particular for complex geometries, it is necessary to master the manufacturing process and consequently the material parameters of the manufactured Composite. Indeed, during the preliminary design phase, these parameters have to be absolutely known. A design approach based on engineering system theory and uncertainty calculation is applied to characterize the Smart Composite structures manufactured. In this paper, a Time-of-Flight method is developed in order to extract the elastic properties of Smart Composite structures. This technique is based on the duration measurements of wave propagation with a simple and low-cost experimental setup. Integrated piezoelectric transducers are used as both transducer and actuator. This method operates the intrinsic abilities of Smart Composite structures, it is much easier and faster than the model techniques, which are widely used nowadays. Especially for Poisson’s Ratio, this method can extract this parameter rapidly without any complex numerical model by analyzing the phase changes of output signals. In fact, the received waveform contains two types of waves, symmetric and antisymmetric, the elastic properties can be directly calculated based on plate wave propagation theory. In this research, a set of plates with piezo ceramic on each corner are manufactured, the elastic properties of the chosen material are accurately known. Then the Time-of-Flight method will be used for extracting the elastic properties of the plates. A series of sinusoidal burst signals (with different cycles) were chosen as input signals, the idea is to identify the parts where they are in phase from the superposition of the output signals. From the first part of the output signals, there were two areas in phase, they were assumed to be the responses of S0 wave and A0 wave, then the Passion’s Ratio is calculated. At the end, the test results and the known parameters of each plate were compared and discussed.
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Smart Composite StructurE (Project SyRaCuSE) Towards mastering challenges concerning the product lifecycle
2017Co-Authors: Yann Meyer, Rémy Lachat, Xianlong Chen, Sébastien Salmon, Morvan OuisseAbstract:Since the middle of the 80’s, Smart Composite structures are announced as being able to revolutionize the industrial world and become a main engine of economic growth. A Smart Composite structure is a structure combining distributed actuator and sensor networks embedded at the heart of the matter and a command and control unit. The idea is to mimic nature in order to produce industrial Composite structures that will adapt their functionality to their environment in a predicted manner. This approach seems attractive with a lot of potential applications: Vibration suppression, non-Destructive Evaluation, Energy Harvesting, Internet of Things... In a way, the Smart Composite structures are indeed at the forefront of the innovation process in the scientific literature. This is true in particular from a numerical modeling point of view. Concerning the prototypes, these structures remain at the draft stage and are mostly far from the real life industrial applications or mass production. Why does a thick border currently exist between the industrial and research worlds? The answer is of course complex. At first order, the selection of the case studies is from technical analyses and not from user-based analysis. This can limit the development of strongly value-added prototypes. Moreover, the balance between the apparent complexity and the performance increasing could be not good enough for industry organizations. The industrial and financial viabilities are clearly considered unfavorable. This is established without a deep analysis. This paper is focused on the early stage design of a Smart Composite structure with embedded piezoelectric sensors and actuators. To guarantee the transducers’ efficiency and keep the geometrical and material properties of the host Composite structure, several major technical issues are identified as having a strong impact on the manufacturing requirements. It is necessary to : - Electrically connect a large number of transducers so as to act on the whole structure. - Make each transducer electrically independent. This is particularly important when developing carbon-fibre-reinforced Composite structures which are naturally conductive. - Perfectly couple the exogenous element with the Composite material so as to guarantee the transducers’ efficiency and reduce the risks of delamination or other failures. - Accurately master the location of the transducers into the structure. This is necessary to create symmetric arrays of transducers and so a highly-symmetric distributed network. - Limit the “cross-talk” between the different embedded elements. - Limit the thickness variations due to the piezoelectric inclusions. - Achieve specific shaped structures (for instance, bi-concave structures) so as to adapt to a wide range of real-life applications. - Achieve a robust link with the outside structure to provide energy or modify the control law or the behavioural law in real time.
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Structural health monitoring of a Smart Composite structure with a Time-of-Flight method
2017Co-Authors: Xianlong Chen, Rémy Lachat, Yann Meyer, Morvan OuisseAbstract:Smart Composite structures with a fully distributed set of integrated piezoelectric transducers are used to demonstrate the feasibility of embedded Structural health monitoring (SHM). Indeed, the piezo ceramics elements have been directly integrated into the heart of the Composite during the manufacturing process. Then, a Time-of-Flight method has been applied. This technique is based on the duration measurements of a wave propagation with a simple and low cost experimental setup. Integrated piezoelectric transducers are used for monitoring the behavior of the structure. In this research, special plates (with a piezo ceramics disk on each corner), made of glass fibre Composite, are manufactured. Different kinds of damages are simulated on these plates, including holes with different diameters. Then a Time-of-Flight method is used for the SHM of these plates. Finally, the preliminary test results obtained on one plate are compared and discussed.
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Multimodal wave propagation in Smart Composite structures with shunted piezoelectric patches
Journal of Intelligent Material Systems and Structures, 2013Co-Authors: Tianli Huang, Mohamed Ichchou, Olivier Bareille, Manuel Collet, Morvan OuisseAbstract:Wave propagation in Composite structures with shunted piezoelectric patches is investigated in this study. The wave finite element approach is first developed as a prediction tool for wave propagation characteristics such as dispersion curves in Composite structures, and subsequently extended to consider shunted piezoelectric elements through the diffusion matrix model. A three-layered Composite beam equipped with a pair of resistor-inductor shunted piezoelectric patches is modeled and analyzed carefully with these numerical techniques. Reflection and transmission coefficients of propagating waves in this Smart Composite structure are calculated, and the performance of shunted piezoelectric patches on the control of wave propagation is investigated numerically with the diffusion matrix model. Another finite element formulation, named modified wave finite element method, which is dedicated to the analysis of wave propagation in multilayered Composite structures, is proposed and developed for considering piezoelectric elements in the structures. It is a dynamic substructuring technique that allows the dynamics of a typical layer cross section to be projected on a reduced local wave mode basis with appropriate dimensions. Results issued from this method are compared to those issued from the classical wave finite element and diffusion matrix model formulations to demonstrate the pertinence of the modelings.
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Multi-modal wave propagation in Smart Composite structures with shunted piezoelectric patches
2012Co-Authors: Tianli Huang, Mohamed Ichchou, Manuel Collet, Flaviano Tateo, Morvan OuisseAbstract:Wave propagation in Composite structures with shunted piezoelectric patches is investigated in this study. The wave finite element approach is first developed as a prediction tool for wave propagation characteristics such as dispersion curves in Composite structures, and subsequently extended to consider shunted piezoelectric elements through the diffusion matrix model. A three-layered Composite beam equipped with a pair of resistor–inductor shunted piezoelectric patches is modeled and analyzed carefully with these numerical techniques. Reflection and transmission coefficients of propagating waves in this Smart Composite structure are calculated, and the performance of shunted piezoelectric patches on the control of wave propagation is investigated numerically with the diffusion matrix model. Another finite element formulation, named modified wave finite element method, which is dedicated to the analysis of wave propagation in multilayered Composite structures, is proposed and developed for considering piezoelectric elements in the structures. It is a dynamic substructuring technique that allows the dynamics of a typical layer cross section to be projected on a reduced local wave mode basis with appropriate dimensions. Results issued from this method are compared to those issued from the classical wave finite element and diffusion matrix model formulations to demonstrate the pertinence of the modelings.
Bin Huang - One of the best experts on this subject based on the ideXlab platform.
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Actuator failure assessment in Smart Composite laminates via principal component analysis
Advances in Mechanical Engineering, 2016Co-Authors: Bin Huang, Ji WangAbstract:In this work, we propose a principal component analysis and system identification–based failure assessment approach for evaluating the partial actuator debonding failures in Smart Composite structu...
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Modeling of a partially debonded piezoelectric actuator in Smart Composite laminates
Smart Materials and Structures, 2015Co-Authors: Bin Huang, Gil Ho YoonAbstract:A partially debonded piezoelectric actuator in Smart Composite laminates was modeled using an improved layerwise displacement field and Heaviside unit step functions. The finite element method with four node plate element and the extended Hamilton principle were used to derive the governing equation. The effects of actuator debonding on the Smart Composite laminate were investigated in both the frequency and time domains. The frequency and transient responses were obtained using the mode superposition method and the Newmark time integration algorithm, respectively. Two partial actuator debonding cases were studied to investigate the debonding effects on the actuation capability of the piezoelectric actuator. The effect of actuator debonding on the natural frequencies was subtler, but severe reductions of the actuation ability were observed in both the frequency and time responses, especially in the edge debonded actuator case. The results provided confirmation that the proposed modeling could be used in virtual experiments of actuator failure in Smart Composite laminates.
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Investigation of actuator debonding effects on active control in Smart Composite laminates
Advances in Mechanical Engineering, 2015Co-Authors: Bin Huang, Heung Soo Kim, Gil Ho YoonAbstract:This article presents a numerical study of active vibration control of Smart Composite laminates in the presence of actuator debonding failures. A comparison between the Smart Composite laminates with healthy actuator and various partially debonded actuator cases is performed to investigate the debonding effects on the vibration suppression. The improved layerwise theory with Heaviside’s unit step function is adopted to model the displacement field with actuator debonding failure. The higher order electric potential field is adopted to describe the potential variation through the thickness. The finite element method–based formulations are derived using the plate element, taking into consideration the electro-mechanical coupling effect. The reduced-order model is represented by the state-space form and further for the vibration suppression using a simple constant gain velocity feedback control strategy. For the purpose of demonstration, a 16-layer cross-ply substrate laminate ([0/90]4s) is employed for the...
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Study on dynamic characteristics of Smart Composite laminates with partially debonded piezoelectric actuator
Proceedings of SPIE, 2015Co-Authors: Bin Huang, Gil Ho YoonAbstract:The dynamic characteristics of Smart Composite laminates with partially debonded piezoelectric actuator are investigated in this work. The proposed work introduces an improved layerwise theory based mathematical modeling with the Heaviside unit step functions to allow the possible sliding of the in-plane displacements and jump of the out-of-plane displacements for the debonded area. The finite element implementation is conducted using the four-node plate element to derive the governing equation. The dynamic characteristics are investigated by the frequency domain and time domain. The influence of actuator debonding to the natural frequencies is subtler for such kind of Smart Composite structures. The debonding of piezoelectric actuator also decreases its actuation ability that is reflected in the magnitudes of the system response. The proposed method can well predict the responses of the Smart Composite laminates with actuator debonding failures and it could be applied to the further damage detection methods.
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Frequency response analysis of a delaminated Smart Composite plate
Journal of Intelligent Material Systems and Structures, 2014Co-Authors: Bin Huang, Heung Soo KimAbstract:A frequency analysis of Smart Composite plate with delamination at ply interface was investigated in this article. The modeling was based on an electro-mechanical coupled improved layerwise theory, with implementing finite element method. Four-node plate elements with Lagrange and Hermite cubic interpolation functions were used for in-plane structural unknowns, electric unknowns, and out-of-plane structural unknowns. The general modal reduction method was applied to solve the second-order differential equation. Numerical results showed significant shift of natural frequencies in the frequency response of tip displacement and three sensor outputs due to the presence of delamination. It is found that the delamination locations also influence the natural frequencies of Smart Composite structure. Thus, the proposed methodology could be a useful tool to develop system identification and structural health monitoring techniques of Smart Composite structure.
Jinsong Leng - One of the best experts on this subject based on the ideXlab platform.
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Recent progress of Smart Composite material in HIT
Fourth International Conference on Experimental Mechanics, 2009Co-Authors: Jinsong Leng, Yanju LiuAbstract:Recent progresses of Smart Composite material in our ongoing research are presented in this paper. In recent years, shape memory polymers (SMPs) and electroactive polymers (EAPs) attract more and more attention in the world. In our researching work, different kinds of reinforcement are embedded into SMPs and EAPs to form Smart Composite materials, aiming to improve the properties or strengthen the materials. Based on the unique properties of SMP based Smart Composite materials, primary application in the deployable morphing wing are also studied, which provide meaningful guidance for further researching works in this area.
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structural health monitoring of Smart Composite materials by using efpi and fbg sensors
Sensors and Actuators A-physical, 2003Co-Authors: Jinsong Leng, Anand AsundiAbstract:Abstract Structural health monitoring (SHM) including the real-time cure monitoring and non-destructive evaluation (NDE) in-service is very important and definitely demanded for safely working of high performance Composite structures in situ. It is very difficult to carry out by using conventional methods. A unique opportunity was provided to real-time monitor the health status of Composite structures by using embedded fiber optic sensors (FOSs). In this paper, the extrinsic Fabry–Perot interferometer (EFPI) and fiber Bragg grating (FBG) sensors are real-time employed to simultaneously monitoring the cure process of CFRP Composite laminates with and without damage. The results show that both embedded EFPI and FBG sensors could be used to monitor the cure progress of Composite materials and detect the occurred damage on-line during the fabrication of Composite structures. Furthermore, the NDE of Smart Composite laminates embedded both EFPI and FBG sensors are performed by using the three-point bending test. The experimental results present that the flexural strain of CFRP Composite laminates with damage is more than that of CFRP laminates without damage under same load as we expected. Both EFPI and FBG sensors also show the excellent correlation during the cure monitoring and bending test.
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Real-time cure monitoring of Smart Composite materials using extrinsic Fabry-Perot interferometer and fiber Bragg grating sensors
2002Co-Authors: Jinsong Leng, J. S. Leng, Anand AsundiAbstract:Real-time cure monitoring of Composite materials is very important to improve the performance of advanced Composite materials. It is very difficult to monitor the cure process online using conventional methods. Fiber optic sensors in Smart Composite materials provide a unique opportunity to monitor the cure process of Composite materials in real time by using embedded sensors. In this paper, extrinsic Fabry-Perot interferometer (EFPI) and fiber Bragg grating (FBG) sensors are embedded in carbon/epoxy Composite laminates and used to monitor the cure process simultaneously. Furthermore, measurements of residual strains of Composite laminates during the cure have been performed. The results show that both EFPI and FBG sensors can be used to monitor the strain development of Composite laminates with and without damage during cure. An excellent correlation between the EFPI and FBG sensors is presented.
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Vibration control of Smart Composite beams with embedded optical fiber sensor and ER fluid
Journal of Vibration and Acoustics Transactions of the ASME, 1999Co-Authors: Jinsong Leng, J. S. Leng, Anand Asundi, Yanju Liu, Y.j LiuAbstract:This paper proposes the use of a fiber optic sensor (FOS) and electrorheological (ER) fluid actuator for vibration monitoring of Smart Composite structures. A new intensity modulated fiber optic vibration sensor is developed following the face coupling theory. It has high sensitivity similar to the traditional piezoelectric sensor. Also it is lower in cost. The experiment of vibration control of Smart Composite beam with embedded intensity modulated optical fiber vibration sensor and ER fluids are described in this paper. It is noted that the most significant change in the structural properties of Smart Composite beam is the change of structural damping and natural frequency, which varies with the electric field intensity imposed upon ER fluid. So the structural vibration can be monitored and controlled effectively utilizing FOS and ER fluids.
