Damage Detection In Composite Materials Research Articles

Low-frequency air-coupled transducer based damage detection in composite materials

In this paper results of simulations of non-contact elastic wave generation in the composite panel based on acoustic to elastic wave transformation are presented. For this purpose simulations of acoustic wave generation and processing are based on the FEM method in COMSOL. Elastic wave generation and propagation are based on the spectral element method (SEM) in the time domain. The SEM model utilises time-varying acoustic pressure distributions calculated in the FEM. The SEM allows to simulate the interactions of elastic waves with the delamination. Damage localization is based on RMS elastic wave energy maps. In this research a panel made of carbon fibre-reinforced polymer composite is investigated. Research related to low-frequency air-coupled transducer (ACT) is presented. The utilisation of low-frequency waves allows for the reduction of the effects of the wave attenuation in composite material. The proposed combination of FEM and SEM gives an efficient tool for the simulation of non-contact wave generation for non-destructive testing analysis.

Experimental and Numerical Study on Vibration-Based Damage Detection and Localization in Laminated Composite Plates

Damage detection in composite materials is crucial for ensuring the safety and reliability of engineering structures. Conventional methods often face challenges in accurately identifying damage in plate-like structures, particularly in scenarios involving multiple damages or small-scale delamination. This study focuses on investigating the detection and localization of delamination in composite plates by employing both experimental and numerical modal analysis. An eight-ply woven Glass-Epoxy composite laminate with and without damage was prepared with the aid of hand lamination technique. Laminate was fixed to a Clamped-Free-Free-Free (CFFF) boundary condition for experimental modal analysis by introducing controlled damage to examine its impact on modal properties. To validate the natural frequencies (NFs) of damaged and undamaged composite laminates, a numerical analysis was conducted using ANSYS Parametric Design Language (APDL). Further, to advance the understanding of using modal shapes and their spatial derivatives for damage localization in composite plates under various damage situations, post-processing of simulation results was conducted using MATLAB. Finite Difference Method has been employed to calculate the derivatives, and a novel damage index (DI) is proposed to enhance damage localization capabilities. The results affirm that the proposed DI is effective and precise in identifying damage in plate-like structures, both for individual and multiple damage scenarios. This research study presents a novel approach for identifying and pinpointing damage in composite plates, thereby making a valuable contribution to the field of structural health monitoring (SHM) applications

An improved convolutional neural network approach for damage localization in composite materials based on modal analysis

Damage detection of composite materials using modal parameters has limitations in terms of sensitivity to small or localized damage and limited accuracy in damage localization. To address this issue, an enhanced channel attention residual network (ECARNet) damage detection model for composite laminates is proposed. First, finite element analysis is used to obtain training samples, which are processed as two-dimensional data to take full advantage of the convolutional neural network. Then, the residual module uses a multilayer perceptron instead of the traditional convolutional layers to learn the correlation between channels to enhance the generalization ability of the model, and uses the tanh activation function to retain negative information. Finally, a channel focus mechanism is introduced to enable the network to learn key features adaptively. Experimental results on two datasets with different levels of damage demonstrate the superior detection performance of ECARNet, achieving average detection accuracies of 98.13% and 97.94% respectively. A comparison with other methods verifies the effectiveness and reliability of the proposed approach. Furthermore, the effectiveness of the new method is validated on real-world test data.

A systematic approach to find the hyperparameters of artificial neural networks applied to damage detection in composite materials

A systematic approach to find the hyperparameters of artificial neural networks applied to damage detection in composite materials

Vibro-Acoustic Modulation with broadband pump excitation for efficient impact damage detection in composite materials

In the past few decades, the need for efficient and reliable Structural Health Monitoring strategies has led to the development of several approaches for damage detection and characterization purposes. Among them, the Nonlinear Vibro-Acoustic Modulation (VAM) exploits the modulation arising from the interaction of two concurrently applied driving waves, namely the probe and the pump excitations, in the presence of nonlinear scatters such as cracks and defects. Therefore, the VAM provides information on the emergence of internal damage by extracting the nonlinear modulated components of the response of a damaged system. Originally proposed for granular media, the method has shown to be effective in detecting the presence of defects also in metals and composite materials. Nonetheless, its efficacy is highly affected by the excitation frequencies, which are usually chosen among the system resonances. The need for a preliminary modal analysis and, at once, the risk of selecting pump-probe frequency combinations with low sensitivity to damage may make the procedure time-consuming and not fully reliable, preventing the VAM technique from being widely accepted as a robust monitoring tool. To overcome these limitations, a broadband excitation may be used. This study assesses the effectiveness of the VAM technique when a combination of a frequency-swept pump excitation and a mono-harmonic probe wave is applied to drive the sample. Experimental tests were conducted on a composite laminated beam mounted on an electrodynamic shaker and tested in both pristine and damaged conditions. Low-profile surface-bonded piezoceramic transducers were used for both probe excitation and sensing. Barely visible impact damage (BVID) was introduced in the composite beam to examine the potential of the approach for the detection of very small, localized damage. The results show that the use of VAM with a broadband low-frequency excitation may be an effective option for identifying nonlinearities associated with typical damage occurring in composite structures.

Influence of Sensor Position and Low-Frequency Modal Shape on the Sensitivity of Vibro-Acoustic Modulation for Impact Damage Detection in Composite Materials

Very sensitive structural health monitoring methods are needed to detect barely visible impact damage in composite materials. Based on extracting non-linear modulated components from the frequency response of the damaged system, vibro-acoustic modulation (VAM) has shown to be effective in identifying the presence of damage at its early stage. A decisive role in the success of this technique is played by the choice of the high-frequency probe and the low-frequency pump sinusoidal signals that simultaneously excites the system. This study explores how the position of the sensing transducer, with respect to the modal shape of the pump excitation, may influence the sensitivity of the VAM technique for impact damage detection in composite laminates. This aspect has been scarcely investigated in previous research works, as other studies have focused more on the role of the probe frequency. Here, VAM tests were performed on a composite beam by using a frequency-swept pump vibration simultaneously with a high frequency probe excitation. The results of the experimental tests indicate that the VAM technique is capable of clearly revealing the presence of impact damage only when the sensor is placed on appropriate locations, which are directly related to the shape of the deformation activated by the applied excitation. These results suggest the adoption of low frequency excitations that activate multiple modal shapes to improve the effectiveness and reliability of VAM approaches.

Full scale promoted convolution neural network for intelligent terahertz 3D characterization of GFRP delamination

Damage detection of composite materials is crucial to monitor the component condition over the life cycle for the maintenance management and possible replacement. Delamination damage, as a common damage form in glass-fiber reinforced polymer (GFRP) composites, may occur during the manufacturing and service process due to the mechanical and thermal loads. Terahertz (THz) NDT technique, as a novel characterization approach, can provide promising alternatives to fulfill the 3D characterization of delamination defects in multi-layer GFRP composites. During THz testing, in order to attain adequate discrimination in depth direction, complex signal processing and prior knowledge of the undamaged stratigraphy are usually required to suppress confounding effects from noise, overlap, and dispersion of THz signal, which hinders the realization of automatic defect detection. Therefore, here we propose an effective, reliable, and end-to-end 3D THz characterization system based on deep learning methods to fulfill the automatic localization and imaging of delamination defects in GFRP composites without any additional signal processing or prior knowledge. In the localization process, the full-scale promoted convolution neural network (FSP–CNN) is developed by integrating dual mechanisms of the full-scale feature learning and the promoted classifier. In the imaging process, the class encoding strategy is employed to obtain the 2D and 3D information of delamination defects based on the classification results. Finally, a series of experiments validate the effectiveness of the system for automatic localization and imaging of delamination defects in GFRP composites, which provides a novel and efficient paradigm for the intelligent and automatic THz 3D characterization of hidden delamination defects in composites.

Damage Detection in Composite Materials by Flexural Dynamic Excitation and Accelerometer-Based Acquisition

Composite materials provide many advantages over more conventional materials. However, their susceptibility to impact damage can question their use in critical load-bearing structures, and efficient methods are needed for early damage detection. To this purpose, the nonlinear vibro-acoustic modulation (VAM) technique applies a low-frequency pump excitation and a high-frequency probe excitation to exploit the onset of harmonic components around the probe frequency of the damaged structural response. The VAM technique has been widely studied on structures instrumented with piezoceramic transducers used for both actuation and sensing, but few attempts have been made to use equipment typical of modal testing, such as shakers and accelerometers. In this study, the VAM technique is applied to a composite laminate beam by employing an electro-dynamic shaker to generate low-frequency flexural excitation, a low-profile piezoceramic transducer to introduce the probe wave, and a micro-accelerometer to sense the structural response. Three resonance low frequencies and two acoustic frequencies are considered in different testing scenarios, at increasing levels of excitation amplitude. The results show a general good performance of the technique with the adopted experimental setup, the choice of the probe frequency and the higher level of the pump excitation having a significant impact on its sensitivity.

Simulated Lamb wave propagation method for nondestructive monitoring of matrix cracking in laminated composites

The estimation of the damping coefficient may help to improve the damage detection in composite materials. The purpose of this study was to develop the simulated Lamb wave propagation method for nondestructive monitoring of matrix cracking in laminated composites via the accurate estimation of their damping coefficient. Cross-ply composite specimens with different crack densities were fabricated and tested by the Lamb wave propagation technique. The phase velocity of the Lamb wave and the damping coefficient of the specimens were measured. The finite element models were developed at micro-scale (representative volume elements) and macro-scale (laminated specimens) levels to simulate the Lamb wave propagation in composite specimens. An optimization process was performed through the model updating procedure to achieve finite element models that were in good agreement with experiments. The phase velocity and damping coefficient, obtained from the updated FE models for two crack densities other than those used in the model updating procedure, were successfully examined by experimental results. It was also revealed that the damping coefficient and the rate of increase in the damping coefficient in terms of the crack density were higher for the composite laminates with a higher number of 90° layers. The damping of the fiber–matrix interphase and crack regions were considered in the model and shown as a significant contribution to the overall damping of the composite specimens. The proposed simulated Lamb wave propagation method can be used as a virtual lab for in-situ monitoring of laminated composites with different material properties, stacking sequences, and crack densities.

Damage Detection in Composite Materials Using Tap Test Technique and Neural Networks

The wind energy sources promote the generation of electricity, being environmentally safe, clean and its use has been growing in Brazil, especially in the northeastern states with the implementation of new wind farms. Wind turbines, however, are subject to weather, risk of animal shocks, materials carried by the wind, and the vibrations of the system itself. The blade is the most important component of a wind turbine and is the one with the greatest risk of failure. They are usually made of a composite fiber-reinforced polymer matrix and balsa wood as structural reinforcement. As the material composing this blade has heterogeneous and anisotropic characteristics, conventional inspection techniques are not considered effective. The non-destructive Tap Test technique can be a safe option in composite materials because it does not suffer from these limitations. The objective of this work is to inspect composite plates of polymeric resin used in wind turbines with discontinuities using the non-destructive Tap Test technique, where regions with and without defect were analyzed. The collected signals from an accelerometer and a microphone were processed, to allow the extraction of features and the recognition of discontinuities with the aid of a neural network.

Ultrahigh Resolution Pulsed Laser-Induced Photoacoustic Detection of Multi-Scale Damage in CFRP Composites

This paper presents a photoacoustic non-destructive evaluation (pNDE) system with an ultrahigh resolution for the detection of multi-scale damage in carbon fiber-reinforced plastic (CFRP) composites. The pNDE system consists of three main components: a picosecond pulsed laser-based ultrasonic actuator, an ultrasound receiver, and a data acquisition/computing subsystem. During the operation, high-frequency ultrasound is generated by pulsed laser and recorded by an ultrasound receiver. By implementing a two-dimensional back projection algorithm, pNDE images can be reconstructed from the recorded ultrasound signals to represent the embedded damage. Both potential macroscopic and microscopic damages, such as surface notches and delamination in CFRP, can be identified by examining the reconstructed pNDE images. Three ultrasonic presentation modes including A-scan, B-scan, and C-scan are employed to analyze the recorded signals for the representation of the detected micro-scale damage in two-dimensional and three-dimensional images with a high spatial resolution of up to 60 µm. Macro-scale delamination and transverse ply cracks are clearly visualized, identifying the edges of the damaged area. The results of the study demonstrate that the developed pNDE system provides a non-destructive and robust approach for multi-scale damage detection in composite materials.

Impact damage detection in smart composites using nonlinear acoustics—cointegration analysis for removal of undesired load effect

The paper presents a reliable methodology—based on nonlinear acoustics—for impact damage detection in composite materials. The nonlinear vibro-acoustic wave modulation technique is used to detect damage. The problem of operational variability of the method with respect to the selection of frequency and amplitude of low-frequency (LF) modal excitation is investigated. This problem is addressed using the concept of stationarity of time series of vibro-acoustic data. Cointegration analysis is employed to compensate for the effect of variable operational conditions associated with LF modal (or vibration) excitation in nonlinear vibro-acoustic wave modulations. Analysis of stationary statistical characteristics of vibro-acoustic responses—after cointegration analysis—are used for damage detection. The proposed method is validated using vibro-acoustic data from laminated composite plates and composite sandwich panels. The results demonstrate that the proposed approach can effectively compensate for the effect of LF modal excitation on nonlinear vibro-acoustic wave modulations and detect the damage more accurately and robustly than the existing nonlinear acoustics based on the analysis of modulation sidebands.

円孔近傍に損傷を有する複合材料の損傷検出のためのひずみ応答解析

円孔近傍に損傷を有する複合材料の損傷検出のためのひずみ応答解析

Electromagnetic Sensors for Improvement of Damage Detection in Composite Materials Reinforced with Carbon Woven Fibers

This paper presents two methods for electromagnetic nondestructive evaluation (eNDE) of composite materials reinforced with carbon woven fibers using a sensor with orthogonal coils and a sensor with metamaterials lens. The samples were impacted with low energy in order to study delamination influence. The electromagnetic behavior of composite was simulated by finite-difference time-domain (FDTD) software, showing a very good concordance with eNDE tests.

Triple Correlation Technique for Damage Detection in Composite Materials

Over the last few decades a number of different techniques have been developed for impact damage detection in composite structures. The most frequently used methods in Non-Destructive Testing (NDT) are: ultrasonic testing, acoustics emission, X-ray and visual inspection. These methods are quite effective but often require expensive equipment, a large number of transducers or highly qualified staff. Additionally, these techniques are used locally. Therefore monitoring of large structures in many cases is very difficult or even impossible. Recent years have seen many new developments mostly free from these limitations. This paper investigates the triple correlation technique for impact damage detection in composite structures. The method correlates fundamental and higher harmonics of signal vibration response

Modal Acoustic Emission Investigation for Progressive Failure Monitoring in Thin Composite Plates under Tensile Test

Acoustic Emission (AE) is one of the popular non-destructive (NDT) techniques and its applications have increased subsequently for Structural Health Monitoring (SHM). During the past few decades, many successful research works have evidently shown remarkable capability of AE for early damage detection of composite materials. This paper investigated the application of single channel acoustic emission (AE) source location detection method, utilizing time-frequency analysis for thin composite plates. Besides, failure characterization using Modal Acoustic Emission (MAE) also presented. Modal analysis of AE signals or MAE can offers a better theoretical background for acoustic emission analysis; which is necessary to get more qualitative and quantitative result and therefore, increase the reliability of early failure characterization for thin composite plates. For this study, tensile tests were conducted on the glass fiber epoxy resin specimen with small notch; and four channels of acoustic emission system were used to acquire AE signals. The results revealed that in practical, single channel AE source location was difficult to be done. Also, the study has successfully showed that matrix cracks and fiber fracture produced AE signals which dominated by symmetric wave mode.

Damage detection at cryogenic temperatures in composites using piezoelectric wafer active sensors

An experimental evaluation of the structural health monitoring capability of piezoelectric wafer active sensors on composite structures at cryogenic temperatures is presented. The piezoelectric wafer active sensor–based electromechanical impedance and the pitch–catch methods were first qualified for cryogenic temperatures using piezoelectric wafer active sensor–instrumented composite specimens dipped in liquid N2. Subsequently, damage detection experiments were performed on laboratory-scale composite specimens with (a) impact damage and (b) built-in Teflon patches simulating in service delaminations. Finally, a comprehensive damage detection test was performed on a full-scale specimen subjected to pressure and cryogenic temperature cycles. Based on these tests, we conclude that piezoelectric wafer active sensor–based structural health monitoring methods show promise for damage detection in composite materials even in extreme cryogenic conditions. Recommendations for further work are also included.

Vibration Tests in CFRP Plates for Damage Detection via Non-Parametric Signal Analysis

In this paper, two procedures for damage detection in Carbon Fiber-Reinforced Polymer (CFRP) plates are shown. One is based on the use of statistical frequency series to detect the presence of damage. This method was tested experimentally on a CFRP plate with induced damage. The other one is a procedure based on Ritz method and wavelet transform that was applied to the numerical vibration modes of a damaged CFRP plate. The former method can also be used experimentally, even if the ma- terial engineering constants are unknown. Damage detection in composite materials is a very interesting subject in aeronautical engineering, since it permits important maintenance cost reductions and moreover reduces the risk of critical structural failure which might produce fatal consequences in terms of human lives. Clearly it is necessary to develop new techniques to detect damage efficiently. Even if these new techniques cannot locate the damage, they can be used in conjunction with traditional ones for a complete damage characterization. Many of the new damage detection methods are based on vibration test techniques, given the fact that damage modifies the physical characteristics of the material. The nat- ural frequencies and vibration modes therefore change with respect to the undamaged material. The present study is divided into two parts. First, an experimental study of undamaged and damaged clamped plates is performed, and a damage index based on statistical and frequency series is defined. The damage index is an indicator capable of revealing the presence and extent of plate damage. It cannot, however, reveal its position. The piezoelectrics used in the experiments are very thin, and can thus be used as embeded sensors for Structural Health Monitoring (SHM). Second, using the plate vibration modes obtained with a Finite Element Model (FEM), a damage location tech- nique based on the variational Ritz method and wavelet analysis is developed. In this respect, the FEM allows us to simulate different damage types. With the Ritz method, the transversal displacement is approximated by a product series of functions compatible with the boundary conditions, as in the classical work (1).

Damage detection in composite materials using deflectometry, a full-field slope measurement technique

This paper presents a method for detecting damage in layered composite materials using a simple measurement technique, deflectometry. The aim is to locate the damage in a specimen and provide a “signature” in the form of surface slopes. The first part of the paper presents the experimental procedure: material, lay-up and sample types, then the set-up and data extraction are detailed followed by the finite element (FE) models. Finally the results are presented and commented.

Application of Improved BPNN to Damage Detection of Composite Materials

A dynamic method based on improved algorithm BP neural network for damage identification of composite materials was proposed. By using wavelet series, the features of signals were extracted and input to improved algorithm BP neural network for training the network and identifying the damages. Finally, the experiment results show that this proposed method can exactly identify the faults of composite materials.