Detection Of Delamination Damage Research Articles

A Two-step Inverse Method for Quantitative Damage Evaluation of Plate-like Structures Using Vibration Approach

This study presents a novel two-step approach to assess plate-like structural laminar damages, particularly for delamination damage detection of composite structures. Firstly, a 2-D continuous wavelet transform is employed to identify the damage location and sizes from vibration curvature data. An inverse method is subsequently then used to determine the bending stiffness reduction ratio along a specified direction, enabling the quantification of the delamination severity. The method employed in this study is an extension from the one-dimensional inverse method developed in a previous work of the authors. The applicability of the two-step inverse approach is demonstrated in a simulation analysis and by an experimental study on a cantilever composite plate containing a single delamination. The inverse method is shown to have the capacity to reveal the detailed damage information of delamination within a constrained searching space and can be used to determine the effective flexural stiffness of composite plate structures, even in cases of complex delamination damage. Conflict of Interest Statement The authors declare no conflicts of interest.

A novel delamination damage detection strategy based on inverse finite element method for structural health monitoring of composite structures

In recent years, structural health monitoring (SHM) has been revolutionized with the advent of the inverse finite element method (iFEM), which is a superior sensing technology based on the minimization of a weighted least squares error functional between experimental and numerical strain measures. This approach is suitable for damage detection thanks to its highly accurate and full-field displacement reconstruction capability within the physical domain of the structure. This study focuses on the development of a novel damage detection strategy for identifying internal/external defect types in composites, e.g., delamination, surface debonding, etc., by utilizing iFEM. The core formulation is derived by employing the kinematic relations of the refined zigzag theory (RZT) within the iFEM framework. By utilizing the field variables achieved via the iFEM-RZT, equivalent von Mises strains are computed for individual plies. After that, through the definition of various damage indices, the health of the structure is evaluated in terms of the presence of damage as well as its extent and through-the-thickness position and in-plane size of the damage in laminated composite materials. Various case studies with different damage scenarios are simulated for the assessment of iFEM-RZT capability in terms of shape-sensing and SHM. As a result, the inverse algorithm shows its remarkable efficiency and accuracy in detecting flawed regions over the problem domain and through the thickness of layered materials, both in terms of the location of the damage as well as its morphology.

Damage detection in composite laminates using nonlinear guided wave mixing

This paper presents a delamination damage detection technique based on the nonlinear response of Lamb waves in composite laminates. In the approach, a network of transducers is employed to sequentially scan the structure by actuating and receiving dual guided waves. Using combined frequency waves originated due to contact nonlinearity when the incident dual frequency wave interacts with the damage, a damage localization imaging algorithm is proposed to locate the damage and determine the damage location. The proposed damage localization imaging algorithm is based on analysing the cross-correlation of the signal envelope at combined frequency wave with the excitation pulse envelope at incident waves for each transducer pair, the damage localization image is constructed. A numerical study using an experimentally validated finite element model is used to verify the proposed damage detection technique. The results of the numerical study show that, despite the small amplitude of the nonlinear components, the proposed method can effectively predict the damage location, and it does not require baseline measurements, which makes it potential to be a baseline-free damage detection technique.

An Intelligent Health Monitoring Model Based on Fuzzy Deep Neural Network.

An intelligent health detection model is a new technology developed under an artificial intelligence environment, which is of great significance to the care of the elderly and other people who cannot take care of themselves. This paper comprehensively reviews the structural health monitoring method based on an intelligent algorithm, introduces the application model of neural networks in structural health monitoring in detail, and points out the shortcomings of using neural network technology alone. On the basis of previous work, the genetic algorithm and fuzzy theory were introduced as optimization tools, and a new neural network training algorithm was constructed by combining genetic algorithm, fuzzy theory, and neural network technology for structural health monitoring research. Aimed at the shortcoming of insufficient samples for training neural networks based on experimental data, this paper proposes to use the finite element method to construct a genetic fuzzy RBF neural network after corresponding processing of the first six-order bending modal frequencies of the structure, so as to realize the localization and detection of delamination damage of composite beams. Injury Assessment. The experimental results of this paper show that the finite element method proposed in this paper can effectively carry out damage localization and damage assessment; compared with the traditional algorithm, the localization accuracy of this algorithm is improved by 20%, and the damage assessment performance is improved by 10%.

Contact delamination detection of anisotropic composite plates using non-elliptical probability imaging of nonlinear ultrasonic guided waves

Contact delamination damage easily occurs inside the composite. The extension and accumulation of the damage occupy most of the time from damage appearance to failure. However, the anisotropy of materials and the small size of early damage make accurate detection difficult. In this paper, a non-elliptical probability imaging (NEPI) method based on nonlinear ultrasonic guided waves is proposed for the delamination damage detection in anisotropic composites. Firstly, the anisotropic characteristics of the composite are analyzed theoretically, and the velocity in all directions is obtained by numerical simulation. Secondly, the arrival time is obtained by the intersection of the upper and lower envelope fitting lines, and nonlinear coefficient is calculated based on the smooth pseudo Wigner–Ville distribution (SPWVD). Then, the time coefficient (CT) and nonlinear damage index (NDI) are defined and applied in the NEPI. By comparison with a reference point, the problem that the damage location of anisotropic composite cannot be solved analytically is avoided skillfully. Finally, the NEPI method is used to present the damage. The experiment results show that the NEPI method can accurately display the damage location. The sensitivity and reliability of NDI based on SPWVD are further verified by comparison with damage index of scattered signal and time–frequency analysis methods such as fast Fourier transform, short-time Fourier transform, and S-transform. The proposed NEPI method based on nonlinear ultrasonic guided waves can detect the delamination damage with good location accuracy and high damage sensitivity.

Design development of (Ba1-xCax)(Ti1-ySny)O3 lead-free piezo ceramic by two manufacturing methods of CSS and SPS, promising for delamination damage detection

Delamination in laminated composite structures plays a major role in decreasing structural strength and stiffness, consequently downgrading system integrity and reliability. Therefore, the delamination detection by the method of sending and receiving propagated wave with piezoelectric sensors is very important. In order to detect the structural damage using piezo ceramics sensors with a high piezoelectric coefficient (d33), a lead-free piezo ceramic (B1-xCxT1-ySy)O3 or (Ba1-xCax)(Ti1-ySny)O3 was designed and manufactured by two methods of conventional solid-state reaction sintering (CSS) and spark plasma sintering (SPS). The electrical and electromechanical properties, X-ray diffraction analysis, thermal analysis (DSC) and scanning electron microscopy (SEM) were investigated on the samples and the samples properties were compared with different contents of Ca and Sn dopants. (Ba1-xCax)(Ti1-ySny)O3 (x = 0.05, 0.1 mole% and y = 0.02–0.12 mole %) ceramics with a high relative density over 97.02 (±0.2)% were prepared by CSS method at 1480 °C. A polymorphic phase transition from orthorhombic phase to tetragonal phase was confirmed in the composition range of x = 0.05, 0.1 and 0.02 ≤ y ≤ 0.12 by XRD analysis that was measured at room temperature. In CSS method a high piezoelectric coefficient (d33) up to 605 pC/N was obtained for x = 0.05 mole% and y = 0.09 mole%, which was higher than the other previously reported components of B1-xCxT1-ySy system. The corresponding planar electromechanical coupling factor (kp) and inversed piezoelectric coefficient (dS/dE) reached to 42.8% and 1203 pm/V, respectively. For the prepared SPS samples at 1330 °C and under the pressure of 55 MPa, the corresponding d33, kp, tanδ and dS/dE were 752 pC/N, 54.2%, 2.7% and 1248 pm/V, respectively. The average relative density of SPSed samples of the same composition reached to 99.50 (±0.2)%. It seems that designing and forming a suitable phase boundary starting from a tricritical triple point in the MPB zone that along with SPS manufacturing method could enhance and develop high-performance Pb-free piezoelectrics.

Damage assessment of composite plate structures with material and measurement uncertainty

Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problem in damage assessment. A recently developed C0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data.

Buckling behavior of bidirectional composite flat panels with delaminations in hygrothermal field

Hygrothermal influence on the buckling behavior of bidirectional glass/epoxy composite panels having delaminations was studied numerically and verified by conducting several experiments. First-order shear deformation theory was used to develope a finite element model for numerical predictions with an 8-noded quadratic isoparametric element that takes care of the effects of delamination area and hygrothermal conditions of composite panels. Verification of results of the numerical analysis was done by conducting several experiments showing the effects of various parameters like temperature, moisture, area of delaminations, orientations of fibers, stacking sequence and boundary conditions on the buckling characteristics of bidirectional glass/epoxy composite panels. Experimental buckling loads were calculated using an INSTRON 8862 universal testing machine for hygrothermally treated composite panels having delaminations. It was observed that there is a good comparison of predicted and experimental buckling loads. The effects of various parameters on the buckling behavior of composite panels are presented. The buckling results can be utilized as a tool for detection of delamination damage in composite plates subjected to hygrothermal environment.

Detection of delamination in composites by using electromagnetic penetrating radar

Composites made from E-glass/epoxy or aramid/epoxy are frequently used in aircraft and aerospace industries. These materials are prone to suffer from the presence of delamination, which can reduce severely the performance of aircrafts and even threaten their safety. Since electric conductivity of these composites is rather small, they can propagate electromagnetic waves. Detection of delamination damage can then be monitored by using an electromagnetic penetrating radar scanner, which consists of emitting waves having the form of short time pulses that are centered on a given work frequency. While propagating, these waves undergo partial reflection when running into an obstacle or a material discontinuity. Habitually, the radar is moved at constant speed along a straight path and the reflected signal is processed as a radargram that gives the reflected energy as function of the two-way time and the antenna position.In this work, modeling of electromagnetic wave propagation in composites made from E-glass/epoxy was performed analytically. The electromagnetic wave reflection from a delamination defect was analyzed as function of key intervening factors which include the defect extent and depth, as well as the work frequency. Various simulations were performed and the obtained results have enabled to correlate the reflection pattern image features to the actual delamination defect characteristics which can provide quantification of delamination.

Delamination detection with error and noise polluted natural frequencies using computational intelligence concepts

Delaminations are one of the most prevalent defects noticed in laminated composite structures. The existence of delaminations changes the vibration characteristics of laminates and hence such indicators can be used to quantify the health characteristics of laminates and detect potential risk of catastrophic failures. An approach for online health monitoring of in-service composite laminates is presented in this paper that relies on methods based on computational intelligence. Typical changes in the observed vibration characteristics (i.e. change in natural frequencies) are considered as inputs to identify the existence, location and magnitude of delaminations. The performance of the proposed approach is demonstrated using both numerical models and experimental studies of composite laminates. Since this identification problem essentially involves the solution of an optimization problem, the use of finite element (FE) methods as the underlying tool for analysis turns out to be computationally expensive. A surrogate assisted optimization approach is hence introduced to contain the computational time within affordable limits. An artificial neural network (ANN) model with Bayesian regularization is used as the underlying approximation scheme while an improved rate of convergence is achieved using a memetic algorithm. However, building of ANN surrogate models usually requires large training datasets. K-means clustering is effectively employed to reduce the size of datasets. ANN is also used for the solution of the inverse problem to determine the interface, size and location of delaminations using changes in measured natural frequencies before and after damage. The algorithms successfully performed delamination detection given limited amount of training datasets. Since in all practical problems, noise and error are inherently present, the performance of the proposed approach is also evaluated under varying levels of noise and error. The results clearly highlight the efficiency and the robustness of the approach. Hence, a delamination prediction strategy via K-means clustering, ANN and optimization algorithms integrated with surrogate models based on ANN for computational enhancement have been successfully developed and found efficient for detection of the interface of delamination, its size and location in FRP composite laminates using variations in natural frequencies. The developed algorithms are applied to composite beams. Results clearly indicate the delamination detection capability of the algorithms. The results demonstrate that the proposed techniques provide remarkable accurate detection of delamination damage with error and noise corrupted natural frequency validation data. The algorithms are quite promising, successful, flexible and practical with significant increase in terms of efficiency and effectiveness for SHM.

Delamination damage detection of laminated composite beams using air-coupled ultrasonic transducers

Air-coupled ultrasonic transducers are used to generate and receive Lamb waves in quasi-isotropic laminated composite beams for delamination detection. The influence of incident angle on the excited mode is studied. Numerical calculation and experimental results show that a pure Lamb wave mode can be generated if the transmitting transducer is oriented at a specific angle, and the receiving transducer can either be oriented to detect the same mode as that generated by the transmitter or to detect another mode generated by mode conversion at a defect. A three-dimensional finite element model is created to predict the interaction of Lamb waves with delamination, and some unique mechanisms of interaction between A0 mode Lamb waves and delamination are revealed in detail. The experimental results obtained on laminated composite beam using air-coupled ultrasonic transducers are well in accordance with finite element simulation results. Research results show that air-coupled ultrasonic guided waves can be used for delamination damage detection effectively in laminated composite beams.

Validation of algorithms for delamination detection in composite structures using experimental data

This research work deals with aspects concerned with delamination detection in composite structures as revealed by an approach based on vibration measurements. Variations in vibration characteristics generated in composite laminates indicate the existence of delaminations because degradation due to delamination causes reduction in flexural stiffness and strength of the material and as a result vibration parameters like natural frequency responses are changed. Hence, it is possible to monitor the variation in natural frequencies to identify the presence of delamination, and assess its size and location for online structural health monitoring (SHM). The approach to this paper, therefore, typically depends on undertaking the analysis of structural models implemented by finite element analysis (FEA). The numerical solutions using FE models known as the simulator computes the natural frequencies for the delaminated and undelaminated specimens of composite laminates. However, these FE models are computationally expensive, and surrogate (approximation) models are introduced to curtail the computational expense. The simulator is employed to solve the inverse problem using algorithms based on computational intelligence concepts. An artificial neural network (ANN) model is developed to also solve the inverse problem for delamination detection directly and to provide surrogate models integrated with optimization algorithms (the gradient-based local search and non-dominated sorting genetic algorithm-II) to contain the computationally expensive simulations by FEA. This approach is termed as surrogate assisted optimization and it is seen that the engagement of surrogate models in lieu of the FE models in the optimization loop greatly enhances the accuracy of delamination detection results within an affordable computational cost and provides control over handling different variables. Meanwhile, to aid with the building of effective surrogate models using substantial number of training datasets, K-means clustering algorithm is harnessed and this effectively reduces the large training datasets usually required for ANN training. This paper demonstrated that ANN and optimization algorithms with surrogates show immense potentialities for use in delamination damage detection scenarios. Prediction errors of the algorithms were quantified and they were shown to be satisfactory when applied to previously experimental data. The algorithms in their inverse formulations are capable of predicting accurately delamination parameters. Hence, these algorithms should be employed for application in the domain of SHM where their small computational requirements could be exploited for online damage detection.

Cost Effective Air-Coupled Impact-Echo Sensing for Rapid Detection of Delamination Damage in Concrete Structures

Recently, air-coupled impact-echo (IE) tests for rapid damage detection in concrete structures have been reported, where an acoustically shielded, high sensitivity, pre-polarized air-pressure sensor was employed. However, this sensor is expensive and inconvenient compared with conventional (contact sensor) IE testing systems. In this study, a low cost dynamic microphone is evaluated with regard to characterization of delamination damage in a concrete slab using the IE method. Artificial delaminations with various sizes and depths are simulated by embedding plastic double sheets into a concrete slab. Results from both point and areal scanning IE tests that were carried out over the test slab surface are reported. Results show that the dynamic microphone successfully captures impact-echo signals in a contactless manner and without acoustic shielding. Near-surface delaminations in the concrete slab were clearly identified, where the obtained results are equivalent to those results obtained with the high sensitivity sensor.

Detection of Delamination Damage in a Composite Laminate Beam Utilising the Principle of Strain Compatibility

This paper presents an experimental investigation of a new method for damage detection based on the most fundamental concept in continuum mechanics: strain compatibility. Compliance with this principle implies a deformed material is free from discontinuities, which are indicative of many types of structural damage. Therefore the principle of strain compatibility, in its ability to identify discontinuities, is very promising as a new foundation for future research into non-destructive evaluation and structural health monitoring technologies. The proposed method has many advantages compared to existing damage detection techniques, such as its invariance to material properties, type and intensity of loading, and the geometry of the structure. In this paper, a proposed formulation of the strain compatibility equation for beam structures, which is invariant to loading intensity, is presented. An experimental investigation of the proposed algorithm was conducted on a delaminated cantilever beam, utilising a PSV-3D scanning laser vibrometer. The experiment demonstrated that the strain compatibility technique can accurately locate delamination damage in composite beam structures.

Detection of delamination damage in composite beams and plates using wavelet analysis

The effectiveness of wavelet transform in detecting delamination damages in multilayered composite beams and plates is studied here. The damaged composite beams and plates are modeled in finite element software ABAQUS and the first few mode shapes are obtained. The mode shapes of the damaged structures are then wavelet transformed. It is observed that the distribution of wavelet coefficients can identify the damage location of beams and plates by showing higher values of wavelet coefficients at the position of damage. The effectiveness of the method is studied for different boundary conditions, damage location and size for single as well as multiple delaminations in composite beams and plates. It is observed that both discrete wavelet transform (DWT) and continuous wavelet transform (CWT) can detect the presence and location of the damaged region from the mode shapes of the structures. DWT may be used to approximately evaluate the size of the delamination area, whereas, CWT is efficient to detect smaller delamination areas in composites.

Detection of delamination damage in composite plates using energy spectrum of structural dynamic responses decomposed by wavelet analysis

Damage detection of local and tiny delamination in a laminated composite plate is studied in this paper using piezoelectric patches embedded in composite plate and the energy distribution of structural dynamic responses decomposed in various frequency bands by wavelet packet analysis. This method is based on energy distribution of structural vibration sub-signal and can be in situ implemented using a few piezoelectric patch sensors and actuators embedded in the composite plate. The obtained results show that the method for structural damage detection proposed in this paper is much more sensitive than the existing methods. Using this method, a delamination area of only 0.13% of the total area of the composite plate may be detected. The results show that numerical simulation are quite consistent with experiment results.