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The stiffened composite panels are widely used in various engineering structures, but their nondestructive testing methods face certain limitations. The traditional wave field imaging method faces difficulties when applied for damage detection in complex composite structures. An improved adjacent wave subtraction (AWS) method is proposed in this research to visualize the multiple damage in stiffened composite panels. The method is based on the concept that the Lamb wave signals from two adjacent scanning points at healthy area are very similar and the anomalous wave, caused by the structural discontinuities including the damage, has different signal packets at any two adjacent scanning points. The ${S_0}$ mode Lamb wave signals are used in the proposed AWS method due to their faster speed in low-frequency domains. A damage index is proposed to show the signal difference of any two adjacent points, which can indicate the damage locations. A robust time window is used to enhance the anomalous wave signals and improve the damage imaging results. The prosed method is proven to be effective for damage detection in stiffened composite panels with numerical simulations and experiments. [ABSTRACT FROM AUTHOR]

An integrated system is proposed to visualize subsurface barely visible impact damage (BVID) in composite structures using three-dimensional (3D) digital image correlation (3D DIC). This system uses a pair of digital cameras to record video frames in the field-of-view (FOV) of the structure's surface, capturing the wavefield generated via chirp excitation in the near-ultrasonic frequency range. Significant pitfalls of previous efforts of damage imaging using two-dimensional DIC have been largely mitigated. First, 3D DIC enables capturing out-of-plane displacements, which are much larger in amplitude versus in-plane displacements that a single camera would be limited to sensing, thus increasing the signal-to-noise ratio. This enhancement in turn increases the sensitivity of the stereo-camera system. Second, a total wave energy (TWE) damage imaging condition is proposed to visualize the local damage region. The monogenic signal obtained via Reisz transform (RT) is employed to compute the instantaneous amplitude, with which the local wave energy can be calculated spatially over time. Since a high displacement amplitude and thus high wave energy will occur in the damage region due to the local resonance, the proposed TWE imaging condition can relax the Nyquist sampling requirement, unlike guided-wave-based structural health monitoring techniques which require fully reconstructing the wavefield and wave modes through sampling that satisfies the Nyquist criterion. As such, a much lower camera frame rate is adequate for the proposed system. Consequently, the maximum spatial resolution of the camera for a given FOV can be achieved at the expense of a reduced frame rate. With the maximized pixel resolution and reduced frame rate for employing the TWE imaging condition, composite structures can be inspected or monitored with a larger FOV. As a result, there is no longer any need to apply signal enhancement techniques, such as sample interleaving, image stitching, or averaging, to increase the effective performance of the camera. Rather than needing thousands of repeated videos for minimizing the incoherent noise, only a single stereo-video with a few seconds of sampling duration is necessary for damage imaging. The use of a powerful piezo-shaker also increases the wave signal amplitude and further enhances sensitivity without permanent adhesion. To demonstrate this stereo-camera concept with the TWE imaging condition, the system was used to image damage in two carbon fiber reinforced polymer composite honeycomb panels, which had been subjected to low-velocity impacts (2 J). For each panel, two excitation configurations were used to verify the robustness of the system. Initial damage maps produced for a 100 × 100-mm FOV using a three-second stereo-video show accurate damage imaging ability that is independent of excitation location and comparable to benchmark damage images computed from laser Doppler vibrometer data and those gathered from ultrasonic and X-ray computerized tomography scans. This efficient and reliable integrated system demonstrated high potential for in-time damage inspection on composite aircraft and other critical structures. [ABSTRACT FROM AUTHOR]

This paper proposes a phase-reversal method (PRM) for damage imaging in plate structures. The PRM is a novel Lamb-wave-based method that mainly focuses on phase spectrum information of scattering waves reflected from a defect. The PRM reverses the phase angle along the propagation path by using the inverse Fourier transform first, and then the reversal reconstruction of the wave field in the frequency domain is performed for damage imaging. The proposed method analyzes the scattered wave field without using the baseline data and structural parameters. Moreover, dispersion characteristics and anisotropy are not involved in the process of damage positioning, thus making the PRM suitable for damage monitoring of composite laminates. To improve the PRM accuracy further, a combined addition and multiplication method of the correlation coefficient (CAMM) is proposed, which can reduce the effects of phase and noise artifacts and distortion. The results of the finite element simulations and experiments show that the combination of the PRM and CAMM methods can accurately locate damage in composite structures. Therefore, the PRM and CAMM methods have great application potential in damage imaging in composite laminates. [ABSTRACT FROM AUTHOR]

In this paper, a damage quantification strategy relying on post-processing of Lamb wave based damage localization results is presented. This method is able to predict the upcoming sizes of a delamination after a training step. Inputs of the proposed method are localization index maps produced by damage localization algorithms and representing the presence likelihood of a damage over the structure under study. The area covered by a high localization index around the estimated damage location are then extracted from these spatial probability maps. A data-driven model representing the mathematical relationship between this quantification feature and the actual size of the damage is finally inferred and used to predict future damage size. The proposed method is successfully validated on experimental data coming from CFRP plate samples equipped with piezoelectric transducers. Delaminations induced by fatigue testing and laser shock are studied. The sensitivity of the method to input frequency and damage localization algorithms parameters is assessed and a method to automatically select its own parameters is proposed. Furthermore, it is demonstrated that a model can be confidently learned on a given CFRP plate sample and transferred to predict damage size on another similar CFRP plate sample. [ABSTRACT FROM AUTHOR]

Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures. [ABSTRACT FROM AUTHOR]

The spatial-wavenumber filtering technique of Lamb wave is gradually applied for damage inspection of composite structure in recent years because it is an effective approach to distinguish the wave propagating direction and mode. But for on-line damage monitoring of composite structure by using spatial-wavenumber filter, the problem is how to realize the spatial-wavenumber filtering of Lamb wave when the wavenumber response cannot be measured or modeled. This paper proposes a scanning spatial-wavenumber filter and piezoelectric sensor (referred to as PZT) 2-D cruciform array based on-line damage imaging method of composite structure. In this method, a 2-D cruciform array constructed by two linear PZT arrays is placed on composite structure permanently to acquire Lamb wave damage scattering signal on-line. For one linear PZT array, a scanning spatial-wavenumber filter which does not rely on any modeled or measured wavenumber response is designed to filter the damage scattering signal at a designed wavenumber bandwidth to give out a wavenumber-time image. Based on the image, the wavenumber of the damage scattering signal projecting at the array can be obtained. The same process can be also applied to the other linear PZT array to get the wavenumber projecting at that array direction. By combining with the two projection wavenumbers, the damage can be localized without blind angle. The method is validated on an aircraft composite oil tank of variable thickness. The validation results show that the damage direction estimation error is less than 2° and the damage distance estimation error is around 20 mm in the monitoring area of nearly 600 mm × 300 mm. It indicates an acceptable performance of the damage imaging method for complex composite structure. [ABSTRACT FROM AUTHOR]

Ultrasonic guided wave is a promising technique for structural health monitoring and nondestructive testing. However, due to the anisotropy and complexity of composite materials, the imaging performance of numerous signal processing methods deteriorates with significant artifacts and unsatisfactory accuracy. To obtain a better damage imaging performance of Lamb waves in noisy and noise-free conditions, a weighted delay-and-sum (DAS) imaging method based on denoising autoencoder (DAE) learning is developed for complex composite structures. The traditional DAS formulation is modified to be more compatible with anisotropic materials. The DAE with feature learning capability is then employed to extract potentially efficient features and remove noise from ultrasonic signals. Several verification experiments conducted on flat or curved and stiffened composite structures have confirmed the ability of the DAE-DAS method to suppress artificial noise and to intensify singularities induced by the anomalies. By comparing with the unweighted DAS methods and the weighted DAS method without feature extraction, the proposed algorithm has satisfactory robustness to achieve higher localization accuracy and fewer artifacts. [ABSTRACT FROM AUTHOR]

In this paper, a damage imaging algorithm based on fractal dimension is developed for quantitative damage detection of composite structures. Box-counting dimension, a typical fractal dimension, is employed to analyze the difference of Lamb wave signals, extract damage feature and define damage index. An enhanced reconstruction algorithm for probabilistic inspection of damage is developed for damage imaging. Experimental investigation in a composite laminate and a stiffened composite panel shows that the developed algorithm could quantitatively predict the location and size of not only single but also multiple damages. The influence of parameters in the developed algorithm on the imaging quality and accuracy is studied, and reference values for parameters are presented. [ABSTRACT FROM AUTHOR]

Time reversal focusing method has been proved to be an effective method for active Lamb wave–based structural health monitoring. In this article, aiming at developing a practical method for online localization of damage on aircraft composite structures that can take advantage of time reversal focusing and do not rely on the transfer function, a phase synthesis–based time reversal focusing method was proposed. In this method, damage images are given out directly through time reversal focusing, and the other imaging processes such as the delay-and-sum imaging method adopted in many researches of time reversal focusing are not needed. Based on the damage imaging method, a structural health monitoring demonstration system was built on a composite panel of an aircraft wing box with many bolt holes and stiffeners. The demonstrated results show that this method can estimate the positions of damages efficiently with a low sensitivity of group velocity errors and a high antijamming capability. [ABSTRACT FROM PUBLISHER]

• Guided wavefield curvature is proposed for the detection of structural damage. • The guided wavefield curvature can highlight the damage-related wavefield anomalies. • Damage maps are constructed by fusing wavefield curvature energy images. • The damage maps are successfully applied for the imaging of invisible damage. Guided wavefields in composite structures carry a wealth of information about wavefield anomalies from damage–wave interactions. Although such anomalies can be used for damage detection, they are easily masked by incident waves from actuators and reflected waves from structural boundaries. This research presents a concept of guided wavefield curvature for the detection of structural damage. Wavefield curvature analysis is able to highlight the amplitudes of local anomalies in the wavefield signals associated with damage. A wavefield curvature imaging algorithm is developed for visualizing invisible damage in composite structures. The algorithm is first verified by detecting delamination in a carbon fiber reinforced polymer (CFRP) plate and then applied for detection of debonding in a honeycomb sandwich panel. In the experiments, wavefields are generated by a PZT transducer and are then registered by a scanning laser Doppler vibrometer. The experimental results accord well with the actual locations, sizes, and shapes of the delamination and debonding, confirming the effectiveness of the proposed algorithm for the detection of invisible damage in composite structures. [ABSTRACT FROM AUTHOR]

Lamb wave–based structural health monitoring technology has attracted great interest and wide attention. Most of the Lamb wave–based structural health monitoring algorithms utilize scattering signals subtracted between baseline and current signals, which are recorded before and after damage and are easily influenced by environmental changes. In this article, a baseline-free method based on similar path is proposed to identify the damage in metal and composite structures. Due to Lamb wave scattering on damage, the first wave packet of signal for the transmitter–receiver path passing through or near the damage will be weakened. Based on sensor spacing (and direction for composites), all transmitter–receiver paths of transducer array can be classified as some groups, each having similar paths. The first wave packet energies of the paths in the same group are compared with each other to calculate damage indices, which are used to image the damage. Simulations were carried out to identify single- and multi-damages in the metal and composite plates. In addition, an experiment was also conducted to verify the algorithm. Both simulation and experimental results demonstrate the feasibility and effectiveness of similar path-based damage identification method. [ABSTRACT FROM AUTHOR]