Dispersion of Lamb waves in a honeycomb composite sandwich panel

Model-Assisted Guided-Wave-Based Approach for Disbond Detection and Size Estimation in Honeycomb Sandwich Composites

One of the axioms of structural health monitoring states that the severity of damage assessment can only be done in a learning mode under the supervision of an expert. Therefore, a numerical analysis was conducted to gain knowledge regarding the influence of the damage size on the propagation of elastic waves in a honeycomb sandwich composite panel. Core-skin debonding was considered as damage. For this purpose, a panel was modelled taking into account the real geometry of the honeycomb core using the time-domain spectral element method and two-dimensional elements. The presented model was compared with the homogenized model of the honeycomb core and validated in the experimental investigation. The result of the parametric study is a function of the influence of damage on the amplitude and energy of propagating waves.

Optimizing the placement of piezoelectric wafers on closed sections using a genetic algorithm - Towards application in structural health monitoring

Sensor network design is essential to efficiently integrate Structural Health Monitoring (SHM) systems in aerospace, automotive, and civil structures. This study describes an optimization model for piezoelectric (PZT) wafer placement on curved structures and closed sections. The proposed approach relied on the transformation of any complex/closed surface regardless of the shape of its cross-section into a flat plate and imposed a set of boundary conditions to account for the wave propagation characteristics. Because the structure was continuous and the wave could propagate in every direction, for simplicity and without sacrificing accuracy, our model assumed that a pair of PZT elements communicated information in the two shortest directions. Thus, the concept of having two paths for each PZT couple was introduced to tackle this multidirectional behavior. The plate was then discretized into a set of control points that represented the structure geometry. The PZT couples covered the control points along the line of sight and in the neighborhood of their direct and indirect paths. The objective function was to maximize the number of covered points while minimizing the number of PZT wafers. The proposed model was solved using a genetic algorithm and was validated on circular and square sections. Sensors were spread on the circumference of the structure rather than mounting them in the form of rings or axial lines. The optimized PZT networks had high coverage that reached 99% in simulations. Notably, the optimized model improved the preliminary solution coverage by 14%. Experimental validation was performed on the circular section (pipe). The results demonstrated the proficiency of the developed model in distributing the PZT wafers on closed sections. The coverage was further evaluated by assessing if damaged areas on the pipe surface could be identified. Artificial damage was accurately located within 18 mm from the actual location. These results demonstrate that our model efficiently distributes PZT wafers on closed structures.

Low-Velocity Impact Localization on a Honeycomb Sandwich Panel Using a Balanced Projective Dictionary Pair Learning Classifier

Carbon-fiber aluminum honeycomb sandwich panels are vulnerable to low-velocity impacts, which can cause structural damage and failures that reduce the bearing performance and reliability of the structure. Therefore, a method for locating such impacts through a sensor network is very important for structural health monitoring. Unlike composite laminates, the stress wave generated by an impact is damped rapidly in a sandwich panel, meaning that the signal qualities measured by different sensors vary greatly, thereby making it difficult to locate the impact. This paper presents a method for locating impacts on carbon-fiber aluminum honeycomb sandwich panels utilizing fiber Bragg grating sensors. This method is based on a projective dictionary pair learning algorithm and uses structural sparse representation for impact localization. The measurement area is divided into several sub-areas, and a corresponding dictionary is trained separately for each sub-area. For each dictionary, the sensors are grouped into main sensors within the sub-area and auxiliary sensors outside the sub-area. A balancing weight factor is added to optimize the proportion of the two types of sensor in the recognition model, and the algorithm for determining the balancing weight factor is designed to suppress the negative effects on the positioning of the sensors with poor signal quality. The experimental results show that on a 300 mm × 300 mm × 15 mm sandwich panel, the impact positioning accuracy of this method is 96.7% and the average positioning error is 0.85 mm, which are both sufficient for structural health monitoring.

Lamb wave-based mapping of plate structures via frontier exploration

Substantial improvements in material processing and manufacturing techniques in recent years necessitate the introduction of effective and efficient nondestructive testing (NDT) methods that can seamlessly integrate into day-to-day aircraft and aerospace operations. Lamb wave-based methods have been identified as one of the most promising candidates for the inspection of large-scale structures. At the same time, there is presently a high level of research in the field of autonomous mobile robotics, especially in simultaneous localization and mapping (SLAM). Thus, this paper investigates a means to automate Lamb wave-based NDT by positioning sensors along a planar structure through mobile service robots. To this end, a generalized method for the mapping of plate structures using scattered Lamb waves by means of frontier exploration is presented such that an autonomous SLAM-capable NDT system can become realizable. The performance of this novel Lamb wave-based frontier exploration is first evaluated in simulation. It is shown that it generally outperforms a random frontier exploration and may even perform near-optimal in the case of an isotropic, square panel. These findings are then validated in laboratory experiments, confirming the general feasibility of utilizing Lamb waves for SLAM. Furthermore, the versatility of the developed methodology is successfully demonstrated on a more complexly shaped stiffened panel.

Semi-analytical modeling of anchor loss in plate-mounted resonators

A semi-analytical technique for estimating the energy loss in a resonator mounted to an infinite plate substrate is proposed in this paper. In a plate, only Lamb waves have to be considered, leading to a simplified characterization of the energy carried away from a vibrating source on the plate surface. Instead of employing absorbing elements at the boundaries of the plate-resonator finite element model, it is shown how the semi-analytical approach of stitching together analytical Lamb wave expressions to the finite element model can be utilized. The approach is demonstrated for single and double cantilever configurations on a plate. The results have excellent agreement with those of conventional transient finite element simulations.

Core-Skin Disbond Detection in a Composite Sandwich Panel Using Guided Ultrasonic Waves

Advanced composite materials are being increasingly used in state-of-the-art aircraft and aerospace structures due to their many desirable properties. However, such composite materials are highly susceptible to developing internal damage. Thus, safe operation of such structures requires a comprehensive program of effective nondestructive inspection and maintenance of their critical load bearing components before the defects grow and become unstable, resulting in failure of the entire structure. Ultrasonic guided wave-based methods have the potential to significantly improve current inspection techniques for large plate-like structural components due to the waves' large propagation range and sensitivity to defects in their propagation path. The application of guided waves for nondestructive evaluation (NDE) of real structures, however, requires a thorough understanding of the characteristics of guided waves in composite structures in the presence and absence of any defects. In this paper, the interaction of guided waves with a core–skin disbond in a composite sandwich panel is studied using a semi-analytical method, numerical simulations, and laboratory experiments. It is shown that the disbond causes complex mode conversion at its leading and trailing edges. The theoretical findings are verified with laboratory experiments, and the applicability of the proposed pitch–catch setup for NDE of complex composite structures for damage detection is discussed.

A Fatigue Crack Size Evaluation Method Based on Lamb Wave Simulation and Limited Experimental Data

This paper presents a systematic and general method for Lamb wave-based crack size quantification using finite element simulations and Bayesian updating. The method consists of construction of a baseline quantification model using finite element simulation data and Bayesian updating with limited Lamb wave data from target structure. The baseline model correlates two proposed damage sensitive features, namely the normalized amplitude and phase change, with the crack length through a response surface model. The two damage sensitive features are extracted from the first received S₀ mode wave package. The model parameters of the baseline model are estimated using finite element simulation data. To account for uncertainties from numerical modeling, geometry, material and manufacturing between the baseline model and the target model, Bayesian method is employed to update the baseline model with a few measurements acquired from the actual target structure. A rigorous validation is made using in-situ fatigue testing and Lamb wave data from coupon specimens and realistic lap-joint components. The effectiveness and accuracy of the proposed method is demonstrated under different loading and damage conditions.

Multi-Mode Electromagnetic Ultrasonic Lamb Wave Tomography Imaging for Variable-Depth Defects in Metal Plates

This paper proposes a new cross-hole tomography imaging (CTI) method for variable-depth defects in metal plates based on multi-mode electromagnetic ultrasonic Lamb waves (LWs). The dispersion characteristics determine that different modes of LWs are sensitive to different thicknesses of metal plates. In this work, the sensitivities to thickness variation of A0- and S0-mode LWs are theoretically studied. The principles and procedures for the cooperation of A0- and S0-mode LW CTI are proposed. Moreover, the experimental LW imaging system on an aluminum plate with a variable-depth defect is set up, based on A0- and S0-mode EMAT (electromagnetic acoustic transducer) arrays. For comparison, the traditional single-mode LW CTI method is used in the same experimental platform. The imaging results show that the computed thickness distribution by the proposed multi-mode method more accurately reflects the actual thickness variation of the defect, while neither the S0 nor the A0 single-mode method was able to distinguish thickness variation in the defect region. Moreover, the quantification of the defect’s thickness variation is more accurate with the multi-mode method. Therefore, theoretical and practical results prove that the variable-depth defect in metal plates can be successfully quantified and visualized by the proposed multi-mode electromagnetic ultrasonic LW CTI method.