Theoretical and experimental investigations on control parameters of piezo-based vibro-acoustic modulation health monitoring of contact acoustic nonlinearity in a sandwich beam

Contact-type defects are prevalent in composite constructions and sandwich panels due to failure mechanisms such as bolt loosening and delamination. Contact acoustic nonlinearity is a manifestation of such defects that nonlinear health monitoring systems can detect. Vibro-acoustic modulation (VAM) is a well-established technique for the early detection of nonlinear defects in structures. It employs bi-tone excitation to reveal damage-induced nonlinearity, which results in the appearance of sidebands in the response spectrum. The objective of this research is to use PZT-based excitation to monitor bolt loosening in a sandwich beam in real-time. To address the limited capacity of the PZT transducers to excite the nonlinear mechanism, a sensitivity analysis (SA) for input factors of VAM testing was conducted to improve damage detection using the results. The Morris approach is used to investigate the sensitivity of VAM damage metrics derived analytically in the frequency domain. To reduce the number of tests required for the experimental SA, the response surface methodology (RSM) is applied. The analysis of variance and Fischer's statistics are used to calculate the SA of experimental damage indices. In RSM computations, the discrete influence of excitation frequencies on the modulation sidebands is addressed. For reliable SA of experimental results, the effect of background noise is taken into account. The findings of this study may be applied to the selection of appropriate damage metrics in real-world applications of VAM health monitoring systems, as well as the effective tuning of input control parameters to maximize damage detectability

Three-dimensional scaled boundary finite element method to simulate Lamb wave health monitoring of homogeneous structures: Experiment and modelling

Exploiting scattering and reflection related data of ultrasonic Lamb wave interactions with damage is a common approach to health monitoring of thin-walled structures. Using thin PZT sensors, the method can be implemented in real-time. Simulation of Lamb wave propagation and its interaction with damage plays an important role in damage diagnosis and prognosis. It is, however, a time-consuming task due to the high-frequency waves that are commonly used to detect tiny damage. The current study employs the Scaled Boundary Finite Element Method (SBFEM) for effective modeling of Lamb wave health monitoring of homogenous thin plates. The electromechanical effects of piezoelectric sensors are included in the model to improve accuracy and make the results comparable to those of laboratory experiments. Simple meshing of complex topologies is possible by converting standard finite elements to scaled boundary elements. The 3D SBFEM wave motion equations are solved in the time domain to capture the sensor's PZT response to a high-frequency tone-burst actuation. The results are validated by pitch-catch and pulse-echo laboratory tests carried out on thin plates. SBFEM is used to study wave propagation in complex configurations, such as a stiffened plate, and the results are compared to their FEM counterparts. According to the findings, SBFEM significantly reduces the computational costs associated with simulation of Lamb wave health monitoring while also providing significant accuracy in comparison to the experimental results

Numerical Modelling of Stochastic Fatigue Damage Accumulation in Thick Composites

In an earlier research, experimental evidence was given on the ability to use Piezo Wafer Active Sensors and acousto-ultrasonics to monitor the accumulation of fatigue damage in a thick composite structure. As a next step, numerical models are investigated as they aid in the further understanding of the governing phenomena and a quantification of the accumulated damage. However, they suffer from high computational demands, due to a high mesh density, the stochastic nature of crack initiation and the combination of initiation and propagation of cracks. The Polynomial Chaos Expansion (PCE) method is employed to efficiently make meta models and, with these models, account for the stochastic behaviour of crack initiation and formation of delaminations. The meta models thus allow predicting the overall effect of damage accumulations within certain bounds of uncertainty. This aids in the quantification of damage accumulation, hence allowing for a damage severity estimation based on the experimental results. The input for the PCE method is a 2D Finite Element (FE) model. Cracks and delaminations are generated using Random Variables (RV) describing the geometrical position and length and orientation. Moreover, the number of cracks and delaminations is randomized as well. The necessary remeshing is done automatically, allowing for a completely automated simulation for a large number of FE simulations to feed the PCE model. Several Quantities of Interests (QoI) are defined and tested against their sensitivity to the increasing amount of damage accumulation. A global sensitivity analysis is used to identify the importance of each of the Random Variables. Random variables with a low sensitivity can be eliminated from the analysis, improving the efficiency