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

Effect of Adhesive and Its Aging on the Performance of Piezoelectric Sensors in Structural Health Monitoring Systems

Adhesive and its aging can have influence on the Piezoelectric (PZT) elements in structural health monitoring (SHM) systems. However, the current research pays little attention to the effect of adhesives in SHM systems, and the mechanism of adhesive aging on monitoring signals is still unclear. In the present study, the relationship between types of adhesives, adhesive thickness, accelerated aging, and monitoring signal was analyzed in detail. The study was carried out with three kinds of epoxy resin AB adhesive (AW106, E-30CL, and E-120HP) and bonding thicknesses (0.01, 0.05, and 0.12 mm), and the elevated temperature was 100 °C for 45 days. The signal-based monitoring method was used to extract the characteristic parameters. The experimental results indicated that the standard shear strength and thickness of the adhesive may have a combined effect on the monitoring signal. Increasing the thickness may enhance the shear strength between PZT and the matrix. For the effectiveness of monitoring the signal propagation, however, increase in thickness may have a negative influence. Moreover, the elevated temperature will bring the signal amplitude to a peak in the first period of aging, and the highest point appears in 10 to 15 days. Nevertheless, with the increase of aging time, the adhesive will finally be degraded, resulting in the decrease of the signal amplitude. The experimental results may provide useful information for practical monitoring in the SHM field

Hole-Edge Corrosion Expansion Monitoring Based on Lamb Wave

Corrosion is a critical issue for engineered metallic components in mechanical and aerospace industries. Due to the complexity of aerospace aluminum alloy structure, corrosion is particularly tend to occur and expand in stress concentration areas, such as the edge of a hole, which causes the overall structure to be more likely to fail. In this paper, a Lamb wave-based active sensing method with improved sensors network was used to detect the hole-edge corrosion expansion. A0 wave packet of Lamb wave is extracted from signals, and two damage factors are used as characteristics of the signals. Probabilistic imaging algorithm is used to imaging and quantify the hole-edge corrosion area. Five corrosion extension tests show that the proposed method can effectively locate and quantify the hole-edge corrosion damage expansion of a single-hole structure; furthermore, the normalized amplitude damage index and phase change damage index can be used to predict hole-edge corrosion expansion effectively