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

Abstract

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.

Fatigue-Damage Evolution of Notched Composite Multilayered Structures under Tensile Loads

“…However, those results cannot be used for the quantitative evaluation of the fatigue degradation. For the simplest example of a single crack in an aluminum specimen, the discrepancy between theoretical predictions and variations of the signal-processing features was also observed [32]. 10): I-actuator and sensors s3 or s7 where the wave crossed the hole, II-actuator and sensors s8 or s4 where the wave moved at the direction of the cracks along the fibers oriented at 45° (red lines in Figure 10) and III-actuator and sensors s9 and s8 where the wave was transmitted mainly in the composite plate area.…”

“…However, those results cannot be used for the quantitative evaluation of the fatigue degradation. For the simplest example of a single crack in an aluminum specimen, the discrepancy between theoretical predictions and variations of the signal-processing features was also observed [32]. …”

Optimizing the Calibration Error of Refraction Angles in Ultrasonic Angle Beam Testing

“…For example, F. Bettayeb suppressed noise to enhance flaw location by wavelet transform [9]; C. Zhou developed the probability-based diagnostic imaging approach to improve the accuracy [10]; L. Gandossi, J. He and J. Yang used Bayesian updating to improve accuracy [7,11,12]; J. Zhang used the scattering-matrix-based approach to increase sensitivity in ultrasonic arrays testing [13]; L. De Marchi used the warped frequency transform technology to overcome the difficulties associated with wave arrival time detection [14,15]. J.…”

A Real-Valued Genetic Algorithm for Optimization of Sensor Placement for Guided Wave-Based Structural Health Monitoring

“…The propagating wave may be used to cover a large area and through the processing of the time of flight (TOF) allows damage isolation. The GW have been shown to be sensitive to extremely small levels of damage and have been employed for detection of damage due to impact, corrosion, and fatigue [1][2][3][4].…”