Poster + Paper
25 April 2023 Mode-converted Lamb wave sensitivity prediction for part-thickness crack-like defects
Author Affiliations +
Conference Poster
Abstract
Fatigue crack growth is one of the most common damage types in aluminum components, widely used in aircraft structures. Detection of fatigue cracks at an early stage is important to guarantee aircraft safety. Efficient non-destructive evaluation (NDE) and structural health monitoring (SHM) can be achieved by employing low frequency guided ultrasonic waves, as they can propagate long distances along plate structures. SHM systems using distributed guided waves sensors have been proposed for efficient monitoring, but have limitations due to environmental influences such as the temperature stability of the conventional baseline subtraction method. The scattering and mode conversion of guided waves at part-thickness defects was investigated to quantify the sensitivity for defect detection and the potential for the development of a baseline-free SHM methodology employing mode converted guided waves. Baseline-free SHM methodology employing mode conversion is expected to overcome some of the limitations caused by environmental factors and to improve sensitivity and stability by employing new or modified signal processing algorithms. A three dimensional (3D) Finite Element (FE) model was developed to predict the mode conversion of the fundamental guided wave modes. The influence of defect length and depth on detection results were investigated numerically. The detection sensitivity for part-thickness defects in a plate is quantified.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. Lijian and P. Fromme "Mode-converted Lamb wave sensitivity prediction for part-thickness crack-like defects", Proc. SPIE 12488, Health Monitoring of Structural and Biological Systems XVII, 1248821 (25 April 2023); https://doi.org/10.1117/12.2657951
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KEYWORDS
Scattering

Waveguides

Structural health monitoring

Wave propagation

Aluminum

Material fatigue

Nondestructive evaluation

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