Paper
15 April 2011 Monitoring fatigue crack growth in narrow structural components using Lamb wave technique
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Abstract
Fatigue is a progressive and localised damage that occurs when a material is subjected to cyclic loading. Historical cases have shown that undetected fatigue cracks often lead to catastrophic failure, including loss of lives and assets. It is therefore important to have a robust Structural Health Monitoring (SHM) technique to detect and monitor these cracks. The Lamb Wave technique for SHM is promising due to its ability to interrogate a large area of the structure from only a few locations. The feasibility of fatigue crack detection in wide specimens, where the effect of boundary reflections is not significant in the signal processing and damage quantification process, have been investigated by other researchers7-9. However, in a narrow structural component, the boundary reflection has a significant role in the sensor signal and the damage quantifier from available literatures cannot be applied readily. The main focus of this study is to investigate the feasibility of monitoring fatigue crack growth in a narrow structural component using the Lamb Wave technique. Experimental study conducted on lab-sized aluminum beam finds that as crack propagates amplitude of the sensor signal decreases. A damage index is proposed, and a linear relationship between the damage index and the crack length is identified. With the proposed damage index, a crack length can be estimated from the acquired sensor signals through a correlation factor.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Say Ian Lim, Lin Cui, Yu Liu, and Chee Kiong Soh "Monitoring fatigue crack growth in narrow structural components using Lamb wave technique", Proc. SPIE 7981, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011, 798143 (15 April 2011); https://doi.org/10.1117/12.880327
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Cited by 8 scholarly publications.
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KEYWORDS
Sensors

Structural health monitoring

Wave propagation

Signal processing

Transducers

Actuators

Ferroelectric materials

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