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Proceedings Paper

Identifying transition of fatigue cracks from tensile to shear mode based on acoustic emission signals
Author(s): Kassahun Asamene; Duy Tran; Mannur Sundaresan
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Paper Abstract

Acoustic emission (AE) based structural health monitoring relies on detection and analysis of stress waves released by damage growth. The features of AE waveforms such as amplitude, frequency, energy, and rise time could be used characterize the relationship between acoustic emission signals received at a particular instant and the nature of damage growth, and several studies have examined such relationships. Acoustic emission generated by fatigue cracks propagate as a combination of a number of Lamb wave modes in plates, and hence by identifying the modal components it is potentially possible to learn about the conditions under which the crack is propagating. This paper examines the modal features of the acoustic emission signals generated at different stages of fatigue crack growth. A key requirement for this analysis is high fidelity required from the sensor recording AE signals, so that the different modes can be identified. Fatigue crack in a 6061 aluminum plate was monitored using a wideband sensor. The fatigue crack grew over a length of about 3 inches during 74,000 cycles and resulted in over 100,000 waveforms. The waveforms were examined in detail and the features were evaluated. As expected, the waveform’s peak amplitude and energy content were indicative of the rate of fatigue crack growth. More importantly, the modal features of the waveform were found to be indicative of the nature of crack growth. Mode 1 crack growth that resulted in signals that contained almost exclusively the fundamental symmetric mode S0. When the crack is propagating in shear mode, the waveforms contained dominant A0 mode. Hence, acoustic emission waveform can potentially identify the transition of a Mode 1 crack to shear crack.

Paper Details

Date Published: 1 April 2019
PDF: 6 pages
Proc. SPIE 10971, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIII, 109711L (1 April 2019); doi: 10.1117/12.2518737
Show Author Affiliations
Kassahun Asamene, North Carolina A&T State Univ. (United States)
Duy Tran, North Carolina A&T State Univ. (United States)
Mannur Sundaresan, North Carolina A&T State Univ. (United States)


Published in SPIE Proceedings Vol. 10971:
Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIII
Andrew L. Gyekenyesi, Editor(s)

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