Identifying fatigue crack geometric features from acoustic emission signals

Jingjing Bao; Banibrata Poddar; Victor Giurgiutiu

doi:10.1117/12.2219307

1 April 2016 Identifying fatigue crack geometric features from acoustic emission signals

Jingjing Bao, Banibrata Poddar, Victor Giurgiutiu

Proceedings Volume 9805, Health Monitoring of Structural and Biological Systems 2016; 98051J (2016) https://doi.org/10.1117/12.2219307
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2016, Las Vegas, Nevada, United States

Abstract

Acoustic emission (AE) caused by the growth of fatigue crack were well studied by researchers. Conventional approaches predominantly are based on statistical analysis. In this study we focus on identifying geometric features of the crack from the AE signals using physics based approach. One of the main challenges of this approach is to develop a physics of materials based understanding of the generation and propagation of acoustic emissions due to the growth of a fatigue crack. As the geometry changes due to the crack growth, so does the local vibration modes around the crack. Our aim is to understand these changing local vibration modes and find possible relation between the AE signal features and the geometric features of the crack. Finite element (FE) analysis was used to model AE events due to fatigue crack growth. This was done using dipole excitation at the crack tips. Harmonic analysis was also performed on these FE models to understand the local vibration modes. Experimental study was carried out to verify these results. Piezoelectric wafer active sensors (PWAS) were used to excite cracked specimen and the local vibration modes were captured using laser Doppler vibrometry. The preliminary results show that the AE signals do carry the information related to the crack geometry.

Citation Download Citation

Jingjing Bao, Banibrata Poddar, and Victor Giurgiutiu "Identifying fatigue crack geometric features from acoustic emission signals", Proc. SPIE 9805, Health Monitoring of Structural and Biological Systems 2016, 98051J (1 April 2016); https://doi.org/10.1117/12.2219307

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