期刊
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
卷 22, 期 2, 页码 927-947出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/14759217221094462
关键词
acoustic emission; damage localization; stiffened plate; time-reversal; time-domain spectral finite element method
A novel AE source locating approach is proposed in this study, which can efficiently and accurately locate the damage source in stiffened plates. By combining the concepts of time-reversal guided wave and time-domain spectral finite element method, the focused wavefield can be rapidly obtained without the need for high-cost and large devices. Experimental validation demonstrates the feasibility and accuracy of this method.
Stiffened thin-walled structures are widely utilized in aerospace engineering as critical load-bearing components. These structures are prone to be damaged from external impact or corrosion, and fatigue cracks. Acoustic emission (AE) is a key phenomenon accompanying damage and can be used as an efficient indicator to locate the damage in stiffened structures. In this paper, a novel AE source locating approach is proposed, which is based on combining the concepts of the time-reversal (T-R) guided wave and time-domain spectral finite element method (T-D SFEM), in which an improved T-R strategy named stepwise T-R is developed to overcome the defocus issue, and the T-D SFEM is utilized to simulate the re-emitted wavefield. Benefit from the improvement and virtual simulation, the focused wavefield can be rapidly obtained without high-cost and large bulk wavefield imagine devices. The approach is validated experimentally. In addition, the effects of the signal length, mesh size, and noise levels on locating are studied in different scenarios. The results show that the proposed approach can locate the AE source in the stiffened plate efficiently and accurately. The optimal signal length and suggested mesh size are also decided. Besides, the robustness of the proposed method is demonstrated and the results are effective in the case of the measured signals with 30% white noise.
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