Presentation + Paper
18 April 2023 The efficiency of arrival time picking methods for acoustic emission source localization in structures with simultaneous damage mechanisms
Author Affiliations +
Abstract
Acoustic Emission (AE) source localization is an effective technique to monitor the invisible damage in structures. However, when multiple damage mechanisms coincide, a single AE hit may summate multiple AE events. Concrete structures, especially 3D geometries such as slabs, may have multiple crack initiations simultaneously, which influence the arrival time accuracy. The source localization is highly affected by the selected arrival time picking method. Most commercial data acquisition systems use a threshold-based method to extract the arrival time. Due to the occurrence of multiple cracks simultaneously and the influence of system noises, signal with low signal-to-noise ratios or the continuation of a prior event in the pre-trigger regime are more likely to have more significant errors. This paper implements the conventional threshold-based method, floating threshold-based method and Akaike’s Information Criteria (AIC) method. In addition, the wavelet transformation technique was applied to the waveform to decompose the complex multi-frequency signal into a family of single-frequency wavelets. Damage-related wavelet was selected based on the wavelet coefficients in the wavelet spectrogram. This paper compares these two methods' results using raw and decomposed signals. Efficiency of the results were verified by conducting the source localization algorithm. The source localization results illustrated that the accuracy of the damage localization is significantly improved by adapting the wavelet transformation on threshold-based since the arrival time was picked more accurate.
Conference Presentation
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Tonghao Zhang, Sena Tayfur, and Didem Ozevin "The efficiency of arrival time picking methods for acoustic emission source localization in structures with simultaneous damage mechanisms", Proc. SPIE 12487, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVII, 124870N (18 April 2023); https://doi.org/10.1117/12.2658577
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KEYWORDS
Wavelets

Source localization

Sensors

Signal detection

Interference (communication)

Acoustic emission

Signal to noise ratio

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