An entropy-based probabilistic model for acoustic emission RA-value-average ‎frequency data

Pedram Bazrafshan; Arvin Ebrahimkhanlou

doi:10.1117/12.3009974

9 May 2024 An entropy-based probabilistic model for acoustic emission RA-value-average ‎frequency data

Proceedings Volume 12951, Health Monitoring of Structural and Biological Systems XVIII; 129512E (2024) https://doi.org/10.1117/12.3009974
Event: SPIE Smart Structures + Nondestructive Evaluation, 2024, Long Beach, California, United States

Abstract

This study presents an innovative method for probabilistic modeling of acoustic emission by applying the principles of maximum entropy and utilizing a non-Gaussian probability distribution. The focus is on mathematical modeling of the RA (rise time to amplitude ratio) values versus the Average Frequency (AF) using a fourth-order non-Gaussian probability distribution. The main goal is to introduce this probabilistic model for AE data and showcase some of its benefits. Specifically, the model can 1) identify cracks at early stages and 2) distinguish between shear cracks and tensile (flexural) cracks within concrete and wood. To confirm the effectiveness of the proposed model, experimental data from acoustic emission tests on a concrete slab and a wood specimen are used. The parameters of the proposed probabilistic model capture the transition from one cracking mode to another. The results demonstrate the model’s success in detecting the transition of cracks from tensile to shear at different stages. Capturing the evolution of the cracks is made possible by incorporating the parameter of time alongside the proposed fourth-order probabilistic model. These results indicate that the suggested method is a powerful mathematical approach for probabilistic modeling of RA-AF plots of AE data.

Conference Presentation

Citation Download Citation

Pedram Bazrafshan and Arvin Ebrahimkhanlou "An entropy-based probabilistic model for acoustic emission RA-value-average ‎frequency data", Proc. SPIE 12951, Health Monitoring of Structural and Biological Systems XVIII, 129512E (9 May 2024); https://doi.org/10.1117/12.3009974

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