Abstract
Modal Acoustic Emission (MAE) is a branch of Acoustic Emission (AE) with proven capabilities for Structural Health Monitoring (SHM) of plate-like structures. MAE differences from AE in that MAE uses the understanding of the wave propagation to characterize and locate the source. The analysis of the waveform includes the use of time frequency techniques to determine the Time Of Arrival (TOA) of the different modes. This paper proposes the use of Bayesian inference to quantify the uncertainty in the source location for two different MAE location techniques. The first technique uses only the TOA of the extensional (symmetric) mode, while the second technique uses the TOA of both extensional and flexural (antisymmetric) modes. The Morlet wavelet is used to determine the scalogram of the waveform. The scalogram is reassigned and Markov Chain Monte Carlo (MCMC) is used to sample the posterior distribution built through Bayesian inference. Results are presented from location of Pencil Lead Breaks (PLBs) in an aluminum plate of 1/8in of thickness and 36in by 36in. Results show that using the TOA of only the symmetric mode leads to a lower level of uncertainty compared to using both extensional and flexural modes, because of the difficulty in assessing the time of arrival of the flexural mode.
Highlights
Acoustic Emission (AE) is a Non-Destructive Testing (NDT) method that allows in situ monitoring of structures and has been successfully used in different Structural Health Monitoring (SHM) applications (Cuadra and Vanniamparambil et al 2015, Zárate and Caicedo et al 2012, Ozevin and Hardin 2012)
This paper proposes the use of Bayesian inference to quantify the uncertainty in the location calculated by two Modal Acoustic Emission (MAE) location techniques
The first technique uses the Time Of Arrival (TOA) of only the extensional mode, and the source is located based on the difference in TOA of the extensional mode to the different sensors
Summary
El análisis de la forma de onda incluye el uso de técnicas de frecuencia de tiempo para determinar el Tiempo de Llegada (TOA) de los diferentes modos. La ondícula de Morlet se utiliza para determinar el escalograma de la forma de onda. El escalograma se reasigna y se utiliza la Cadena de Markov Monte Carlo (MCMC) para muestrear la distribución posterior construida a través de la inferencia bayesiana. Los resultados muestran que el uso del TOA de sólo el modo simétrico conduce a un nivel más bajo de incertidumbre en comparación con el uso de ambos modos de extensión y flexión, debido a la dificultad de evaluar el tiempo de llegada del modo de flexión. The analysis of the waveform includes the use of time frequency techniques to determine the Time Of Arrival (TOA) of the different modes. Results show that using the TOA of only the symmetric mode leads to a lower level of uncertainty compared to using both extensional and flexural modes, because of the difficulty in assessing the time of arrival of the flexural mode
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