Abstract
This paper proposes a novel data processing framework dedicated to bedload monitoring in underwater environments. After calibration, by integration the of total energy in the nominal bandwidth, the proposed experimental set-up is able to accurately measure the mass of individual sediments hitting the steel plate. This requires a priori knowledge of the vibration transients in order to match a predefined dictionary. Based on unsupervised hierarchical agglomeration of complex vibration spectra, the proposed algorithms allow accurate localization of the transients corresponding to the shocks created by sediment impacts on a steel plate.
Highlights
Underwater bedload transport surveys are important for assessing stability issues such as reservoir silting or channel self-cleaning
We propose a novel framework for detecting and localizing the transients corresponding to the shocks created by sediment impacts on the steel plate
This paper proposed a new framework for detecting and localizing the transients corresponding to the shocks created by sediment impacts on the steel plate
Summary
Underwater bedload transport surveys are important for assessing stability issues such as reservoir silting or channel self-cleaning. By integrating the total energy in the nominal bandwidth, the proposed experimental setup is able to accurately measure the mass of individual sediments hitting the steel plate. This requires a priori knowledge of the vibration transients in order to match a predefined dictionary. The multivariate segmentation algorithm proposed in [10] is selected: the multimodal signals are analyzed by exploiting the asymptotic distribution of the covariance matrix of the complex spectra Within this context, this manuscript synthesizes the results presented in [11,12] in order to propose a unified acoustic data processing and analysis framework for the monitoring of the bedload transport in underwater environments.
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