Journals Proceedings

International Journal of Advancements in Mechanical and Aeronautical Engineering

Optimum Position of Acoustic Emission Sensors for Ship Hull Structural Health Monitoring Based on Deep Machine Learning

Author(s) : GEORGE GEORGOULAS , PETROS KARVELIS , VASILIS TZITZILONIS , VASSILIOS KAPPATOS

Abstract

Abstract—In this paper a method for the estimation of the optimum sensor positions for acoustic emission localization on ship hull structures is presented. The optimum sensor positions are treated as a classification (localization) problem based on a deep learning paradigm. In order to avoid complex and timeconsuming implementations, the proposed approach uses a simple feature extraction module, which significantly reduces the extremely high dimensionality of the raw signals/data. The optimum sensor position is defined by the maximum localization rate. In simulation experiments, where a stiffened plate model was partially sunk into the water, the localization rate of acoustic emission events in a noise-free environment is greater than 99.5 %, using only a single sensor.

No fo Author(s) : 4
Page(s) : 125-128
Electronic ISSN : 2372-4153
Volume 5 : Issue 1
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