Acoustic emission characterisation of two pre-cracked specimens

Antonio Gálvez, Diego Galar, Asier Alonso, Borja Errasti-Alcalá, Ismael Bienvenido, Patxi Ortego, Esko Juuso

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This article contains the experiments carried-out to study the capabilities of Acoustic Emissions (AE) in a Ship To Shore (STS) crane. This solution studies the implementation of Structural Health Monitoring (SHM) in an STS crane based on acoustic emissions (AE) technique for detecting cracks and assessing their growth in steel elements subjected to fatigue. The first experiment is performed using a compact tension specimen (CT) made of steel S355 whose dimensions are 125x120x50 mm and its cracks and dimensions are defined based on ASTM and ISO standards. The CT is monitored using AE sensors, and then, the features are extracted from the raw data and used to train, test and validate an unsupervised model. The crack detection model obtains a remarkable accuracy; crack detection at sizing of 3 mm length. As the CT dimensions are small, it is difficult to evaluate the attenuation of AE signals, which is completely necessary for monitoring STS cranes. Therefore, a second experiment is performed using a panel made of steel S355, whose dimensions are 2120x200x8 mm; the panel contains a crack of 50x3 mm. This experiment is performed to analyse the AE signals that come from cracks; specifically, to assess signals attenuation, how the attenuation affects cracks detection in the panel, and features evolution while crack propagation. This is led by monitoring the crack growth with crack detection gauges and installing the AE sensors at different distances of the crack. The assessment is used to develop an unsupervised model to detect cracks and an algorithm for localizing them.

Original languageEnglish
Title of host publication18th International Conference on Condition Monitoring and Asset Management, CM 2022
PublisherBritish Institute of Non-Destructive Testing
Pages87-110
Number of pages24
ISBN (Electronic)9781713862277
Publication statusPublished - 2022
Event18th International Conference on Condition Monitoring and Asset Management, CM 2022 - London, United Kingdom
Duration: 7 Jun 20229 Jun 2022

Publication series

Name18th International Conference on Condition Monitoring and Asset Management, CM 2022

Conference

Conference18th International Conference on Condition Monitoring and Asset Management, CM 2022
Country/TerritoryUnited Kingdom
CityLondon
Period7/06/229/06/22

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