Deep machine learning for structural health monitoring on ship hulls using acoustic emission method-Reference-Cited by-同舟云学术

Deep machine learning for structural health monitoring on ship hulls using acoustic emission method

Published:2020-03-06 Issue:4 Volume:16 Page:440-448
ISSN:1744-5302
Container-title:Ships and Offshore Structures
language:en
Short-container-title:Ships and Offshore Structures

Author:

Karvelis Petros¹^ORCID,Georgoulas George²^ORCID,Kappatos Vassilios³^ORCID,Stylios Chrysostomos¹^ORCID

Affiliation:

1. Laboratory of Knowledge and Intelligent Computing, Department of Informatics and Telecommunications, University of Ioannina, Ioannina, Greece

2. DataWise LLC, Atlanta, GA, USA

3. Laboratory of Constructural and Infrastructure Research in Maritime and Air Transport, Hellenic Institute of Transport (HIT), Center for Research and Technology Hellas (CERTH), Thessaloniki, Greece

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Ocean Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/17445302.2020.1735844

Reference45 articles.

1. [ABoS] American Bureau of Shipping. 2002. Technical analysis related to the prestige casualty on 13 November.

2. [ABS] American Bureau of Shipping. 2007. Hull survey for new construction.

3. Discrete Cosine Transform

4. Acoustic emission monitoring for detecting structural defects in vessels and offshore structures

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