Vassilios Kappatos

Dr. Vassilios Kappatos

Hellenic Institute of Transport (HIT), Center for Research and Technology Hellas (CERTH), 6th Km Charilaou, Thermi Rd., 57001 Thermi, Thessaloniki, Greece
orcid

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 November 2015 in Renewable Energy
Verified
Journal Article
Open access
HHHossein Habibi
Hossein Habibi
LCLiang Cheng
Liang Cheng
HZHAITAO ZHENG
HAITAO ZHENG
Vassilios KappatosVassilios Kappatos
Vassilios Kappatos
CSCem Selcuk
Cem Selcuk
TGTat-Hean Gan
Tat-Hean Gan

1 July 2015 in Ocean Engineering
Verified
Journal Article
Closed access
Mathew LeggMathew Legg
Mathew Legg
MYM.K. Yücel
M.K. Yücel
ICI. Garcia de Carellan
I. Garcia de Carellan
Vassilios KappatosVassilios Kappatos
Vassilios Kappatos
CSC. Selcuk
C. Selcuk
TGT.H. Gan
T.H. Gan

1 January 2016 in Renewable Energy
Verified
Journal Article
Closed access
Mayorkinos PapaeliasMayorkinos Papaelias
Mayorkinos Papaelias
LCLiang Cheng
Liang Cheng
MKMaria Kogia
Maria Kogia
AMAbbas Mohimi
Abbas Mohimi
Vassilios KappatosVassilios Kappatos
Vassilios Kappatos
TGTat-Hean Gan
Tat-Hean Gan

1 March 2015 in Applied Acoustics
Verified
Journal Article
Closed access
JCJuan Luis Ferrando Chacon
Juan Luis Ferrando Chacon
Vassilios KappatosVassilios Kappatos
Vassilios Kappatos
WBWamadeva Balachandran
Wamadeva Balachandran
TGTat-Hean Gan
Tat-Hean Gan

6 March 2020 in Ships and Offshore Structures
Verified
Journal Article
Closed access
PKPetros Karvelis
Petros Karvelis
GGGeorge Georgoulas
George Georgoulas
Vassilios KappatosVassilios Kappatos
Vassilios Kappatos
Chrysostomos StyliosChrysostomos Stylios
Chrysostomos Stylios
Corrosion, fatigue and corrosion-fatigue cracking are the most pervasive types of structural problems experienced by ship structures. These damage modes, can potentially lead to unanticipated out of service time or catastrophic failure. Acoustic Emission is gaining ground as a complementary Structural Health Monitoring (SHM) technique, since it can offer real-time damage detection. Deep learning, on the other hand, has shown great success over the last years for a large number of applications. In this paper, the SHM on ship hulls is treated as a classification problem. Firstly, the AE signals are transformed, using the Discrete Cosine Transform, followed by a dimensionality reduction stage. Afterwards, a Deep Neural Network is employed by the classification module. The proposed approach was validated and the results indicate that our proposed method can be very effective and efficient, selecting the optimum AE sensor positions and providing almost perfect localisation results.

1 November 2014 in Applied Acoustics
Verified
Journal Article
Closed access
JCJuan Luis Ferrando Chacon
Juan Luis Ferrando Chacon
EAEstefania Artigao
Estefania Artigao
Vassilios KappatosVassilios Kappatos
Vassilios Kappatos
GAGeorgios Asfis
Georgios Asfis
TGTat-Hean Gan
Tat-Hean Gan
WBWamadeva Balachandran
Wamadeva Balachandran