Structural Artificial Intelligence Health Monitoring System - SAIHMS
Typ
Examensarbete för masterexamen
Program
Publicerad
2021
Författare
OLMEDO ÁVILA, ANTONIO
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
This Master thesis has the purpose to perform a study of the possibilities and
methods applicable to the development of a health monitoring system in an
innovative new type of floating offshore wind turbine platform. The lack of
knowledge of the behaviour in service of elements not used before in this specific
application, like sheaves and dynamic mooring lines, makes necessary the use of
monitoring systems during the operation of the reduced scale prototype.
Lately the use of Artificial Intelligence methods is being developed to process the
big amount of data produced during the constant monitoring process. The good
results obtained in the combination of monitoring services with Artificial
Intelligence make those systems very attractive to possible investor in the
offshore field that see their maintenance and inspections costs reduced thanks to
the possibility to apply preventive maintenance before severe damage appear in
the structure.
The simple Neural Network architecture developed in this study proves the
accuracy and efficiency of the Artificial Intelligence techniques in the structural
state classification that see its efficiency improved by its combination with
Machine Learning metaheuristic algorithms during its training process.
Beskrivning
Ämne/nyckelord
ds: offshore, offshore wind, offshore platform, floating structures, structural health monitoring , neural network, artificial intelligence, biogeography based optimization, machine learning, damage detection