Share this page on:

Conference programme 

Back to the programme printer.gif Print

Poster session

Lead Session Chair:
Stephan Barth, Managing Director, ForWind - Center for Wind Energy Research, Germany

Printer friendly version: printer.gif Print

Download poster(1.39 MB)

Presenter's biography

Biographies are supplied directly by presenters at OFFSHORE 2015 and are published here unedited

Mr Iliopoulos is a graduate mechanical engineer of the National Technical University of Athens. He conducted his master thesis in the laboratory of aerodynamics, fluid mechanics section in the prestigious and challenging topic of offshore wind turbine technology. After his dissertation, he worked as a research assistant for the Offshore Code Comparison Collaboration Continuation (OC4) International Energy Agency (IEA) annex. Currently, he is a PhD student of the Vrije Universiteit Brussel working within the framework of the IWT SBO project entitled “Serviceability Optimisation for the next generation Offshore Wind Turbines”


Life time assessment of offshore foundations using a virtual sensor approach


Offshore Wind turbines are exposed to continuous wind and wave excitations that lead to high periodic stresses and strains at critical locations. This makes the structures prone to structural failure due to possible crack initiations and propagations. Therefore, the monitoring of the condition of the offshore wind turbine during its operational states offers the possibility of improving the safety of a mission. Fatigue deterioration, affecting the wind turbine, represents, in fact, one of the major issues regarding mission safety that needs to be addressed during its entire life.


The efficacy of structural monitoring in the case of the offshore wind turbine, though, is undermined by the practical limitations connected to the measurement system in terms of cost, weight and feasibility of sensor mounting (e.g. at mudline level 30m below the water level). This limitation is overcome by reconstructing the full-field response of the structure based on the limited number of measured responses and a calibrated Finite Element Model (FEM) of the system. A modal decomposition and expansion approach is used for reconstructing the responses at all degrees of freedom of the finite element model.

Main body of abstract

The calibration of the FEM is performed by comparing the experimentally obtained modeshapes with the corresponding numerical modeshapes in terms of the Modal Assurance Criteria (MAC). A state of the art operational modal analysis technique called pLSCF, that has been automated is used to identify the modal parameters from 2 weeks of operational data while the wind turbine was in parked conditions.As long as the finite element model is calibrated, the combined use of operational acceleration data and modeshape components derived from the finite element model is able to provide sufficient information for the prediction of accelerations and strainsat different levels along the height of the structure. The prediction is based upon a modal decomposition of the measured accelerations that results in the estimation of the modal coordinates. The relation between the modal coordinate and the acceleration/strain in an arbitrary point is established by making use of the corresponding numerically obtained mode shapes. Once the strain response time histories are predicted, they can easily be translated in stress response time histories which can be used for the estimation of the expected damage accumulation and remaining life-time of the structure. Available time domain methods (e.g. rainflow counting) and frequency domain stochastic fatigue methods, based on the Palmgren-Miner damage rule and Dirlik’s probability distribution of the stress range, will be used to predict the expected fatigue damage accumulation of the structure in terms of the power spectral density (PSD) of the predicted stresses.


A fast, easy to implement, reliable and effective technique for dynamic response prediction and life-time assessment from a limited number of vibration data is introduced. The algorithm is validated using real time data (accelerations and strains) obtained from a monitoring campaign on an offshore Vestas V90 3 MW wind turbine on a monopile foundation in the Belgian North Sea.

Learning objectives
The academic objectives of this PhD research are clearly driven by actual industrial and technological requirements and include:
• Improvement of the design and concepts of offshore wind park components and their serviceability
• Development and validation of advanced numerical and experimental modelling techniques
• Development of robust and effective Structural Health and Condition Monitoring techniques for offshore wind energy through advanced data-processing
• Development of reliable remaining lifetime prediction tools