Vrije Universiteit Brussel

Output based methods for in-situ fatigue monitoring for design optimization and lifetime extension of monopile foundationsHenkel, Maximilian; Weijtjens, Wout; Devriendt, Christof

Publication date:2019

Document Version:Final published version

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Citation for published version (APA):Henkel, M., Weijtjens, W. (Ed.), & Devriendt, C. (Ed.) (2019). Output based methods for in-situ fatiguemonitoring for design optimization and life time extension of monopile foundations. Poster session presented atWind Europe Offshore 2019, .

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Download date: 22. Aug. 2020

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1. Ziegler et al., Structural monitoring for lifetime extension of offshore wind monopiles: Verification of strain-based load extrapolation algorithm, Marine Structures 154-163, 66 (2019)

2. Henkel et al., Sub-soil strain measurements on an operational wind turbine for design validation and fatigue assessment, J. Phys. Conf. Ser. 1037 (2018)

3. Iliopoulos et al., A modal decomposition and expansion approach for prediction of dynamic responses on a monopile offshore wind turbine using a limited number of vibration sensors, Mechanical Systems and Signal Processing 68-69, 84 (2016)

Three monopiles at the Nobelwind offshore wind farm were instrumented with an array of optical fiber strain gauge sensors. This offers the possibility to measure the strain on the most fatigue critical locations on the monopile. Theses measurements will be used to validate the concepts of virtual sensing

Fatigue loading of offshore wind turbines is an interaction of wave loads, windloads and the first structural modes of a wind turbine substructure. The designof most offshore wind turbines on monopile(MP) foundation is driven by thefatigue life of the welded connections in the MP. As a result of designoptimization typically the first welds beneath the sea bed are most fatiguecritical and determine the lifetime of the offshore wind turbine. Accurateinformation about damage progress is essential for O&M strategies but also forfurther design optimization while both visual inspections and sensor installationare not favorable for those locations.

Abstract Results

Monopile strain monitoring

Conclusions and Future work

Virtual sensing : Concept

References

Two fast, easy to implement, reliable and effective technique for output basedfatigue prediction and life-time assessment from a limited number of sensorsare introduced. The algorithms are validated using 30d of measurement dataobtained from a monitoring campaign on a monopile foundation in the BelgianNorth Sea. During the benchmarking both methods showed the ability topredict subsoil fatigue accurately.The availability of subsoil data within this project is exceptional. Commonlymode shapes for virtual sensing and the transfer function of DEL extrapolationmethods will be trained with FE data. It is desired to evaluate the influence ofsuch an approach. Furthermore, it is envisioned to extend the validation periodto analyze influence of time varying effects e.g. scouring. Therefore virtualsensing will be integrated in a model updating scheme. Within the continuedwork on virtual sensing adaptations of the method will be considered to betterdeal with subsoil-damping and uncertainties in the mode shapes.

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Output based methods for in-situ fatigue monitoring for design optimization and life time extension of monopile foundations

M Henkel/ W Weijtjens/ C DevriendtOWI-Lab/ Vrije Universiteit Brussel (VUB)

Virtual sensing2 estimates strain history of differentlocations on the monopile based on outputmeasurements in easily accessible locations i.e.turbine tower. Unlike a digital twin, virtual sensing willnot require any additional simulations or a detailedmodel. Virtual sensing uses dynamic responsemeasurements to compose virtual measurements. Bystarting from response measurement the methodinherently captures the interaction between wind andwave loads and the dynamic offshore wind turbine.

Estimation consists of quasi-static and dynamic band.First combines a SG sensor with the static deflectionof the turbine and latter ACC sensors with thedynamic modes. It is already successfully applied tothe welds of offshore wind turbines on monopilessubstructures for locations above water3.

Accelerometer (ACC)Strain gauge (STR)Virtual sensor (EST)

As a benchmark the DEL extrapolation method1 isused. This method relates the recorded damage of asingle SG sensor level to another. This DEL ratiobetween measurement and virtual location isdetermined over various conditions during a trainingperiod. In this research the DEL ratio is trained withmeasurement data.

1 DEL predicted/measured [-]

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Virtual sensingDEL extrapolation

Subsequently, DELs are calculated fromtime history assuming linear damage.Results are compared to the direct DELextrapolation showing very similaraccuracy of both methods in estimatingDELs of a subsoil location (left). Onaverage an error of 5% occurs for thevirtual sensing approach while the erroris slightly smaller for the DELextrapolation method. However accuracyappeared to depend noticeable from thetraining period.

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Frequency

MeasurementVirtual sensing

“Measuring loads directly on the monopile

will not be feasible for existing offshore wind

turbines, therefore virtual sensing can be

used.”

DEL

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Time

Over a period of 30 days virtualsensing and the DEL extrapolationmethod are tested thus theirperformance over many differentoperational and environmentalconditions are analyzed. Thisvirtual sensing approach usesmode shapes obtained from 7d ofmeasurements while thecompeting method is trained withdata of the 30d previous validationperiod. In a first step strain historyis generated for every 10mincondition via virtual sensing(right).The PSD shows a good fit of theestimation in the quasi-static bandand for the first two dynamicmodes. In time domain a timedelay becomes apparent which islikely due to damping.

Time