K. Schröder, S. Grove, S. Tsiapoki, C.G. Gebhardt and R ... · Gebhardt and R. Rolfes. EERA...

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Structural Change Identification at a Wind Turbine Blade using Model Updating

K. Schröder, S. Grove, S. Tsiapoki, C.G. Gebhardt and R. Rolfes

EERA DeepWind’18, 18.01.18

DeepWind’18 18.01.18 2

Content

I. Motivation

II. Optimization based model updating

III. Rotor blade test

IV. Model updating at the rotor blade1. Damage localization2. Ice accretion

V. Conclusion and Outlook

DeepWind’18 18.01.18 3

Motivation

• Remote location

• Rotor blades: costly and time-consuming repair

• Ice accretion: - Risk of ice throw

- Undesired loads

Localization and quantification of structuralchanges using model updating

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Finite Element Model Updating

Damage event

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Deviation between numerical model andmeasured data

Modal parameters

Transmissibility functions

• Eigenvalues• Mode shapes

Quantification of the „difference“ between model and measurement

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Minimization of the deviation

• Nonlinear• Constrained• Nonconvex• Several local minima

Global optimization algorithm:Simulated Quenching

Local optimization algorithm:Sequential Quadratic Programming

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Rotor blade test

• Hammer excitation

• 12 measurement channels

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• Hammer excitation

• 12 measurement channels

• Ice mass

• Damage

Trailing edge bondline: Spot of damage initiation

Trailing edge – PressureSide (outside)

Rotor blade test

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Numerical Modeling

•Rectangular Cross Section

•Known: EI and mass

•26 Timoshenko beam elements

•Clamping at blade root

•Material damping

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Numerical validation

Stiffness reduction

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Numerical validation–Modal Parameters

Parameter number

Parameter number

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Numerical validation –Transmissibility Functions

Parameter number

Parameter number

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Ice accretion

• 4 steps

• Variation of density

• Optimization problem:

• Step 3: 14,4kg at 32m-33m and 33m-34m

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Ice localization – Modal Parameters

• Correct Localizations in runs 1, 3, 7, 9 und 11

• Verification using objective function value

• Ice localization using modal parameters is possible

Parameter number

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Ice quantification – Modal ParametersSt

iffne

ssPa

ram

eter

4 in

%

Ice set (rotor blade mass in %)0.1 0.3 0.6 0.9

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Conclusion & Outlook

• Updating in numerical examplesand for ice quantification successful

• Minimization using global two-step optimization algorithm• No success for damage localization using measured data• Modal parameters superior to transmissibility functions

• Investigate more advanced metrics for model updating• Application to changing conditions (in situ)

Conclusion

Outlook

DeepWind’18 18.01.18 17

Thank you for your attention!

Leibniz Universität HannoverInstitute of Structural Analysis (ISD)Appelstraße 9a, 30167 Hannover

+49 511 762 8063k.schroeder@isd.uni-hannover.de