Rotor imbalance determination fit for Condition Monitoring

Johann Radon Institute for Computational and Applied Mathematics

Rotor imbalance determinationfit for Condition Monitoring

Jenny Niebsch (RICAM, Linz, Österreich)

Michael Melsheimer (BerlinWind GmbH)

EWEA

Vienna, 7. February 2013

Founded by Österreichische Forschungsförderungsgesellschaft mbH (FFG)


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Introduction and Aims

Problem

• Imbalanced rotors cause serious problems in the operation of Wind Energy Converters (WEC)

• Lifespan of components decreases

• State-of-the-art balancing methods are expensive

Aims

• Include imbalance determination in Condition Monitoring System (CMS)

• Compute absolute value and position from lateral vibration


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Introduction

State of the art

• Signal processing methods generate alarm system [1]

computation of actual value and position of imbalance not possible

• Field measurements with test weights (BerlinWind GmbH)

elaborate and expensive

[1] Caselitz, Giebhardt (2005)


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General idea

Mathematical formulation of the problem

• Replace the experimental model by a mathematical model

• Imbalance load p and vibration u coupled by equation

• Computation of imbalance from vibration data

Inverse Problem

€

u = A(p)


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Procedure

Forward Problem: How to get A ?

• M, S Mass and stiffness matrix derived from FE-model of WEA

•

• mr absolute value

• φ position of imbalance

• Solution of vibration equation

€

u = A(p)€

p(t) =ω 2mrcos(ωt +ϕ )


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Procedure

Inverse problem

• vibration data u measured with additional sensor in nacelle

• rotational frequency ω constant during measurement

• compute mr and φ in p

Raw data Preprocessed data

Imbalance and balancing weights


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Field tests

WEC types• Südwind S77-1.5MW (85 m)• Vestas V80-2MW (78 m)• Vestas V82-1.65MW (80 m)• Vestas V90-2MW (105 m)

Measurements

S77 V80 V82 V90

Amplitude in mg 0.496 1.68 5.95 2.15

% of Eigenfreq. 82% 90% 74% 95%


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Absolute value of imbalance in kgm

Field test results

S77 V80 V82 V90

BerlinWind in kgm 84 168 2072 225

Model based (kgm) 82 166 2040 194

Relative error 2.4% 1.2% 1.5% 13.8%


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Conclusion

• all test results within the confidential interval of BerlinWind

• new method reliable to quantify mass imbalance

• fit for implementation in CMS

Outlook

• Test for angle reconstruction

• expansion of method to aerodynamic imbalances (pitch angle deviation)

• methods for non-stationary frequency data

Rotor imbalance determination fit for Condition Monitoring

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