rotor imbalance determination fit for condition monitoring
DESCRIPTION
Rotor imbalance determination fit for Condition Monitoring. Jenny Niebsch (RICAM, Linz, Österreich) Michael Melsheimer (BerlinWind GmbH) EWEA Vienna, 7. February 2013 Founded by Österreichische Forschungsförderungsgesellschaft mbH (FFG). Introduction and Aims. Problem - PowerPoint PPT PresentationTRANSCRIPT
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)
Johann Radon Institute for Computational and Applied Mathematics
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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
Johann Radon Institute for Computational and Applied Mathematics
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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)
Johann Radon Institute for Computational and Applied Mathematics
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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)
Johann Radon Institute for Computational and Applied Mathematics
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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 )
Johann Radon Institute for Computational and Applied Mathematics
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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
Johann Radon Institute for Computational and Applied Mathematics
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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%
Johann Radon Institute for Computational and Applied Mathematics
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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%
Johann Radon Institute for Computational and Applied Mathematics
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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