2015 12-02-optiwind-offshore-wind-turbine-modelling-lms-samsef-siemens
TRANSCRIPT
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Emilio Di Lorenzo – Research engineer – Siemens Industry Software nv PhD candidate at KU Leuven and University of Naples "Federico II" [email protected]
OFFSHORE WIND TURBINE MODELLING IN LMS SAMCEF TO DERIVE AND VALIDATE NEW PROCESSING APPROACHES
Optiwind Open Project Meeting, Leuven, Belgium 02/12/2015
E. Di Lorenzo, S. Manzato
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Agenda
1. Introduction
2. Rotor analysis
1. MBC transformation
2. HPS method
3. Validation cases
4. Conclusions
3. Gearbox analysis
1. Operational Modal Analysis
2. Order-Based Modal Analysis
3. Validation cases
4. Conclusions
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Objectives
• Understand the problems and limitations of applying Operational Modal Analysis (OMA) techniques to wind turbines in operation
Deal with the time-variant nature of the structure Deal with presence of harmonics components
• Development of methodologies for automated data
processing for online structural health monitoring (SHM) applications
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Operational Modal Analysis - OMA
• Identification of modal parameters (natural frequencies, damping ratios, mode shapes) from response data measured in operating conditions
• Operational Modal Analysis = identifying H without knowing U (white noise assumption) based on Y
Unkown input Structure Measured output
U H
Y
310.000.00 s
0.34
-0.36
Rea
lg
1.00
0.00
Ampl
itude
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OMA: Limitations and solutions
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Agenda
1. Introduction
2. Rotor analysis
1. MBC transformation
2. HPS method
3. Validation cases
4. Conclusions
3. Gearbox analysis
1. Operational Modal Analysis
2. Order-Based Modal Analysis
3. Validation cases
4. Conclusions
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Rotor analysis
• Analyze the modal behaviour of Linear Time Periodic (LTP) systems.
• Analyze data with an harmonic dominance which masks the structural dynamics.
• Find modal parameters sensitive to small structural damages for SHM purposes.
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Multi-Blade coordinate transformation - MBC
• Method to describe the motions of individual blades in the same coordinate system as the structure supporting the rotor
• Offers physical insight into rotor dynamics and how rotor interacts with fixed-system entities
• Fundamental assumption: rotor must be isotropic
• Filters out all periodic terms except those which are integral multiples of ΩN, where Ω is the rotor angular speed and N is the number of blades G.S.Bir – Multiblade Coordinate Transformation and
its Application to Wind Turbine Analysis
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Multi-Blade coordinate transformation - MBC
∑=
=N
bibi q
Nq
1,,0
1
( )b
N
bibic nq
Nq ψ∑
=
=1
,, cos2
)(sin21
,, b
N
bibis nq
Nq ψ∑
=
=
Mode animation
Mode shapes in physical coordinates
Inverse MBC transformation
OMA
Mode shapes in multiblade coordinates
Modal frequencies & damping ratios
Accelerations in multiblade coordinates
MBC transformation
Accelerations of points on the
blades
Data from measurement campaign/aeroelastic code
Accelerations of points on the tower/nacelle
RESULTS
)sin()cos( ,,,0, bisbiciib qqqq ψψ ++=
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• Input at a single frequency will cause output at a single frequency
𝑢 𝑡 = 𝑢0 sin 𝜔𝑡
y 𝑡 = 𝑦0 sin 𝜔𝑡 − 𝜙
Harmonic Power Spectrum - HPS
Linear Time Invariant (LTI) system �̇� = 𝑨𝑥 + 𝑩𝑢 𝑦 = 𝑪𝑥 + 𝑫𝑢
Linear Time Periodic (LTP) systems �̇� = 𝑨(𝑡 + 𝑇𝐴)𝑥 + 𝑩(𝑡 + 𝑇𝐴)𝑢
𝑦 = 𝑪(𝑡 + 𝑇𝐴)𝑥 + 𝑫(𝑡 + 𝑇𝐴)𝑢
• Input at a single frequency will cause output at an infinite number of frequencies
𝑢 𝑡 = 𝑢0 sin 𝜔𝑡
y 𝑡 = 𝑦0 sin 𝜔𝑡 − 𝜙 + 𝑦1 sin (𝜔 + 𝜔𝐴𝑡) − 𝜙 + ⋯
𝜔𝐴 =2𝜋𝑇𝐴
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Harmonic Power Spectrum - HPS
Linear Time Invariant (LTI) system �̇� = 𝑨𝑥 + 𝑩𝑢 𝑦 = 𝑪𝑥 + 𝑫𝑢
Linear Time Periodic (LTP) systems �̇� = 𝑨(𝑡 + 𝑇𝐴)𝑥 + 𝑩(𝑡 + 𝑇𝐴)𝑢
𝑦 = 𝑪(𝑡 + 𝑇𝐴)𝑥 + 𝑫(𝑡 + 𝑇𝐴)𝑢
𝑢 𝑡 = 𝑢0 sin 𝜔𝑡
y 𝑡 = 𝑦0 sin 𝜔𝑡 − 𝜙 + 𝑦1 sin (𝜔 + 𝜔𝐴)𝑡 − 𝜙 + ⋯ y 𝑡 = 𝑦0 sin 𝜔𝑡 − 𝜙
u𝑛 𝑡 = � 𝑢(𝑡)𝑒 𝑖𝜔+𝑖𝑛𝜔𝐴 𝑡𝑑𝑡∞
−∞
y𝑛 𝑡 = � 𝑦(𝑡)𝑒 𝑖𝜔+𝑖𝑛𝜔𝐴 𝑡𝑑𝑡∞
−∞
Power Spectrum (LTI system) Harmonic Power Spectrum (LTP system)
𝑢 𝑡 = 𝑢0 sin 𝜔𝑡
M. S. Allen et al. – Output-Only Modal Analysis of Linear Time Periodic Systems with Application to Wind Turbine Simulation Data
EMP
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Harmonic Power Spectrum - HPS
Mode animation
Time periodic mode shapes
Harmonic Power
Spectrum (HPS)
Modal frequencies & damping ratios
Exponentially Modulated
Periodic (EMP) signal
Accelerations of points on the wind turbine under random
excitation
Data from measurement campaign/aeroelastic code
RESULTS
OMA
Summation over the
harmonics
Mode shapes at different harmonics
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Reference wind turbines
NREL 5-MW WIND TURBINE Rated rotor speed 12.1 rpm Generator rated power 5 MW Tower Height 87.6 m Tower Mass 347*103 kg Nacelle Mass 240*103 kg
NREL 5-MW Wind Turbine
DTU 10-MW WIND TURBINE Rated rotor speed 9.6 rpm Generator rated power 10 MW Tower Height 119 m Tower Mass 628*103 kg Nacelle Mass 446*103 kg
DTU 10-MW Wind Turbine
2D WIND TURBINE m1 = m2 = m3 41,7*103 kg mT 446*103 kg k1 = k2 = k3 2,006*108 Nm/rad kH 2,6*106 N/m kV 5,2*108 N/m
2D Wind Turbine
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2D Wind Turbine
1.500.00 Hz
0.01e-3
1.00e-12Lo
g
g2
180.00
-180.00
°
Before MBC - bladeAfter MBC - bladeTower
1.500.00 Hz
0.01e-3
0.10e-12
Log
g2
180.00
-180.00
°
Before MBC - bladeAfter MBC - bladeTower
• Crosspower comparison before and after MBC transformation • Isotropic rotor vs. Anisotropic rotor (k3=0.85*k1) • Same considerations can be done by applying HPS method • Very good match between MBC and HPS results has been found
Isotropic rotor Anisotropic rotor
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2D Wind Turbine
No transformation
• White noise input • Extract displacement from the model and
apply OMA technique • Estimate modal parameters by means of
Operational Polymax
MBC transformation
HPS method
MBC AutoMAC HPS AutoMAC
MAC: (MBC) vs. (HPS selection)
Mode #
Freq [Hz]
S2S 0,37
B_as 0,84
B_coll 0,84
B_as 0,92
Mode #
Freq [Hz]
S2S 0,37
B_bw 0,74
B_coll 0,86
B_fw 1,06
Parked Operating (Ω=0.16 Hz)
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2D Wind Turbine
Tower S2S mode Collective Edge mode
Backward Whirling
mode
Forward Whirling
mode
Backward Whirling Mode
f=0.37 f=0.74 f=0.86 f=1.06
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2D Wind Turbine
Backward Whirling Mode
k1= 0.98*k1
• Isotropic conditions: Backward and forward whirling mode shapes have a constant amplitude for each blade and the phase lag between the blades is equal to 120°
• Anisotropic conditions: These properties are lost. The damaged blade amplitude is higher than the others. The phase lag is not anymore equal to 120°
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DTU 10-MW wind turbine
10 MW HAWT vs
Antonov An-225 Mriya
Rotor Diameter 178.3 m vs
Wing Span 88.4 m
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DTU 10-MW wind turbine: modeling
TOWER • 10 – segments tower • Steel S355 • Diameters linearly variable from the base to the top • Thickness constant in each segment.
BLADES • Bladed rotor concept • Distributed properties assigned along the blades.
DRIVETRAIN • A rigid drivetrain has been written in Samcef code • The rigid connection can be exchanged with a flexible one • Several kinematic chains have been investigated.
CONTROLLER Generator Torque Law • Below rated conditions
• Gain speed to reach the rated speed. • Above rated conditions
• Keep the power produced constant. Pitch controller law • Pitch to feather • Pitch to stall
FFA – W3 – xxx
NACA 0015 cylinder
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DTU 10-MW wind turbine: OMA in parked conditions
Turbulence: Kaimal Model Turbine class: 1A Wind speed: 10 m/s
Turbine instrumented with virtual accelerometers
Mode DTU [Hz]
SWT [Hz]
Error [%]
1st Tower FA 0.249 0.247 < 1 %
1st Tower S2S 0.251 0.251 < 1 %
1st flap with yaw 0.547 0.549 < 1 %
1st flap with tilt 0.590 0.598 1.3 %
1st collective flap 0.634 0.636 < 1 %
1st edge with tilt 0.922 0.942 2.2 %
1st edge with yaw 0.936 0.959 2.4 %
2nd flap with yaw 1.376 1.413 2.7 %
2nd flap with tilt 1.550 1.573 1.5 %
2nd collective flap 1.763 1.812 2.7 %
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DTU 10-MW wind turbine: OMA in parked conditions
Ice density
Ice but one Germanischer Lloyd WindEnergie GmbH: Guideline for the Certification of Wind Turbines, Edition 2010
5.000.08 Hz
-40.00
-100.00
dBg2
no iceice
5.000.00 Hz
-40.00
-100.00
dBg2
no iceice
5.000.00 Hz
-40.00
-90.00
dBg2
no iceice
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DTU 10-MW wind turbine: OMA in power production
1st Backward Whirling Mode 1st Forward Whirling Mode 1st Tower modes
2nd Backward Whirling Mode
2nd Forward Whirling Mode
ROTATING – MBC
1st Flap Yaw
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DTU 10-MW wind turbine: OMA in power production
3.500.00 Hz
0.01
0.01e-6
Log
g2
0.16
OperatingParked
1.400.10 Hz
3.36e-3
1.98e-6
Log
g23p 6p0.80 1.12
F Before MBCF After MBC
• Crosspower comparison: parked vs operating conditions • All pairs of asymmetric rotor edgewise modes in parked conditions become pairs of
rotor whirling modes owing to the rotation
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Conclusions
Two methods for taking into account the time varying nature of the wind turbine have been implemented and applied to different test cases:
Multi-Blade Coordinate transformation (MBC) Harmonic Power Spectrum method (HPS)
Conventional OMA techniques can be applied to estimate the modal parameters
FUTURE DIRECTIONS • Further studies will be done regarding SHM techniques for wind turbine
blades • Applicability of the implemented methods will be tested in case of real
experimental data
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Emilio Di Lorenzo – Research engineer – Siemens Industry Software nv PhD candidate at KU Leuven and University of Naples "Federico II" [email protected]
Questions?