Aerospace Testing 2011, Hamburg, Germany, April 6 2011Jan Debille – Solutions Manager Aerospace & Defense
Industrial solutions for in-flight & offline experimental flutter analysisA. Lepage, P. Naudin, J. Roubertier, A. Cordeau ONERAM.A. Oliver-Escandell, S. Leroy, AIRBUSJan Debille, LMS
2 copyright LMS International - 2010
Presentation outline
Flutter testing: What, When and How?
Validation
Required technology
Industrial implementation
1
5
2
3
Conclusions
4
3 copyright LMS International - 2010
What is Flutter?
Flutter is an aero-elastic phenomenonUnstable self-excited vibrationStructure extracts energy from the air stream
Flutter starts to occur at a certain speedNegative damping start to occur at flight points
where two modes are coupled in an unstable wayTypical coupling: wing bending/torsion, wing
torsion/control surface, wing/engine
4 copyright LMS International - 2010
Component CAE Component Physical Test
Subsystem CAE Subsystem Physical Test
Full Virtual Prototype Full Physical Test
Perform
ance
Explorat
ion
Perform
ance
Explorat
ion
Component
Concept Validation & Target
Concept Validation & Target
Cascading
Cascading
Certific
ation
Certific
ation
Upfront Engineering Detailed Engineering Refinement Engineering
Full Aircraft
Models &Loads
Subsystem
Feasibility Definition InServiceConcept Development
Market
StudyConce
pt Sele
cted
Agreemen
t With
Primary
Partners
Authority T
o Offe
rPro
gramLau
nch Major
Assem
blies
Entry In
to Serv
ice
Certific
ation
First F
light
Major B
ody
Sectio
ns
Component
Design
GVT/Flutter/FEC
Stages of Aircraft Development & Flutter: When?
5 copyright LMS International - 2010
Flight Envelope Clearance
Flutter in the design process flow
Pre-Test & De-Risking
Ground Vibration Test
Identify & ValidateModes
CorrelateModel
GO-NO/GO First Flight
Update / refine Models
Virtual PrototypeFE Model
Analytical Modal Model
Physical Prototype
Flutter Simulation &
Prediction
Define Flight Envelope
Flight Envelope Opening
Flight Envelope Expansion
Feasibility Definition InServiceConcept Development
Market
StudyConce
pt Sele
cted
Agreemen
t With
Primary
Partners
Authority T
o Offe
rPro
gramLau
nch Major
Assem
blies
Entry In
to Serv
ice
Certific
ation
First F
light
Major B
ody
Sectio
ns
Component
Design
Gvt/Flutter/FEC
LMS Flutter Analysis
6 copyright LMS International - 2010
Aero-elastic simulation and in-flight flutter testing
FE Model Test Model (GVT) Aerodyn. Panel Model Physical prototype
0)()()()( =−++ xFtKxtxCtxM a&&&
Traditional FEM, GVT-updated FEM, or direct GVT
Aerodynamic panel method
Due to presence of aero-dynamic term, modes of structural system are changing with airspeed and altitudeFlutter analysis = assessing evolution of modes (zero-crossing of damping value)
7 copyright LMS International - 2010
Flutter procedure: extract from NASA technical memo
Fly at several stabilized speedsIncreasing dynamic pressureIncreasing MACH number
Ref: NASA Technical Memorandum 4720, “A Historical Overview of Flight Flutter Testing,” October 1995
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Flight flutter testing & in-flight modal analysis
Background Testing Analysis
s
Rea
l( m
/s2)
Dam
ping
Airspeed
Flutter
Ampl
itude
g2
Telemetry link
Hz-180.00
180.00
°
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Flutter testing procedure
Find frequency and damping of critical modesFor increasing Speeds increases the dynamic loadAt different Altitudes the lower the altitude, the higher the dynamic loadAt different MACH values
True Air Speed(knots)
Altitude (feet)
40,000
30,000
20,000
10,000
100 200 300 400 500
MACH 0.95
MACH 0.90
MACH 0.85
10 copyright LMS International - 2010
Presentation outline
Flutter testing: What, When and How?
Validation
Required technology
Industrial implementation
1
5
2
3
Conclusions
4
11 copyright LMS International - 2010
Flutter testing requirements
Get accurate damping estimate in an operational situationAccuracy
Waiting Time is Money aircraft is airborne during the analysis
Waiting Time is Dangerous during the analysis time, the aircraft may be exposed to near-flutter conditions!
Speed
Modal Analysis on operational (output-only) dataModal Analysis
12 copyright LMS International - 2010
EUREKA project FLITE2 – Structural testing and modal analysis for aeronautics and space applications
Airbus FranceDassault AviationLambert Aircraft EngineeringPZL Mielec
LMS
ILOTINRIAONERASOPEMEA
University of Brussels (VUB)University of Krakau (AGH)University of Leuven (KUL)University of Manchester (UMAN)
LMS Net Funding in FLITE2:378 kEUR
13 copyright LMS International - 2010
EUREKA project FLITE2 – Structural testing and modal analysis for aeronautics and space applications
Faster testing for GVTSmart combination of broadband / sweep / stepped
Assessment of non-linear behavior using multi-sinesModal parameter estimation: iterative methods using noise information and yielding uncertainty bounds on estimates (PolyMAX results as starting values)Flight flutter testing: OMAX identification framework, i.e. combination of known and unknown excitation (EMA + OMA)Use of GVT for flutter safety prediction
Aerodynamic panel model
Hz
dB( (
m/s
2)/N
)
0.00
1.00
Ampl
itude
/
F FRF0F Variance0B COH0
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Stable, robust and reliable modal analysison operational data
Identification of modal parameters from response data (accelerations) measured in operating conditions
EigenfrequenciesDamping ratiosMode shapes
Operational modal analysis = identifying HBased on YWithout knowing U(BUT white noiseassumption) White noise
HU Y
White noise + harmonic
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Output only: artificial vs. natural excitation
Operational Modal Analysis: Output-only analysis no FRFs but Crosspowers between responses and reference responsesReference responses: wing tips, tail tips, nose; in general: well excited pointsOperational PolyMAXRequires natural, operational excitation!
OMA with artificial excitationOnly operational responses are considered…but: all modes are well-excited due to force input!…and: additional operational excitation used
0 . 0 0
0 . 1 0
Log
( g/N
)
H z- 1 8 0 . 0 0
1 8 0 . 0 0
Phas
e
°
PolyMAXPolyMAX
© NASA
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Modal analysis LMS PolyMAX - theory & implementation
Step 1:Denominator matrix
polynomial (in z-domain)Poles and participation factors
Step 2:Stabilisation diagram
Step 3:LSFD to estimate mode
shapes and upper/lower residues from selected poles
[ ] [ ][ ] [ ] [ ] [ ]"")()()(
00
111 zzz
ABHp
pp
p−
−− β++β+β=ωω=ω
K
00
11 zzz p
pp
p ⎥⎦⎤
⎢⎣⎡−
⎥⎦⎤
⎢⎣⎡
−⎥⎦⎤
⎢⎣⎡ α++α+α K
[ ]
[ ][ ]
[ ]0))(,( 1
0
=
⎟⎟⎟⎟⎟
⎠
⎞
⎜⎜⎜⎜⎜
⎝
⎛
α
αα
ωω
p
HML
[ ] { } { }URLRlvlv
Hn H
iiTii +−
><+
><=ω ∑
*
)(jji ii ωλ−ωλ−ω=
21
*
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Modal analysis LMS PolyMAX vs. LSCE
Same 3-step procedure
Step 1 differsLSCE uses impulse responsesPolyMAX uses FRFs
Big difference in stabilization diagram
LMS PolyMAX excels in both high and low damping cases !
Tim
e M
DO
FP
olyM
AX
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Modal analysis LMS PolyMAX vs. Other Frequency-Domain Methods
Frequency domain methods
Powers of the frequency axisNumerical conditioning problemsConsequences:
• Limited frequency range (ω)• Limited model order (p)
Not in PolyMAX!
[ ] [ ] [ ] [ ]( ) [ ] [ ] [ ]( ) 10
110
11 )()(.)()()( −−
−−
− α++ωα+ωαβ++ωβ+ωβ=ω KK pp
pp
pp
pp jjjjH
LMS PolyMAX excels in broadband, high model order analyses !
tjez ∆ω= )(21)(2
1
1
fftff
end −=∆−π=ω Re
Im
f1
f2
…
fend
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Modal analysis LMS PolyMAX
Extremely clear stabilization Easy pole selectionFaster analysisUser-independent resultsMore modes found
“General purpose” methodSingle broadband analysisHigh & low dampingNoisy data
“Modal analysis, an area where no substantial advances were to be expected …?”
“LMS PolyMAX, A Revolution in Modal Parameter Estimation!”
20 copyright LMS International - 2010
LMS Test.Lab automatic modal parameter selection Speed up modal analysis
Rule-based methodNot affected by ability of human mind
to treat informationHigh accuracy on pole selectionReduce uncertainty
Improve productivity
Guidance tool for all
Extensible to automatic modal analysisAnalyze multi-patches measurementLow modal density cases (ex. Body-
in-white car)Flight qualification of aircraftStructural damage detection /
Structural health monitoring
One push instead of manual
selections
All physical poles selected at a glance in stabilization
diagram
© NASA
21 copyright LMS International - 2010
Presentation outline
Flutter testing: What, When and How?
Validation
Required technology
Industrial implementation
1
5
2
3
Conclusions
4
22 copyright LMS International - 2010
Telemetry ground station
LMS Scadas Mobile data acquisition system
Flutter testing procedure: Data acquisition
In-flight data recorder & telemetry transmitter
On-board flight data recorder and
telemetry system
Ground station: receive data, split fast/slow channels
Data acquisition with Scadas F/E or
3rd part software
Dynamic data
Flight parameters
D/A
TCP/IP
Flight data3rd party software:
Data tape/card reader
ONLINE data preparationOFFLINE data preparation
(Altitude, CAS, MACH, etc.)
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Flutter testing procedure: cyclic
Flight envelope definition: Determined by real-time flight parameters.After 1 cycle, the pilot is instructed to move on to the next flight pointComplete offline processing possible: allows in-depth analysis afterwards, accounts for telemetry-based data errors
Measure with Spectral Testing from telemetry
Average flight parameters fix the flight point
Automate OMA (minimal
interaction)
Evaluate evolution of f and ζ for each mode in display
The Flutter application consists of 2 dedicated GUIs:A Flutter Progress window that is always on top:The dedicated Flutter worksheet which
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Flutter analysis: viewing results
Measurements are displayed in the flight envelope
Selected poles are added to the Pole Table, based on a match in frequency using “pole tolerance” parameter.
Poles are displayed in U/L display with amplitude in the upper display and damping in the lower display.
The Displays group allows to select a different x-axis, or to fix against a slow channel parameter (e.g. MACH value)
Support for military damping standard g=2*ζ
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Flutter testing: Overview
Operational Modal Analysis with artificial excitation & PolyMAX parameter estimation method
Analysis
AMPS: automatic modal parameter selection in stabilization diagram
Automated
AMPS: deterministic method! Always yields the same results with the same parameters
Repeatability
Flutter condition can be determined in as fast as 10 seconds
Speed
Experts can interact with the automated procedure
Expert interaction
26 copyright LMS International - 2010
Presentation outline
Flutter testing: What, When and How?
Validation
Required technology
Industrial implementation
1
5
2
3
Conclusions
4
27 copyright LMS International - 2010
ONERA flutter data set generator
Aim:Simulate data for testingClassical wind-bending and torsion coupling
Procedure:Input altitude and speedRun simulation to get time histories
Output:Time domain data of 4 simulated sensor responses
Model (state-space):Structural: GVT result: first 7 symmetrical wing vibration modesAerodynamic: Generalized aero-elastic forces - Doublet Lattice Method
Input for time-response calculation: impulsion on the command of a wing aileron
Altitude Speed
Time domain vibration response to wing aileron impulse
Transonic flutter
simulator
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ONERA Flutter simulatordataset
Available data set: 8 flight points
constant MACH #decreasing altitudeincreasing airspeed
=> increasing dynamic pressure
Constant MACH
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
870 880 890 900 910 920 930 940
Speed (km/h)
Alti
tude
(m)
MeasuredMACH 0.8
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ONERA Flutter Simulatorsample time data (1)
4 channels per flight point16 seconds per flight point32 seconds for near-flutter 4000 m set
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ONERA Flutter Simulatorsample time data (2)
Evolution vs. altitudeDecrease in damping clearly visible in response
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ONERA Flutter Simulatorevolution of modes vs. flight conditions
Flutter analysis
0
5
10
15
20
25
30
35
40
475.0 480.0 485.0 490.0 495.0 500.0 505.0 510.0
CAS (knots)
Freq
uenc
y (H
z)
Mode 1: 9.79HzMode 2: 10.05HzMode 3: 16.76HzMode 4: 19.03HzMode 5: 27.75HzMode 6: 34HzMode 7: 34.02Hz
Flutter analysis
0
2
4
6
8
10
12
14
475.0 480.0 485.0 490.0 495.0 500.0 505.0 510.0
CAS (knots)
Dam
ping
(%)
Mode 1: 9.79HzMode 2: 10.05HzMode 3: 16.76HzMode 4: 19.03HzMode 5: 27.75HzMode 6: 34HzMode 7: 34.02Hz
7 modes in modelModes 1 & 2 coupleStructural frequencies: 8.98 Hz ; 5.88 %10.47 Hz ; 1.81 %
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LMS PolyMAX results – 8000 m altitude
First bending mode: 8.9 Hz ; 5.9 % First torsion mode: 10.5 Hz ; 1.8 %
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LMS PolyMAX results – 4000 m alt. – near-flutter condition
Strong coupling between first bending and first torsion mode
First bending mode: 9.8 Hz ; 12 %VERY HIGH damping
First bending mode: 10.1 Hz ; 0.16 %VERY LOW damping
34 copyright LMS International - 2010
Quality check of PolyMAX modal parameter extractionSynthesis of Cross Powers
70.4e-6
0.09
Log
V2 (1/s
)s
CrossPow er Aile:Point11:+Z/Aile:Point15:+ZSynthesized Crosspow er Aile:Point11:+Z/Aile:Point15:+Z
0.00 40.00Hz-180.00
180.00°
Synthesized Crosspow er Aile:Point11:+Z/Aile:Point15:+Z
15.1e-6
2.22e-3
Log
V2 (1/s
)s
CrossPower Aile:Point11:+Z/Aile:Point15:+ZSynthesized Crosspower Aile:Point11:+Z/Aile:Point15:+Z
0.00 40.00Hz-180.00
180.00
°
Synthesized Crosspower Aile:Point11:+Z/Aile:Point15:+Z
Green = Synthesized – Red = measured
8000 m – safe flight point 4000 m – dangerous flight point
35 copyright LMS International - 2010
LMS PolyMAX results overview
Evolution of frequency & damping as a function of altitudeDecreasing altitude increase of dynamic pressure
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Final check: comparison analytical modes vs PolyMAX resultFrequencies
Frequency vs Altitude
8.5
9
9.5
10
10.5
11
3000 4000 5000 6000 7000 8000 9000 10000 11000 12000
Altitude (m)
Freq
uenc
y (H
z)
Analytical Mode 1Analytical Mode 2Calc. Mode 1Calc. Mode 2
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Final check: comparison analytical modes vs PolyMAX resultDamping
Damping vs Altitude
-2
0
2
4
6
8
10
12
14
3000 4000 5000 6000 7000 8000 9000 10000 11000 12000
Altitude (m)
Dam
ping
(%)
Analytical Mode 1Analytical Mode 2Calc. Mode 1Calc. Mode 2
38 copyright LMS International - 2010
Flutter testing at Airbus
Fly-by-wire: excitation via control surfacesSweep: detailed engineering / Pulse: crew/aircraft safetyONERA: MEFAS (Methodes et Exploitation des essais de Flottement de l’Avion Souple)Pierre Vacher, Alain Bucharles: “A Multi-Sensor Parametric Identification Procedure in the Frequency Domain for the Real-Time Surveillance of Flutter”, SYSID 2006.
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Accelerometers
“General Group”Only primary control surface accelerometers have been removed
Otherwise control surfaces modes identified rather than structural ones
150 accelerometersDistributed over the main aircraft structure
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Geometry representation (adding slave DOFs)
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Accelerometer sub-set
“Reduit Symetrique Group”Used for in-flight real-time analysis (MEFAS)Fast and accurate identificationAccelerometers with best SNR
Wing tipsElevator tipsEnginesSome on fuselage
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Symmetric sweep
Left wing tip and right wing tip
s
Ampl
itude
Time WINL:951:+ZTime WINR:951:+Z
s
Ampl
itude
Time WINL:951:+ZTime WINR:951:+Z
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FRFs – fuselage
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50700002:+Z/2:11111111:+ZB Coherence 2:50700002:+Z/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50700106:+Z/2:11111111:+ZB Coherence 2:50700106:+Z/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50701042:+Z/2:11111111:+ZB Coherence 2:50701042:+Z/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50701132:+Z/2:11111111:+ZB Coherence 2:50701132:+Z/2:11111111:+Z
nose rear
Central – bottom front
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FRFs – engines
Outer Z Outer Y
Inner Z Inner Y
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50710042:+Z/2:11111111:+ZB Coherence 2:50710042:+Z/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 1:50710041:+Y/2:11111111:+ZB Coherence 1:50710041:+Y/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50720042:+Z/2:11111111:+ZB Coherence 2:50720042:+Z/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 1:50720041:+Y/2:11111111:+ZB Coherence 1:50720041:+Y/2:11111111:+Z
45 copyright LMS International - 2010
FRFs – wings
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 0:50760950:+X/2:11111111:+ZB Coherence 0:50760950:+X/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50760951:+Z/2:11111111:+ZB Coherence 2:50760952:+Z/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 0:50770950:+X/2:11111111:+ZB Coherence 0:50770950:+X/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50770951:+Z/2:11111111:+ZB Coherence 2:50770952:+Z/2:11111111:+Z
Left X Left Z
Right X Right Z
46 copyright LMS International - 2010
FRFs – elevator
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50780141:+Z/2:11111111:+ZB Coherence 2:50780141:+Z/2:11111111:+Z
Hz
dB( g/N
)
0.00
1.00
Rea
l
/
F FRF 2:50790141:+Z/2:11111111:+ZB Coherence 2:50790141:+Z/2:11111111:+Z
Left Right
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Hz0.00
1.00
Ampl
itude
/
Coherence & geometry
128 coherence functions in excitation frequency band
Averaged over excitation frequency bandAveraged over DOFs / nodeAveraged coherence color scale from 0 - 1
Geometry mapping
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FRF – PolyMAX
Accelerometer sub-set
Hz
dB( g/N
)
F Sum FRF SUMF Synthesized FRF SUM
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FRF – PolyMAX
All sensors
-80.00
-30.00
dB( g/N
)
Sum FRF SUMSynthesized FRF SUM
Hz-180.00
180.00
Phas
e°
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Influence of pre-processing
Varying block size N, N/2, N/4, N/8Other FRF estimation parameters constant (Hanningwindow, overlap)
PolyMAX resultsFrequency variations small (±2%)Dramatic damping ratio variations (+200%)
Trade-offSmaller block size: Hanning window bias largerLarger block size: noise variance larger (few averages)
Frequency variations
Damping variations
51 copyright LMS International - 2010
Influence of pre-processing
Workaround for trade-off1st step: large block size FRFs suffering from noise2nd step: IRFs truncated by rectangular window
Influence on modal parameter estimatesBiased participation factors (closed-form expression describing bias exists)
AlternativesExponential windowFrequency-averaging
52 copyright LMS International - 2010
Output-only modal parameter estimation procedureSpectrum estimation: leakage-free and Hanning window-free
Weighted correlogramHigh-speed estimation of correlations with positive time lagsExponential window
• Reduces the effect of leakage• Reduces the influence of the
higher time lags having a larger variance
• Compatible with the modal model ( ↔ Hanning window with biased damping)
DFT of windowed correlation sequence
Practical: selection of referencesLeft wing tip, right wing tip, tail plane
53 copyright LMS International - 2010
PolyMAX: EMA vs. OMAdB( g
/N)
Sum FRF SUMSynthesized FRF SUM
Hz-180.00
180.00
Phas
e°
dB
Sum Crosspow er SUMSynthesized Crosspow er SUM
Hz-180.00
180.00
Phas
e°
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Pulse excitation and wing response
s
Rea
lN
Rea
l
g
F Time Force:ref:+ZB Time WINR:952:+Z
Hz
dBN dB g
F Spectrum Force:ref:+ZB Spectrum WINR:952:+Z
s
Rea
lN
Rea
l
g
F Time Force:ref:+ZB Time WINR:952:+Z
Hz
dBN dB g
F Spectrum Force:ref:+ZB Spectrum WINR:952:+Z
Raw
Tim
e do
mai
nFr
eq. d
omai
n
Filtered / decimated
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Pulse excitation – OMA results
dBg2 (1
/s)s
AutoPow er FIN:091:+YSynthesized Crosspow er FIN:091:+YAutoPow er WINL:952:+ZSynthesized Crosspow er WINL:952:+Z
-180.00
180.00Ph
ase
°
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In-flight OMA mode shape (1/4)
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In-flight OMA mode shape (2/4)
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In-flight OMA mode shape (3/4)
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In-flight OMA mode shape (4/4)
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Conclusions
Extensive studyStandard EMA vs. Operational Modal AnalysisParameter estimation: MEFAS, PolyMAX, TimeMDOF, logarithmic decrementWindowing, SNR, sensor groups, frequency resolution, …
OMAOnly response signals used in analysis, but artificial excitation was usedUse of output cross-correlationsGood performance wrt. noiseEliminate windowing problems: exponential window leads to unbiased damping estimates
61 copyright LMS International - 2010
Presentation outline
Flutter testing: What, When and How?
Validation
Required technology
Industrial implementation
1
5
2
3
Conclusions
4
62 copyright LMS International - 2010
Conclusions
True Air Speed(knots)
Altitude (feet)
40,000
30,000
20,000
10,000
100 200 300 400 500
MACH 0.95
MACH 0.90
MACH 0.85
True Air Speed(knots)
Altitude (feet)
40,000
30,000
20,000
10,000
100 200 300 400 500
MACH 0.95
MACH 0.90
MACH 0.85
OMA: some important flutter-critical modes not excitedEMA: some modes mainly excited by the turbulences may not be identifiedConclusion: beneficial to use artificial excitation, but data analysed with stochastic methods that also take into account the unknown excitation
Airbus flight test team evaluated LMS Test.Lab using large-aircraft data“We actually achieved better results using operational techniques than with classical EMA. We found more modes. The synthesis was better with higher correlation and fewer errors. And the in-flight mode shapes looked much nicer!”“We found that the exponential window, which allowed for cross-correlation calculations was a good de-noising tool for our in-flight data.”
Aerospace Testing 2011, Hamburg, Germany, April 6 2011Jan Debille – Solutions Manager Aerospace & Defense
Thank you
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