Copyright LMS International 1 Marie Curie Graduate School on Vehicle Mechatronics & Dynamics, Leuven, 5-8 February 2013 Bart Peeters NVH Lecture 7: Operational Modal Analysis 2 copyright LMS International - 2011 Operational Modal Analysis Why? Identify models that represent real behaviour Real operating conditions laboratory conditions Effects due to: • Non-linearities e.g. car suspension • Environment Experimental models that give best linear representation under the relevant operating conditions Practical problems for executing lab-test Access to the actual structure Problems for applying adequate input forces • Impossible, difficult • Expensive Presence of substantial ambient excitation Health monitoring / damage detection: in-situ Make extended use of available data (ODS) Any public or commercial use requires the agreement of the author.
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Copyright LMS International 1
Marie Curie Graduate School on Vehicle Mechatronics & Dynamics, Leuven, 5-8 February 2013 Bart Peeters
NVH Lecture 7: Operational Modal Analysis
2 copyright LMS International - 2011
Operational Modal Analysis
Why?
Identify models that represent real behaviour
Real operating conditions laboratory conditions Effects due to:
• Non-linearities e.g. car suspension
• Environment Experimental models that give best linear representation
under the relevant operating conditions Practical problems for executing lab-test
Access to the actual structure Problems for applying adequate input forces
• Impossible, difficult • Expensive
Presence of substantial ambient excitation Health monitoring / damage detection: in-situ Make extended use of available data (ODS)
Any public or commercial use requires the agreement of the author.
Copyright LMS International 2
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Operational Modal Analysis
In-operation testing
Some applications permit the use of Input - output (FRF) data during normal operation
Any public or commercial use requires the agreement of the author.
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Next: 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 altitude
Flutter analysis = assessing evolution of modes (zero-crossing
of damping value)
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Flight flutter testing – turbulence excitation
s
Rea
l(m
/s2 )
0.00 3.20 LinearHz
Am
plitu
deg2
0.00 3.20 LinearHz
Hz-180.00
180.00
°
Da
mp
ing
Airspeed
Flutter
Telemetry link
Background Testing Analysis
Context: FLITE 2 research project with Airbus France, Dassault Aviation, PZL, LAE, VUB,
KUL, AGH, UMAN, INRIA, SOPEMEA, ONERA, LMS
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Application to aircraft flight test data
Generally only a few sensors
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A380 in-flight tests
But sometimes a bit more: 150 accelerometers
Any public or commercial use requires the agreement of the author.
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OMA – PolyMAX
0.71 6.05Linear
Hz
dB
Sum Crosspow er SUMSynthesized Crosspow er SUM0.71 6.05Linear
Hz
Hz-180.00
180.00
Phas
e°
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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
In-flight testing
OMA: some important flutter-critical modes not excited EMA: some modes mainly excited by the turbulences
may not be identified Conclusion: 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.‖
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
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OMA has its roots in Civil Engineering
7 November 1940 – Tacoma (USA) 10 June 2000 – London (UK)
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Applications: civil engineering
Design verification FE model correlation / updating Identification of damping properties Indirect identification of cable forces Structural health monitoring Verify effectiveness of rehabilitation
0.30 3.00 LinearHz
-130.00
-100.00
dBg2
Deck:117:+ZSynthesized Crosspow er Deck:117:+Z
0.30 3.00 LinearHz
0.30 3.00 Hz-180.00
180.00
°
Guadiana Bridge
Millennium Bridge
Øresund Bridge
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23/11/2002: Bradford City – Sheffield United: 0 – 5
Data acquisition: 4 h Sampled at 80 Hz (down-sampled to 20 Hz) Sliding RMS value ( — )
1000 samples, 50% overlap
0.00 15000.00 s-0.02
0.02 R
eal
(m/s
2 )
-0.20
0.20
Rea
l
(m/s
2 )
F time_record roof:1:+X / Root Mean SquareB time_record roof:1:+X
Goal 1 Goal 2 Goal 3 Goal 4 Goal 5
Half time Empty Filling Seated Emptying
End of game
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Continuous monitoring of the
Bradford and Bingley Stadium
Data: Paul Reynolds, Sheffield University
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Ambient Vibration Testing of the Millau Viaduct
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Millau Viaduct – LMS Test.Lab PolyMAX results
Source: E. Caetano,
F. Magalhaes, A.
Cunha (univ. Porto),
O. Flamand, G.
Grillaud (CSTB)
EVACES Conference,
Porto, 2007
Any public or commercial use requires the agreement of the author.
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Guadiana Bridge – Modal parameters
Mode Freq.
[Hz]
Damp.
[%]
1 0.384 1.32
2 0.522 1.20
3 0.558 1.57
4 0.951 0.69
5 1.036 0.49
6 1.299 0.46
Mode Freq.
[Hz]
Damp.
[%]
7 1.448 0.54
8 1.654 0.66
9 1.880 0.57
10 2.248 0.60
11 2.547 0.72
12 2.778 0.23
PolyMAX – single analysis results
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Ship hull vibration measurements
5 Three-axis acceleration sensors At forward, aft ends and center of upper deck At end of front & aft of compass deck (longitudinal,
lateral and torsion vibrations measurement of deckhouse)
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Change of Vibration Acceleration at aftbody
Change of order components for engine speed
Change of frequency component for
engine speed
0 50Hz
DeckL:1:+Z (CH3)
380
680
rpm
Rp
m E
xtr
(T
1)
-140.00
-40.00
dB g
1.00 2.00
6.00
380 680rpm
0.00
7.40e-3
g
545.00 665.00
F Order 1.00 DeckL:1:+ZF Order 2.00 DeckL:1:+ZF Order 6.00 DeckL:1:+Z
0 50Hz
DeckL:1:+Z (CH3)
380
680
rpm
Rp
m E
xtr
(T
1)
-140.00
-40.00
dB g
0.37 1.00 1.49
3.40 9.1011.10
14.20
380 680rpm
0.00
7.40e-3
g
545.00 665.00
F Frequency 3.40 Hz DeckL:1:+ZF Frequency 9.10 Hz DeckL:1:+ZF Frequency 11.10 Hz DeckL:1:+ZF Frequency 14.20 Hz DeckL:1:+Z
Measurement point 1, Z direction
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OMA results: hull vertical vibration modes
Hull Vertical
3 nodes 6.1 Hz
Hull Vertical
4 nodes 9.1 Hz
Hull Vertical
5 nodes 11.1 Hz
Hull Vertical
6 nodes 14.3 Hz
0
5
10
15
20
25
30
0 5 10 15 20 25
Mode number
Fre
qu
en
cy [
Hz]
Glabal vibration mode Hull lateral mode
Hull vertical mode Upper structure mode
Hull Vertical
2 nodes 3.4 Hz
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Ship hull vibration measurements – conclusions
Classical modal analysis requires excitation devices Costly / cumbersome Not enough excitation energy for large-dimension ships (poor
SNR)
Operational Modal Analysis is powerful tool for identifying the vibration behavior of the global and local structure of a large ship in operational conditions
Ambient excitation = white noise + harmonic forces from propulsion (engine and propeller system)
Higher-frequency modes successfully identified from engine run-up data
Results are in good agreement with anchor drop test and wave-induced vibrations
Unbalance shaker Impact test
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Validation of Complete Vehicle Model (CVM)
LMS Virtual.Lab correlation LMS Test.Lab PolyMAX
Test wireframe
NASTRAN FEM
Source: Martin Olofsson, Peter Nilsson (Volvo Truck)
IOMAC, Copenhagen, 2007
• Simulated operation data • 4-poster measurements • Test track measurements
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Mode shape correlation (MAC)
OMA shows better correlation with FEM than ODS
Not all FEM modes could be found in operational data (not well excited by 4-poster, too highly damped)
Others have high correlation
ODS
ODS / OMA vs. FEM
FEM
Reduced FEM vs. OMA mode shape
OMA
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Testing and identification of active systems
Intelligent and complex systems engineering Multi-physics system simulation: 1D,
3D, control State estimator: processing data by
models • Applied to Vehicle Dynamics
Control (Flanders’ Drive project) Testing of active system
Model validation and updating Case study
Ford S-MAX 4-poster and Proving Ground tests
Steering
Suspension force
elements
Suspension force
elements
15 DOF
Compliances
Sensors
Tires
Road input / 4 Post Shaker
Steering
Suspension force
elements
Suspension force
elements
15 DOF
Compliances
Sensors
Tires
Road input / 4 Post Shaker
Steering
Suspension force
elements
Suspension force
elements
15 DOF
Compliances
Sensors
Tires
Road input / 4 Post Shaker
Steering
Suspension force
elements
Suspension force
elements
15 DOF
Compliances
Sensors
Tires
Road input / 4 Post Shaker
Any public or commercial use requires the agreement of the author.