troubleshooting torsional vibration challenges with
TRANSCRIPT
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Troubleshooting torsional
vibration challenges with
rotating machinery
Where today meets tomorrow.Unestricted © Siemens 2020
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Agenda:Non stationary phenomenaPractical examples
Order tracking
Torsional vibrations
Angle domain
Simcenter (Testing) solutions
Customer examples
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Noise, vibration and durability of machines
Why are rotating components “different”?
air-bornestructure-
bornestructure-
borne
Rotation speed
can change !
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A systematic approach: source – transfer – receiver
=X
Worst Case!
=X
Critical Loads =X
Critical Dynamics =X
=>
Reduce unbalance
Change engine
Change operating range
Source is NOT the reason !
Change specific components
(but which ones ?)
Work on source AND transfer
Isolate the receiver side
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Non-Stationary Signals: Frequency content
FFT FFT FFT
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Non-Stationary Signals: Frequency content
FFT FFT FFT
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Non-Stationary Signals: Frequency content
FFT FFT FFT
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Non-Stationary Signals: Frequency content
FFT FFT FFT
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Non-Stationary Signals: Frequency content
FFT FFT FFT
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Waterfall and Colourmap
600.000.00 Hz
T10_Intake_Manifold_:-Z (CH7)
6100.00
1000.00
rpm
1_C
yc (
T1)
0.10
1.00e-3
Log
gSpectrum T10_Intake_Manifold_:-Z WF 201 [1014.7-6000 rpm]
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Orders and Resonances
600.000.00 Hz
T10_Intake_Manifold_:-Z (CH7)
6100.00
1000.00
rpm
1_C
yc (
T1)
0.10
1.00e-3
Log
gSpectrum T10_Intake_Manifold_:-Z WF 201 [1014.7-6000 rpm]
reso
nan
ce
> frequency >
> s
peed
>
> frequency >
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Relation between frequency and order
FFT
Correlate vibration/noise with rotational speed
« n-th order » = peak in FFT at a frequency = n x rotational frequency
Example:
• Rotational speed = 2400 rpm
• 1st order = 2400/60 (Hz) x 1 = peak around 40 Hz
• 2nd order = 2400/60 (Hz) x 2 = peak around 80 Hz
2400 rpm
40Hz = 1st order
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How to measure RPM?
Remote Optical Probe
▪ Piece of reflective tape needed on shaft
Magnetic Pick-up
▪ Connected to Engine coder or Starter wheel
Rpm = 60 x 1 / ΔT
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Agenda:Non stationary phenomena
Practical examplesOrder tracking
Torsional vibrations
Angle domain
Simcenter (Testing) solutions
Customer examples
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Frequency
Hz
Am
plit
ud
e
0 10050 200150 250 300
Connected shafts
Shaft 1
Shaft 2
Pulley Ratio: 3 to 1
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Connected shafts
Shaft 1
Shaft 2
Pulley Ratio: 3 to 1
Frequency
Hz
Am
plit
ud
e
0 10050 200150 250 300
What if all speeds are
relative to Shaft 2?
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Fan blades
Fan spins @ 600 rpm
What is the blade pass frequency?
What is the main order in the noise?
Fan spins @ 600 rpm
600 rpm = 10Hz (shaft)
6 blades = 60Hz peak in mic
Blade passing frequency
Blade passing frequency depends on rpm !
6th order is independent from rpm
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Gear
Gear spins @ 600 rpm
Gear has 86 teeth
What is the main order?
Gear spins @ 600 rpm
600 rpm = 10Hz (shaft)
86 teeth = 86th order = 860Hz peak
Gear meshing frequency
If ≠ 860Hz => transmission error
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Connected gears
Gear 1 spins @ 600 rpm and has 13 teeth
connected to gear 2 with 8 teeth
What is the main order of gear 2?
Gear 1 spins @ 600 rpm
600 rpm = 10Hz (shaft)
Gear 2 spins @ 13/8 = 16.25Hz
Order 1.625 (compared to main shaft)
Gear meshing frequency ?
16.25 * 8 = 10 * 13 = 130 Hz
Gear 1
Gear 2
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Gears and prime numbers …
Often – a meshing gear pair
will have a prime number of
teeth on one or both gears….
If two gears share a common factor, then
the same teeth will engage more frequently,
leading to wear & damage.
How many rotations will Gear1
rotate before the same two teeth
mate again?
Gear1: 60
Gear2: 30
Answer: 1
rotation
Gear1: 65
Gear2: 53
Answer: 53
rotations!
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Combustion engine
Inta
ke
Co
mp
re
ss
ion
Po
wer
Exh
au
st
12
34
1stre
vo
luti
on
2n
dre
vo
luti
on
Sin
gle
fu
ll c
ycle
An ‘order’ is a frequency component with a
rotational speed dependency
4-stroke, 4-cylinder engine
▪ Order 0.5 = camshaft rotation
▪ Order 2 = combustion
▪ Order 4 = cylinder movement
▪ Etc.
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250.000.00 Hz
(Frequency)
2850.00
1650.00
rpm
z_axis
0
-75.00
-125.00
dB g
0.50 2.00 4.00
Combustion engine
Camshaft
Combustion
Cylinders
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Electric motor
25000.000.00 Hz
(Frequency)
5800.00
400.00
rpm
Engin
e:T
acho (
T1)
110.00
20.00
dB
(A)
Pa
PWM
carrier
frequency
Motor orders
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Transmission
Which issues can we detect?
Perfect mesh Misalignment Eccentricity
1.000.00 s
1.10
-1.10
Real
g
1.000.00 s
1.00
-1.00
Real
g
1.000.00 s
1.10
-1.10R
eal
g
1.000.00 s
1.00
-1.00
Real
g
1.000.00 s
1.00
-1.00
Real
g
1.000.00 s
1.10
-1.10
Real
g
Gear meshing order 1st order modulation 2nd order modulation
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Transmission
Order analysis
Order offset vs.
meshing frequencyCauses
0
▪ High meshing
forces
▪ Bad gear teeth
design
1
▪ Load imbalance
▪ Shaft resonance
▪ Improper
installation
2▪ Gear eccentricity
▪ Manufacturing
issue11090 100.095.0 105.0
Hz
1.00
0.00
Am
plit
ude (
Peak)
g
Offset RotationEccentric GearGear Mesh Only
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Transmission
Order analysis
Sideband level variation with
RPM and load in real life
Root-cause amplification
possible due to structural
resonances
5000.000.00 Hz
VIBR:2:+Z (CH2)
2900.00
900.00
rpm
TA
CH
:9999:+
RX
(T
1)
25.00
-60.00
dB g
Meshing
orderSidebands
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Bearings
What causes bearing defects?
Excessive forces:
• Load imbalance
• Misalignment
• Shaft vibrations
Many rotating components
with different RPM than output
shaft
Expect unique orders per
defective component
Outer race
Roller cage
Rollers
Inner race
What causes bearing defects?
Improper maintenance:
▪ Insufficient lubrication
▪ Lubrication aging
▪ Dust contamination
Material
wear
Crack
formation
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Bearings
Order analysis
Bearing order Cause Mathematical frequency Empirical frequency
Ball Pass Frequency Outer (BPFO) Outer race defects 𝐵𝑃𝐹𝑂 = 𝑅𝑃𝑀 ∙𝑁𝐵2
1 −𝐵𝐷𝑃𝐷
cos(𝛽) 𝐵𝑃𝐹𝑂 = 0.4 ∙ 𝑁𝐵 ∙ 𝑅𝑃𝑀
Ball Pass Frequency Inner (BPFI) Inner race defects 𝐵𝑃𝐹𝐼 = 𝑅𝑃𝑀 ∙𝑁𝐵2
1 +𝐵𝐷𝑃𝐷
cos(𝛽) 𝐵𝑃𝐹𝐼 = 0.6 ∙ 𝑁𝐵 ∙ 𝑅𝑃𝑀
Ball Spin Frequency (BSF) Rolling element defects 𝐵𝑆𝐹 = 𝑅𝑃𝑀 ∙𝑃𝐷𝐵𝐷
1 −𝐵𝐷𝑃𝐷
cos(𝛽)
2
–
Fundamental Train Frequency (FTF) Cage defects 𝐹𝑇𝐹 = 𝑅𝑃𝑀 ∙1
21 −
𝐵𝐷𝑃𝐷
cos(𝛽) 𝐹𝑇𝐹 = 0.4 ∙ 𝑅𝑃𝑀
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Bearings
Order analysis
• Pitch diameter = 1.548 inch
• Ball diameter = 0.3125 inch
• Number of balls = 9
RPM BPFO (Hz) BPFI (Hz) BSF (Hz) FTF (Hz)
100 6.077258 8.922742 3.979451 0.675251
500 30.38629 44.61371 19.89726 3.376254
1000 60.77258 89.22742 39.79451 6.752509
1500 91.15887 133.8411 59.69177 10.12876
2000 121.5452 178.4548 79.58902 13.50502
2500 151.9315 223.0685 99.48628 16.88127
3000 182.3177 267.6823 119.3835 20.25753
3500 212.704 312.296 139.2808 23.63378
4000 243.0903 356.9097 159.178 27.01004
O = 3.646 O = 5.354 O = 2.387 O = 0.405
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Agenda:Non stationary phenomena
Practical examples
Order trackingTorsional vibrations
Angle domain
Simcenter (Testing) solutions
Customer examples
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Fixed sampling for runups?
Fixed sampling: provides global overview
• Basic order analysis (limited maximum order and
order resolution)
• Not well suited for fast runups and/or detailed analysis
• High orders are smeared in frequency domain
• At low RPM, no good distinction between orders
• Powerful for measuring resonances
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Fixed sampling vs synchronous order tracking
Fixed sampling: provides global overview
• Basic order analysis (limited maximum order and
order resolution)
• Not well suited for fast runups and/or detailed analysis
• High orders are smeared in frequency domain
• At low RPM, no good distinction between orders
• Powerful for measuring resonances
Order tracking: allows accurate order analysis
• High orders, fine order resolution
• Fast runups
• Always good distinction between orders
• Non precise resonance measurements
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Fixed sampling vs synchronous order tracking
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Fixed sampling vs synchronous order tracking
▪ Accurate order analysis
▪ Separates closely spaced orders at low rpm’s
▪ High orders, fine order resolution
▪ Fast run-ups
▪ Synchronous Order Tracking
▪ Sampling at constant angle increments
▪ Order spectra and orders
▪ Narrowband Fixed sampling
▪ Constant sampling frequency
▪ Frequency spectra and orders
▪ Global overview
▪ Investigates harmonics vs. resonances
▪ Less computationally intensive
▪ Higher channel counts
Why not using both at the same time?
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Agenda:Non stationary phenomena
Practical examples
Order tracking
Torsional vibrationsAngle domain
Simcenter (Testing) solutions
Customer examples
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0.00 19.00 s
200.00
2200.00
Am
plit
ude
rpm
F 1:Tacho1
Why does this RPM
curve look fuzzy?
13.98 14.44 s
1635.46
1764.56
Am
plit
ude
rpm
F 1:Tacho1
Inertia forces cause
fluctuating RPM!
Torsional vibrations
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How to measure those speed variations?
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How to measure those speed variations?
Analog vs. digital pulse detection
Example:
Transmission error analysis
Maximum 5000 RPM
+
Incremental encoder with
1200 PPR
=
~ 100.000 pulses per second
Analog Tacho
▪ All type of sensors
▪ Up to 40.000 pulses per second
User defined
trigger level
5V
0V
Digital Tacho – TTL
▪ Optical sensors / Incremental
encoders
▪ Up to 1.000.000 pulses per
second
5V
0V
0V
5V
Digital Tacho – RS422/485
▪ Optical sensors / Incremental
encoders
▪ Differential TTL for electrically
noisy environment
▪ Up to 1.000.000 pulses per
second
Incremental
Encoder
Torsional Laser
Optel-Thevon
optical
probes
Magnetic
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How to measure those speed variations?
Magnetic pickup sensors
☺ Easy to instrument
☺ Sensor price
☺ Gears often part of standard component
☺ No external power required
Pulses per revolution not flexible, equal
to # gear teeth
Sensitive to teeth dimensions,
manufacturing tolerances
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How to measure those speed variations?
Optical sensors
☺ Easy instrumentation, on any shaft
or gear wheel
☺ High pulse rates, depends on zebra
tape
Sensitive to ambient light
Zebra tape defects
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How to measure those speed variations?
Incremental Encoders
☺ Extremely accurate
☺ Extremely high number of pulses
☺ Includes direction of rotation
Complex instrumentation
Mass loading
Very convenient when the instrumentation can be part of the test bench
Three output signals:
✓ Square wave outputs
✓ Quadrature square wave outputs
✓ Single pulse/rev as absolute reference
http://www.heidenhain.com/en_
US/products/rotary-encoders/
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Agenda:Non stationary phenomena
Practical examples
Order tracking
Torsional vibrations
Angle domainSimcenter (Testing) solutions
Customer examples
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What is Angle Domain analysis?
Application examples
Gear rattle
Piston Noise
Valve Impact
Noise
Combustion profileEngine surface
vibration
Engine knock
Engine ancillaries
Unbalanced inertia forces
Cylinder to cylinder
variation of combustion
Bending of crankshaft
Valve train dynamics
Bearing forces
Camshaft bending
Torsional vibrations
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What is Angle Domain analysis?
Cylinder pressure analysis example
0.040-0.040 -0.030 -0.020 -0.010 0.000 0.010 0.020 0.030
s
CylPressure (CH12)
22.00
0.00
Am
plit
ude
ba
r
7200 100 200 300 400 500 60050 150 250 350 450 550 650
°
CylPressure (CH12)
22.00
0.00
Am
plit
ude
ba
rF Angle CylPressure 1699.7 rpm
F Angle CylPressure 2890.4 rpm
rpm
Time
Offset between cylinders
Variable pulse length
☺ Direct comparison of cylinder pressure at any RPM
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What is Angle Domain analysis?
Cylinder pressure analysis example
▪ Gated analysis
▪ E.g. Gate 1 = Valve inlet
Gate 2 = Combustion
▪ Offset compensation
▪ Align phenomena with fixed
angle offset720.000.00 °
720.000.00 °
720.000.00 °
720.000.00 °
Cyl 1
Cyl 3
Cyl 3
Cyl 1
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What is combustion analysis?
P-V diagram
Cylinder
pressure
Cylinder
volume
Positive work
Negative work
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What is combustion analysis?
Mean Effective Pressure – IMEP / PMEP / NMEP
How much energy is my
combustion delivering?
Indicated Mean Effective Pressure (IMEP)The IMEP abbreviation often refers to the Gross Indicated Mean Effective Pressure
𝐼𝑀𝐸𝑃 =∆𝛼
𝑉𝑠
𝑛𝑖1
𝑛𝑖2
𝑝 𝑖 .𝑑𝑉(𝑖)
𝑑𝛼
Pumping Mean Effective Pressure (PMEP)
𝑃𝑀𝐸𝑃 =∆𝛼
𝑉𝑠
𝑛𝑝1
𝑛𝑝2
𝑝 𝑖 .𝑑𝑉(𝑖)
𝑑𝛼
Net Mean Effective Pressure (NMEP)
𝑁𝑀𝐸𝑃 =∆𝛼
𝑉𝑠
𝑛1
𝑛2
𝑝 𝑖 .𝑑𝑉(𝑖)
𝑑𝛼
How much energy is
lost during operation?
How efficient is my
engine control strategy?
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Agenda:Non stationary phenomena
Practical examples
Order tracking
Torsional vibrations
Angle domain
Simcenter (Testing) solutionsCustomer examples
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Page 51 Siemens Digital Industries Software
Digital Transformation with a Holistic Digital Twin
UtilizationIdeation Realization
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Page 53 Siemens Digital Industries Software
Simcenter™Engineer innovation.
Simulate. Explore. Test.
Simcenter Portfolio
Engineer innovation for rotating machinery performance
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Page 54 Siemens Digital Industries Software
Simcenter Portfolio
Engineer innovation for rotating machinery performance
Noise & VibrationRattle, Whine, Torsional Vibrations, Rotor Dynamics, N&V Levels
ReliabilityStructural integrity, Durability, Thermo-fluids, EMC, Maintenance
PerformanceEfficiency, Controls, Flowrate, Torque Power, Power Conversion
IntegrationMulti-attribute Balancing, Sizing, Troubleshooting, Data Management, IOT
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Page 55 Siemens Digital Industries Software
Simcenter Testing Solutions
Single platform multi-physics applications portfolio
Data acquisi t ion
Data sharing and
reporting
Data analytics
Data management
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Page 56 Siemens Digital Industries Software
Signature testing
Order tracking
Angle domain
analysis
Torsional vibration
analysis
Time data acquisition and
processing
Rotating machinery
Turbine testing
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Unrestricted © Siemens 2020
Page 57 Siemens Digital Industries Software
Simcenter™Engineer innovation.
Simulate. Explore. Test.
Simcenter Portfolio
Engineer innovation for rotating machinery performance
![Page 55: Troubleshooting torsional vibration challenges with](https://reader031.vdocument.in/reader031/viewer/2022012417/61726c925011db514a794457/html5/thumbnails/55.jpg)
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Page 58 Siemens Digital Industries Software
Simcenter Amesim model
measured rpm
Simcenter Testlab measures RPM
RPM
Vary
ing
belt s
peed
Electrical
motortransmission beltvarying rpm varying rpm Belt speedrpm
Virtual sensor
Varying belt speed
Model Based
System Testing
MBST
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Agenda:Non stationary phenomena
Practical examples
Order tracking
Torsional vibrations
Angle domain
Simcenter (Testing) solutions
Customer examples
![Page 57: Troubleshooting torsional vibration challenges with](https://reader031.vdocument.in/reader031/viewer/2022012417/61726c925011db514a794457/html5/thumbnails/57.jpg)
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Page 60 Siemens Digital Industries Software
Noise, vibration and durability of machines
Why are rotating components “different”?
air-bornestructure-
bornestructure-
borne
Rotation speed
can change !
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Page 61 Siemens Digital Industries Software
Benefit
Challenge
Solution
Industrial pumps
Signature testing - Vibration troubleshooting
• Troubleshoot a wide range of noise and
vibration problems on pumps, valves, actuators..
• Better understand the underlying phenomena
• Worldwide standardization of tools used
• Simcenter SCADAS Recorder & Simcenter
Testlab
• Tokens based licensing for worldwide sharing of
resources
• 30% investment saving thanks to single tool for
routine measurements & advanced engineering
• 40% faster insight into problem root causes
• 35% efficiency gain via collaboration worldwide
“The tokens concept allows us to offer a variety of
capabilities to the industry partners we work with, as the
tasks and requirements differ from project to project.”
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Benefit
Challenge
Solution
Bearings
Simcenter Testxpress analyzer – More efficient servicing @ end customer
• More efficient and effective on-site
interventions
• More systematic and detailed analysis of
noise and vibration issues
• Application = troubleshoot noise and
vibration issues in assembled product
• Product = Simcenter Testxpress FFT
analyzer with envelope analysis
• Solve conflicts with end user OEM
• Envelope analysis points out the guilty part
of the bearing
• Full frequency details available
The Simcenter Testxpress software is so easy to use,
customers are up and running within the hour.
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Page 63 Siemens Digital Industries Software
Benefit
Challenge
Solution
High precision gears
Simcenter Soundbrush – Objectively compare noise of different designs
• Dispute between OEM and supplier on the
“guilty component” - risk liability claims
• Quickly and objectively compare different
noise sources and different designs
• Application = quickly compare noise
generated by different components
• Product = Simcenter Soundbrush
• Released from liability claims
• Real-time visual identification of different
noise sources
Simcenter Soundbrush helps objectively comparing noise
generated by the different components.
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Page 64 Siemens Digital Industries Software
Benefit
Challenge
Solution
Electrical motor
Operational modal analysis – End user complaint on vibration levels
• No in-house NVH experience on how to solve
customer complaints on high vibrations
• Trial and error approach
• Inefficient reporting takes 2 days
• Application = reduce vibration levels and
increase lifetime of mount brackets
• Product = Simcenter Testlab operational
modal + Polymax and batch reporting
• Gain experience via ES technology transfer
• Systematic source transfer receiver
approach leads to solution
• Higher efficiency via batch reporting
The efficiency increase is incredible – using Simcenter
Testlab Polymax, operational modal and batch reporting.
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Page 65 Siemens Digital Industries Software
Benefit
Challenge
Solution
Printing plate production machine
Simcenter SCADAS XS – Reduce time/cost for global servicing
• How to avoid costly engineer travel time for
simple troubleshooting task
• Need for mobile measurement equipment
• Application = local vibration troubleshooting
by an operator, engineer stays @ HQ
• Product = Simcenter SCADAS XS with tablet
and predefined test template
• Simcenter SCADAS XS is shipped
• Operator can do the test
• Engineer only analyzes the data
Thanks to the Simcenter SCADAS XS, a typical intervention
went from 1 week down to only 2 days.
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Page 66 Siemens Digital Industries Software
Benefit
Challenge
Solution
Wood working machine
Modal analysis – Increase production speed + improve finishing quality
• Unexpected quality problems at certain
operating speeds, machines run sub-optimal
• How to balance production speed vs. quality
vs. energy efficiency
• Application = avoiding resonances that affect
produced quality
• Product = Simcenter Testlab modal analysis
• Systematic understanding of dynamics in
the machine that might affect quality
• Machines run more efficient
Moving from mass production to tailor-made machines
requires full understanding of the dynamics.
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Thank you.
Frank Demesmaeker
Business Development Manager
Simcenter Testing Solutions