vibration measurements2
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Vibration of Structures
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Vibration Measurements
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Course ContentsSDOF M-DOFCables/String Bars Shafts Vibration Attenuation Beams Membranes & Thin Plateso Vibration Testing and Measurements
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Objectives
• Vibration Measurements Hardware• Introduction to signal Processing• Vibration Measurements Terminology
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Objectives
• Vibration Measurements Hardware• Introduction to signal Processing• Vibration Measurements Terminology
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Measurements Hardware
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Measurements Hardware
Active health monitoring of an aircraft wing with embedded piezoelectric sensor/actuator network, Smart Mater. Struct. 16 (2007) 1208–1217
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Measurements Hardware• Transducers• Exciters• Signal Conditioning• Analyzer
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Measurements HW: Transducers• Load cell: a piezoceramic device
configured to produce a voltage proportional to force
• Accelerometer: (piezoceramic) produce a signal proportional to acceleration at the point of attachment
• Proximity probes: magnetic device gives a signal proportional to local displacement
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• Laser vibrometers: give a signal proportional to local velocity (or scanned to give velocity field)
• Strain gauges: (local strain or strain rate)
Measurements HW: Transducers
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• Electromagnetic shakers: which may apply a force through a range of frequencies (harmonic or random inputs)
• Instrumented hammers: which simulate an impact
Measurements HW: Exciters
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• The direct out put of a transducer not usually well suited for input into an analyzer: Impedance miss matched, voltage or current levels too low
• SC is a charge or voltage amp designed to take an accelerometer signal and match it to the input requirements of the analyzer
Measurements HW: SC
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• Electronic boxes (dedicated computers) gathers signals and manipulate them mathematically
• Modern analyzers have evolved almost in to chip sized devices
• Main source of manipulation is Digital Fourier Transforms for manipulating the vibration data in the frequency domain
Measurements HW: Analyzer
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Objectives
• Vibration Measurements Hardware• Introduction to Signal Processing• Vibration Measurements Terminology
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Fourier Series: Physical Meaning
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Fourier Series of F(t) of period T
,....3,2,1
)sin()(2 ,)cos()(2
)(2
2
)sin()cos(2
)(
00
00
1
0
n
dttntFT
bdttntFT
a
dttFT
a
T
tnbtnaatF
T
Tn
T
Tn
T
T
nTnTn
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Fourier Series: Physical Meaning
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Fourier Series: Physical Meaning
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Fourier Series: Physical Meaning
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Digital Signal Processing
The analyzer takes signals form the transducer and puts the signal into a form that can be mathematically `manipulated
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Analog-to-Digital Converter
Analog signal x(t) is sampled at manyequally spaced time intervals to producethe digital record:
{x(t1), x(t2), ….x(tN)}where x(tk) is the discrete value of x(t) at
time tk and N is the number of samples
taken
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Analog-to-Digital ConverterWhat happens if Sampling rate is too
large?
sec1
)4
7sin(
)4
sin(
2
1
T
tx
tx
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Analog-to-Digital Converter
What happens if Sampling rate is too large?
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Analog-to-Digital Converter
• Aliasing: When sampling rate is too large, the digital record does not catch the details of the analog signal
• What is the optimum Sampling rate?• Min. 2 Samples / Cycle• Experience: 2.5 Samples / Cycle
Shannon’s sampling theorem
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Analog-to-Digital Converter
• Antialiasing Filter: low-pass Filter(only allows low frequencies through).
• The filter cuts off frequencies higher than about half the maximum frequency of interest: (ωmax , Nyquist frequency).
• Most modern digital analyzers provide built-in antialiasing filters.
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Digital Fourier Transform
,....3,2,1
2sin1 ,2cos1
1
2sin2cos2
)(
11
10
2/
1
0
n
tTnx
Nbt
Tnx
Na
xN
a
tTnbt
Tnaatxx
N
kkkn
N
kkkn
N
kk
N
nknknkk
N is fixed by hardware (a power of 2)
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Digital Fourier TransformAbove becomes the matrix equation
x=Ca Where:C: contains the sin and cos termsx: is the vector of samples anda: is the vector of Fourier Coefficients• Analyzer computes the coefficientsin the DFT formula:
a=C-1x
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Digital Fourier TransformWhat happens if Samples do not match the periods?
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Digital Fourier TransformLeakage: If the signal is not periodic in N samples (signal cut off mid period) the DFT willproduce extra frequencies
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Digital Fourier TransformWindowing: multiply signal by a function which is zero at the end points
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Radom Signals• Autocorrelation: Tells how fast x(t) is
changing
T
Tkxx dtxtxT
tR0
)()(1lim)(
dexRS jxxxx )(
21)(
• Power Spectral Density (PSD): Frequency domain of Autocorrelation [ FT(Rxx) ]
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Radom Signals• Crosscorrelation: Tells how fast x(t) is
changing w.r.t. f(x)
T
Tkxf dtftxT
tR0
)()(1lim)(
dexRS jxfxf )(
21)(
• Cross Spectral Density (PSD): Frequency domain of Autocorrelation FT(Rxf)