Practical Aspects of Digital Data Acquisition (Understanding Sources of Error in the Measurement Chain)
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Practical Aspects of Digital Data Acquisition
(Understanding Sources of Error in the
Measurement Chain)Digital Data Acquisition Agenda
1 Introduction
2 Measurement Chain
3 Sources of Error
4 Filtering
5 How Do I Read a Spec Sheet
6 Advanced TopicsSignals and Processing
Signal: measurable quantity carrying information about some physical phenomenon
Pressure, displacement, acceleration, …
Temperature, voltage, biomedical potential (EKG, EEG, ...)
The signal is generated by a sensor or transducer
Accelerometer: acceleration voltage
Microphone: pressure voltage
Strain Gauge: strain (deformation) voltage
Thermocouple: temperature changes voltage
Signal will be digitized and stored has a time history
Analog SignalObjective Avoid Bad Data
Digital Data Acquisition Agenda
1 Introduction
2 Measurement Chain
3 Sources of Error
4 Filtering
5 How Do I Read a Spec Sheet
6 Advanced Topics
5 copyright LMS International - 2011Measurement Chain
Analog Domain Digital Domain
physically measured Digital signal
quantity + noise representation
Sensor supply
Structure
Signal
Sensor Conditioning Gain Alias ADC DSP
Protection
sensor Cable Conditioner and Filter ADC Calculation
sensor supply accuracy
noise noise noise noise noise
6Digital Data Acquisition Agenda
1 Structure
2 Sensor
3 Wiring
4 Signal Conditioning
5 Alias Filter
6 Analog to Digital Converter
7 Time File
7 copyright LMS International - 2011Structure
• Sensors can go just about
anywhere and measure just
about any physical phenomena
• The structure can have an
effect on the measurement
8 copyright LMS International - 2011Structure Wind Turbines
BLADES NACELLE
& HUB GEARBOX GENERATOR
& TOWER
• High power / high current /high frequency controlled electronics e.g.
• Long power wires from inverter at the bottom to the rotor of the generator at
the top.
• Power cables to the grid in the ground have shown serious problems for long
microphone cables when doing outdoor sound power.
• Metal structures that are controlled by electrical engines can also present a
high frequency antenna that easily couples to strain gauges.Structure Examples
Easier HarderPotential Structure Issue Summary Do you have to run long lead wires? Does the structure have large electric currents? Common Noise Generators: Temperature changes?
Digital Data Acquisition Agenda
1 Structure
2 Sensor
3 Wiring
4 Signal Conditioning
5 Alias Filter
6 Analog to Digital Converter
7 Time File
12 copyright LMS International - 2011Typical Sensors
Wheel force Stress/Strain Acceleration Pressure
Microphones
Strain gages DC-accelerometers
Pressure transducer
ICP-accelerometers
WFT
• Tension
• Compression
• Force Fx, Fy, Fz • Sound Pressure
• Torque • Body accelerations
• Moment Mx, My, Mz • Brake pressure
• Local stresses • Subsystems
• Angle, speed • Air pressure - dampers
Force / Moment Displacement Temperature Others
Load Cells String pots Thermocouple • RPM
Torque Sensors LVDT • GPS – Global position
• CAN signals
• Video
• Absolute displ.
• Engine torque • Relative displ. • Engine
• Drive shafts e.g. damper, bushings • GearboxActive vs Passive Sensors
“Passive” sensors add little or no noise to the measurement chain:
Piezoelectric (charge) transducers
Strain gauges
“Active” sensors have on-board electronics that do add noise:
ICP sensors
PCB
333Bxx
DC accelerometers
PCB
3711B03
14Isolated vs Non Isolated Sensors
A sensor is isolated form the structure when current cannot flow
between the sensor and structure
Sensors that are Electrically Isolated from the Structure
Strain Gages are usually Isolated from Structure
Some commercial sensors provide electrical Isolation
• Accelerometers – PCB J Suffix
Sensors that are commonly not isolated from structure
Thermocouple
Some Accelerometers
These sensors require floating or isolated grounds to prevent ground loops
When taking Operational Measurements it is recommended to Isolate sensors
from the structureGround Loops • When installing accelerometers onto electrically conductive surfaces, there exists the risk of ground noise pick-up. • If Sensor is grounded at a different electrical potential than the signal conditioning and readout equipment, ground loops can occur • Noise from other electrical equipment and machines that are grounded to the structure can enter the ground path of the measurement signal through the base of a standard accelerometer
Possible Causes / How Do Ground Loops Appear in Data
Although usually 50 or 60 Hz
Ground Loop can be any frequency
created large power devices like
frequency controlled electric motors
Possible sources are:
• motors, pumps, generators,…
• mains supply, electric power
to machines
• other EM field sources
17 copyright LMS International - 2011How Do We Fix Ground Loops
• The easiest solution is to break the ground loop is by electrically isolating or
"floating" the accelerometer from the test structure:
• In case no manufacturer provided isolation is available, one can make use of
insulating materials.
These include:
• isolating tape
• a piece of Bakelite
• gluing paper between sensor and structure can already improve the situation
substantiallyOther Options to Deal With Ground Loops • Other tips for decreasing ground loop effects: • If possible, make sure all parts of the loop are grounded on the same physical ground. This also includes the amplifier. • Try to switch off possible EMC sources in the vicinity of the test table. •Unplug data acquisition system from AC power •If using AC power make sure grounding plug is working •Use grounding strap •Use Isolated Ground Transformer •Use Clean Power – Orange plug • Try using a signal conditioner with a floating ground
Digital Data Acquisition Agenda
1 Structure
2 Sensor
3 Wiring
4 Signal Conditioning
5 Alias Filter
6 Analog to Digital Converter
7 Time File
20 copyright LMS International - 2011Wiring
• Wiring can be complicated sometimes
• Connectors can be critical for field data acquisition
• Rough environments can cause intermittent
connections
• Unshielded cable can act as antennas for Electro Static
Interference
• Cables can act as low pass filters
• Cross TalkCabling Noise Sources – Electro-Magnetic Interference EMI
Electrostatic
Electrostatic Fields - generated by the presence of
voltage with, or without current flow
Mechanism: capacitive coupling, by which charges
of correspondingly alternating sign are developed
on any electrical conductors subjected to the field
Example Fluorescent Lights
Magnetic
created either by the flow of electric current or by
the presence of permanent magnetism
In order for noise voltage to be developed in a
conductor, magnetic lines of flux must be “cut” by
the conductor
Examples Electric Motors and TransformersCountermeasure Electrostatic - Shielding Transducer Lead wires become antennas The simplest and most effective barrier against electrostatic noise pickup is a conductive shield, sometimes referred to as a Faraday cage It functions by capturing the charges that would otherwise reach the signal wiring Must be provided with a low resistance drainage path (ground) Popular types of cable shields are braided wire and conductive foil.
Countermeasure for Electro-Magnetic Noise
Electrostatic shield wires ineffective, requires different shielding principle that bends
or shunts the magnetic field
Ensure that noise voltages are induced equally in both sides of the amplifier input
Common Mode Noise Reduction: covered in Signal Conditioning
The noise voltages (V1 and V2) induced in the signal wires will therefore depend
greatly upon their distances from the current-carrying conductors
Twisting the signal conductors together tends to make the distances equal, on
the average, thereby inducing equal noise voltages which will cancel each
other.
Special attention required for cables running in parallel with high current lines.
(Current produces magnetic fields).Cabling Best Practices More twists per unit length better If must have excess cable avoid coiling fold instead
Long Wires on Strain Gauges
• Lead-wire causes voltage drop – so you do not
get requested excitation
• This de-sensitizes the Bridge cause in an error
in calibration (sensitivity)
• Two Countermeasures:
1. Lead wire compensation: measure lead
wire resistance and mathematically
calculate error in sensitivity
2. Sense Line: Non current carrying line
that allows system to adjust excitation
voltage to ensure you get the specified
excitation
• When long reaches of multiple conductors are
run adjacent to each other, problems with
crosstalk between conductors can be
encountered. With runs of 50 feet [15 m] or
more, significant levels of noise can be induced
into sensitive conductors through both magnetic
and electrostatic coupling
• Countermeasure individually shielded
pairs one pair for excitation, and one pair
for the signalLong Wires on Accelerometers Capacitance in wire acts as low pass filter (rc-circuit)
Cable Length Example
Example:
•100 ft. cable
•capacitance of 30 pF/ft, the total
capacitance is 3000 pF.
•This value can be found along the
diagonal cable capacitance lines.
•Maximum output range of 5 volts
•constant current signal conditioner is set
at 2mA,
•The ratio on the vertical axis can be
calculated to equal 5.
•The intersection of the total cable
capacitance and this ratio result in a
maximum frequency of approximately
10.2 kHzFrequency Dependent Calibration
FRF Inverse FRF
Short Cable
Long cable
Impulse Response
Long cable compensated
Supporting long cable or measurement distortion
compensationDigital Data Acquisition Agenda
1 Structure
2 Sensor
3 Wiring
4 Signal Conditioning
5 Alias Filter
6 Analog to Digital Converter
7 Time File
30 copyright LMS International - 2011Sources of Noise Electronics noise
Analog electronic circuits are built with resistors,
capacitors, inductors, semiconductors and
switches. Each electronic component has a
certain noise contribution
Signal conditioning and anti alias filtering adds
thermal noise
Sensor supply circuits can also produce noise
31Signal Conditioning - Components
Signal conditioning means manipulating an analog signal in such a
way that it meets the requirements of the next stage for further
processing.
Can Include AC Coupling - ICP
Sensor Supply:
Provides low noise excitation source either current or voltage to
transducer
Amplifier:
Scales input voltages to input of ADC
Single ended and DifferentialHardware AC Coupling Filter
freq (Hz) Amplitude
0.01 0.019996001
0.02 0.039968038
0.03 0.059892291
0.04 0.079745222
0.05 0.099503719
0.06 0.119145221
0.07 0.138647845
0.08 0.157990501
0.09 0.177152998
0.1 0.196116135
0.2 0.371390676
0.3 0.514495755
0.4 0.624695048
0.5 0.707106781
0.6 0.76822128
0.7 0.813733471
0.8 0.847998304
0.9 0.874157276
1 0.894427191
2 0.9701425
3 0.986393924
4 0.992277877
5 0.99503719Instrumentation Amplifiers
Single-ended. An unbalanced input, non-isolated. Suitable for measurements where common mode
voltages are zero, or extremely small.
Differential. A balanced input, non-isolated. Suitable for measurements where the sum of common
mode and normal mode voltages remains within the measurement range of the amplifier.
Helps common mode voltage noises
Single-ended, floating common. An isolated and quasi-balanced input (the floating common is
typically connected to the (-) input of a differential amplifier). Suitable for off-ground measurements up
to the breakdown voltage of the isolation barrier, and exhibits very good common mode rejection (100
db typical).
Differential, floating common. An, isolated and balanced input. Suitable for off-ground
measurements to the breakdown voltage of the isolation barrier, and exhibits superb common mode
rejection (>120 db).Common Mode Noise Rejection
Cancels Common Mode Voltages: appears simultaneously and in phase on each of the
instrument's inputs with respect to power ground.
Common Mode Noise Rejection property of Differential amplifier typical spec 80dB
Example: Assume that you want to measure a 3VDC normal-mode signal in the presence
of a +6VDC CMV, and assume that
the normal-mode signal gain is 1.
80dB = 20 log (VCMV in / VCMV out) Product Spec:
Common Mode Rejection (60Hz):
80dB = 20 log (6VDC / VCMV out) 79dB@10V input range, 99dB@1V input
4 = log (6VDC / VCMV out) range and 109dB@£100mV input range
10,000 = 6VDC / VCMV out
VCMV out = 0.6mVQuarter vs Full Bridge
• Full Bridge has common mode noise rejection because of 2 wire
(differential) connection to amp
• Differential Voltage
• Quarter and Half Bridges have a one wire connection
• Single ended Voltage
Quarter Bridge Full Bridge
36 copyright LMS International - 2011Common Mode Noise Reduction
1.00
F AutoPow er Quarter Bridge Curve 10.00 600.00 RMS Hz
500e-3 F AutoPow er Full Bridge
300e-3
0.02 9.34e-3 0.35 muE
200e-3 1.38e-3 1.01e-3 0.02 muE
100e-3
70e-3
50e-3
30e-3
20e-3
muE
Log
10e-3
7e-3
5e-3
3e-3
2e-3
1e-3
700e-6
500e-6
300e-6
200e-6
100e-6 10.00 60.00 600.00
10.00 50 100 150 200 250 300 350 400 450 500 550 600.00
Hz
37 copyright LMS International - 2011Digital Data Acquisition Agenda
1 Structure
2 Sensor
3 Wiring
4 Signal Conditioning
5 Alias Filter
6 Analog to Digital Converter
7 Time File
38 copyright LMS International - 2011Antialiasing Filter
Purpose : To prevent folding of frequency content above Nyquist
frequency into Measurement Bandwidth
Nyquist frequency
(Bandwidth)
fs
f max =
2
LMS System prevents Aliasing by the combination of an Analog anti-
aliasing filter and Over Sampling in the Sigma-Delta ConverterScadas Anti-Aliasing FIlter
ALIASING Are you sure you’re getting what you think you’re getting?
Alisasing - Sampling = only look from time to time …
∆t
1
Fs =
∆t
Are you getting the right amplitude?
Are you getting the correct frequency???Beneficial use of Aliasing Need to gemovie in
Something
strange?
Glass vibrates
at 608 Hz,
while we see it
vibrating at 2
Hz!Sampling – Potential Source of Trouble
1.5
1
0.5
0
-0.5
-1
-1.5
Sample Actual Observed
Hz Frequency Frequency
100 25 25
100 50 50 Nyquist Frequency f max
100 60 40
100 75 25
100 100 0
100 125 25
100 150 50
100 160 40
100 175 25
100 200 0
“Observed”
frequencies f /2
s
True
frequencies
0 fs/2 fs 2fs 3fsHow Do I Minimize Aliasing
Sample Extremely high: If there is no frequency
content above Nyquist Frequency then there is
no Aliasing
This is not always practical or possible:
• Large files sizes,
• Limitations of data acquisition equipment
Anti-Aliasing Filter
Low Pass Analog and Digital filters
45 copyright LMS International - 2011Practical Sample Rate Considerations
Anti-aliasing filters are a necessary part of most data acquisition
system systems.
In order to ensure alias free data in the band of interest sample
rates are often:
f s ≥ 2.5 f max
This places the filter roll-ff outside the band of interest
Example for 100 Hz Alias free band
250
100 * 2.5 = 250 → = 125 → 125 * .8 = 100 Hz
2Digital Data Acquisition Agenda
1 Structure
2 Sensor
3 Wiring
4 Signal Conditioning
5 Alias Filter
6 Analog to Digital Converter
7 Time File
47 copyright LMS International - 2011The Analog to Digital Converter (ADC, A/D or A to D)
Converts a continuous quantity to a discrete time digital
representational
Typically device that converts an input analog
voltage or current to a digital number proportional to
the magnitude of the voltage or current
Reverse is called Digital to Analog Converter (DAC)
Resolution of the converter indicates the number of
discrete values it can produce over the range of analog
values.
The values are usually stored electronically in binary
form, so the resolution is usually expressed in bits. In
consequence, the number of discrete values available,
or "levels", is a power of two
http://en.wikipedia.org/wiki/Analog-to-digital_converterSome ADC Formulas
The number of voltage intervals is given by
where M is the ADC's resolution in bits.
The voltage resolution of an ADC is equal to its overall
voltage measurement range divided by the number of discrete
values:
where M is the ADC's resolution in bits and EFSR is the
full scale voltage range (also called 'span'). EFSR is
given by
# of Bits # of Voltage steps (+/-10 Volts)/Bit
8 255 7.81E-02
12 4095 4.88E-03
16 65535 3.05E-04
24 16777215 1.19E-06
http://en.wikipedia.org/wiki/Analog-to-digital_converterADC Not only the resolution, but also the type of ADC can be crucial The ADC resolution (in # of bits) doesn’t always reflect its dynamic range (in dB) In general, Σ∆ A/D converters are a good compromise for NVH and durability test scenarios
Types of ADC’s A direct-conversion ADC A successive-approximation ADC A ramp-compare ADC The Wilkinson ADC An integrating ADC (also dual-slope or multi-slope ADC) A delta-encoded ADC or counter-ramp A pipeline ADC (also called subranging quantizer) A sigma-delta ADC (also known as a delta-sigma ADC) A time-interleaved ADC An ADC with intermediate FM stage http://en.wikipedia.org/wiki/Analog-to-digital_converter
ADC Errors Aliasing. A precondition of the sampling theorem is that the signal be bandlimited. However, in practice, no time-limited signal can be bandlimited. Since signals of interest are almost always time- limited (e.g., at most spanning the lifetime of the sampling device in question), it follows that they are not bandlimited. However, by designing a sampler with an appropriate guard band, it is possible to obtain output that is as accurate as necessary. Integration effect or aperture effect. This results from the fact that the sample is obtained as a time average within a sampling region, rather than just being equal to the signal value at the sampling instant. The integration effect is readily noticeable in photography when the exposure is too long and creates a blur in the image. An ideal camera would have an exposure time of zero. In a capacitor- based sample and hold circuit, the integration effect is introduced because the capacitor cannot instantly change voltage thus requiring the sample to have non-zero width. Jitter or deviation from the precise sample timing intervals. Noise, including thermal sensor noise, analog circuit noise, etc. Slew rate limit error, caused by an inability for an ADC output value to change sufficiently rapidly. Quantization as a consequence of the finite precision of words that represent the converted values. Error due to other non-linear effects of the mapping of input voltage to converted output value (in addition to the effects of quantization). http://en.wikipedia.org/wiki/Analog-to-digital_converter
Sigma Delta ADC Process
24 Bit Sigma-Delta Converter Process on Scadas Mobile
Over Sample - Max Sample Rate
• 32 x 204.8 KHz = 6.5 MS/sec (MS= Million Samples)
Decimate to ADC Rate 204.8 KHz
• Resampling requires digital re-sampling filter to prevent aliasing
• digital filter of 150dB/Oct roll-off
• 100dB alias protection
• Provides Alias free bandwidth of 92kHz -
Further decimation to software selectable sample rate in steps of 2 and 2.5
• Each decimation requires re-sampling filterDecimation to User defined Rate
Phase Match Basics of Sine Waves - Phase
x(t ) = A sin( 2πft + θ ) Phase Match: Maximum
time stamp error of a
given frequency sine
wave at a specified input
1.00
range:
0.70
0.50
0.20
θ = 2πft
Real
0.00
/
-0.30
-0.50
OR
-0.80
-1.00
1.00
1.02 1.05
1.041.06 1.08 1.10 1.12 1.141.161.18 1.20 1.221.241.261.28 1.30 1.32 1.35
θ = ωt
sChannel to Channel Skew Eliminated Simultaneous Sampling Eliminates time skew between channels Simplifies both time and frequency based analysis techniques Multiplexed Sampling Channels are sampled sequentially May require software correction for detecting certain patterns
What is Quantization?
In analog-to-digital conversion, the difference between the actual analog
value and quantized digital value is called quantization error or
quantization distortion.
This error is either due to rounding or truncation. The error signal is
sometimes considered as an additional random signal called quantization
noise because of its stochastic behavior.
The continuous amplitude of the real time signal will be split up in discrete
levels (= 2NUMBER of BITS) QUANTIZATION
Quantization refers to the precision of amplitude conversion
TimeProperties of Quantization Error (Noise):
Random (stochastic)
If not at max range
Considered as an additional random signal called quantization noise because of its
stochastic behavior
Proportional to input range
Proportional to the number of bits in the systems
At lower amplitudes the quantization error becomes dependent on the input signal, resulting
in distortion
In an ideal analog-to-digital converter, where the quantization error is uniformly distributed
between −1/2 LSB and +1/2 LSB, and the signal has a uniform distribution covering all
quantization levels, the Signal-to-quantization-noise ratio (SQNR) can be calculated from
• Where Q is the number of quantization bits
• The most common test signals that fulfill this are full amplitude triangle waves and
saw tooth waves.
Ideal SQNR dB
12 72.24
16 96.32
24 144.48Analog to Digital Converter (ADC)
Voltage
Bits
Levels
8 256
12 4096
16 65536
24 16777216
Precision of
conversion is
controlled by the
number of bits of
resolution in the
Analog to Digital
Converter.What does Quantization Noise look like
Signal looks Blurry
Bit NoiseWhat Can Causes a Quantization Noise - Underload
Under-load AKA
improper Input
Range SettingHow to Mitigate Quantization Errors
Optimize the Input Range on your acquisition systemResult of Optimized input Range
Clean clear signal
High dynamic
RangeInstrument specifications
• System Specification Terms
• Dynamic Range
• Spurious Free Floor or Noise Floor
• Spurious Free Dynamic Range
• Signal to Noise
• Harmonic Distortion
• Common Mode Noise Rejection
• Phase Match
Signal
• Cross Talk Conditioning Gain Alias
Protection
ADC DSP
Conditioner and Filter ADC Calculation
sensor supply accuracy
noise noise noise
64Summary – Considerations for Getting a Better Measuement
Measurement uncertainty in a function of the entire measurement chain
Spec sheets quantify system performance only
Ways to reduce noise and signal reduction:
Differential amplifier – Common Mode Noise Rejection (CMR)
Properly grounded measurement system
Good anti-aliasing system 5.40
5
1.00
High # of bits in A/D 5
4
F Time 1:+Z
Cable shielding 3
3
Good resampling filter 3
Amplitude
Real
g
2
Individual A/D per channel 2
1
Set range correctly 500e-3
0
-500e-3
-1.20 0.00
0.00 10e-3 20e-3 30e-3 40e-3 50e-3 60e-3 70e-3 80e-3 90e-3 100e-3 0.11
sThank you
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