Introduction
Electronic Instrumentation
Electronic Instrumentation
Chapter 1
Introduction
Pablo Acedo / Jose A. García Souto
1
Introduction
Electronic Instrumentation
Chapter 1. Introduction
• Basic Architecture for an Electronic/Optoelectronic
Instrumentation Measurement System. Definitions.
• Sensors and Categories of Sensor by Input Mechanisms
• Characterization of Sensors and Measurement Systems
• Calibration Curve/Transfer Function
• Static Characteristics
• Dynamic Characteristics
• Errors in Measurements
• Summary
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Introduction
Electronic Instrumentation
Basic Architecture for an Electronic
Instrumentation Measurement System
q: Sensor/transducer output
(electrical magnitude)
Vo: Output voltage of the
Signal conditioning circuit
q
Vo
m
p1
p2
Sensor/
Transducer
Analog Signal
Conditioning
ADC
p3
Storage
m: Magnitude to be measured
Transmission
p1, p2,… : Influence magnitudes/variables
Display
Pablo Acedo / Jose A. García Souto
Digital Signal
Conditioning:
FPGA, µC,
µP, DSP
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Introduction
Electronic Instrumentation
Basic Architecture for an Opto-Electronic
Instrumentation Measurement System
Light Input
Light
Output
m
p1
p2
q
Detection
Analog Signal
Conditioning
Vo
p3
•
•
•
•
Light Input from a Semiconductor laser diode or LED (sometimes not necessary).
“Optical Signal conditioning” sometimes present (eg. Interferometer).
Output from detector can be either a current (photodiode) an impedance change (photoconductor) or a
voltage (photovoltaic sensor).
The information from the interest magnitude can be either in the amplitude, phase, polarization or
wavelength of the light.
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Introduction
Electronic Instrumentation
Sensors
A sensor is a device that receives a stimulus and
responds with an electrical signal
• There is always a form of energy conversion associated to the transduction
process.
• A sensor can be a simple sensor or can be a complex system.
• Sensors can be classified in many ways depending on the criteria chosen:
• Field of applications
• Conversion Phenomena
• Specification
• Other
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Introduction
Electronic Instrumentation
Categories of Sensor Input Mechanisms
• Resistive Sensors
• Variable Inductance/Magnetic Coupling
Sensors
• Capacitive Sensors
• Voltage Generating Sensors
• Current Generating Sensors/optical Sensors
Passive Sensors
Active Sensors
• Other Sensors
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Introduction
Electronic Instrumentation
Characterization of Sensors and
Measurement Systems
• Transfer Function:
• Calibration Curve (static):
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Introduction
Electronic Instrumentation
Output (q)
Calibration Curve
9
8
7
• Input Range
Output Range
6
• Output Range
5
• Span
4
• Full Scale Input
3
2
• Full-Scale Output
1
0
0
2
4
6
Input Range
8
10
Magnitude (m)
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Introduction
Electronic Instrumentation
Calibration Curve: Example
RT/R0
4
3,5
Pt100
Cu100
3
Ni120
2,5
2
1,5
1
0,5
-200
-100
0
100
200
Pablo Acedo / Jose A. García Souto
300
400
T, ºC
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Introduction
Electronic Instrumentation
Output (q)
Sensitivity
9
• Definition:
8
7
6
5
4
• Local Value
3
• UNITS!!
• Slope of the transfer
function (local)
2
1
0
0
2
4
6
8
10
Magnitude (m)
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Introduction
Electronic Instrumentation
Output (q)
Non-Linearity
•Associated to a linear
approximation of the
transfer function.
9
8
Least-Squares
aproximation
7
•IMPORTANT: Different
linear aproximations
may be used, leading to
different non-linearity
error values
6
5
4
3
Terminal points
aproximation
2
1
0
0
2
4
6
8
•Maximum deviation
from the nonlinear
transfer function
(usually in percent of
FS value)
10
Magnitude (m)
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Introduction
Electronic Instrumentation
Output (q)
Hysteresis
9
•Deviation of the sensor’s
output at specified point
when it is approached
from the opposite
directions (usually in
percent of FS value)
8
7
6
5
4
• Typical causes of
Hysteresis are friction
and structural changes in
the materials
3
2
1
0
0
2
4
6
8
10
Magnitude (m)
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Introduction
Electronic Instrumentation
Resolution
• Resolution: The smallest increment of the input that can be sensed.
0.8
0.8
0.6
0.6
0.4
0.4
0.2
0.2
Amplitude (mV)
Amplitude (mV)
• Important: For sensors with a continuous response some texts talk about
infinitesimal resolution. That does not mean “infinite Resolution”.
0
-0.2
0
-0.2
-0.4
-0.4
-0.6
-0.6
-0.8
-0.8
0
200
400
600
800
1000
0
200
400
600
800
1000
time (ms)
time (ms)
Limited by the Signal-to-Noise ratio (S/N=0dB)
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Introduction
Electronic Instrumentation
Output (q)
Resolution
• In sensors with discrete
response (after ADC
conversion for exampled),
the minimum resolution
achievable is usually
limited by A/D quantization
error (step size).
1000
0110
0100
10
00
0
2
4
6
8
Input (m)
Pablo Acedo / Jose A. García Souto
• NOTE: that only will be
true if the resolution
asociated to the SN ratio at
the ADC input is lower than
the ADC’s resolution.
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Introduction
Electronic Instrumentation
Output (q)
Precision/Accuracy
9
8
• Precision: consistency of
the measurement. It is
associated to the capacity of
the sensor to give the same
output (measurement) under
the same input (Stimulus).
7
6
5
4
• In modern sensors
uncertainty is preferred
asociated to the Limiting error
of the measurement (to be
discussed later)
3
2
1
0
0
2
4
6
8
10
Magnitude (m)
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Introduction
Electronic Instrumentation
Sample Count
Precision
80
70
• Precision of the nth measurement
60
50
• Where:
40
30
20
10
0
0.25
0.5
0.75
1
1.25
1.5
1.75
Measured Value (q)
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Introduction
Electronic Instrumentation
NOTE
• Precision: Quality of the system to give always the same output under
the same stimulus (input)
• Accuracy: Error between the measurement and the true value (Y): i.e.
conformance between the measurement and the standard.
Accurate Measurements require the use of a
precision measurement system which is
calibrated against a certified, accurate standard
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Introduction
Electronic Instrumentation
Other Parameters
• Stability: Quality of the system to maintain its characteristics under
changes of the measurement conditions (e.g. Temperature) or aging.
Usually characterized through drifts in the calibration curve (offset &
sensitivity drifts).
• Dead Band: Insensitivity of a sensor in a specific range of input signals.
• Those related to the physical/electronic characteristics of the
sensor/transducer:
• Output Impedance
• Excitation (Power supply)
• Weigh
• ……
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Example of Datasheet
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Introduction
Electronic Instrumentation
Dynamic Characteristics
• Dynamic Transfer Function:
V (t ) = f [m(t ),...]
• Transient Response:
•
•
Previous characteristics assume a steady state. The time response shows
the behavior of the sensor or the instrumentation system to the changes in
the magnitude of interest by observing the signal output with time. The
step response is used as a basic test and for characterizing the system.
Basic parameters are: overshoot in the under-damped response, peak
time, settling time that is the time to reach and thereafter remain within a
prescribed percentage of the steady-state value (5%), rise time and delay.
• Frequency Response:
•
•
•
Range of work frequencies, bandwidth and types of pass-band.
Some cases don´t respond to a constant. Even more, narrow-band ones.
Dynamic sensitivity for the amplitude. Don´t forget the phase.
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Introduction
Electronic Instrumentation
Parameters of the time response
Step response
Output response
Error band (±ε)
tp
100%
Os
Value 2
•
•
•
tr
50%
•
•
0% Value 1
td
ts
Os: overshoot
ts: settling time
tr: rise time
t10-90
td: delay
tp: peak time
Magnitude of interest: analog step or discrete change
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Introduction
Electronic Instrumentation
Frequency response
F [ jω ]
Dynamic sensitivity: sensitivity for each frequency input
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Introduction
Electronic Instrumentation
Dynamic Characteristics
• Step Response:
• Frequency Response: F [ jω ]
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Introduction
Electronic Instrumentation
Errors in Measurements
All measuring instruments should be regarded as
guilty until proven innocent (P.K. Stein)
Sources/Classification of Errors
• Systematic Errors
• Random Errors (Noise/Interference)
• Gross Errors (Northrop)/Human Errors (Stein)
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Introduction
Electronic Instrumentation
Limiting Error (LE)
Limiting Error (guarantee error) describes the
outer bounds of the expected worst case error
• It includes all source of errors (gross/human errors
apart)
• Value given by designer/manufacturers to specify
the precision (accuracy) of the instrument/sensor
• Related to uncertainty
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Introduction
Electronic Instrumentation
Systematic Errors (I)
• The output of a sensor or a complete measurement
system (Vo) will be function of the mesurand (q)
and other, indirect factors, along with the
characteristics of signal conditioning.
• The influence of this factors in the final output is
deterministic. Sources:
• Signal conditioning and its imperfections.
• Influence Variables.
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Introduction
Electronic Instrumentation
Propagation of Systematic Errors
• As the influence of the different parameters is
deterministic, the combined effect of errors (∆xi)
using the linear error-propagation law using Taylor
series and removing all second and higher-order
terms.
• Usually is expressed in relative error.
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Introduction
Electronic Instrumentation
Example
• Let’s calculate the LE in the calculation of the DC
power in a resistor from the measurement of the
current and its value:
• If we use a 2% precision multimeter and the value
of the resistor is known to the 1%, the LE in the DC
power calculation is 5%
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Introduction
Electronic Instrumentation
Influence Variables
• The output of the sensor is related not only to the
measurand value and the signal conditioning
(former example), but to other environmental
variables:
• Temperature
• Pressure
• Vibration
• ….
• The influence is also studied using the deterministic
linear error propagation law that allows also for
cancelation of effects (next chapter).
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Introduction
Electronic Instrumentation
Random Errors (I)
• Associated to any measurement or electronic
signal we find random, non-deterministic variations
as the result of different sources:
• Electronic noise (Johnson, shot,..)
• Interference
• It is important to note that whilst some sources
may well be truly random (noise), some can be
rendered as systematic (interference) if enough
effort is devoted to discover and model the
sources. However, usually is easier to model them
directly as noise.
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Introduction
Electronic Instrumentation
Propagation of Random Errors
• In this case all the sources are independent and
their influence are added to the variance of the
final result.
• This quantity is usually expressed in terms of signalto-noise ratio as will be discussed further .
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Introduction
Electronic Instrumentation
Gross/Human Errors
• Humans are always part of an instrument chain as
designers, manufacturers or observers.
• History is full of examples of errors due to wrong
use of measurment units (SI vs Standard/Imperial)
• Instrumentation misuse, calculation errors and
other human mistakes are the main source of
wrong measurements!!!!
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Introduction
Electronic Instrumentation
Summary
• The typical Architecture for an Electronic/Optoelectronic
Instrumentation Measurement System has been
presented, along with different sensor input mechanisms
• The Characterization of Sensors and Measurement
Systems has been presented through the description of
the Static and Dynamic Characteristics from the
Calibration Curve/Transfer Function
• Errors in Measurements have been also described and
classified as something inherent to every measurement.
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