Schmalzel, J.L.. “Instruments”
The Electrical Engineering Handbook
Ed. Richard C. Dorf
Boca Raton: CRC Press LLC, 2000
108
Instruments
108.1 Introduction
108.2 Physical Variables
108.3 Transducers
108.4 Instrument Elements
108.5 Instrumentation System
108.6 Modeling Elements of an Instrumentation System
108.7 Summary of Noise Reduction Techniques
108.8 Personal Computer-Based Instruments
108.9 Modeling PC-Based Instruments
108.10The Effects of Sampling
108.11Other Factors
108.1 Introduction
Instruments are the means for monitoring or measuring physical variables. The basic elements of an instru-
mentation application are shown in Fig. 108.1. A physical system produces a measurand, m(t), shown as time-
varying, which is transformed by a transducer into an electrical signal, s(t), that is then processed by an
instrument to yield the desired output information variable, i(t). Producing meaningful information from
physical variables requires conversion and processing. Electronic instruments require that physical variables be
converted to electrical signals through a process of transduction, followed by signal conditioning and signal
processing to obtain useful results.
108.2 Physical Variables
The measurand can be one of many physical variables; the type depends on the application. For example, in
process control, typical measurands can include pressure, temperature, and flow. Representative physical vari-
ables with corresponding units are summarized in Table 108.1.
108.3 Transducers
Transducers convert one form of energy to another. To be useful for an electronic instrument, a transducer
must produce an electrical output such as voltage or current to allow required signal conditioning and signal
processing steps to be completed. A variety of transducers are available to meet a measurement requirement;
some common examples are listed in Table 108.2. Transducers can be compared based on their operating
principles, the measurand range, interface design, and reliability. Khazan [1994] gives a complete summary of
transducer schemes.
John L. Schmalzel
Rowan University
? 2000 by CRC Press LLC
108.4 Instrument Elements
Signal conditioning consists of amplification, filtering, limiting, and other operations that prepare the raw
instrument input signal for further operations. The signal may be the output of a transducer or it may be an
electrical signal obtained directly from an electronic device or circuit. Signal processing applies some algorithm
to the basic signal in order to obtain meaningful information. Signal conditioning and processing operations
may be performed using analog or digital circuit techniques, or using a combination of methods. There are a
variety of trade-offs between them. For example, analog methods offer bandwidth advantages, whereas digital
techniques offer advanced algorithm support and long-term stability. The use of microprocessors within an
instrument makes it possible to perform many useful functions including calibration, linearization, conversion,
storage, display, and transmission. A block diagram of a representative microprocessor-based instrument is
shown in Fig. 108.2.
FIGURE 108.1 Generalized block diagram of an instrument applied to a physical measurement.
TABLE 108.1 Representative Physical Variables,
Symbols, and Units
Physical Variable Symbol SI Units, Abbreviations
Current I ampere, A
Energy E joule, J
Force F newton, N
Flow Q volume flow rate, m
3
/s
Frequency f hertz, Hz
Length L meter, m
Mass m kilogram, kg
Pressure P N/m
2
Power P Watt, W
Resistance R ohm, W
Temperature T Kelvin, K
Time t second, s
Velocity V m/s
Voltage V volt, V
TABLE 108.2 Representative Transducers
Measurand Transducer Operating Principles
Displacement Resistive Change in resistance, capacitance, or
(Length) Capacitive inductance caused by linear or angular
Inductive displacement of transducer element
Force Strain gage Resistance, piezoresistivity
Temperature Thermistor Resistance
Thermocouple Peltier, seebeck effect
Pressure Diaphragm Diaphragm motion sensed by a
displacement technique.
Flow Differential pressure Pressure drop across restriction
Turbine Angular velocity proportional to flow rate
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108.5 Instrumentation System
An instrument is never used in isolation. The instrumentation components contribute to an overall system
response in a number of ways that are based on the measurement system elements present. These elements
include: (1) sources, (2) interconnect, (3) device or system under test, (4) response measuring equipment, and
(5) environmental variables. Figure 108.3 shows the elements of a typical instrumentation system.
108.6 Modeling Elements of an Instrumentation System
Best results are achieved when the instrumentation system is clearly understood, and its effects compensated
for when practical. Lumped parameter modeling of the elements shown in Fig. 108.3 provides a means for
determining the contribution each element makes to the overall system behavior. Of particular importance are
the input and output impedances of each element. In addition, the effects of interconnect and environmental
variables can also be modeled to determine their influence on the system. The relative dimensions of the
measurement system with respect to the highest frequencies encountered—whether signal or noise—determine
whether simplified circuit theory models, or generalized solutions to Maxwell's equations must be used.
Generally, if measurement system dimensions are on the order of 1/20 of the shortest wavelength, simple circuit
theory models can be used. Operation in this regime also allows impedance matching to be largely ignored;
e.g., not requiring mandatory use of 50 W sources, 50 W transmission lines, and 50 W terminations which is
commonly encountered in high-frequency systems. Table 108.3 summarizes several common instruments and
input or output impedance models corresponding to Fig. 108.4. At low frequencies, interconnect can be modeled
by ignoring the very low series resistance and inductance (Zs1, Zs2) terms, and considering only the shunt
FIGURE 108.2 Block diagram of generalized, microprocessor-based instrument.
FIGURE 108.3 Fundamental elements of an instrumentation system.
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CASSINI SPACECRAFT
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capacitance (Zp) which is in the range of 50 to 150 pF/m for different types of cable. At high frequencies, the
characteristic impedance of the interconnect is used; e.g., 50 W or 75 W for commonly used coaxial cables;
120 W for twisted pair.
The response of an entire instrumentation system can be modeled by interconnecting the individual model
elements. Figure 108.5 shows an example that was obtained by substituting models for an operational amplifier
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The flight vehicle consists of the main Cassini spacecraft and the ESA-built Huygens Probe, a
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conduct a detailed exploration of the whole Saturnian system, including Titan and the planet’s other icy
moons. (Courtesy of National Aeronautics and Space Administration.)
This artist’s concept shows the Cassini spacecraft orbiting around Saturn,
just after deploying a probe that will descend into the atmosphere of
Saturn’s moon Titan. Launched October 1997, Cassini will reach Saturn
in July 2004 and orbit the planet for four years thereafter. (Photo courtesy
of National Aeronautics and Space Administration.)
O
(op amp) circuit (corresponds to the device under test in Fig. 108.3) that was driven by a function generator
for the source, and that measured the response with an oscilloscope connected to the output of the op amp
using a 10X probe. In this application, the impedance of the interconnect between the source and op amp can
be neglected since the frequencies are low and the input impedance of the op amp is much greater than that
of the cable. The circuit model of the compensated 10X probe contains a very high series impedance
(9 MW||1.14 pF) relative to the oscilloscope (1 MW||13 pF) so it cannot be ignored.
The models can be used to determine the frequency response of the complete system which describes the
magnitude and phase response of the system to sinusoidal, steady-state inputs. This can reveal the contribution
of each element to the overall response and helps indicate which elements produce the dominant response.
The graphical results of the frequency response analysis is termed a Bode plot. If each of N elements has an
individual transfer function, H
i
(jw), i = 1 to N, then a composite transfer function can be found for the total
system, T(jw), which is generally not the simple product of each transfer function, H
1
(jw)·H
2
(jw)·…·H
N
(jw)
due to loading effects between elements. The use of a circuit simulation program such as PSpice (MicroSim
Corp.) simplifies the investigation into instrument behavior. A library of subcircuit models can be developed
for each instrumentation and interconnect element to support measurement system loading effects analysis.
For example, a PSpice subcircuit definition for the HP54601A oscilloscope is:
.SUBCKT HP54601A 1 2
Cin 1 2 13p
Rin 1 2 1MEG
.ENDS
TABLE 108.3 Summary of Common Instruments and Their Lumped-Parameter Models
Instrument Description, Model, Manufacturer Input Impedance, Zi Output Impedance, Zo
Function generator, FG501A, Tektronix 50 W
Multimeter, DM501A, Tektronix 10 MW (Volts mode)
Oscilloscope, 54601A, Hewlett Packard 1 MW||13 pF
FIGURE 108.4 Simplified output and input models for instrument elements.
FIGURE 108.5 Model of representative instrumentation system. Each variable would be substituted as required. For
example, Vs = 1.0sin2p1000t for a 0.707 Vrms, 1 kHz sine wave; Zo = 50 W for the FG501A; Zi = 1 kW for an op amp
configured as an inverting amplifier with Ri = 1 kW; and gain of 10; AcVi = -10.0sin2p1000t; Zo = 1 W for low current
output; Zi = 9 MW||1.4 pF for a compensated 10X probe; and with Zi = 1 MW||13 pF for the input model of the HP54601A
oscilloscope.
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This network model would be added as a load to the output of the device under test in order to predict its
loaded behavior.
108.7 Summary of Noise Reduction Techniques
Elimination of undesired measurement errors benefits from a systematic approach to identifying and solving
noise problems. Source, interconnect, and response elements of a measurement system can be treated individ-
ually. Some techniques, such as shielding, are applicable to all three. Various combinations of techniques should
be tried to achieve best results. There are many choices of grounding techniques that vary depending on whether
elements are floating or ground-referred, and based on bandwidth. In general, multiple ground connections
that create ground loops should be avoided. Difficult ground loop problems may require isolation or other
techniques to interrupt the ground connection between elements. Table 108.4 summarizes a checklist of noise
reduction techniques.
108.8 Personal Computer-Based Instruments
Many instrument functions are available for interface to personal computer (PC) systems. These range from
plug-in cards that reside on the PC backplane to standalone instruments that communicate with the PC over
standard interfaces such as RS-232 or IEEE-488. Software to control data acquisition, analysis, and display
completes the computer-based instrument. Examples of such software include Lab Windows or Lab View
(National Instruments), HP VEE (Hewlett-Packard), and Testpoint (Keithley-Metrabyte). Figure 108.6 shows a
block diagram of an output screen developed using Lab Windows for an acoustic measurement application. A
TABLE 108.4 Noise Reduction Checklist
Source Interconnect Response
Shield enclosures Shield leads Shield enclosures
Filter inputs and outputs Minimize loop area (twist leads) Filter inputs and outputs
Limit bandwidth Keep signal leads near ground Limit bandwidth
Minimize loop areas Separate low-, high-level signals Minimize loop areas
Keep signal and ground leads short
Low f: Use single ground
High f: Use multiple grounds
Source: H.W. Ott, Noise Reduction Techniques in Electronic Systems, 2nd ed., New York: John
Wiley & Sons, 1988. With permission.
FIGURE 108.6 Example block diagram of a virtual instrument user interface.
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menu bar provides pull-down options. Several windows simultaneously display selection options and present
results graphically and with text.
108.9 Modeling PC-Based Instruments
The approach outlined previously for modeling conventional measurement systems can be extended to PC-
based instruments with one major difference: PC-based instruments by their nature are digital machines and
perform functions in discrete time. Best performance of PC-based instrument systems must therefore consider
sampled data effects. Figure 108.7 shows a data acquisition system modeled using an ideal sampler which
instantaneously samples a continuous signal, s(t), every T seconds. This yields a sequence, s(nT), of discrete
values that represent the value of the continuous signal at integer multiples of T seconds.
108.10 The Effects of Sampling
The Fourier transform of a sampled signal yields a frequency domain function that is periodic in frequency,
with a period that is 1/f
s
. The sampling theorem states that in order to unambiguously preserve information,
the sampling frequency, f
s
= 1/T, must be at least twice the highest frequency present in the continuous-time
signal. If f
s
is less than twice the highest frequency, aliasing will occur. Aliased frequencies are indistinguishable
from one another. A useful method for visualizing this result is through the use of an aliasing diagram. An
example is shown in Fig. 108.8. Note that the Nyquist frequency is defined to be f
s
/2.
108.11 Other Factors
Other important factors that should be considered when using PC-based instruments over manual counterparts
are summarized in Table 108.5. Perhaps the most important choice is the selection of a minimum sampling
rate for the data acquisition process. It must be chosen to meet the requirements of the Nyquist frequency.
However, in order to ensure that no higher frequencies are present, an anti-aliasing low pass filter that eliminates
energy above the Nyquist frequency should be employed. In order to provide sufficient transition bandwidth
for the filter, a slightly higher sampling rate should generally be employed. A factor of 1.25 to 5 times the
minimum f
s
is a good compromise. Automated equipment may introduce substantial transients into the
measurement system. Sufficient time must be provided for the resulting transients to settle to an acceptable
error bound; for example, 1%.
FIGURE 108.7 Sampling a continuous-time signal yields a discrete-time signal.
FIGURE 108.8 Aliasing diagram. The two baseband frequencies, f1 and f2, have aliases at frequencies that intersect the
vertical dashed lines. For example, using a sampling frequency of 10 kHz (F
n
= 5 kHz) with f1 = 1 kHz and f2 = 3.5 kHz,
signals at 9 kHz (f
1a
) and 11 kHz (f
1b
) would be aliased to 1 kHz (f
1
), while signals at 6.5 kHz (f
2a
) and 13.5 kHz (f
2b
) would
be aliased to 3.5 kHz (f
2
).
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Defining Terms
Instrument: The means for monitoring or measuring physical variables. Usually includes transducers, signal
conditioning, signal processing, and display.
Measurement system: The sum of all stimulus and response instrumentation, device under test, interconnect,
environmental variables, and the interaction among the elements.
Transducer: A device that transforms one form of energy to an electrical output that can be processed by an
instrument.
Virtual instrument: An instrument created through computer control of instrumentation resources with
analysis and display of the data collected.
Related Topics
3.1 Voltage and Current Laws ? 8.5 Sampled Data ? 73.2 Noise ? 112.1 Introduction
References
N. Ahmed and T. Natarajan, Discrete-Time Signals and Systems, Reston, Vir.:, Reston Publishing, 1983.
E.O. Doebelin, Measurement Systems: Application and Design, 4th ed., New York: McGraw-Hill, 1990.
J.P. Holman, Experimental Methods for Engineers, 6th ed., New York: McGraw-Hill, 1994.
A.D. Khazan, Transducers and Their Elements: Design and Application, Englewood Cliffs, N.J.: Prentice-Hall,
1994.
H.W. Ott, Noise Reduction Techniques in Electronic Systems, 2nd ed., New York: John Wiley & Sons, 1988.
W.J. Tompkins and J.G. Webster, Eds., Interfacing Sensors to the IBM PC, Englewood Cliffs, N.J.: Prentice-Hall,
1988.
Further Information
The monthly journals, IEEE Transactions on Instrumentation and Measurement, and IEEE Transactions on
Biomedical Instrumentation, report advances in instrumentation. For subscription information, contact: IEEE
Service Center, 445 Hoes Lane, PO Box 1331, Piscataway, NJ 08855-1331. (800) 678-IEEE.
Information about automatic test equipment and software for data acquisition, analysis, and display, can be
obtained from several vendors; for example, Hewlett-Packard, Englewood, CO, (800)-829-4444; Keithley-
Metrabyte, Taunton, MA, (800) 348-0033; and National Instruments, Austin, TX, (512) 794-0100. Information
about transducers can be obtained from Omega International, Stamford, CT, (203) 359-1660.
TABLE 108.5 Automated Measurement Factors
Factor Consideration
Leveling Frequency response measurements require use of a leveled generator. Alternatively, store a calibration curve.
Multiplexing Measurements from multiple nodes require lead switching to shared instruments; consider these effects.
Sampling frequency Must exceed the Nyquist frequency. Include an anti-aliasing filter. Manual instruments typically use
integrating (dual-slope) analog-to-digital converters which give good noise rejection over integer numbers
of line cycles. Faster sampling rates for ATE are achieved using successive-approximation or other
techniques. User may have to perform averaging as a post-processing step in order to achieve acceptable
signal-to-noise ratios.
Settling time Allow sufficient time for transients to settle for both stimulus/response instruments and device under test.
Storage Automatic measurements can produce large arrays of data at high speeds. Actual throughput to a hard disk
may be much less than the maximum sampling rate of a data acquisition element (plug-in board, external
instrument).
Triggering Choices between free-running, external, and internal.
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