Mechanical Engineering
The third edition of Measurement and Data Analysis for Engineering and Science provides an
up-to-date approach to presenting the methods of experimentation in science and engineering. Widely
adopted by colleges and universities within the U.S. and abroad, this edition has been developed as a
modular work to make it more adaptable to different approaches from various schools.
This text details current methods and highlights the six fundamental tools required for implementation:
planning an experiment, identifying measurement system components, assessing measurement
system component performance, setting signal sampling conditions, analyzing experimental results,
and reporting experimental results.
What’s New in the Third Edition
This latest edition includes a new chapter order that presents a logical sequence of topics in
experimentation, from the planning of an experiment to the reporting of the experimental results. It
adds a new chapter on sensors and transducers that describes approximately 50 different sensors
commonly used in engineering, presents uncertainty analysis in two separate chapters, and provides
a problem topic summary in each chapter.
New topics include smart measurement systems, focusing on the Arduino® microcontroller and its use
in the wireless transmission of data, and MATLAB® and Simulink® programming for microcontrollers.
Further topic additions are on the rejection of data outliers, light radiation, calibrations of sensors,
comparison of first-order sensor responses, the voltage divider, determining an appropriate sample
period, and planning a successful experiment.
Measurement and Data Analysis for Engineering and Science also contains more than 100
solved example problems, over 400 homework problems, and provides over 75 MATLAB® Sidebars
with accompanying MATLAB M-files, Arduino codes, and data files available for download.
K20700
Measurement and Data Analysis
for Engineering and Science
Measurement and Data Analysis
for Engineering and Science
Dunn
THIRD
EDITION
ISBN: 978-1-4665-9496-8
90000
9 781466 594968
K20700_COVER_final.indd 1
4/23/14 10:39 AM
Measurement and Data Analysis
for Engineering and Science
THIRD EDITION
Patrick F. Dunn
University of Notre Dame
Indiana, USA
Cover
The background on the cover includes photographs and figures from the author’s experimental research spanning 45 years. Included are photographs of
liquid-droplet and solid-particle electrosprays and their generators, a Na-Ar
magnetohydrodynamic facility, and nuclear aerosols impacted on a wire. The
figures are of microparticle detachment versus time, single-electrode voltage
and current versus time of a spinal motor neuron, and microparticle adhesion
analysis. This research was conducted at Purdue University, Duke University,
Argonne National Laboratory, and the University of Notre Dame. The collage
format of the cover was developed by the author and designed by Joanne D.
Birdsell, Director of Communications and Marketing, Dean’s Office - College
of Engineering, University of Notre Dame.
MATLAB® is a trademark of The MathWorks, Inc. and is used with permission. The MathWorks does
not warrant the accuracy of the text or exercises in this book. This book’s use or discussion of MATLAB® software or related products does not constitute endorsement or sponsorship by The MathWorks
of a particular pedagogical approach or particular use of the MATLAB® software.
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© 2015 by Taylor & Francis Group, LLC
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Version Date: 20140407
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Contents
1 Fundamentals of Experimentation
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . .
2 Experiments
2.1 Chapter Overview . . . . . . . . . .
2.2 Experimental Approach . . . . . . .
2.3 Role of Experiments . . . . . . . . .
2.4 The Experiment . . . . . . . . . . .
2.5 Classification of Experiments . . . .
2.6 Plan for Successful Experimentation
2.7 Hypothesis Testing* . . . . . . . . .
2.8 Design of Experiments* . . . . . . .
2.9 Factorial Design* . . . . . . . . . .
2.10 Problems . . . . . . . . . . . . . . .
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Bibliography
3 Fundamental Electronics
3.1 Chapter Overview . . . . . . . .
3.2 Concepts and Definitions . . . .
3.2.1 Charge . . . . . . . . . .
3.2.2 Current . . . . . . . . . .
3.2.3 Force . . . . . . . . . . .
3.2.4 Field . . . . . . . . . . . .
3.2.5 Potential . . . . . . . . .
3.2.6 Resistance and Resistivity
3.2.7 Power . . . . . . . . . . .
3.2.8 Capacitance . . . . . . . .
3.2.9 Inductance . . . . . . . .
3.3 Circuit Elements . . . . . . . . .
3.3.1 Resistor . . . . . . . . . .
3.3.2 Capacitor . . . . . . . . .
3.3.3 Inductor . . . . . . . . . .
3.3.4 Transistor . . . . . . . . .
3.3.5 Voltage Source . . . . . .
3.3.6 Current Source . . . . . .
3.4 RLC Combinations . . . . . . .
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Elementary DC Circuit Analysis . . . . .
3.5.1 Voltage Divider . . . . . . . . . . .
3.5.2 Electric Motor with Battery . . . .
3.5.3 Wheatstone Bridge . . . . . . . . .
3.6 Elementary AC Circuit Analysis . . . . .
3.7 Equivalent Circuits* . . . . . . . . . . . .
3.8 Meters* . . . . . . . . . . . . . . . . . . .
3.9 Impedance Matching and Loading Error*
3.10 Electrical Noise* . . . . . . . . . . . . . .
3.11 Problems . . . . . . . . . . . . . . . . . .
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Bibliography
4
Measurement Systems: Sensors
4.1 Chapter Overview . . . . . . .
4.2 Measurement System Overview
4.3 Sensor Domains . . . . . . . .
4.4 Sensor Characteristics . . . . .
4.5 Physical Principles of Sensors .
4.6 Electric . . . . . . . . . . . . .
4.6.1 Resistive . . . . . . . . .
4.6.2 Capacitive . . . . . . . .
4.6.3 Inductive . . . . . . . .
4.7 Piezoelectric . . . . . . . . . .
4.8 Fluid Mechanic . . . . . . . .
4.9 Optic . . . . . . . . . . . . . .
4.10 Photoelastic . . . . . . . . . .
4.11 Thermoelectric . . . . . . . . .
4.12 Electrochemical . . . . . . . .
4.13 Sensor Scaling* . . . . . . . .
4.14 Problems . . . . . . . . . . . .
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and Transducers
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Bibliography
5 Measurement Systems: Other Components
5.1 Chapter Overview . . . . . . . . . . . . . . . . . . . . . .
5.2 Signal Conditioning, Processing, and Recording . . . . .
5.3 Amplifiers . . . . . . . . . . . . . . . . . . . . . . . . . .
5.4 Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5 Analog-to-Digital Converters . . . . . . . . . . . . . . . .
5.6 Smart Measurement Systems . . . . . . . . . . . . . . . .
5.6.1 Sensors and Microcontroller Platforms . . . . . . .
5.6.2 Arduino Microcontrollers . . . . . . . . . . . . . .
5.6.3 Wireless Transmission of Data . . . . . . . . . . .
5.6.4 Using the MATLAB Programming Environment .
5.6.5 Examples of Arduino Programming using Simulink
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5.7
5.8
Other Example Measurement Systems . . . . . . . . . . . . .
Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Bibliography
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6 Measurement Systems: Calibration and Response
6.1 Chapter Overview . . . . . . . . . . . . . . . . . . .
6.2 Static Response Characterization by Calibration . .
6.3 Dynamic Response Characterization . . . . . . . . .
6.4 Zero-Order System Dynamic Response . . . . . . .
6.5 First-Order System Dynamic Response . . . . . . .
6.5.1 Response to Step-Input Forcing . . . . . . . .
6.5.2 Response to Sinusoidal-Input Forcing . . . .
6.6 Second-Order System Dynamic Response . . . . . .
6.6.1 Response to Step-Input Forcing . . . . . . . .
6.6.2 Response to Sinusoidal-Input Forcing . . . .
6.7 Measurement System Dynamic Response . . . . . .
6.8 Problems . . . . . . . . . . . . . . . . . . . . . . . .
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7 Measurement Systems: Design-Stage Uncertainty
7.1 Chapter Overview . . . . . . . . . . . . . . . . . .
7.2 Design-Stage Uncertainty Analysis . . . . . . . . .
7.3 Design-Stage Uncertainty Estimate of a Measurand
7.4 Design-Stage Uncertainty Estimate of a Result . .
7.5 Problems . . . . . . . . . . . . . . . . . . . . . . .
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8 Signal Characteristics
8.1 Chapter Overview . . . . . .
8.2 Signal Classification . . . . .
8.3 Signal Variables . . . . . . .
8.4 Signal Statistical Parameters
8.5 Problems . . . . . . . . . . .
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Bibliography
9 The
9.1
9.2
9.3
9.4
9.5
9.6
Fourier Transform
Chapter Overview . . . . . . . . .
Fourier Series of a Periodic Signal
Complex Numbers and Waves . .
Exponential Fourier Series . . . .
Spectral Representations . . . . .
Continuous Fourier Transform . .
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Continuous Fourier Transform
Discrete Fourier Transform .
Fast Fourier Transform . . .
Problems . . . . . . . . . . .
Properties* . .
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Bibliography
10 Digital Signal Analysis
10.1 Chapter Overview . . . . . .
10.2 Digital Sampling . . . . . . .
10.3 Digital Sampling Errors . . .
10.3.1 Aliasing . . . . . . . .
10.3.2 Amplitude Ambiguity
10.4 Windowing* . . . . . . . . .
10.5 Determining a Sample Period
10.6 Problems . . . . . . . . . . .
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11 Probability
11.1 Chapter Overview . . . . . . . . . . .
11.2 Relation to Measurements . . . . . .
11.3 Basic Probability Concepts . . . . . .
11.3.1 Union and Intersection of Sets
11.3.2 Conditional Probability . . . .
11.4 Sample versus Population . . . . . . .
11.5 Plotting Statistical Information . . .
11.6 Probability Density Function . . . . .
11.7 Various Probability Density Functions
11.7.1 Binomial Distribution . . . . .
11.7.2 Poisson Distribution . . . . . .
11.8 Central Moments . . . . . . . . . . .
11.9 Probability Distribution Function . .
11.10 Problems . . . . . . . . . . . . . . . .
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Bibliography
12 Statistics
12.1 Chapter Overview . . . . . . . . . . . . . . .
12.2 Normal Distribution . . . . . . . . . . . . . .
12.3 Normalized Variables . . . . . . . . . . . . .
12.4 Student’s t Distribution . . . . . . . . . . . .
12.5 Rejection of Data . . . . . . . . . . . . . . .
12.5.1 Single-Variable Outlier Determination
12.5.2 Paired-Variable Outlier Determination
12.6 Standard Deviation of the Means . . . . . .
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12.7 Chi-Square Distribution . . . . . . . . . . . . . . . . . .
12.7.1 Estimating the True Variance . . . . . . . . . . .
12.7.2 Establishing a Rejection Criterion . . . . . . . .
12.7.3 Comparing Observed and Expected Distributions
12.8 Pooling Samples* . . . . . . . . . . . . . . . . . . . . .
12.9 Problems . . . . . . . . . . . . . . . . . . . . . . . . . .
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423
13 Uncertainty Analysis
13.1 Chapter Overview . . . . . . . . . . . . . . . . . . . . .
13.2 Modeling and Experimental Uncertainties . . . . . . . .
13.3 Probabilistic Basis of Uncertainty . . . . . . . . . . . .
13.4 Identifying Sources of Error . . . . . . . . . . . . . . . .
13.5 Systematic and Random Errors . . . . . . . . . . . . .
13.6 Quantifying Systematic and Random Errors . . . . . .
13.7 Measurement Uncertainty Analysis . . . . . . . . . . .
13.8 Uncertainty Analysis of a Multiple-Measurement Result
13.9 Uncertainty Analyses for Other Measurement Situations
13.10 Uncertainty Analysis Summary . . . . . . . . . . . . .
13.11 Finite-Difference Uncertainties* . . . . . . . . . . . . .
13.11.1 Derivative Approximation* . . . . . . . . . . . .
13.11.2 Integral Approximation* . . . . . . . . . . . . .
13.11.3 Uncertainty Estimate Approximation* . . . . .
13.12 Uncertainty Based upon Interval Statistics* . . . . . .
13.13 Problems . . . . . . . . . . . . . . . . . . . . . . . . . .
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14 Regression and Correlation
14.1 Chapter Overview . . . . . . . . .
14.2 Least-Squares Approach . . . . . .
14.3 Least-Squares Regression Analysis
14.4 Linear Analysis . . . . . . . . . .
14.5 Higher-Order Analysis* . . . . . .
14.6 Multi-Variable Linear Analysis* .
14.7 Determining the Appropriate Fit .
14.8 Regression Confidence Intervals .
14.9 Regression Parameters . . . . . .
14.10 Linear Correlation Analysis . . .
14.11 Signal Correlations in Time* . . .
14.11.1 Autocorrelation* . . . . . .
14.11.2 Cross-Correlation* . . . . .
14.12 Problems . . . . . . . . . . . . . .
Bibliography
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15 Units and Significant Figures
15.1 Chapter Overview . . . . . . . . . . . . . . .
15.2 English and Metric Systems . . . . . . . . .
15.3 Systems of Units . . . . . . . . . . . . . . . .
15.4 SI Standards . . . . . . . . . . . . . . . . . .
15.5 Technical English and SI Conversion Factors
15.5.1 Length . . . . . . . . . . . . . . . . . .
15.5.2 Area and Volume . . . . . . . . . . . .
15.5.3 Density . . . . . . . . . . . . . . . . .
15.5.4 Mass and Weight . . . . . . . . . . . .
15.5.5 Force . . . . . . . . . . . . . . . . . .
15.5.6 Work and Energy . . . . . . . . . . . .
15.5.7 Power . . . . . . . . . . . . . . . . . .
15.5.8 Light Radiation . . . . . . . . . . . . .
15.5.9 Temperature . . . . . . . . . . . . . .
15.5.10 Other Properties . . . . . . . . . . . .
15.6 Prefixes . . . . . . . . . . . . . . . . . . . . .
15.7 Significant Figures . . . . . . . . . . . . . . .
15.8 Problems . . . . . . . . . . . . . . . . . . . .
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16 Technical Communication
16.1 Chapter Overview . . . . . . . . . . .
16.2 Guidelines for Writing . . . . . . . . .
16.2.1 Writing in General . . . . . . .
16.2.2 Writing Technical Memoranda
16.2.3 Number and Unit Formats . .
16.2.4 Graphical Presentation . . . .
16.3 Technical Memo . . . . . . . . . . . .
16.4 Technical Report . . . . . . . . . . . .
16.5 Oral Technical Presentation . . . . .
16.6 Problems . . . . . . . . . . . . . . . .
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Bibliography
581
A Glossary
583
B Symbols
597
C Review Problem Answers
607
Index
609
Preface
This text covers the fundamental tools of experimentation that are currently
used by both engineers and scientists. These fundamentals relate to planning
an experiment, identifying measurement system components, assessing measurement system component performance, setting signal sampling conditions,
analyzing experimental results, and reporting experimental results. Historical
perspectives also are provided.
This is the third edition of Measurement and Data Analysis for Engineering and Science. The first edition was published in 2005 by McGrawHill. Since then, the text has been adopted by more and more universities and
colleges within the U.S. and abroad. New features include the following:
• A new chapter order reflects a logical sequence of topics in experimentation, from the planning of an experiment to the reporting of the experimental results. This has been found to be the most effective approach
to learn the subject matter.
• Sections that typically are not covered in an introductory undergraduate
course on experimentation are denoted by asterisks. The text including
all sections can be used in an upper-level undergraduate or introductory
graduate course on experimentation.
• A new chapter (Chapter 4) on sensors and transducers has been added.
This chapter follows the unique approach of presenting sensors according to their physical basis, starting from their fundamental principles
and leading to their input/output equations. Approximately 50 different sensors commonly used in engineering are described.
• New topics have been added on (a) smart measurement systems, including the Arduinor microcontroller and its use in the wireless transmission
of data, (b) MATLAB Simulinkr programming for microcontrollers, (c)
the rejection of data outliers, (d) light radiation, (e) calibrations of sensors, (f) the comparison of several first-order sensor responses, (g) the
voltage divider, (h) how to determine an appropriate sample period, and
(i) a plan for a successful experiment.
• Uncertainty analysis is presented in two separate chapters (Chapters 7
and 13). Chapter 7 covers basic uncertainty analysis as applied to the
design of an experiment. The more extensive uncertainty analysis that
has been adopted internationally is given in Chapter 13.
xi
xii
• More new problems have been added. There are now more than 100
solved example problems presented in the text and more than 400
homework problems. The latter problems are presented as either shortanswer review problems or more-extended homework problems. A Problem Topic Summary is included in each chapter immediately before chapter review and homework problems to reinforce a particular subject.
• Over seventy-five MATLABr Sidebars have been included. These
demonstrate the use of MATLAB in the analysis of experimental data
and the presentation of experimental results. MATLAB Simulinkr is
used to illustrate how construct Arduinor codes. Accompanying MATLAB M-files, Arduino codes, and data files are provided on the text
website for download.
• The text is complemented by an extensive text website. Second-edition
chapter sections and appendices not in the third edition, codes, files,
and much more are available at the site.
Instructors who adopt this text for their course can receive the problem
solutions manual, a laboratory exercise solution manual, and recent slide presentations from Notre Dame’s course in Measurement and Data Analysis by
contacting the publisher.
Since the second edition, contributions were made by several Notre Dame
engineering students, primarily Brian Quinn, Adam Smith, and Jonathan
MacArt, by my most recent senior graduate teaching assistants, Chris Kelley
and Patrick Bowles, and by my colleagues Professor David Go, Professor Mihir Sen, and Dr. Edmundo Corona. Greg Brownell designed and built almost
all of the electronics used in the laboratory exercises. John Ott, Kevin Peters, and Leon Hluchota gladly assisted when needed. Professor Scott Sanders
(University of Wisconsin - Madison) and Professor Milivoje Kostic (Northern
Illinois University) provided valuable comments. Shashi Kumar gave superb
LATEX assistance whenever needed. Jonathan Plant, my editor for all three
editions, always encouraged and supported me.
Most importantly, each and every member of my family always has been
there to support me along the way. This extends from my wife, through my
children, to my grandsons. Gwynn, our Welsh springer spaniel, also is included.
She never left my side during writing episodes, resting faithfully on the study
floor next to my desk. All are happy to see the third edition completed!
Patrick F. Dunn, University of Notre Dame
Author Text Web Site: www.nd.edu/∼pdunn/www.text/measurements.html
Publisher Text Web Site: www.crcpress.com/product/isbn/9781466594968
Written while at the University of Notre Dame, Notre Dame, Indiana, the University of Notre Dame London Centre, London, England, and Delft University
of Technology, Delft, The Netherlands.
xiii
For product information about MATLAB and Simulink, contact:
The MathWorks, Inc.
3 Apple Hill Drive
Matick, MA 01760-2098 USA
Tel: 508-647-7000
Fax: 508-647-7001
E-mail: info@mathworks.com
Web: www.mathworks.com
Arduino is an open-source electronics prototyping platform based on flexible,
easy-to-use hardware and software. It’s intended for artists, designers, hobbyists and anyone interested in creating interactive objects or environments. For
product information see:
Web: http://arduino.cc/
Author
Patrick F. Dunn, Ph.D., P.E., is a professor of aerospace and mechanical
engineering at the University of Notre Dame, where he has been a faculty
member since 1985. Prior to 1985, he was a mechanical engineer at Argonne
National Laboratory from 1976 to 1985 and a postdoctoral fellow at Duke
University from 1974 to 1976. He earned his B.S., M.S., and Ph.D. degrees
in engineering from Purdue University (1970, 1971, and 1974). He graduated
from Abbot Pennings High School in 1966.
Professor Dunn is the author of over 160 scientific journal and refereed
symposia publications, mostly involving experimentation, and a professional
engineer in Indiana and Illinois. He is a Fellow of the American Society of
Mechanical Engineers and an Associate Fellow of the American Institute of
Aeronautics and Astronautics. He is the recipient of departmental, college,
and university teaching awards.
Professor Dunn’s scientific expertise is in fluid mechanics and microparticle behavior in flows. He is an experimentalist with over 45 years of laboratory experience. He is the author of the textbooks Measurement and
Data Analysis for Engineering and Science (first edition by McGrawHill, 2005; second edition by Taylor & Francis / CRC Press, 2010; this third
edition by Taylor & Francis / CRC Press), Fundamentals of Sensors for
Engineering and Science (first edition by Taylor & Francis / CRC Press,
2011) and Uncertainty Analysis for Forensic Science with R.M. Brach
(first and second editions by Lawyers & Judges Publishing Company, 2004
and 2009).
xv
1
Fundamentals of Experimentation
CONTENTS
1.1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1
... the ultimate arbiter of truth is experiment, not the comfort one derives
from a priori beliefs, nor the beauty or elegance one ascribes to one’s
theoretical models.
R
Lawrence M. Krauss. 2012. A Universe from Nothing. New York: Free Press.
Measure what can be measured and make measurable what cannot be
measured.
R
Galileo Galilei, c.1600.
Chance favours only the prepared mind.
Louis Pasteur, 1879.
1.1
Introduction
This is a text about the fundamentals of experimentation and its current
methods. It progressively presents the phases of the process of experimentation. These six phases, from planning an experiment to reporting experimental
results, are shown in Figure 1.1. The phases, along with associated practical
questions that are answered in this text, are as follows:
1
2
Measurement and Data Analysis for Engineering and Science
Planning an Experiment
Identifying Measurement
System Components
Assessing Measurement
System Performance
Setting Signal
Sampling Conditions
Analyzing Experimental Results
Reporting Experimental Results
FIGURE 1.1
The phases of experimentation.
1. Planning an Experiment (Chapter 2):
• What is the role of experimentation in science and engineering?
• What exactly defines an experiment?
• How are experiments classified?
• What approach should be taken in an experiment?
• What methods can be used to efficiently plan and conduct an experiment?
2. Identifying Measurement System Components (Chapters 3, 4, and 5):
• What basic elements comprise a measurement system?
• What elementary electronics are used in measurement systems?
• How can the physical variables of interest be sensed?
• What electronic conditioning of the sensed signal is required?
• What specific components are needed for a system?
• What are some examples of current measurement systems?
Fundamentals of Experimentation
3
3. Assessing Measurement System Performance (Chapters 6 and 7):
• How is the measurement system output related to the input physical stimulus?
• How are measurement system components calibrated?
• What characterizes the static and dynamic responses of the components?
• What uncertainties arise using measurement system components?
4. Setting Signal Sampling Conditions (Chapters 8, 9, and 10):
• How are signals classified?
• How does their classification affect measurement conditions?
• How much data should be acquired?
• What is the required sampling rate?
• How do sampling conditions affect the fidelity of the results?
5. Analyzing Experimental Results (Chapters 11, 12, 13, and 14):
• What analytical techniques are used to express experimental results?
• What statistics are required?
• What statistical confidence is associated with the data?
• How are the data correlated?
• How do they compare with theory and/or other experiments?
• What are the overall uncertainties in the results?
• When is it appropriate to reject some data?
6. Reporting Experimental Results (Chapters 15 and 16):
• What are the proper number, unit, and uncertainty expressions?
• What are the appropriate formats for the written document?
• What elements are needed to communicate effectively in writing?
• What elements are needed to communicate effectively in an oral
presentation?
References
2 Chapter 2: Experiments
[1] Park, R.L. 2000. Voodoo Science: The Road from
Foolishness to Fraud. New York: Oxford University Press.
[2] Coleman, H.W. and W. G. Steele. 1999. Experimentation
and Uncertainty Analysis for Engineers. 2nd ed. New York:
Wiley Interscience.
[3] Gregory, A. 2001. Eureka! The Birth of Science.
Duxford, Cambridge, UK: Icon Books.
[4] Harre´, R. 1984. Great Scientific Experiments. New
York: Oxford University Press.
[5] Boorstin, D.J. 1985. The Discoverers. New York: Vintage
Books.
[6] Gale, G. 1979. The Theory of Science. New York:
McGraw-Hill.
[7] Medawar, P. 1979. Advice to a Young Scientist. New
York: Harper and Row.
[8] Feynman, R. 1994. The Character of Physical Law. Modern
Library Edition. New York: Random House.
[9] Hayter, A.J. 2002. Probability and Statistics for
Engineers and Scientists. 2nd ed. Pacific Grove:
Duxbury/Thomson Learning.
[10] Hald, A. 1952. Statistical Theory with Engineering
Applications. New York: John Wiley and Sons.
[11] Fisher, R.A. 1935. The Design of Experiments.
Edinburgh: Oliver and Boyd.
[12] Barrentine, L.B. 1999. Introduction to Design of
Experiments: A Simplified Approach. Milwaukee: ASQ Quality
Press.
[13] Gunst, R.F. and R.L. Mason. 1991. How to Construct
Fractional Factorial Experiments. Milwaukee: ASQ Quality
Press.
[14] Montgomery, D.C. 2000. Design and Analysis of
Experiments. 5th ed. New York: John Wiley and Sons.
[15] Brach, R. M. and P. F. Dunn. 2009. Uncertainty
Analysis for Forensic Science. 2nd ed. Tucson: Lawyers &
Judges Publishing Company, Inc. 27 Science
[16] Guttman, I., S. Wilks, and J. Hunter. 1982.
Introductory Engineering Statistics. 3rd ed. New York: John
Wiley and Sons.
[17] Montgomery, D. C. and G.C. Runger. 1994. Applied
Statistics and Probability for Engineers. New York: John
Wiley and Sons.
3 Chapter 3: Fundamental Electronics
[1] Fara, P. 2002. An Entertainment for Angels: Electricity
in the Enlightenment. Duxford: Icon Books.
[2] Horowitz, P. and W. Hill. 1989. The Art of Electronics.
2nd ed. Cambridge: Cambridge University Press.
[3] Oppenheim, A.V. and A.S. Willsky. 1997. Signals and
Systems. 2nd ed. New York: Prentice Hall.
[4] Alciatore, D.G. and Histand, M.B. 2003. Introduction to
Mechatronics and Measurement Systems. 2nd ed. New York:
McGraw-Hill.
[5] Dunn, P.F. and W.A. Wilson. 1977. Development of the
Single Microelectrode Current and Voltage Clamp for Central
Nervous System Neurons. Electroencephalography and Clinical
Neurophysiology 43: 752-756. 71
4 Chapter 4: Measurement Systems: Sensors
and Transducers
[1] Kovacs, G.T.A. 1998. Micromachined Transducers
Sourcebook. New York: McGraw-Hill.
[2] Barrett, K.E., S.M. Barman, S. Boitano, and H.L.
Brooks. 2010. Ganong’s Review of Medical Physiology. 23rd
ed. New York: McGraw-Hill, Inc.
[3] Dunn, P.F. 2011. Fundamentals of Sensors for
Engineering and Science. Boca Raton: CRC Press: Taylor and
Francis Group.
[4] Bentley, J.P. 2005. Principles of Measurement Systems.
4th ed. New York: Pearson Prentice Hall.
[5] Alciatore, D.G. and Histand, M.B. 2003. Introduction to
Mechatronics and Measurement Systems. 2nd ed. New York:
McGraw-Hill.
[6] Lykoudis, P.S. and Dunn, P.F. 1973.
Magneto-Fluid-Mechanic Heat Transfer from Hot-Film Probes.
Int. J. Heat and Mass Trans.. 16, 14391452.
[7] Vetelino, J. and Reghu, A. 2011. Introduction to
Sensors. New York: CRC Press.
[8] Kim, O.V. and Dunn, P.F. 2010. Real-Time Direct Charge
Measurements of Microdroplets and Comparison with Indirect
Methods. Aerosol Sci. & Tech., 44, 292-301.
[9] Hsu, T-R. 2002. MEMS & Microsystems: Design and
Manufacture. New York: McGraw-Hill.
[10] Dunn, P.F., Brach, R.M., and Caylor, M.J. 1995.
Experiments on the Low Velocity Impact of Microspheres with
Planar Surfaces. Aerosol Sci. and Tech.. 23, 80-95.
[11] Dunn, P.F., Thomas, F.O., Davis, M.P. and Dorofeeva,
I.E. 2010. Experimental Characterization of Aviation-Fuel
Cavitation. Phys. Fluids, 22, 117102-117119.
[12] Incropera, F.P. and De Witt, D.P. 1985. Fundamentals
of Heat and Mass Transfer. 2nd. ed. New York: John Wiley
and Sons.
[13] van de Hulst, H.C. 1981. Light Scattering by Small
Particles. New York: Dover Publications. 143 Science
[14] National Institute of Standards and Technology.
http://www.nist.gov/index.html
[15] Horowitz, P. and Hill, W. 1989. The Art of
Electronics. 2nd ed. Cambridge: Cambridge University Press.
[16] Madou, M. 1997. Fundamentals of Microfabrication. New
York: CRC Press.
5 Chapter 5: Measurement Systems: Other
Components
[1] Horowitz, P. and W. Hill, W. 1989. The Art of
Electronics. 2nd ed. Cambridge: Cambridge University Press.
[2] Oppenheim, A.V. and A.S. Willsky. 1997. Signals and
Systems. 2nd ed. New York: Prentice Hall.
[3] Wheeler, A.J. and A.R. Ganji. 2010. Introduction to
Engineering Experimentation. 3rd ed. New York: Prentice
Hall.
[4] Arduino. http://arduino.cc/en/Main/HomePage
[5] The National Association for Amateur Radio.
http://www.arrl.org/getting-licensed
[6] Szarek, T.S. 2003. On The Use Of Microcontrollers For
Data Acquisition In An Introductory Measurements Course.
M.S. Thesis. Department of Aerospace and Mechanical
Engineering. Indiana: University of Notre Dame. 195
6 Chapter 6: Measurement Systems:
Calibration and Response
[1] Boyce, W.E. and R.C. Di Prima. 1997. Elementary
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