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.
Table of Contents:
Fundamentals of Experimentation
Introduction
Experiments
Chapter Overview
Experimental Approach
Role of Experiments
The Experiment
Classification of Experiments
Plan for Successful Experimentation
Hypothesis Testing*
Design of Experiments*
Factorial Design*
Problems
Bibliography
Fundamental Electronics
Chapter Overview
Concepts and Definitions
Circuit Elements
RLC Combinations
Elementary DC Circuit Analysis
Elementary AC Circuit Analysis
Equivalent Circuits*
Meters*
Impedance Matching and Loading Error*
Electrical Noise*
Problems
Bibliography
Measurement Systems: Sensors and Transducers
Chapter Overview
Measurement System Overview
Sensor Domains
Sensor Characteristics
Physical Principles of Sensors
Electric
Piezoelectric
Fluid Mechanic
Optic
Photoelastic
Thermoelectric
Electrochemical
Sensor Scaling*
Problems
Bibliography
Measurement Systems: Other Components
Chapter Overview
Signal Conditioning, Processing, and Recording
Amplifiers
Filters
Analog-to-Digital Converters
Smart Measurement Systems
Other Example Measurement Systems
Problems
Bibliography
Measurement Systems: Calibration and Response
Chapter Overview
Static Response Characterization by Calibration
Dynamic Response Characterization
Zero-Order System Dynamic Response
First-Order System Dynamic Response
Second-Order System Dynamic Response
Measurement System Dynamic Response
Problems
Bibliography
Measurement Systems: Design-Stage Uncertainty
Chapter Overview
Design-Stage Uncertainty Analysis
Design-Stage Uncertainty Estimate of a Measurand
Design-Stage Uncertainty Estimate of a Result
Problems
Bibliography
Signal Characteristics
Chapter Overview
Signal Classification
Signal Variables
Signal Statistical Parameters
Problems
Bibliography
The Fourier Transform
Chapter Overview
Fourier Series of a Periodic Signal
Complex Numbers and Waves
Exponential Fourier Series
Spectral Representations
Continuous Fourier Transform
Continuous Fourier Transform Properties*
Discrete Fourier Transform
Fast Fourier Transform
Problems
Bibliography
Digital Signal Analysis
Chapter Overview
Digital Sampling
Digital Sampling Errors
Windowing*
Determining a Sample Period
Problems
Bibliography
Probability
Chapter Overview
Relation to Measurements
Basic Probability Concepts
Sample versus Population
Plotting Statistical Information
Probability Density Function
Various Probability Density Functions
Central Moments
Probability Distribution Function
Problems
Bibliography
Statistics
Chapter Overview
Normal Distribution
Normalized Variables
Student's t Distribution
Rejection of Data
Standard Deviation of the Means
Chi-Square Distribution
Pooling Samples*
Problems
Bibliography
Uncertainty Analysis
Chapter Overview
Modeling and Experimental Uncertainties
Probabilistic Basis of Uncertainty
Identifying Sources of Error
Systematic and Random Errors
Quantifying Systematic and Random Errors
Measurement Uncertainty Analysis
Uncertainty Analysis of a Multiple-Measurement Result
Uncertainty Analyses for Other Measurement Situations
Uncertainty Analysis Summary
Finite-Difference Uncertainties*
Uncertainty Based upon Interval Statistics*
Problems
Bibliography
Regression and Correlation
Chapter Overview
Least-Squares Approach
Least-Squares Regression Analysis
Linear Analysis
Higher-Order Analysis*
Multi-Variable Linear Analysis*
Determining the Appropriate Fit
Regression Confidence Intervals
Regression Parameters
Linear Correlation Analysis
Signal Correlations in Time*
Problems
Bibliography
Units and Significant Figures
Chapter Overview
English and Metric Systems
Systems of Units
SI Standards
Technical English and SI Conversion Factors
Prefixes
Significant Figures
Problems
Bibliography
Technical Communication
Chapter Overview
Guidelines for Writing
Technical Memo
Technical Report
Oral Technical Presentation
Problems
Bibliography
A Glossary
B Symbols
C Review Problem Answers
Index
About the Author :
Patrick F. Dunn, Ph.D., P.E., is a professor of aerospace and mechanical engineering at the University of Notre Dame. He earned his B.S., M.S., and Ph.D. degrees in engineering from Purdue University (1970, 1971, and 1974). Professor Dunn is the author of over 160 scientific journal and refereed symposia publications, and various textbooks including Measurement and Data Analysis for Engineering and Science Second Edition by Taylor & Francis / CRC Press, 2010; Measurement and Data Analysis for Engineering and Science, Third Edition by Taylor & Francis / CRC Press; and Fundamentals of Sensors for Engineering and Science First Edition by Taylor & Francis / CRC Press, 2011.
