Dunn | Measurement and Data Analysis for Engineering and Science, Third Edition | Buch | 978-1-4665-9496-8 | www.sack.de

Buch, Englisch, 632 Seiten, Format (B × H): 163 mm x 240 mm, Gewicht: 1023 g

Dunn

Measurement and Data Analysis for Engineering and Science, Third Edition


3rd Revised Auflage
ISBN: 978-1-4665-9496-8
Verlag: Taylor & Francis Ltd (Sales)

Buch, Englisch, 632 Seiten, Format (B × H): 163 mm x 240 mm, Gewicht: 1023 g

ISBN: 978-1-4665-9496-8
Verlag: Taylor & Francis Ltd (Sales)


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.

Dunn Measurement and Data Analysis for Engineering and Science, Third Edition jetzt bestellen!

Zielgruppe


Mechanical and aerospace engineering students, engineers and researchers wanting a readable, up-to-date survey of measurement techniques.


Autoren/Hrsg.


Weitere Infos & Material


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


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.



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