Measurement and Data Analysis for Engineering and Science (4th Ed.)
Auteurs : F Dunn Patrick, P. Davis Michael
Measurement and Data Analysis for Engineering and Science, Fourth Edition, provides up-to-date coverage of experimentation methods in science and engineering. This edition adds five new "concept chapters" to introduce major areas of experimentation generally before the topics are treated in detail, to make the text more accessible for undergraduate students. These feature Measurement System Components, Assessing Measurement System Performance, Setting Signal Sampling Conditions, Analyzing Experimental Results, and Reporting Experimental Results. More practical examples, case studies, and a variety of homework problems have been added; and MATLAB and Simulink resources have been updated.
Fundamentals of Experimentation. Experiments. Concept Chapter: Measurement System Components. Fundamental Electronics. Measurement Systems: Sensors and Transducers. Mesurement Systems: Other Components. Concept Chapter: Assessing Measurement Systems Performance. Measurement Systems: Calibration and Response. Measurement Systems: Design-Stage Uncertainty. Concept Chapter: Setting Signal Sampling Conditions. Signal Characteristics. The Fourier Transform. Digital Signal Analysis. Concept Chapter: Analizing Experimental Results. Probability. Statistics. Uncertainty Analysis. Regression and Correlation. Concept Chapter: Units and Significant Figures. Technical Communication. Glossary. Symbols. Review Problem Answers. Index.
Patrick F. Dunn, Ph.D., P.E., is a retired 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. Michael P. Davis (Ph.D., University of Notre Dame) has extensive experience in industry as a practicing engineer, in both the shipbuilding and aerospace fields. As a senior machinery engineer with Bath Iron Works, Dr. Davis was responsible for the design and integration of propulsion systems (including main engines, shafting, and propellers) for the newest class of U.S. Navy destroyers. While at Pratt and Whitney, he worked as a controls engineer for a new generation of commercial aircraft engines. He currently teaches in the Mechanical Engineering department at the University of Southern Maine.
Date de parution : 12-2017
17.8x25.4 cm
Thèmes de Measurement and Data Analysis for Engineering and Science :
Mots-clés :
MATLAB Command; Measurement; Strain Gage; Hypothesis testing; Pitot Static Tube; Design of experiments; Amplitude Frequency Spectrum; Factorial design; Wheatstone Bridge; Sensors; Probability Density Function; Sensor domains; Magnitude Ratio; Microcontrollers; Output Voltage; Design-stage uncertainty models; Voltage Divider; Signal variables; Data Set; Fourier series; Follow; Spectral representation; Ordinary Differential Equations; Continuous Fourier series; Loading Error; Digital sampling; Precision Interval; Windowing; RLC Circuit; Probability; Normal Probability Density Function; Central moments; Percent Uncertainty; Binomial distribution; Pedal Cadence; Poison distribution; Time History Record; Probability distribution function; Input Signal; Normal distribution; DFT; Normalized variables; FSO; Chi-Square distribution; Operational Amplifier; Uncertainty analysis; Cadence Sensor; Finite-difference uncertainties; Heart Rate Response; Interval statistics; Regression; Correlation; Report writing; Patrick F; Dunn; Michael P; Davis