Measurement and Instrumentation: Theory and Application

Author:   Alan S. Morris (Department of Automatic Control and Systems Engineering, University of Sheffield, UK) ,  Reza Langari (Professor, Mechanical Engineering Department, Texas A&M University, College Station, TX, USA)
Publisher:   Elsevier Science Publishing Co Inc
Edition:   3rd edition
ISBN:  

9780128171417


Pages:   736
Publication Date:   04 December 2020
Format:   Paperback
Availability:   In stock   Availability explained
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Measurement and Instrumentation: Theory and Application


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Overview

Measurement and Instrumentation: Theory and Application, Third Edition, introduces undergraduate engineering students to measurement principles and the range of sensors and instruments used for measuring physical variables. Providing the most balanced coverage of measurement theory/technologies and instrumentation, this clearly and comprehensively written text arms students and recently graduated engineers with the knowledge and tools to design and build measurement systems for virtually any engineering application.

Full Product Details

Author:   Alan S. Morris (Department of Automatic Control and Systems Engineering, University of Sheffield, UK) ,  Reza Langari (Professor, Mechanical Engineering Department, Texas A&M University, College Station, TX, USA)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Edition:   3rd edition
Weight:   1.040kg
ISBN:  

9780128171417


ISBN 10:   0128171413
Pages:   736
Publication Date:   04 December 2020
Audience:   College/higher education ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

1. Fundamentals of Measurement Systems 2. Instrument Types and Performance Characteristics 3. Measurement Uncertainty 4. Statistical Analysis of Measurements Subject to Random Errors 5. Calibration of Measuring Sensors and Instruments 6. Data Acquisition and Signal Processing 7. Variable Conversion 8. Measurement Signal Transmission 9. Display, Recording, and Presentation of Measurement Data 10. Intelligent Devices 11. Measurement Reliability and Safety Systems 12. Data Acquisition with LabVIEW 13. Sensor Technologies 14. Temperature Measurement 15. Pressure Measurement 16. Flow Measurement 17. Level Measurement 18. Mass, Force, and Torque Measurement 19. Translational Motion, Vibration, and Shock Measurement 20. Rotational Motion Transducers 21. Summary of Other Measurements Appendix 1. Imperial-Metric-SI Conversion Tables 2. Thévenin’s Theorem 3. Thermocouple Tables 4. Using Mathematical Tables

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Author Information

Dr. Morris Retired senior lecturer in the Department of Automatic Control & Systems Engineering at the University of Sheffield. He has taught the undergraduate course in measurement and instrumentation for nearly 30 years, as well as undergraduate courses in robot technology, engineering design and laboratory skills, and graduate level courses in robot control, modeling and measurement for quality assurance. He is the author of eight books and more than 130 research papers in the fields of measurement and instrumentation and robot control. Dr. Langari is a professor in the Department of Mechanical Engineering at Texas A&M University and head of the Department of Engineering Technology and Industrial Distribution. He earned bachelor's, master's and doctoral degrees from the University of California, Berkeley. He has held research positions at NASA Ames Research Center, Rockwell International Science Center, United Technologies Research Center, as well as the U.S. Air Force Research Laboratory. Langari's expertise is in the area of computational intelligence with application to mechatronic systems and industrial automation. He has played a significant role in the development of theoretical foundations of fuzzy logic control and its applications to problems in mechanical engineering. His work on stability of fuzzy control systems is widely recognized as pioneering the use of nonlinear systems analysis techniques to fuzzy logic.

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