Measurement and Instrumentation
Theory and Application
- 2nd Edition - September 8, 2015
- Authors: Alan S. Morris, Reza Langari
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 0 0 8 8 4 - 3
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 0 1 1 3 2 - 4
Measurement and Instrumentation: Theory and Application, Second Edition, introduces undergraduate engineering students to measurement principles and the range of sensors and instr… Read more
Measurement and Instrumentation: Theory and Application, Second Edition,
introduces undergraduate engineering students to measurement principles and the range of sensors and instruments used for measuring physical variables.This updated edition provides new coverage of the latest developments in measurement technologies, including smart sensors, intelligent instruments, microsensors, digital recorders, displays, and interfaces, also featuring chapters on data acquisition and signal processing with LabVIEW from Dr. Reza Langari.
Written clearly and comprehensively, this text provides students and recently graduated engineers with the knowledge and tools to design and build measurement systems for virtually any engineering application.
- Provides early coverage of measurement system design to facilitate a better framework for understanding the importance of studying measurement and instrumentation
- Covers the latest developments in measurement technologies, including smart sensors, intelligent instruments, microsensors, digital recorders, displays, and interfaces
- Includes significant material on data acquisition and signal processing with LabVIEW
- Extensive coverage of measurement uncertainty aids students’ ability to determine the accuracy of instruments and measurement systems
Junior and senior undergraduate engineering students taking measurement and instrumentation courses primarily in mechanical and aerospace engineering departments
- Preface
- Acknowledgement
- Chapter 1. Fundamentals of Measurement Systems
- 1.1. Introduction
- 1.2. Measurement Units
- 1.3. Measurement System Design
- 1.4. Measurement System Applications
- 1.5. Summary
- 1.6. Problems
- Chapter 2. Instrument Types and Performance Characteristics
- 2.1. Introduction
- 2.2. Review of Instrument Types
- 2.3. Static Characteristics of Instruments
- 2.4. Dynamic Characteristics of Instruments
- 2.5. Necessity for Calibration
- 2.6. Summary
- 2.7. Problems
- Chapter 3. Measurement Uncertainty
- 3.1. Introduction
- 3.2. Sources of Systematic Error
- 3.3. Reduction of Systematic Errors
- 3.4. Quantification of Systematic Errors
- 3.5. Sources and Treatment of Random Errors
- 3.6. Induced Measurement Noise
- 3.7. Techniques for Reducing Induced Measurement Noise
- 3.8. Summary
- 3.9. Problems
- Chapter 4. Statistical Analysis of Measurements Subject to Random Errors
- 4.1. Introduction
- 4.2. Mean and Median Values
- 4.3. Standard Deviation and Variance
- 4.4. Graphical Data Analysis Techniques—Frequency Distributions
- 4.5. Gaussian (Normal) Distribution
- 4.6. Standard Gaussian Tables (z-Distribution)
- 4.7. Standard Error of the Mean
- 4.8. Estimation of Random Error in a Single Measurement
- 4.9. Distribution of Manufacturing Tolerances
- 4.10. Chi-Squared (χ2) Distribution
- 4.11. Goodness of Fit to a Gaussian Distribution
- 4.12. Rogue Data Points (Data Outliers)
- 4.13. Student t-Distribution
- 4.14. Aggregation of Measurement System Errors
- 4.15. Summary
- 4.16. Problems
- Chapter 5. Calibration of Measuring Sensors and Instruments
- 5.1. Introduction
- 5.2. Principles of Calibration
- 5.3. Control of Calibration Environment
- 5.4. Calibration Chain and Traceability
- 5.5. Calibration Records
- 5.6. Summary
- 5.7. Problems
- Chapter 6. Data Acquisition and Signal Processing
- 6.1. Introduction
- 6.2. Preliminary Definitions
- 6.3. Sensor Signal Characteristics
- 6.4. Aliasing
- 6.5. Quantization
- 6.6. Analog Signal Processing
- 6.7. Passive Filters
- 6.8. Active Filters Using Op-Amps
- 6.9. Signal Amplification
- 6.10. Digital Filters
- 6.11. Summary
- 6.12. Exercises
- 6.13. Appendix
- Chapter 7. Variable Conversion
- 7.1. Introduction
- 7.2. Bridge Circuits
- 7.3. Resistance Measurement
- 7.4. Inductance Measurement
- 7.5. Capacitance Measurement
- 7.6. Current Measurement
- 7.7. Frequency Measurement
- 7.8. Phase Measurement
- 7.9. Summary
- 7.10. Problems
- Chapter 8. Measurement Signal Transmission
- 8.1. Introduction
- 8.2. Electrical Transmission
- 8.3. Pneumatic Transmission
- 8.4. Fiber Optic Transmission
- 8.5. Optical Wireless Telemetry (Open Air Path Transmission)
- 8.6. Radio Telemetry (Radio Wireless Transmission)
- 8.7. Digital Transmission Protocols
- 8.8. Summary
- 8.9. Problems
- Chapter 9. Display, Recording, and Presentation of Measurement Data
- 9.1. Introduction
- 9.2. Display of Measurement Signals
- 9.3. Recording of Measurement Data
- 9.4. Presentation of Data
- 9.5. Summary
- 9.6. Problems
- Chapter 10. Intelligent Devices
- 10.1. Introduction
- 10.2. Principles of Digital Computation
- 10.3. Intelligent Devices
- 10.4. Communication with Intelligent Devices
- 10.5. Summary
- 10.6. Problems
- Chapter 11. Measurement Reliability and Safety Systems
- 11.1. Introduction
- 11.2. Reliability
- 11.3. Safety Systems
- 11.4. Summary
- 11.5. Problems
- Chapter 12. Data Acquisition with LabVIEW
- 12.1. Introduction
- 12.2. Computer-Based DAQ
- 12.3. Acquisition of Data
- 12.4. National Instruments LabVIEW
- 12.5. Introduction to Graphical Programming in LabVIEW
- 12.6. Elements of the Tools Palette
- 12.7. Logic Operations in LabVIEW
- 12.8. Loops in LabVIEW
- 12.9. Case Structure in LabVIEW
- 12.10. DAQ Using LabVIEW
- 12.11. LabVIEW Implementation of Digital Filters
- 12.12. Summary
- 12.13. Exercises
- Chapter 13. Sensor Technologies
- 13.1. Introduction
- 13.2. Capacitive Sensors
- 13.3. Resistive Sensors
- 13.4. Magnetic Sensors
- 13.5. Hall Effect Sensors
- 13.6. Piezoelectric Transducers
- 13.7. Strain Gauges
- 13.8. Piezoresistive Sensors
- 13.9. Optical Sensors
- 13.10. Ultrasonic Transducers
- 13.11. Nuclear Sensors
- 13.12. Microsensors (MEMS Sensors)
- 13.13. Nanosensors (NEMS Sensors)
- 13.14. Summary
- 13.15. Problems
- Chapter 14. Temperature Measurement
- 14.1. Introduction
- 14.2. Thermoelectric Effect Sensors (Thermocouples)
- 14.3. Varying Resistance Devices
- 14.4. Semiconductor Devices
- 14.5. Radiation Thermometers
- 14.6. Thermography (Thermal Imaging)
- 14.7. Thermal Expansion Methods
- 14.8. Fiber-Optic Temperature Sensors
- 14.9. Color Indicators
- 14.10. Change of State of Materials
- 14.11. Intelligent Temperature-Measuring Instruments
- 14.12. MEMS Temperature Sensors
- 14.13. Choice between Temperature Transducers
- 14.14. Calibration of Temperature Transducers
- 14.15. Summary
- 14.16. Problems
- Chapter 15. Pressure Measurement
- 15.1. Introduction
- 15.2. Diaphragms
- 15.3. Capacitive Pressure Sensor
- 15.4. Fiber-Optic Pressure Sensors
- 15.5. Bellows
- 15.6. Bourdon Tube
- 15.7. Manometers
- 15.8. Resonant Wire Devices
- 15.9. Electronic Pressure Gauges
- 15.10. MEMS Pressure Sensors
- 15.11. Special Measurement Devices for Low Pressures (Vacuum Pressures)
- 15.12. High-Pressure Measurement (Greater than 7000 bar)
- 15.13. Intelligent Pressure Transducers
- 15.14. Differential Pressure-Measuring Devices
- 15.15. Selection of Pressure Sensors
- 15.16. Calibration of Pressure Sensors
- 15.17. Summary
- 15.18. Problems
- Chapter 16. Flow Measurement
- 16.1. Introduction
- 16.2. Mass Flow Rate
- 16.3. Volume Flow Rate
- 16.4. Intelligent Flowmeters
- 16.5. Choice between Flowmeters for Particular Applications
- 16.6. Calibration of Flowmeters
- 16.7. Summary
- 16.8. Problems
- Chapter 17. Level Measurement
- 17.1. Introduction
- 17.2. Dipsticks
- 17.3. Float Systems
- 17.4. Pressure-Measuring Devices (Hydrostatic Systems)
- 17.5. Capacitive Devices
- 17.6. Ultrasonic Level Gauge
- 17.7. Radar (Microwave) Sensors
- 17.8. Nucleonic (or Radiometric) Sensors
- 17.9. Vibrating Level Sensor
- 17.10. Intelligent Level-Measuring Instruments
- 17.11. Choice between Different Level Sensors
- 17.12. Calibration of Level Sensors
- 17.13. Summary
- 17.14. Problems
- Chapter 18. Mass, Force, and Torque Measurement
- 18.1. Introduction
- 18.2. Mass (Weight) Measurement
- 18.3. Force Measurement
- 18.4. Torque Measurement
- 18.5. Calibration of Mass-, Force-, and Torque-Measuring Sensors
- 18.6. Summary
- 18.7. Problems
- Chapter 19. Translational Motion, Vibration, and Shock Measurement
- 19.1. Introduction
- 19.2. Displacement
- 19.3. Velocity
- 19.4. Acceleration
- 19.5. Vibration
- 19.6. Shock
- 19.7. Summary
- 19.8. Problems
- Chapter 20. Rotational Motion Transducers
- 20.1. Introduction
- 20.2. Rotational Displacement
- 20.3. Rotational Velocity
- 20.4. Rotational Acceleration
- 20.5. Summary
- 20.6. Problems
- Chapter 21. Summary of Other Measurements
- 21.1. Introduction
- 21.2. Dimension Measurement
- 21.3. Angle Measurement
- 21.4. Surface Flatness Measurement
- 21.5. Volume Measurement
- 21.6. Viscosity Measurement
- 21.7. Moisture Measurement
- 21.8. Sound Measurement
- 21.9. pH Measurement
- 21.10. Gas Sensing and Analysis
- 21.11. Summary
- 21.12. Problems
- Appendix 1. Imperial—Metric—SI Conversion Tables
- Appendix 2. The´venin’s Theorem
- Appendix 3. Thermocouple Tables
- Appendix 4. Using Mathematical Tables
- Index
- Edition: 2
- Published: September 8, 2015
- Language: English
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Alan S. Morris
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.
Affiliations and expertise
Department of Automatic Control and Systems Engineering, University of Sheffield, UKRL
Reza Langari
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.
Affiliations and expertise
Professor, Mechanical Engineering Department, Texas A&M University, College Station, TX, USARead Measurement and Instrumentation on ScienceDirect