Measurement and Instrumentation

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 Appendix 2: Thévenin's Theorem Appendix 3: Thermocouple Tables Appendix 4: Using mathematical tables

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.