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. Key Features. • 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 Readership.

Chapter 1 Fundamentals of Measurement Systems.1 1.1 Introduction. Measurement and Instrumentation: Theory and Application.

• 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. Enfermagem Pediatrica Wong Pdf. 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.