99544 - Measurement and Instrumentation for Industrial and Energy Engineering M

Learning outcomes

At the end of the course, the student possesses the basic knowledge for understanding the working principle and the specification of the measurement systems used for industrial and energy applications as well as for designing simple measurement systems. In particular, the student: - knows the basics of metrology; - knows the fundamentals of signal processing theory as well as of digital signal processing; - knows the main instrumentation used for industrial and energy applications, even for billing purposes, from the point of view of both operating principle and international Standard requirements

Course contents

1. Fundamentals of Metrology

• Physical quantities and units of measurement
• International System of Units (SI)

2. Probability and Statistics for Measurements

• Random variables
• Probability distributions
• Mean, variance, and standard deviation
• Sampling
• Parameter estimation
• Statistical analysis of experimental data

3. Measurement Uncertainty

• Guide to the Expression of Uncertainty in Measurement (GUM)
• Type A and Type B uncertainty evaluation
• Standard and combined uncertainty
• Uncertainty propagation
• Confidence intervals
• Applications to energy systems
• Calibration and metrological traceability
• Accuracy, precision, repeatability, and reproducibility
• Measurement errors
• Measurement chain

4. Sensors and Transducers

• Transduction principles
• Static and dynamic characteristics
• Instrument transformers
• Voltage and current sensors
• Temperature sensors
• Pressure sensors
• Selection criteria

5. Signal Analysis and Processing

• Discrete-time signals and systems
• Continuous-time signals and systems
• Linear time-invariant (LTI) systems
• Filtering
• Fourier series and Fourier transform
• Spectral analysis
• Sampling

6. Analog-to-Digital Conversion

• Sampling
• Nyquist–Shannon sampling theorem
• Quantization
• Analog-to-digital converters (ADCs)
• Conversion errors
• Data acquisition systems

7. Laboratory Activities and Practical Applications

• Application of the GUM framework to a gas turbine case study
• Power and energy measurements
• Fourier-based signal analysis
• Remote instrumentation control
• Use of microcontrollers for sensor data acquisition and monitoring systems

Readings/Bibliography

Teacher's slides and lectures are sufficient material. 

Every chapter includes a bibliography that the student can use to deepen concepts of interest.

Teaching methods

Lectures consisting in:

• projection of slides
• insights on the blackboard
• Laboratory exercises

Assessment methods

Oral test

Teaching tools

Teaching materials is available on virtuale.unibo.it

Office hours

See the website of Alessandro Mingotti