29697 - Mechanical and Thermal Measurements and Testing T

Learning outcomes

The student acquires knowledge in the field of measurement procedures, uncertainty evaluation and signal processing; moreover he learns testing procedures and operations on a machines and systems.

Course contents

1. Metrology
2. Probability
3. Statistics
4. Statistical tests and Testing Hypotheses
5. Automatic measurement systems
6. Metrological characterization of the measuring instruments
7. Guide to the expression of uncertainty in measurement (GUM): Assessment methods of the uncertainties of Type A and Type B
8. Supplement 1 to the GUM - Monte Carlo Method
9. Analysis of signals in the time domain: causal and non-causal signals; Dirac impulse; sampling of a signal; periodic repetition of a signal; periodic exponential; amplitude modulation of a signal; discrete-time signals; RMS values, Powers, Energies
10. Analysis of systems in the time domain: analysis of LTI systems; causal discrete-time systems; LTI discrete systems
11. System analysis in the frequency domain: Fourier Transform; Parseval Theorem; Fourier Transform of the Dirac impulse; Fourier Series; Fourier Series of a periodic signal; Sampling of a periodic signal; Leakage effect; Sampling Theorem and Aliasing effect; Discrete-Time Fourier Transform; Discrete Fourier Series
12. Input conditioning circuits of measuring instruments: the Op-Amp
13. Sensors and Transducers used for mechanical applications (background)

Readings/Bibliography

Educational material provided by the teacher

Teaching methods

Lectures by using slides and electronic board; laboratory experiments.

Assessment methods

Oral examination

Teaching tools

Laboratory practice with the use of Octaves to analyze measurement uncertainties and to anallize acquired signals in both the time and frequency domains.

Office hours

See the website of Lorenzo Peretto