Synthetic program: il corso si propone come obiettivi fondamentali quelli di fornire i complementi sulle tecniche di misura di grandezze meccaniche e termiche e di rendere lo studente in grado di effettuare correttamente l'acquisizione digitale di dati provenienti da sistemi meccanici in generale, di scegliere la più adatta metodologia di pre-processing e di eseguire analisi al fine dell'identificazione dei parametri caratteristici dei sistemi stessi e della loro diagnostica. Rispetto ai corsi base di Misure questo corso è incentrato sull'analisi dei segnali; vengono impartite e utilizzate tecniche di elaborazione numerica nel dominio del tempo e in quello delle frequenze (risposta in frequenza, funzione di coerenza, trasformata di Hilbert, cepstrum, trasformate tempo-frequenza, zoom-FFT); vengono inoltre impartite nozioni sulle tecniche di condizionamento analogico/digitale dei segnali.
Signals in the time domain Classification of signals and their features: stationary and non-stationary signals, random and deterministic signals.
Analysis in the time domain: statistical parameters and correlation Basic and time-varying statistical parameters. Correlation functions. Advanced techniques for data acquisition Recall of the basic about signal acquisition. Aliasing and different acquisition strategies and high-level sampling techniques.
The convolution integral and the theorem of convolution Dirac function, impulse response. The convolution integral and the theorem of convolution. Frequency response functions.
Signal analysis in the frequency domain Band analysis, Fourier-direct and inverse transform, frequency resolution, leakage, windowing techniques. Characterisation of systems in the frequency domain: spectra, power-spectra, cross-spectra, coherence function, estimation of the frequency response functiona, Hilbert transform, cepstrum, time-frequency transform.
Fieldbus Data Transmission, digital communication, storage and data compression. Big data introduction.
Lecture Notes
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2022/2023 |
Digital notes |
Complete course notes |
2018/2019 |
Handwritten notes |
Complete course notes |
2018/2019 |
Handwritten notes |
Notes and exercises - Part 1 - Signal classification. Time domain signal analysis. Sampling strategies. Asynchronous sampling and synchronous sampling. Time Averaging. Convolution. Frequency domain an |
2011/2012 |
Handwritten notes |
Notes and exercises - Part 2 - Course year 2011/12 Autospettri and Crosspettri. Consistency. Frequency Response Function (FRF). FRF estimators. Arousal techniques. |
2011/2012 |
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Exercises
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Quick daily notes, exercises and audio recordings. Files will be approved on priority but deleted after 365 days. 2 points will be assigned by default.
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