DATA ANALYSIS FOR FUTURE TRANSPORTATION SYSTEMS

Synthetic program:

The course contents are delivered through lectures (also employing innovative teaching apporaches) and lab activities.

The course covers the following topics divided in modules as per the description below:

 

Module 1: Introductory concepts
Topic 1.1: Classification of signals and their features: stationary and non-stationary signals, random and deterministic signals.

Topic 1.2: Basics of signal acquisition. Synchronous and Asynchronous sampling.

 

Module 2: Analysis in the time domain: statistical parameters and correlation
Topic 2.1: Basic and time-varying statistical parameters.

Topic 2.2: Correlation functions.

 

Module 3: Signal analysis in the frequency domain
Topic 4.1: Band analysis, Fourier-direct and inverse transform,  frequency resolution.

Topic 4.2 Leakage and Aliasing.

Topic 4.3: Windowing techniques.

Topic 4.4: Characterization of systems in the frequency domain: spectra, power-spectra, cross-spectra.

 

Module 4: Analysis of Linear Time Invariant Systems
Topic 4.1: Dirac function, impulse response, the convolution integral and the theorem of convolution

Topic 4.2: Frequency response function of mechanical systems and its estimation

Topic 4.3: Coherence function

 

Module 5: Advanced data analysis techniques
Topic 5.1: Hilbert transform.

Topic 5.2: Cepstrum.

Topic 5.3: Time-frequency transform.

Topic 5.4: Introduction to artificial intelligence for system diagnostics.

Topic 5.5: Data Fitting and Regression.