3 ECTS Credits — Semester 1 — Elective
Sensors, measurements, and signal processing are essential components in all fields fields of science, including engineering, healthcare, environmental monitoring, and more. Sensors are devices that detect changes in physical properties and convert them into signals. Measurements involve quantifying these changes using specific units or scales. Signal processing refers to the manipulation of these signals to extract relevant information or enhance their quality.
Syllabus
This course covers the measurement process, the sources of uncertainty, and methods for managing them. It also includes basic signal processing techniques and linear filtering. Additionally, the course will discuss the operating principles of certain sensors, such as light detectors.
Programme:
- Sensors & the measurement processes
- Measurement uncertainty: error propagation, parameter estimation
- Signals in Fourier space
- Passive RLC filters, Transfert functions
- Digital Signal Processing: Sampling, DFT, filtering, etc.
- Wavelets : an introduction
Suggested bibliography
- Asch, G. Poussery, B. Les capteurs en instrumentation industrielle. Dunod.
- Max, J & Lacoume, J.-L.. Méthodes et techniques du traitement du signal. Dunod.
- Barchiesi, D. Mesure physique et instrumentation. Ellipses.
- Bracewell, R. N. The Fourier Transform and its applications. Mc Graw-Hill.
- Taylor, J. R. An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements. University Science Books.
- Fraden, J. Handbook of Modern Sensors. Springer / AIP Press.
- Diefenderfer, A. J. Principles of Electronic Instrumentation. Saunders Golden Series
Prerequisites
- basic knowledge of probability and statistics
- basic understanding of Fourier transforms
- electricity, magnetism, passive electrical circuits