Sensors, Meas. and Signal Processing

This course introduces the measurement process, the sources of uncertainties and the method to handle them. Basic signal processing techniques and linear filtering will also be presented. The principles of operation of some sensors, such as light detectors will be discussed as well.

Syllabus : " Sensors, Measurements and Signal Processing "

- Lectures 12 hours, Tutorials 12 hours, Laboratory Work 6 hours
(1st Semester) -

(Réza Ansari, Zoé Mokhtari)

Chapter 1: Sensors and measurements process
 - Metrology, physical quantities
 - Sensors : Principles of operations and general characteristics

Chapter 2: Uncertainties and measurement errors
- Statistical and systematic uncertainties, error propagation
- Parameter estimation

Chapter 3: Signals in Fourier space
 - Fourier Transform and its properties
 - Convolution and auto-correlation, Spectral energy distribution 
- Fourier series, Sin/Cos Transform

Chapter 4: Linear Filtering & passive RLC filters 
 - Linear time invariant systems, transfer function 
- Passive RLC filters 
 - Bode diagram

Chapter 5: Digital Signal Processing
- Windowing
 - Shannon Sampling theorem: sampling in time, sampling in frequency 
 - DFT (Discrete Fourier Transform) and FFT 

The program is completed by specific laboratory work:
Digital signal processing and filtering, voice signal and image filtering,...

Recommended textbooks:

• Méthodes et techniques du traitement du signal, Jacques Max, Jean-Louis Lacoume, Ed. Dunod
• The Fourier Transform and its Applications, R. N. Bracewell, Mc Graw-Hill
• Mesure Physique et instrumentation, D. Barchiesi, Ed. Ellipses
• Incertitudes et analyse des erreurs dans les mesures physiques, J. Taylor, Ed. Dunod
• Les capteurs en instrumentation industrielle, G. Asch et al., Ed. Dunod
• Handbook of Modern Sensors, J. Fraden, Ed. Springer / AIP Press
• Principles of Electronic Instrumentation, A. J. Diefenderfer, Saunders Golden Series

Course prerequisites and corequisites

 basic knowledge of probability and statistics
 basic understanding of Fourier transform
 electricity, magnetism, passive electrical circuits.

Course concrete goals

On completion of the course students should be able to:

— Compute uncertainties when combining different measurements, how to control and decrease measurement errors
— Understand effect of filters used in measurement systems
— Use basic signal processing algorithms to extract information of enhance signal/noise ratio.