Instrumentation, signal processing and modeling

On completion of the course, students will be able to take part in the design or diagnosis of a measurement system.
This implies being able to:

describe the general operation of a measurement system,
identify, evaluate and propose the characteristics of a measurement system,
test and validate a measurement system,
engage in constructive dialogue with the various parties involved in a project of this type.


Teachers aim to:

raise awareness of the challenges of industrial measurement,
familiarize students with signal processing methods, and make them aware of their benefits,
help students understand the basic principles of modeling, and make them aware of their benefits.

First-year courses in digital and IT tools
First-year courses in electronics
First-year courses in thermodynamics
Second-year courses in the dynamics of chemical systems

Instrumentation, signal processing
The main types of physical sensors (temperature, pressure, flow, etc.) are described, from their operating principle to their implementation. Problems and solutions related to signal shaping and conversion are discussed, with particular emphasis on problems related to sampling.
The most common signal analysis methods are presented (distributions and moments, auto- and inter-correlations, Fourier transforms, power spectral densities), mainly in the discrete domain.
Discrete filters are the signal processing techniques explained next. The practical implementation of these methods is discussed with a view to modeling and process control.
Modeling
The concept of modeling and its relevance to process engineering are discussed. The development of dynamic knowledge models is described on the basis of the conservation principle (mass, energy, momentum) and illustrated by examples.

Engineering Sciences and Techniques

Instrumentation et automatisation industrielle, PEYRUCAT J.F., Dunod Tech, 1993
Le génie chimique à l'usage des chimistes (2° Ed.) LIETO J., Tec et Doc Lavoisier, 2004