BruitAcquisition (GSI)

This course presents an overview of noise in electronic instrumentation systems. All industrial systems are subjected to or generate noise or disturbances that limit the performance of the device itself or surrounding devices. A distinction is made between the source of noise/disturbation and the conditioning which will reduce the effect of disturbances. The concepts of statistical description of random signals will be recalled, with a highly applied objective of classification, identification and location of noise sources in industrial systems. Various fields of industrial applications may be presented during the course of this course by industrial stakeholders and/or foreign researchers. In particular, we will present a very concrete application of the statistical analysis of random signals in the field of Acoustic Emission (AE), a technique particularly used in the non-destructive control industry (NDC), and in the new technologies for manufacturing resistive memories.

Thermal noise theory, electron diffusion noise, random walking noise (Brownian Movement), Poissonian process. Linear filtering, noise transformation, applications to system characterization. Statistical treatment of random noise sources. Statistical decision theory with industrial applications. White Noise Theory - Johnson noise application in resistance - Fish distribution - Brownian movement - Random walking noise - Noise flicker or noise 1/f - Noise transformation. applications for system characterization - Noise Signal Report - Noise Figure - Noise factor - practical applications with noise factor measurement of an amplifier and transistor, noise simulation under Labview, Mathematica and Matlab. Introduction to stochastic systems and their perspectives in resistive memory technology (memristor)

Ongoing monitoring