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Our engineering & Master degrees
Our engineering & Master degrees

> Studies

Energy Monit and Diagnostics - 5PMSEMD0

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  • Number of hours

    • Lectures : 4.0
    • Tutorials : 0
    • Laboratory works : 2.0
    • Projects : 14.0
    • Internship : 0
    • Written tests : 0
    ECTS : 2.0

Goals

  • define the problem of system monitoring and diagnosis
  • complete the tools and methods necessary for this type of application
  • acquire autonomy through practical experiences
Contact Pierre GRANJON, Cornel IOANA

Content

  1. introduction to system monitoring and diagnosis (lecture)
  2. sequential change detection in signals (lecture/labworks)
    • problem statement
    • CuSum type algorithms
    • GLR type algorithms
  3. projects of system monitoring and diagnosis (project)


Prerequisites
  • basics of data science (correlation, spectral analysis, filtering, ...)
  • basics of estimation theory (maximum likelihood estimator)
  • basics of detection theory (binary hypothesis testing)

Tests

Semester 9 - The exam is given in english only 

technical reports (labworks and project)



100% rapports techniques

Additional Information

Semester 9 - This course is given in english only EN

Curriculum->Master TSI SIGMA->Semester 9
Curriculum->SICOM->Semester 9
Curriculum->Double-Diploma SICOM-TSI SIGMA->Semester 9
Curriculum->Master->Semester 9
Curriculum->Double-Diploma Engineer/Master->Semester 9

Bibliography

Detection of Abrupt Changes - Theory and Application. Michèle Basseville, Igor Nikiforov. Prentice Hall - http://people.irisa.fr/Michele.Basseville/kniga/, 1993.

Statistical inference for engineers and data scientists. Pierre Moulin, Venugopal V. Veeravalli. Cambridge University Press, 2019.

The CuSum algorithm - A small review. Pierre Granjon. Technical report - https://hal.archives-ouvertes.fr/hal-00914697, 2013

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Date of update September 13, 2019

Université Grenoble Alpes