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DIAGNOSTIC AUTOMATIQUE DES DEFAUTS DES MOTEURS ASYNCHRONES

Guedalia ILUNGA MUTOMBO, Edouard NDALA

2023frdiagnosticmoteursasynchroneélectromécaniquetechnique

Abstract

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This work addresses the automatic diagnosis of faults in asynchronous (induction) motors, which constitute around 80% of commonly used electric motors due to their robustness, simplicity, and low cost. It first presents the main types of faults that can affect these machines (stator, rotor, and mechanical defects), along with statistical studies and the basic concepts of monitoring, fault detection, and diagnostic methods. The thesis then develops a mathematical model of the asynchronous motor, introduces the Clarke/Concordia and Park transformations, and formulates the state-space representation needed for analysis and simulation. Using this model, various electrical, mechanical, and energetic behaviors of the motor are simulated to study its response under different operating conditions and faults. The overall objective is to contribute to improving the reliability and lifetime of asynchronous motors by supporting the development of automatic diagnostic systems based on both model-based and signal-processing approaches.

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Cite This Work

@article{5a1a68f9-a623-48d0-986f-99f2b3b87982,
  title={DIAGNOSTIC AUTOMATIQUE DES DEFAUTS DES MOTEURS ASYNCHRONES},
  author={Guedalia ILUNGA MUTOMBO and Edouard NDALA},
  year={2023},
  language={fr}
}
TY  - JOUR
TI  - DIAGNOSTIC AUTOMATIQUE DES DEFAUTS DES MOTEURS ASYNCHRONES
AU  - Guedalia ILUNGA MUTOMBO
AU  - Edouard NDALA
PY  - 2023
LA  - fr
ER  -

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