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Model-Based Fault Detection of Permanent Magnet Synchronous Motors of Drones Using Current Sensors

  • Guilhem Jouhet
  • Luis E. González-JiménezEmail author
  • Marco A. Meza-Aguilar
  • Walter A. Mayorga-Macías
  • Luis F. Luque-Vega
Chapter
  • 13 Downloads
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 270)

Abstract

This work proposes a simple, low-cost and effective scheme for the detection of the most common faults in drone actuators which are, usually, permanent magnet synchronous motors (PMSM). The scheme is based on a modelling stage which only requires the current measurements from a faultless motor. From this, a simplified transfer function of the motor is derived. Then, the output of this model and a healthy motor are used as arguments of simple tests to detect the occurrence of a set of characterized faults in the target motor. The setup of the scheme and the development of the tests are straightforward. The faults considered in this work are inter-turn short-circuit, changes in friction constant and flying off propeller and other less common faults. Experimental results show that these faults are accurately detected and characterized by the proposed scheme, opening doors to further work on predictive maintenance and drone adaptive or re-configurable controllers.

Keywords

PMSM modelling Fault detection Drone actuators Current sensor 

Notes

Acknowledgements

This research is funded by National Council of Science and Technology (CONACyT) of México under grants 261774 and 227601.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Guilhem Jouhet
    • 1
  • Luis E. González-Jiménez
    • 2
    Email author
  • Marco A. Meza-Aguilar
    • 2
  • Walter A. Mayorga-Macías
    • 2
  • Luis F. Luque-Vega
    • 3
  1. 1.Ecole Centrale de LyonÉcullyFrance
  2. 2.Electronics, Systems and Informatics DepartmentITESO UniversityTlaquepaqueMexico
  3. 3.Centro de Investigación, Innovación y Desarrollo Tecnológico CIIDETEC-UVMUniversidad del Valle de MéxicoMexico CityMexico

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