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Communication Dans Un Congrès Année : 2015

Stator Current Analysis by Subspace Methods for Fault Detection in Induction Machines

Résumé

This paper aims to develop a condition monitoring architecture for induction machines, with focus on bearing faults. The main objective of this paper is to identify fault signatures at an early stage by using high-resolution frequency estimation techniques. In particular, we present two subspace methods, which are Root-MUSIC and ESPRIT. Once the frequencies are determined, the amplitude estimation is obtained by using the Least Squares Estimator (LSE). Finally, the amplitude estimation is used to derive a fault severity criterion. The experimental results show that the proposed architecture has the ability to measure the faults severity.
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Dates et versions

hal-01264782 , version 1 (01-02-2016)

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Youness Trachi, El Houssin El Bouchikhi, Vincent V. Choqueuse, Mohamed Benbouzid. Stator Current Analysis by Subspace Methods for Fault Detection in Induction Machines. Industrial Electronics Society, IECON 2015 - 41st Annual Conference of the IEEE, Nov 2015, Yokohama, Japan. ⟨10.1109/IECON.2015.7392639⟩. ⟨hal-01264782⟩
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