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Communication Dans Un Congrès Année : 2006

Induction Motors Bearing Failures Detection and Diagnosis Using a RBF ANN Park Pattern Based Method

Résumé

This paper deals with the problem of bearing failure detection and diagnosis in induction motors. The proposed approach is a sensor-based technique using the mains current and the rotor speed measurement. The proposed approach is based on the stator current Park patterns. Induction motor stator currents are measured, recorded and used for Park patterns computation. A Radial Basis Function (RBF) Artificial Neural Network (ANN) is then used to automate the fault detection and diagnosis process. Experimental tests with artificial bearing damages results show that the proposed method can be used for accurate bearing failures detection and diagnosis in induction motors.
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Dates et versions

hal-00527566 , version 1 (19-10-2010)

Identifiants

  • HAL Id : hal-00527566 , version 1

Citer

Izzet Önel, Ibrahim Senol, Mohamed Benbouzid. Induction Motors Bearing Failures Detection and Diagnosis Using a RBF ANN Park Pattern Based Method. ICEM'06, Sep 2006, Chania, Greece. 6pp. ⟨hal-00527566⟩
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