Models for Bearing Damage Detection in Induction Motors Using Stator Current Monitoring

Martin Blödt (1, 2) , Pierre Granjon (3) , Bertrand Raison (1) , Gilles Rostaing (1)

1 G2ELab - Laboratoire de Génie Electrique de Grenoble
2 LAPLACE - LAboratoire PLasma et Conversion d'Energie
3 GIPSA-SA-IGA - GIPSA - Signal et Automatique pour le Diagnostic et la Surveillance

This paper describes a new analytical model for the influence of rolling-element bearing faults on induction motor stator current. Bearing problems are one major cause for drive failures. Their detection is possible by vibration monitoring of characteristic bearing frequencies. As it is possible to detect other machine faults by monitoring the stator current, a great interest exists in applying the same method for bearing fault detection. After a presentation of the existing fault model, a new detailed approach is proposed. It is based on the following two effects of a bearing fault: 1) the introduction of a particular radial rotor movement and 2) load torque variations caused by the bearing fault. The theoretical study results in new expressions for the stator current frequency content. Experimental tests with artificial and realistic bearing damage were conducted by measuring vibration, torque, and stator current. The obtained results by spectral analysis of the measured quantities validate the proposed theoretical approach.

Mots clés: torque variations; spectral analysis; motor current signature analysis; Airgap eccentricity; bearing damage detection; induction motors

Domaines: Energie électrique; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Martin Blödt, Pierre Granjon, Bertrand Raison, Gilles Rostaing. Models for Bearing Damage Detection in Induction Motors Using Stator Current Monitoring. IEEE Transactions on Industrial Electronics, 2008, 55 (4), pp.1813-1822. ⟨10.1109/TIE.2008.917108⟩. ⟨hal-00270747⟩