This paper proposes a novel approach to detect the presence of broken bars in the rotor of a squirrel cage induction motor (SCIM). A mathematical model of the SCIM capturing both the healthy and faulty operating conditions of the motor is introduced, and a model-based FDI observer, based on second order sliding modes (2-SMs), is presented. Appropriate theoretical arguments are invoked to demonstrate that the suggested FDI observer is capable of detecting the occurrence of the Broken Bar Fault (BBF) condition by relying on stator current and shaft speed measurements, which can be easily achieved in practice. Additionally, the proposed observer provides an exponentially convergent estimation of the rotor fluxes and of the the external load torque. The proposed scheme has been experimentally tested by means of a commercial Siemens 1.1-kW three-phase SCIM. The experimental results confirm the robust performance featured by the suggested methodology.

Robust FDI in induction motors via second order sliding mode technique

PILLONI, ALESSANDRO;PISANO, ALESSANDRO;USAI, ELIO
2012-01-01

Abstract

This paper proposes a novel approach to detect the presence of broken bars in the rotor of a squirrel cage induction motor (SCIM). A mathematical model of the SCIM capturing both the healthy and faulty operating conditions of the motor is introduced, and a model-based FDI observer, based on second order sliding modes (2-SMs), is presented. Appropriate theoretical arguments are invoked to demonstrate that the suggested FDI observer is capable of detecting the occurrence of the Broken Bar Fault (BBF) condition by relying on stator current and shaft speed measurements, which can be easily achieved in practice. Additionally, the proposed observer provides an exponentially convergent estimation of the rotor fluxes and of the the external load torque. The proposed scheme has been experimentally tested by means of a commercial Siemens 1.1-kW three-phase SCIM. The experimental results confirm the robust performance featured by the suggested methodology.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/108140
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