Quantitative rotor broken bar evaluation in double squirrel cage induction machines under dynamic operating conditions

Abstract

Advanced monitoring techniques leading to fault diagnosis and prediction of induction machine faults, operating under non-stationary conditions have gained strength because of its considerable influence on the operational continuation of many industrial processes. In case of rotor broken bars, fault detection based on sideband components issued from currents, flux, instantaneous control or power signals under different load conditions, may fail due to the presence of inter-bar currents that reduce the degree of rotor asymmetry, especially for double squirrel cage induction motors. But the produced core vibrations in the axial direction, can be investigated to overcome the limitation of the classical technique using appropriate timefrequency analysis for these purposes. Unlike previous approaches, the presented technique is based on optimized use of the Discrete wavelet transform to overcome the limitation of classical frequency approaches under non-stationary operating conditions. The developed approach is best suited for automotive or high power traction systems, in which safe-operating and availability are mandatory. Experimental results are provided, showing the validity of the investigated technique, leading to an effective diagnosis procedure for incipient rotor broken bars in double or single cage induction machines under dynamic operating conditions.

Diagnosis of mechanical unbalance for double cage induction motor load in time-varying conditions based on motor vibration signature analysis

“…A recent time-frequency technique based on improved performance of wavelet analysis was proposed in [24] for high accuracy detection of incipient electrical faults in induction motors. This technique was successfully extended to the analysis of MVSA for the detection of rotor broken bars in steady-state condition in [25], and more recently in time-varying conditions [26]. In this paper, the detectability of mechanical load unbalance, based on motor vibration signature analysis is investigated in steadystate firstly.…”