Diagnosis of Bearing Faults in Induction Machines by Vibration or Current Signals: A Critical Comparison

Abstract

Mechanical imbalances and bearing faults account for a large majority of the faults in a machine, particularly for small-medium size machines. Therefore, their diagnosis is an intensively investigated field of research. Recently, many research activities were focused on the diagnosis of bearing faults by current signals. This paper compares the bearing fault detection capability obtained with the vibration and current signals. The paper contribution is the use of a simple and effective signal processing technique for both current and vibration signals, and a theoretical analysis of the physical link between faults, modeled as a torque disturbance, and current components. The focus of the paper is on the theoretical development of the correlation between torque disturbances and the amplitude of the current components, together with a review of fault models used in the literature. Another contribution is the re-creation of realistic incipient faults and their experimental validation. Radial effects are visible only in case of large failures that result in air-gap variations. Experiments are reported that confirm the proposed approach.