Mechanical Failure Detection in Induction Motors Using Stator Current and Stray Flux Analysis Techniques

Abstract

Because of its benefits, an induction machine is used in a variety of applications. The machine’s robustness is one of its benefits. Generally, mechanical faults cause torque oscillations, eccentricity, and vibration, which affect the stator current value and magnetic field distribution. As a result, early warning of mechanical failures helps to prevent damage to the induction system or sudden stopping. In this sense, the accuracy of techniques in detecting rolling bearing failure is investigated in this article. The first method focused on stator current analysis and the second on stray flux signature analysis. The aim of this research is to compare the success of the stray flux technique and the stator current analysis in detecting inner raceway faults. In addition, this research suggests a novel method for determining the relationship between two signals based on a transfer function estimate and magnitude-squared coherence between current and flux. Experimental tests were realized in a laboratory to artificially create the bearing damage. After that, the analysis focused on characteristic harmonics related to the different harmonics.

Structural diagram of the built-in diagnostic system for electric drives of vehicles

“…Damage to the bearings (12%) leads to the appearance of vibration and, over time, to the engagement of the rotor in the stator, resulting in damage to the rotor and stator with the closure of the active steel sheets of the magnetic circuit of these elements, which completely removes the electric motor from the working state [12][13][14]. Monitoring the condition of the bearings contributes to the timely detection of damage to the bearings and the prevention of an emergency stop of the electric motor.…”

“…When using vibration diagnostic methods, the presence and degree of damage in an inductions motor are determined by methods of spectral analysis of vibration signals [13,14]. Spectra of vibration signals can be used to determine with sufficient accuracy the type and nature of damage, which requires the presence of special sensors.…”

“…The obtained value of the angle of ellipticity less than π/4 will indicate the presence of an inter-turn short circuit in the stator windings. In the presence of an inter-turn short circuit, the amplitudes and phases of the stator phase currents are calculated using expressions (15)(16), and the number of damaged turns of the winding stator is calculated using expressions (13)(14).…”

Experimental study of a teeth flux sensor for detection, location and severity evaluation of induction machine stator faults

“…), mechanical (wear of bearings, gears, etc.) or thermal (insulation degradation) (Pusca et al , 2022; Irhoumah et al , 2021; Almounajjed et al , 2021). One of the primary faults affecting induction motors is faults in the stator windings (Navarro-Navarro et al , 2022; Lee et al , 2021b; Park et al , 2020b).…”

Convolutional Neural Networks for Automated Rolling Bearing Diagnostics in Induction Motors Based on Electromagnetic Signals

“…More recently, electromagnetic signals proved to be efficient in detecting bearing defects and other mechanical faults. In particular, in [10], two fault severities in the rolling elements and cage of a bearing were recognized via MCSA in an induction motor of 5.5 kW, while in [11], an inner race fault was identified by means of vibration, current, and stray flux analysis in an induction motor of 4 kW. From the comparative study presented in [11], the stray flux seems to provide the best results, as it is insensitive to external vibrations of the motor; nevertheless, the authors suggest using this signal in combination with at least one of the other signals, to increase the reliability of the diagnosis.…”