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

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.

• induction motor
• mechanical fault detection
• stator current analysis
• torque oscillations
• eccentricity
• vibration
• transfer function
• magnitude-squared coherence
• bearing damage

• 9 — Industrie, innovation et infrastructure

• Machine Fault Diagnosis Techniques
• Electric Motor Design and Analysis
• Sensorless Control of Electric Motors
• induction motor
• mechanical fault detection
• stator current analysis
• torque oscillations
• eccentricity
• vibration
• transfer function
• magnitude-squared coherence
• Control and Systems Engineering
• Electrical and Electronic Engineering
• Engineering