Rolling Bearing Failure Detection in Induction Motors using Stator Current, Vibration and Stray Flux Analysis Techniques

Many industrial applications use the induction machine for its advantages, like robustness. But like any other machines, it can be affected by several faults such as broken rotor bars, stator inter-turn short-circuit, bearing faults, etc. On the one hand, mechanical faults produce vibration, eccentricity and torque oscillations which influence the stator current and the distribution of the magnetic field. Therefore, early detection of mechanical faults leads to avoid damage or sudden stop of the induction machine. In this context, this paper studies the performances of three fault detection and diagnostic techniques for rolling bearing failures. The first technique is based on the stator current analysis, the second one uses the vibration signal analysis and the last technique is devoted to the stray flux signature.The aim of the study is to highlight the performances of stray- flux technique in the detection of inner raceway fault comparatively to current and vibration. For this study, experimental tests are realized on a laboratory test bench allowing creation of artificial bearing damage. The analysis is focused on specific harmonics related to the electrical and mechanical frequencies.

• rolling bearing fault detection
• induction motor
• stator current analysis
• vibration analysis
• condition monitoring
• fault diagnosis
• bearing damage

• 9 — الصناعة والابتكار والبنية التحتية

• Machine Fault Diagnosis Techniques
• Electric Motor Design and Analysis
• Sensorless Control of Electric Motors
• rolling bearing fault detection
• induction motor
• stator current analysis
• vibration analysis
• condition monitoring
• fault diagnosis
• bearing damage
• Control and Systems Engineering
• Electrical and Electronic Engineering
• Engineering