Detecting Particle Contamination in Bearings of Inverter-Fed Induction Motors: A Comparative Evaluation of Monitoring Signals

In induction motor bearings, distributed faults are prevalent, often resulting from factors such as inadequate lubrication and particle contamination. Unlike localized faults, distributed faults produce complex and unpredictable motor signal behaviors. Although existing research predominantly addresses localized faults in mains-fed motors, particularly single-point defects, a comprehensive investigation into particle contamination in bearings of inverter-fed motors is essential for a more accurate understanding of real-world bearing issues. This paper conducts a comparative analysis of vibration, stator current, speed, and acoustic signals to detect particle contamination through signal analysis across three domains: time, frequency, and time-frequency. These domains are analyzed to assess and compare the characteristics of each monitored signal in the context of bearing wear detection. The data were collected from both steady-state and startup transients of an induction motor controlled by a variable frequency drive. The experimental results highlight the most significant characteristics of each monitored signal, evaluated across the different domains of analysis. The primary conclusion indicates that, in inverter-fed motors, sound and vibration signals exhibit abnormal levels when the bearing is damaged but the related-fault signature becomes complicated. Additionally, the findings demonstrate that the analysis of startup stator current and speed signals presents the potential to detect distributed bearing damage in inverter-fed induction motors.