A diagnosis method of multiple faults of induction motors based on vibration signal analysis

A Kabul, A Ünsal - 2021 IEEE 13th International Symposium on …, 2021 - ieeexplore.ieee.org
2021 IEEE 13th International Symposium on Diagnostics for …, 2021ieeexplore.ieee.org
Induction motors are widely preferred in industrial applications to provide mechanical
energy. Stator winding and bearing faults are the most common fault types that must be
handled on condition monitoring of induction motors. Condition monitoring of single fault of
induction motor can be effectively monitored by applying conventional Motor Vibration
Signature Analysis (MVSA). However, the effectiveness of these conventional methods is
limited in the presence of multiple faults due to the increasing number of harmonics under …
Induction motors are widely preferred in industrial applications to provide mechanical energy. Stator winding and bearing faults are the most common fault types that must be handled on condition monitoring of induction motors. Condition monitoring of single fault of induction motor can be effectively monitored by applying conventional Motor Vibration Signature Analysis (MVSA). However, the effectiveness of these conventional methods is limited in the presence of multiple faults due to the increasing number of harmonics under varying loading conditions. This paper focuses on the detection of characteristic harmonic components of simultaneous multiple faults including stator inter-turn short circuit and outer-race or inner-race bearing faults under four loading levels based on vibration signal analysis by applying Hilbert envelope analysis. The experimental results show that the proposed method can effectively detect fault characteristic harmonic under 25%, 50%, 75% and 100% loading levels of induction motor.
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