Abstract
This paper deals with induction machine bearing faults detection based on an empirical mode decomposition approach combined to a statistical tool. In particular, it is proposed an innovative fault detector that is based on the dominant intrinsic mode function extraction, through an ensemble empirical mode decomposition, then its cancellation. The validation of this approach is based on simulations and experiments. The achieved simulation and experimental results clearly show that the proposed approach is well suited for bearing faults detection regardless the rank of the intrinsic mode function introduced by the fault.
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