The research objective in this paper is to investigate the feasibility and effectiveness of utilizing envelope extraction combining the multi-scale entropy (MSE) analysis for identifying different roller bearing faults. The features were extracted from the angle-domain vibration signals that were measured through the hardware-implemented order-tracking technique, so that the characteristics of bearing defects are not affected by the rotating speed. The envelope analysis was employed to the vibration measurements as well as the selected intrinsic mode function (IMF) that was separated by the empirical mode decomposition (EMD) method. By using the coarse-grain process, the entropy of the envelope signals in the different scales was calculated to form the MSE distributions that represent the complexity of the signals. The decision tree was used to distinguish the entropy-related features which reveal the different classes of bearing faults.
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