  A non-parametric complementary ensemble empirical mode decomposition
(NPCEEMD) is proposed for identifying bearing defects using weak features.
NPCEEMD is non-parametric because, unlike existing decomposition methods such
as ensemble empirical mode decomposition, it does not require defining the
ideal SNR of noise and the number of ensembles, every time while processing the
signals. The simulation results show that mode mixing in NPCEEMD is less than
the existing decomposition methods. After conducting in-depth simulation
analysis, the proposed method is applied to experimental data. The proposed
NPCEEMD method works in following steps. First raw signal is obtained. Second,
the obtained signal is decomposed. Then, the mutual information (MI) of the raw
signal with NPCEEMD-generated IMFs is computed. Further IMFs with MI above 0.1
are selected and combined to form a resulting signal. Finally, envelope
spectrum of resulting signal is computed to confirm the presence of defect.
