Page 115 - IJOCTA-15-4

Rolling bearing fault diagnosis method based on GJO–VMD, multiscale fuzzy entropy, and GSABO–BP...

Figure 3. A flowchart illustrating the steps in the proposed fault diagnosis method
Abbreviations: BP: Back propagation; GJO: Golden jackal optimization; GSABO: Golden sine
subtraction-average-based optimizer; IMF: Intrinsic mode functions; VMD: Variational mode decomposition.

Figure 4. Time-domain waveform of the simulated signal y(t)

the fault characteristic frequency proved challeng- the GJO algorithm. Specifically, the search range
ing. Therefore, the VMD method was employed for K was set to [2, 7], and for α, it is set to [100,
to decompose the aforementioned signal. 29 5000]. Envelope entropy was adopted as the fit-
ness function to guide the optimization of both
During the VMD decomposition process, the
parameters.
key parameters—K and α—were optimized using
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