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Abstract
<p class="first" id="d2661285e102">Encoder signal as the built-in information is always
used for the speed and motion
control. Meanwhile, it has remarkable superiority in the fault diagnosis of gearbox
compared with the popular vibration signal. Traditional decomposition method, such
as EMD, gradually loses competitiveness with the increase of the complexity of the
encoder signal. To solve the problem, with aid of the unique characteristic of encoder
signal and the decomposition performance of variational mode decomposition (VMD),
a new sparsity-oriented VMD (SOVMD), is originally designed and initially introduced
for encoder signal analysis in this paper. Firstly, SOVMD is free from the selection
of mode number and initial center frequency (ICF), which troubles seriously the application
of VMD. Since a prior ICF which coarsely indicates the location of the fault band
can enhance the decomposing efficiency of VMD, ICF = 0 is more appropriate and easier
for the extraction of fault information concentrated in the low frequency region.
Benefiting from the characteristics of distribution, the optimization of the mode
number is unnecessary since the fault mode will generate in the first mode. Secondly,
with the proposed selection criterion of the balance parameter, SOVMD can decompose
the mode with most fault information more effectively and accurately. Furthermore,
a sparsity operation which is originally designed for the encoder signal analysis
can further suppress noise and enhance the fault impulses. Through the simulation
and experimental cases from the planet gearbox bench, the feasibility and effectiveness
of SOVMD can be verified. Therefore, it is reasonable to conclude that the proposed
SOVMD is an alternative scheme for gearbox fault diagnosis based on built-in encoder
information.
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