Applied Sciences,
Год журнала:
2021,
Номер
11(19), С. 9095 - 9095
Опубликована: Сен. 29, 2021
A
rolling
element
signal
has
a
long
transmission
path
in
the
acquisition
process.
The
fault
feature
of
is
more
difficult
to
be
extracted.
Therefore,
novel
weak
extraction
method
using
optimized
variational
mode
decomposition
with
kurtosis
mean
(KMVMD)
and
maximum
correlated
deconvolution
based
on
power
spectrum
entropy
grid
search
(PGMCKD),
namely
KMVMD-PGMCKD,
proposed.
In
proposed
KMVMD-PGMCKD
method,
VMD
Then
an
adaptive
parameter
selection
for
MCKD,
PGMCKD,
determine
period
T
filter
order
L.
complementary
advantages
KMVMD
PGMCKD
are
integrated
construct
model
(KMVMD-PGMCKD).
Finally,
employed
deal
obtained
by
effectively
implement
extraction.
Bearing
signals
Case
Western
Reserve
University
actual
data
selected
prove
validity
KMVMD-PGMCKD.
experiment
results
show
that
can
extract
features
bearing
elements
accurately
diagnose
faults
under
variable
working
conditions.
Measurement Science and Technology,
Год журнала:
2022,
Номер
33(6), С. 065009 - 065009
Опубликована: Фев. 11, 2022
Abstract
Bearing
is
an
important
component
in
mechanical
equipment.
Its
main
function
to
support
the
rotating
body
and
reduce
friction
coefficient
axial
load.
In
actual
operating
environment,
bearings
are
affected
by
complex
working
conditions
other
factors.
Therefore,
it
very
difficult
effectively
obtain
data
that
meets
of
independent
identical
distribution
training
test
data,
which
result
unsatisfactory
fault
diagnosis
results.
As
a
transfer
learning
method,
joint
adaptive
(JDA)
can
solve
problem
inconsistent
data.
this
paper,
new
bearing
method
based
on
JDA
deep
belief
network
(DBN)
with
improved
sparrow
search
algorithm
(CWTSSA),
namely
JACADN
proposed.
JACADN,
employed
carry
out
feature
between
source
domain
samples
target
samples,
is,
mapped
into
same
space
kernel
function.
Then
maximum
mean
difference
used
as
metric
two
domains.
Aiming
at
parameter
selection
DBN,
(CWTSSA)
global
optimization
ability
optimize
parameters
DBN
order
construct
optimized
model.
The
obtained
divided
set
set,
input
model
for
improving
accuracy.
effectiveness
proposed
verified
vibration
QPZZ-II
machinery.
experimental
results
show
improve
accuracy
rolling
under
variable
conditions.
IEEE Sensors Journal,
Год журнала:
2022,
Номер
22(14), С. 14263 - 14272
Опубликована: Июнь 7, 2022
Parametrized
time-frequency
analysis
(PTFA)
can
effectively
improve
energy
aggregation
of
non-stationary
signal
and
immunity
cross
term
interference,
but
it
exists
the
diffusion
near
real
instantaneous
frequency.
The
improved
multi-synchrosqueezing
transform
(IMSST)
aggregation,
still
has
defects
in
processing
strong
FM
AM
signals
under
noise
interference.
Therefore,
order
to
make
use
their
advantages
overcome
disadvantages,
a
novel
parametrized
method
based
on
weighted
least
square,
IMSST
PTFA,
namely
PMSST
is
proposed
this
paper.
In
PMSST,
designed
obtain
representation
with
high
aggregation.
Then
ridge
extraction
algorithm
employed
extract
frequency
ridges
each
mono-component
signal.
square
used
estimate
parameters
parameterized
kernel.
Finally,
spectrum
superimposed
enhanced
experiment
results
show
that
process
varying
by
simulated
actual
fault
signals.
Applied Sciences,
Год журнала:
2021,
Номер
11(23), С. 11192 - 11192
Опубликована: Ноя. 25, 2021
Aiming
at
the
problems
of
basic
sparrow
search
algorithm
(SSA)
in
terms
slow
convergence
speed
and
ease
falling
into
local
optimum,
chaotic
mapping
strategy,
adaptive
weighting
strategy
t-distribution
mutation
are
introduced
to
develop
a
novel
algorithm,
namely
CWTSSA
this
paper.
In
proposed
CWTSSA,
is
employed
initialize
population
order
enhance
diversity.
The
applied
balance
capabilities
mining
global
exploration,
improve
speed.
An
operator
designed,
which
uses
iteration
number
t
as
degree
freedom
parameter
characteristic
exploration
abilities,
so
avoid
optimum.
prove
effectiveness
15
standard
test
functions
other
improved
SSAs,
differential
evolution
(DE),
particle
swarm
optimization
(PSO),
gray
wolf
(GWO)
selected
here.
compared
experiment
results
indicate
that
can
obtain
higher
accuracy,
faster
speed,
better
diversity
abilities.
It
provides
new
for
solving
complex
problems.
Computational Intelligence and Neuroscience,
Год журнала:
2021,
Номер
2021(1)
Опубликована: Янв. 1, 2021
The
purpose
of
mobile
robot
path
planning
is
to
produce
the
optimal
safe
path.
However,
robots
have
poor
real‐time
obstacle
avoidance
in
local
and
longer
paths
global
planning.
In
order
improve
accuracy
prediction
planning,
shorten
length
reduce
time,
then
obtain
a
better
path,
we
propose
decision
model
based
on
machine
learning
(ML)
algorithms,
an
improved
smooth
rapidly
exploring
random
tree
(S‐RRT)
algorithm,
hybrid
genetic
algorithm‐ant
colony
optimization
(HGA‐ACO).
Firstly,
algorithms
are
used
train
datasets,
established,
cross
validation
performed.
Secondly,
greedy
algorithm
idea
B‐spline
curve
introduced
into
RRT
redundant
nodes
removed,
reverse
iteration
performed
generate
Then,
fitness
function
operation
method
optimized,
pheromone
update
strategy
deadlock
elimination
ant
genetic‐ant
fusion
fuse
two
algorithms.
Finally,
optimized
for
simulation
experiment.
Comparative
experiments
show
that
forest
has
highest
S‐RRT
can
effectively
total
generated
by
HGA‐ACO
number
reasonably,
search
time
effectively,
solution
Boundary Value Problems,
Год журнала:
2025,
Номер
2025(1)
Опубликована: Март 28, 2025
This
research
focuses
on
the
study
of
hybrid
fractional
differential
equations
with
linear
perturbation
second
type.
The
primary
objective
this
work
is
to
establish
existence
solutions
for
proposed
equations.
To
achieve
desired
results,
we
apply
tools
Banach
contraction
and
Krasnoselskii's
fixed
point
theorem
respectively
derive
conditions
considered
problem.
Moreover,
developed
stability
analysis
our
In
addition,
fundamental
types
inequalities
are
used
necessary
minimal
maximal
underlying
equation.
Finally,
present
illustrative
examples
demonstrate
key
findings
study.
IEEE Access,
Год журнала:
2023,
Номер
11, С. 5206 - 5214
Опубликована: Янв. 1, 2023
This
article
focuses
on
a
finite-time
adaptive
dynamic
surface
control
(DSC)
approach
for
kind
of
nonstrict
fractional-order
nonlinear
systems
(FONSs)
with
input
delay.
An
auxiliary
compensation
function
is
presented
by
using
the
integral
signal
to
handle
delay
problem.
To
overcome
problem
inherent
computational
complexity,
filter
applied
virtual
controller
and
its
derivative
in
each
step
backstepping
procedure.
By
technology
neural
network
(NN),
DSC
developed,
stability
criteria
based
Lyapunov
method
are
introduced
prove
convergence
tracking
error
into
small
region
around
origin.
The
effectiveness
scheme
demonstrated
two
examples.
Applied Sciences,
Год журнала:
2021,
Номер
11(23), С. 11480 - 11480
Опубликована: Дек. 3, 2021
Aiming
at
the
problems
of
poor
decomposition
quality
and
extraction
effect
a
weak
signal
with
strong
noise
by
empirical
mode
(EMD),
novel
fault
diagnosis
method
based
on
cascaded
adaptive
second-order
tristable
stochastic
resonance
(CASTSR)
EMD
is
proposed
in
this
paper.
In
method,
low-frequency
interference
components
are
filtered
using
high-pass
filtering,
restriction
conditions
theory
solved
an
ordinary
variable-scale
method.
Then,
chaotic
ant
colony
optimization
algorithm
global
ability
employed
to
adaptively
adjust
parameters
system
obtain
optimal
resonance,
reduction
pretreatment
technology
CASTSR
developed
enhance
characteristics
low
frequency.
Next,
decompose
denoising
extract
characteristic
frequency
from
intrinsic
function
(IMF),
so
as
realize
rolling
bearings.
Finally,
numerical
simulation
actual
bearing
data
selected
prove
validity
The
experiment
results
indicate
that
can
EMD,
effectively
features
signals,
improve
accuracy
diagnosis.
Therefore,
effective
for
rotating
machinery.