Research on Wind Turbine Fault Detection Based on CNN-LSTM
Lin Qi,
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Qianqian Zhang,
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Yunjie Xie
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et al.
Energies,
Journal Year:
2024,
Volume and Issue:
17(17), P. 4497 - 4497
Published: Sept. 7, 2024
With
the
wide
application
of
wind
energy
as
a
clean
source,
to
cope
with
challenge
increasing
maintenance
difficulty
brought
about
by
development
large-scale
power
equipment,
it
is
crucial
monitor
operating
status
turbines
in
real
time
and
accurately
identify
specific
location
faults.
In
this
study,
CNN-LSTM-based
motor
fault
detection
model
constructed
for
four
types
typical
faults,
namely
gearbox
electrical
yaw
pitch
faults
motors,
combining
CNN’s
advantages
excelling
feature
extraction
LSTM’s
dealing
long-time
sequence
data,
achieve
simultaneous
multiple
types.
The
accuracy
turbine
reaches
90.06%,
optimal
results
are
achieved
effective
discovery
system
obtaining
94.09%,
96.46%,
97.39%,
respectively.
CNN-LSTM
proposed
study
improves
effect,
avoids
further
deterioration
provides
direction
preventive
maintenance,
reduces
downtime
loss
due
restorative
essential
sustainable
use
service
life,
which
helps
improve
operation
level
farms.
Language: Английский
Impact contact mechanical characteristics assessment of piezoelectric material using the semi-analytical method
Yingying Lin,
No information about this author
Yuxing Wang,
No information about this author
Xinte Wang
No information about this author
et al.
Mathematics and Mechanics of Solids,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 10, 2024
The
objective
of
this
paper
is
to
study
the
impact
mechanical
performance
piezoelectric
materials.
Therefore,
three-dimensional
frictionless
contact
between
a
half-space
and
conducting
rigid
impactor
investigated.
A
semi-analytical
model
developed
based
on
second-order
Newmark
method
discrete
convolution-fast
Fourier
transform
algorithm.
unknown
reaction
force
impactors
obtained
by
exploiting
conjugate
gradient
dichotomy
method.
detailed
parametric
investigation
conducted
different
types
explore
influences
several
parameters,
including
electric
charge
density,
time
step,
velocity.
results
reveal
that
velocity
density
have
significant
effects
response
material.
Higher
densities
lead
smaller
force,
but
larger
deformation.
insights
gained
from
can
be
applied
analyze
charged
particles
arbitrary
shape
Language: Английский