Applied Sciences,
Год журнала:
2024,
Номер
14(18), С. 8229 - 8229
Опубликована: Сен. 12, 2024
This
paper
combines
self-organizing
mapping
(SOM)
and
a
long
short-term
memory
network
(SOM-LSTM)
to
construct
an
audio-based
motor-fault
diagnosis
system
for
identifying
the
operating
states
of
rotary
motor.
first
uses
audio
signal
collector
measure
motor
sound
data,
fast
Fourier
transform
(FFT)
convert
actual
measured
sound–time-domain
into
frequency-domain
signal,
normalizes
calibrates
ensure
consistency
accuracy
signal.
Secondly,
SOM
is
used
further
analyze
characterized
waveforms
in
order
reveal
intrinsic
structure
pattern
data.
The
LSTM
process
secondary
data
generated
via
SOM.
Dimensional
aggregation
prediction
sequence
long-term
dependencies
accurately
identify
different
possible
abnormal
patterns.
also
experimental
design
Taguchi
method
optimize
parameters
SOM-LSTM
increase
execution
efficiency
fault
diagnosis.
Finally,
applied
real-time
monitoring
operation,
work
type
performed,
tests
under
loads
environments
are
attempted
evaluate
its
feasibility.
completion
this
provides
diagnostic
strategy
that
can
be
followed
when
it
comes
faults.
Through
system,
conditions
equipment
detected,
which
help
with
preventive
maintenance,
make
more
efficient
save
lot
time
costs,
improve
industry’s
ability
monitor
operation
information.
Nuclear Engineering and Technology,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 1, 2024
Optimizing
the
hydraulic
components
of
nuclear
main
pump
(NMP)
and
conducting
performance
verification
is
crucial.
Due
to
large
size
real
NMP,
strict
requirements
operation
high
test-cost,
there
are
many
difficulties
in
test.
The
mixed
flow
NMP
taken
as
research
object,
CAP1400
selected
prototype
(PP).
model
pumps
(MPs)
with
varying
scales
established
based
on
similarity
conversion
algorithm
(SCA).
Then,
influence
different
internal
field
investigated
compared.
It
demonstrated
that
predicted
value
head
4
%
higher
than
design
at
operating
point,
maximum
efficiency
point
close
point.
In
range
full
conditions,
head,
efficiency,
impeller
guide
vane
energy
loss,
field,
vorticity
distribution
PP
MPs
basically
consistent
trend
rate
variations.
conform
SCA.
optimization
achieved
by
using
proportional
scaling
approach.
Journal of Marine Science and Engineering,
Год журнала:
2024,
Номер
12(9), С. 1589 - 1589
Опубликована: Сен. 8, 2024
The
dual-input
single-output
(DI-SO)
cylindrical
spur
gear
system
possesses
advantages
such
as
high
load-carrying
capacity,
precise
transmission,
and
low
energy
loss.
It
is
increasingly
becoming
a
core
component
of
power
transmission
systems
in
maritime
vessels,
aerospace,
marine
engineering,
construction
machinery.
In
practical
operation,
the
stability
DI-SO
influenced
by
complex
excitations.
These
excitations
lead
to
nonlinear
vibration,
meshing
instability,
noise,
which
affect
performance
reliability
entire
equipment.
Hence,
dynamic
thoroughly
investigated
this
research.
impact
factors
on
characteristics
was
comprehensively.
A
comparative
analysis
conducted
establishing
bending–torsional
coupling
vibration
model
under
synchronous
asynchronous
conditions.
Nonlinear
periodic
time-varying
stiffness,
damping,
friction
coefficient,
arms,
load
sharing
ratio,
comprehensive
error,
backlash
were
considered
proposed
model.
Then,
effect
laws
frequency,
driving
fluctuation,
backlash,
error
analyzed.
results
indicate
that
exhibited
staged
stable
unstable
states
different
frequencies
At
medium-frequency
stage
(0.96
×
104~1.78
104
Hz),
alternating
phenomena
multi-periodic,
quasi-periodic,
chaotic
motion
observed.
Moreover,
root
mean
square
value
(RMS)
(DTE)
asynchronized
generally
higher
than
synchronized
system.
found
selecting
appropriate
condition
could
effectively
reduce
amplitude
DTE.
Additionally,
be
significantly
improved
adjusting
control
parameters
fluctuation
(0~179
N),
(0.8
10−4~0.9
10−4
m),
(7.9
10−4~9.4
m).
research
provide
theoretical
guidance
for
design
optimization
Applied Sciences,
Год журнала:
2024,
Номер
14(18), С. 8229 - 8229
Опубликована: Сен. 12, 2024
This
paper
combines
self-organizing
mapping
(SOM)
and
a
long
short-term
memory
network
(SOM-LSTM)
to
construct
an
audio-based
motor-fault
diagnosis
system
for
identifying
the
operating
states
of
rotary
motor.
first
uses
audio
signal
collector
measure
motor
sound
data,
fast
Fourier
transform
(FFT)
convert
actual
measured
sound–time-domain
into
frequency-domain
signal,
normalizes
calibrates
ensure
consistency
accuracy
signal.
Secondly,
SOM
is
used
further
analyze
characterized
waveforms
in
order
reveal
intrinsic
structure
pattern
data.
The
LSTM
process
secondary
data
generated
via
SOM.
Dimensional
aggregation
prediction
sequence
long-term
dependencies
accurately
identify
different
possible
abnormal
patterns.
also
experimental
design
Taguchi
method
optimize
parameters
SOM-LSTM
increase
execution
efficiency
fault
diagnosis.
Finally,
applied
real-time
monitoring
operation,
work
type
performed,
tests
under
loads
environments
are
attempted
evaluate
its
feasibility.
completion
this
provides
diagnostic
strategy
that
can
be
followed
when
it
comes
faults.
Through
system,
conditions
equipment
detected,
which
help
with
preventive
maintenance,
make
more
efficient
save
lot
time
costs,
improve
industry’s
ability
monitor
operation
information.
