Journal of Marine Science and Engineering,
Год журнала:
2023,
Номер
11(3), С. 616 - 616
Опубликована: Март 14, 2023
Hydraulic
axial
piston
pumps
are
the
power
source
of
fluid
systems
and
have
important
applications
in
many
fields.
They
a
compact
structure,
high
efficiency,
large
transmission
power,
excellent
flow
variable
performance.
However,
crucial
components
easily
suffer
from
different
faults.
It
is
therefore
to
investigate
precise
fault
identification
method
maintain
reliability
system.
The
use
deep
models
feature
learning,
data
mining,
automatic
identification,
classification
has
led
development
novel
diagnosis
methods.
In
this
research,
typical
faults
wears
friction
pairs
were
analyzed.
Different
working
conditions
considered
by
monitoring
outlet
pressure
signals.
To
overcome
low
efficiency
time-consuming
nature
traditional
manual
parameter
tuning,
Bayesian
algorithm
was
introduced
for
adaptive
optimization
an
established
learning
model.
proposed
can
explore
potential
information
signals
adaptively
identify
main
types.
average
diagnostic
accuracy
found
reach
up
100%,
indicating
ability
detect
with
precision.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Янв. 7, 2025
Industry
4.0
represents
the
fourth
industrial
revolution,
which
is
characterized
by
incorporation
of
digital
technologies,
Internet
Things
(IoT),
artificial
intelligence,
big
data,
and
other
advanced
technologies
into
processes.
Industrial
Machinery
Health
Management
(IMHM)
a
crucial
element,
based
on
(IIoT),
focuses
monitoring
health
condition
machinery.
The
academic
community
has
focused
various
aspects
IMHM,
such
as
prognostic
maintenance,
monitoring,
estimation
remaining
useful
life
(RUL),
intelligent
fault
diagnosis
(IFD),
architectures
edge
computing.
Each
these
categories
holds
its
own
significance
in
context
In
this
survey,
we
specifically
examine
research
RUL
prediction,
edge-based
architectures,
diagnosis,
with
primary
focus
domain
diagnosis.
importance
IFD
methods
ensuring
smooth
execution
processes
become
increasingly
evident.
However,
most
are
formulated
under
assumption
complete,
balanced,
abundant
often
does
not
align
real-world
engineering
scenarios.
difficulties
linked
to
classifications
IMHM
have
received
noteworthy
attention
from
community,
leading
substantial
number
published
papers
topic.
While
there
existing
comprehensive
reviews
that
address
major
challenges
limitations
field,
still
gap
thoroughly
investigating
perspectives
across
complete
To
fill
gap,
undertake
survey
discusses
achievements
domain,
focusing
IFD.
Initially,
classify
three
distinct
perspectives:
method
processing
aims
optimize
inputs
for
model
mitigate
training
sample
set;
constructing
model,
involves
designing
structure
features
enhance
resilience
challenges;
optimizing
training,
refining
process
models
emphasizes
ideal
data
process.
Subsequently,
covers
techniques
related
prediction
edge-cloud
resource-constrained
environments.
Finally,
consolidates
outlook
relevant
issues
explores
potential
solutions,
offers
practical
recommendations
further
consideration.
Applied Energy,
Год журнала:
2024,
Номер
372, С. 123773 - 123773
Опубликована: Июнь 26, 2024
This
paper
proposes
a
novel
method
namely
WaveletKernelNet-Convolutional
Block
Attention
Module-BiLSTM
for
intelligent
fault
diagnosis
of
drilling
pumps.
Initially,
the
random
forest
is
applied
to
determine
target
signals
that
can
reflect
characteristics
Accordingly,
Module
Net
constructed
noise
reduction
and
feature
extraction
based
on
signals.
The
Convolutional
embedded
in
WaveletKernelNet-CBAM
adjusts
weight
enhances
representation
channel
spatial
dimension.
Finally,
Bidirectional
Long-Short
Term
Memory
concept
introduced
enhance
ability
model
process
time
series
data.
Upon
constructing
network,
Bayesian
optimization
algorithm
utilized
ascertain
fine-tune
ideal
hyperparameters,
thereby
ensuring
network
reaches
its
optimal
performance
level.
With
hybrid
deep
learning
presented,
an
accurate
real
five-cylinder
pump
carried
out
results
confirmed
applicability
reliability.
Two
sets
comparative
experiments
validated
superiority
proposed
method.
Additionally,
generalizability
verified
through
domain
adaptation
experiments.
contributes
safe
production
oil
gas
sector
by
providing
robust
industrial
equipment.
