Journal of Physics Conference Series,
Journal Year:
2024,
Volume and Issue:
2876(1), P. 012011 - 012011
Published: Nov. 1, 2024
Abstract
A
remote
monitoring
technique
for
gateway
electricity
meters
is
introduced
that
leverages
conservation
principles
of
electric
energy,
voltage,
and
current.
It
aims
to
tackle
issues
related
errors
in
energy
transformers
are
challenging
distinguish,
as
well
the
high
costs
associated
with
on-site
testing.
The
ridge
regression
used
solve
formulas
bus
power
current
obtain
metering
points’
error
loops’
error.
voltage
loop
determined
through
an
averaging
method,
which
then
calculate
meters.
consistency
method
synchronize
time
bias
between
meters,
ensuring
accurate
calculations.
analysis
results
indicate
proposed
effectively
monitors
operating
status
offers
greater
accuracy
compared
benchmarks.
This
can
timely
discover
suspected
inaccurate
aiding
their
maintenance
efficient
operation.
Applied Sciences,
Journal Year:
2025,
Volume and Issue:
15(7), P. 3824 - 3824
Published: March 31, 2025
The
main
purpose
of
this
study
is
to
estimate
the
welding
current
using
arc
light
signal
emitted
during
process.
Traditionally,
operators
determine
from
based
on
their
visual
perception.
This
shows
that,
artificial
intelligence
techniques,
can
be
automatically
estimated
through
and
also
useful
for
monitoring
process
detecting
its
disturbances.
For
purpose,
initially,
a
data
acquisition
system
designed
synchronize
movement
sensor
with
electrode
holder.
machine
set
different
maximum
levels,
two
electrodes
diameters
are
used
at
each
level.
During
process,
signals
acquired
simultaneously.
obtained
filtered
aligned
by
cross-correlation.
ANFIS
(adaptive
neuro-fuzzy
inference
system)
model,
defined
as
input
output.
estimation
results
further
improved
filtering,
shifting,
current-limiting
processes.
cross-correlation
values
training
testing
0.9587,
0.9598,
0.9565,
0.9323,
respectively,
while
R-squared
0.7033,
0.7640,
0.6449,
0.5853.
Compared
neural
network
(ANN)
it
observed
that
model
provides
better
prediction
results.
confirm
effectively
prediction.
Therefore,
proposed
approach
contribute
development
intelligent
systems
quality
processes
reducing
operator
dependency.
Sensors,
Journal Year:
2024,
Volume and Issue:
24(12), P. 3817 - 3817
Published: June 13, 2024
Marine
pipeline
vibration
condition
monitoring
is
a
critical
and
challenging
issue,
on
account
of
the
complex
marine
environment,
while
powering
required
sensors
remains
problematic.
This
study
introduces
sensor
based
ball
triboelectric
nanogenerator
(B-TENG)
for
pipelines
monitoring.
The
B-TENG
consists
an
acrylic
cube,
polyester
rope,
aluminum
electrodes,
PTFE
ball,
which
converts
signals
into
electrical
without
need
external
energy
supply.
experimental
results
show
that
can
accurately
monitor
frequency,
amplitude,
direction
in
range
1–5
Hz
with
small
error
0.67%,
4.4%,
5%,
accuracy
0.1
Hz,
0.97
V/mm,
1.5°,
respectively.
hermetically
sealed
underwater
environments.
Therefore,
be
used
as
cost-effective,
self-powered,
highly
accurate
