Enhancing the Accuracy of Triboelectric Sensor Based on Triboelectric Material/Electrode Interface Design Strategy
Nano Energy,
Journal Year:
2025,
Volume and Issue:
unknown, P. 110922 - 110922
Published: March 1, 2025
Language: Английский
Enhanced wind energy harvesting performance of triboelectric-electromagnetic hybrid generator via whale fin blades and speed matching
Nano Energy,
Journal Year:
2024,
Volume and Issue:
unknown, P. 110615 - 110615
Published: Dec. 1, 2024
Language: Английский
Triboelectric-electromagnetic hybrid generator with bionic dolphin blade for enhanced wind energy harvesting
Chemical Engineering Journal,
Journal Year:
2025,
Volume and Issue:
unknown, P. 161036 - 161036
Published: Feb. 1, 2025
Language: Английский
Tree leaf-inspired magnetic nanogenerator for energy harvesting and potential sensing applications
Measurement,
Journal Year:
2025,
Volume and Issue:
unknown, P. 117213 - 117213
Published: March 1, 2025
Language: Английский
Stretchable and Sustainable Paper-based Modular Circuits
Nano Energy,
Journal Year:
2025,
Volume and Issue:
unknown, P. 111153 - 111153
Published: May 1, 2025
Language: Английский
Feature‐Reinforced Strategy for Enhancing the Accuracy of Triboelectric Vibration Sensing Toward Mechanical Equipment Monitoring
Junjun Huang,
No information about this author
Yuting Zong,
No information about this author
Yue Liu
No information about this author
et al.
Small,
Journal Year:
2025,
Volume and Issue:
unknown
Published: May 24, 2025
Abstract
With
the
advancement
of
intelligent
and
refined
manufacturing,
demand
for
vibration
sensors
in
smart
equipment
has
surged.
Traditional
commercial
triboelectric
nanogenerator
(TENG)‐based
are
limited
to
basic
amplitude
frequency
recognition,
failing
address
both
self‐powering
diagnostic
needs
due
inherent
design
constraints.
To
overcome
these
limitations,
this
study
introduces
a
novel
mechanism
combining
interface
dipole
energy
vacuum
level
optimization
materials
explain
charge
generation
separation
under
vibration.
A
TENG
device
with
polydimethylsiloxane
(PDMS)‐encapsulated
metal
electrode
is
designed
developed,
enabling
precise
recognition
operating
status
through
waveform
analysis.
By
optimizing
contact
area
electron
transfer
capacity,
achieves
enhanced
signal
clarity
introduction
subtler
characteristics
waveform.
Furthermore,
integration
deep
learning
algorithm
enables
high‐resolution
classification
states
an
accuracy
98.3%
approximately,
achieving
effective
monitoring
jaw
crusher
vibrating
screen.
This
work
not
only
verifies
feasibility
designing
self‐powered
sensor
but
also
demonstrates
its
potential
real‐time
applications
equipment.
Language: Английский