Abstract
Nowadays, the need for protective devices at man–machine interfaces is
increasing in the fields of traffic, sports, construction, and military, etc.
Dynamic pressure sensing technology with wide measuring range, high
sensitivity, softness, and fast response is crucial for evaluation and
optimization of the personal protective equipment under impact scenarios.
However, current sensors hardly possess all the aforesaid required
characteristics. For the first time, this article reports the evaluation and
application of an innovative soft pressure sensor with modulus of 2 MPa,
maximum pressure of 8 MPa, and over 500-Hz frequency. A theoretical model,
taking strain rate into consideration, is established to characterize the
dynamic sensing behavior. A sensing network in the form of smart clothing is
developed and used in a sled crash test, which is a standard approach to
evaluate the safety of automobiles in collisions. The pressure distribution over
the dummy’s surface during the crash is acquired in real-time, and compared
with numerical simulations. This work is important to the study of occupant
injury and crashworthiness design for vehicles, and it will benefit the
automotive industry. With the built-in sensing network, the smart clothing has
promising applications in the pressure mapping of 3D flexible man–machine
interface under impact scenarios.
increasing in the fields of traffic, sports, construction, and military, etc.
Dynamic pressure sensing technology with wide measuring range, high
sensitivity, softness, and fast response is crucial for evaluation and
optimization of the personal protective equipment under impact scenarios.
However, current sensors hardly possess all the aforesaid required
characteristics. For the first time, this article reports the evaluation and
application of an innovative soft pressure sensor with modulus of 2 MPa,
maximum pressure of 8 MPa, and over 500-Hz frequency. A theoretical model,
taking strain rate into consideration, is established to characterize the
dynamic sensing behavior. A sensing network in the form of smart clothing is
developed and used in a sled crash test, which is a standard approach to
evaluate the safety of automobiles in collisions. The pressure distribution over
the dummy’s surface during the crash is acquired in real-time, and compared
with numerical simulations. This work is important to the study of occupant
injury and crashworthiness design for vehicles, and it will benefit the
automotive industry. With the built-in sensing network, the smart clothing has
promising applications in the pressure mapping of 3D flexible man–machine
interface under impact scenarios.
| Original language | English |
|---|---|
| Article number | 2200019 |
| Journal | Advanced Sensor Research |
| Publication status | Published - 2022 |