Smart Clothing with Built‐In Soft Sensing Network for Measuring Temporal and Spatial Distribution of Pressure under Impact Scenarios. Issue 2 (4th December 2022)

• Record Type: Journal Article
• Authors: Wang, Fei; Zhu, Bo; Shu, Lin; Li, Ying; Lai, Xinghua; Ma, Lingchen; Ji, Peijun; Zhou, Qing; Yu, Tongxi; Tao, Xiaoming
• Is Part Of: ADVANCED SENSOR RESEARCH. Volume 2:Issue 2(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-04
• Subjects: crash dummies -- impact tests -- in situ measurement -- pressure sensors -- smart clothing -- strain rate; 681.2
• DOI: 10.1002/adsr.202200019
• Languages: English
• ISSNs: 2751-1219

Abstract

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 study 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. Abstract : For the first time, this research uses a smart clothing to acquire the in situ and quantitative values of pressure distribution between the seat belts, seat cushion, and the dummy in a standard sled crash test. The smart clothing with soft pressure sensing network can be used in real‐time pressure mapping of a 3D flexible man–machine interface under impact scenarios.