Synchronized Measurement of Electromechanical Responses of Fabric Strain Sensors Under Large Deformation
DOI:
https://doi.org/10.47852/bonviewSWT52026022Keywords:
synchronized measurement, fabric strain sensor, electromechanical behavior, dynamic loading, large deformationAbstract
Fabric-based strain sensors hold significant potential across various applications, including sports, healthcare, rehabilitation, etc. Nonetheless, their complex performance under large deformation and varying loading rates, arising from material viscoelasticity and textile structure intricacies, remains inadequately understood. The primary constraint in evaluating their performance lies in the absence of electromechanically coupled instrumentation. This paper endeavors to overcome the limitation by developing a synchronized measurement system, which integrates mechanically controlled loading, voltage divider circuits, and visual measurement technologies. This system enables synchronized acquisition of mechanical and electrical signals spanning from 0.01 mm/min to 6 m/s, by employing material testing machines for low-speed loading and split Hopkinson pressure bars for medium-to-high-speed loading, and combining electrical performance measurements with displacement and strain field analyses. Experiments revealed that sensor sensitivity increased linearly with the logarithm of loading rates, while deformation patterns evolved with loading speed, thereby offering valuable insights into design and calibration of fabric-based strain sensors under dynamic conditions.
Received: 27 April 2025 | Revised: 11 June 2025 | Accepted: 26 June 2025
Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.
Data Availability Statement
Data are available on request from the corresponding author upon reasonable request.
Author Contribution Statement
Bao Yang: Conceptualization, Methodology, Formal analysis, Resources, Writing – original draft, Writing – review & editing, Supervision, Project administration, Funding acquisition. Xianyu Zhu: Software, Formal analysis, Data curation, Writing – original draft. Chang Peng: Software, Validation, Formal analysis, Investigation, Data curation, Visualization. Licheng Zhou: Conceptualization, Methodology, Resources, Writing – review & editing, Supervision, Funding acquisition. Fei Wang: Conceptualization, Methodology, Resources, Writing – original draft, Writing – review & editing, Supervision, Funding acquisition. Zejia Liu: Conceptualization, Methodology, Resources, Supervision, Project administration, Funding acquisition. Liqun Tang: Conceptualization, Methodology, Resources, Supervision, Funding acquisition. Zhenyu Jiang: Conceptualization, Methodology, Resources, Supervision, Funding acquisition. Yiping Liu: Conceptualization, Methodology, Resources, Supervision, Funding acquisition. Senxin Chen: Software, Validation, Investigation.
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Funding data
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National Natural Science Foundation of China
Grant numbers 12472179 -
Natural Science Foundation of Guangdong Province
Grant numbers 2024A1515011076 -
Natural Science Foundation of Guangdong Province
Grant numbers 2025A1515011999 -
Natural Science Foundation of Guangdong Province
Grant numbers 2023A1515012942 -
National Natural Science Foundation of China
Grant numbers 12432008 -
National Natural Science Foundation of China
Grant numbers 12472180 -
National Natural Science Foundation of China
Grant numbers 12372181