Quantitative Evaluation of Pseudo Strain Signals Caused by Yarn Structural Deformation

Shihui Lin; Leitao Cao; Zhuochen Lv; Jing Ren; Shengjie Ling

doi:10.1007/s42765-021-00101-y

Advanced Fiber Materials ›› 2021, Vol. 4 ›› Issue (2) : 214 -225. DOI: 10.1007/s42765-021-00101-y

Letter

Quantitative Evaluation of Pseudo Strain Signals Caused by Yarn Structural Deformation

Author information +

¹School of Physical Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, 201210, Shanghai, China

^e lingshj@shanghaitech.edu.cn

Shihui Lin

received her B.S. in Material Science and Engineering from ShanghaiTech University in China in 2018. She is currently a graduate student in the School of Physical Science and Technology (SPST) at ShanghaiTech University. Her research focuses on the mechanical properties and device application of natural fibers.

Leitao Cao

is currently a postdoctoral in the School of Physical Science and Technology (SPST) at ShanghaiTech University. He received his B. S. degree in Textile Engineering from Jiangnan University in 2013, and Ph. D. in Textile Materials and Textile design from Donghua University in 2020. His research focuses on the fabrication of natural materials-based nanofiber assemblies and their functional applications.

Zhuochen Lv

received his B. S. degree in Material Science and Engineering from ShanghaiTech University in 2020. He is now a graduate student in the School of Physical Science and Technology (SPST) of ShanghaiTech University. His researches focus on the structure-property relationship of natural fibers.

Jing Ren

is currently a Research Assistant Professor in the School of Physical Science and Technology at ShanghaiTech University. She received her B.S. in Chemistry at Lanzhou University in China in 2007, Ph.D. in Macromolecular Chemistry and Physics at Fudan University in China in 2016. She then worked at Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine before joining ShanghaiTech University in 2018. She focuses on the development of functional natural materials for wearable applications.

Shengjie Ling

is an assistant professor in the School of Physical Science and Technology at ShanghaiTech University. His research focuses on developing biopolymer functional materials through the integration of synchrotron-based characterization, computational modeling and bioinspired & biomimetic fabrication. He obtained his B.S. degree from the Zhejiang University of Technology (2009) and Ph.D. from Fudan University (2014). During 2012–2013, He awarded the State Scholarship Fund of China to pursue his study at ETH Zurich, Switzerland, as a joint Ph.D. student. Before joining ShanghaiTech University, he worked as a postdoctoral associate at MIT and Tufts University (2014–2017).

Show less

History +

PDF

Abstract

Yarn-based strain sensors (YSSs) have shown great promising in the fabrication of wearable devices for their good comfortability and flexible designability. However, the false signals generated by the changes in the yarn structure of the YSSs are usually ignored. In this study, the generation, the characteristic, and the prediction of these signals were investigated. We recognized that these signals are composed of two negative pseudo peaks and a spurious resistance response plateau. These responses are found to have nothing in common with a true tensile strain, but be attributed to plastic deformation of the fibers. This is due to the fact that the deformation of YSSs exceeds the linear elastic range of the fibers. Although the use of pure elastic fibers can eliminate the spurious resistance response plateau, it will lead to an increase in the pseudo peak to the value compared with a true strain signal peak. Hence, a theoretical model was established to decouple the real signals from the false responses, ensuring the high sensing accuracy of YSSs for applications in wearable devices and artificial intelligence interfaces. This work provides an in-depth understanding of the response of the YSSs, which might provide inspiration and guidance in the design of high-accuracy fiber-based strain sensors.

Cite this article

Download citation ▾

Shihui Lin, Leitao Cao, Zhuochen Lv, Jing Ren, Shengjie Ling. Quantitative Evaluation of Pseudo Strain Signals Caused by Yarn Structural Deformation. Advanced Fiber Materials, 2021, 4(2): 214-225 DOI:10.1007/s42765-021-00101-y