4.7 Article

Modeling the stress and resistance relaxation of conductive composites-coated fabric strain sensors

期刊

COMPOSITES SCIENCE AND TECHNOLOGY
卷 204, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.compscitech.2021.108645

关键词

Fabrics/textiles; Polymer-matrix composites; Electro-mechanical behavior; Material modeling; Stress relaxation

资金

  1. National Natural Science Foundation of China [12002085, 51603039]
  2. Shanghai Pujiang Program
  3. Fundamental Research Funds for the Central Universities
  4. Key Laboratory of Textile Science and Technology (Donghua University)
  5. Initial Research Funds for Young Teachers of Donghua University
  6. Ministry of Education

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The mechanical model of fabric strain sensors based on carbon-particle-filled conductive polymer and knitted fabric substrate was established and implemented for predicting resistance response during relaxations. The predicted relative mean error of resistance was only 0.2%, with an average correlation of 0.9783 between predicted and measured resistance.
Electrical relaxation of flexible sensors using the conductive polymer composites as sensing materials has been constantly reported as major obstacle for accurate measurement, yet still roughly characterized by mechanical relaxation rather than an effective underlying mechanism. In this work, fabric strain sensors based on carbon-particle-filled conductive polymer and knitted fabric substrate were studied. A serial mechanical model of the sensor was established according to its structure, and then extended to an electromechanical model by introducing strain-resistance properties for mechanical elements. Methods were elaborated on extracting the mechanical, electrical and status parameters of the model. Tests were conducted on 5 randomly-chosen samples. The model was firstly determined for each sample using proposed methods and then implemented to predict resistance response during relaxations. Results show that the relative mean error of the predicted resistance was only 0.2%, with an averaged determination of fit 0.9230. The correlation between predicted and measured resistance was observed 0.9783 on average. Conclusion can be drawn that the model is effective to characterize the sensing mechanism and resistance relaxation of the fabric strain sensors.

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