journal article·2020-11

Knitted piezoresistive strain sensor performance, impact of conductive area and profile design

Rafiu K Raji, Xuhong Miao, Shu Zhang, Yutian Li, Ailan Wan, Andrews Boakye

Journal of Industrial Textiles· Volume 50· Issue 5
Publisher page

Abstract

While many of the factors influencing strain sensor properties have been explained in literature, other very important parameters that influence actual design performance of sensors remain obscure. This paper investigates the impact of conductive profile and area design including post fabric treatments such as dyeing and washing on sensor performance. 1 × 1 mock rib was the fabric structure of choice, and silver-plaited nylon was the conductive yarn used in knitting all the samples. Six main polygonal shapes including ellipse, diamond shape, corrugated rectangular shape, rectangular horse shoe, rectangular dough roller shape, and plain rectangular shape were designed and knitted. Plain rectangular profile has been found to deliver the best results characterized by noiseless signals, highest gauge factor, and good result repeatability. The analysis of results also reveals a positive linear correlation between conductive path and initial electrical resistance of a sensor. The inverse is true for the relation between the conductive width values and their corresponding initial resistances. Higher conductive widths led to low initial resistance, and values less than 20 Ω for a sensor could lead to inferior sensor sensitivity. High conductive paths produced high initial resistances, and values within the range of 40–120 Ω could deliver higher sensitivity. This study thus concludes that the optimum aspect ratio range for conductive area to deliver satisfactory sensitivity results is approximately between 24:1 and 77:1 cm. Laundry and dyeing have also been found to result in reduced sensor dimensions, resistance, and sensitivity levels.
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Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Smart Materials for Construction · Advanced MEMS and NEMS Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Textiles and Clothing, Jiangnan University, China

Funding

Science Foundation of Jiangsu Province · Fundamental Research Funds for the Central Universities

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