2023
DOI: 10.3390/s23062874
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Directional Torsion Sensor Based on a Two-Core Fiber with a Helical Structure

Abstract: A fiber-optic torsion sensor based on a helical two-core fiber (HTCF) is proposed and experimentally demonstrated for simultaneously measuring torsion angle and torsion direction. The sensor consists of a segment of HTCF and two single-mode fibers (SMFs) forming a Mach–Zehnder interferometer (MZI). The helical structure is implemented by pre-twisting a 1 cm long two-core fiber (TCF). The performance of the sensor with pre-twisted angles of 180°, 360°, and 540° is experimentally analyzed. The results show that … Show more

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Cited by 9 publications
(2 citation statements)
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“…They also calibrated the sensor's temperature properties, and the sensitivity was attained at 32 pm/ • C, which means that the tapered CTMCF can eliminate the cross-sensitivity to temperature. Song also demonstrated this characteristic of CTMCF via experimental verification [89]. Xiang utilized the CO 2 laser method to fabricate an LPG from a twisted MCF, which also demonstrated low-temperature cross-sensitivity [29].…”
Section: Chiral Twisted Multicore Fibersmentioning
confidence: 88%
“…They also calibrated the sensor's temperature properties, and the sensitivity was attained at 32 pm/ • C, which means that the tapered CTMCF can eliminate the cross-sensitivity to temperature. Song also demonstrated this characteristic of CTMCF via experimental verification [89]. Xiang utilized the CO 2 laser method to fabricate an LPG from a twisted MCF, which also demonstrated low-temperature cross-sensitivity [29].…”
Section: Chiral Twisted Multicore Fibersmentioning
confidence: 88%
“…This model included a material constant, denoted as 'G' in [24], and it was calculated experimentally. Such an approach has limitations when it comes to representing the twist, considering the non-linear nature of the strain vs. twist angle [74]. In addition, testing bending along with the twist requires calculating the material constant for each curvature.…”
Section: Model Validationmentioning
confidence: 99%