Study on sliding-window length based on Rayleigh backscattering spectrum correlation in distributed optical-fiber strain measurement

Suo, Liujia; Lei, Zhenkun; Zhao, Shiyuan; Wu, Zhen; Takezawa, Akihiro

doi:10.1016/j.yofte.2018.11.030

Cited by 7 publications

(1 citation statement)

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“…This data size is definitely sufficient to offer a reliable cross-correlation analysis. However, research shows that a slide window with a data size around 300–400 can also perform strain sensing with sufficient reliability [ 25 ]. Other factors, including the nonlinear tuning of the light source, phase noise, polarization effects of the spectrum, noise in the measurement environment, as well as the error in bonding location will lead to a more severe error.…”

Section: Rayleigh Backscattering Sensing Systemmentioning

confidence: 99%

Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor

Khodaei

2020

Sensors

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In this paper, Rayleigh backscattering sensors (RBS) are used to realize shape sensing of beam-like structures. Compared to conventional shape sensing systems based on fibre Bragg grating (FBG) sensors, RBS are capable of continuous lateral sensing. Compared to other types of distributed fibre optic sensors (FOS), RBS have a higher spatial resolution. First, the RBS’s strain sensing accuracy is validated by an experiment comparing it with strain gauge response. After that, two shape sensing algorithms (the coordinate transformation method (CTM) and the strain-deflection equation method (SDEM)) based on the distributed FOS’ input strain data are derived. The algorithms are then optimized according to the distributed FOS’ features, to make it applicable to complex and/or combine loading situations while maintaining high reliability in case of sensing part malfunction. Numerical simulations are carried out to validate the algorithms’ accuracy and compare their accuracy. The simulation shows that compared to the FBG-based system, the RBS system has a better performance in configuring the shape when the structure is under complex loading. Finally, a validation experiment is conducted in which the RBS-based shape sensing system is used to configure the shape of a composite cantilever-beam-like specimen under concentrated loading. The result is then compared with the optical camera-measured shape. The experimental results show that both shape sensing algorithms predict the shape with high accuracy comparable with the optical camera result.

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Section: Rayleigh Backscattering Sensing Systemmentioning

confidence: 99%