Shape Sensing with Rayleigh Backscattering Fibre Optic Sensor

被引:12
|
作者
Xu, Cheng [1 ]
Sharif Khodaei, Zahra [1 ]
机构
[1] Imperial Coll London, Dept Aeronaut, London SW7 2AZ, England
关键词
fibre optic sensors; Rayleigh backscattering sensors; shape sensing; structural health monitoring; SPECTRUM;
D O I
10.3390/s20144040
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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.
引用
收藏
页码:1 / 19
页数:19
相关论文
共 50 条
  • [21] Self aligning fibre for a fibre optic voltage sensor
    Hambley, P.
    Michie, A.
    Bassett, I.
    Henry, P.
    Ingram, J.
    19TH INTERNATIONAL CONFERENCE ON OPTICAL FIBRE SENSORS, PTS 1 AND 2, 2008, 7004
  • [22] Modified sensing element of a fibre-optic current sensor based on a low-eigenellipticity spun fibre
    Przhiyalkovsky, Ya. V.
    Morshnev, S. K.
    Starostin, N. I.
    Gubin, V. P.
    QUANTUM ELECTRONICS, 2014, 44 (10) : 957 - 964
  • [23] Field examples for optical fibre sensor condition diagnostics based on distributed fibre-optic strain sensing
    Kusche, Nadine
    Schukar, Vivien
    Hofmann, Detlef
    Basedau, Frank
    Habel, Wolfgang
    Woschitz, Helmut
    Lienhart, Werner
    FIFTH EUROPEAN WORKSHOP ON OPTICAL FIBRE SENSORS, 2013, 8794
  • [24] Fibre optic sensing for underground mining
    Samson, Peter J.
    Australian Journal of Instrumentation and Control, 1992, 7 (02):
  • [25] Differential fibre optic sensing and switching
    Indian J Pure Appl Phys, 10 (823):
  • [26] Hybrid Distributed Fiber-Optic Sensing System by Using Rayleigh Backscattering Lightwave as Probe of Stimulated Brillouin Scattering
    Huang, Linjing
    Fan, Xinyu
    He, Zuyuan
    JOURNAL OF LIGHTWAVE TECHNOLOGY, 2023, 41 (13) : 4374 - 4380
  • [27] Distributed crack width measurement in concrete structures using fibre-optic sensor technology - New application of distributed fibre optic sensing
    Vorwagner, Alois
    Kwapisz, Maciej
    Lienhart, Werner
    Winkler, Madeleine
    Monsberger, Christoph
    Prammer, Dominik
    BETON- UND STAHLBETONBAU, 2021, 116 (10) : 727 - 740
  • [28] Fibre-optic sensor boom
    不详
    PROFESSIONAL ENGINEERING, 1998, 11 (07) : 9 - 9
  • [29] Fibre optic current sensor network
    Goyal, S.
    Irvine-Halliday, D.
    Thomson, R.M.
    Shelley, J.T.
    Canalizo, A.E.
    Journal of Electrical and Electronics Engineering, Australia, 1998, 18 (03): : 197 - 204
  • [30] Segmental Sensor Weighting Accuracy Evaluation Method for Fiber Optic Shape Sensing
    Yang, Zidong
    Liu, Shidi
    Yang, Tianyu
    Wu, Guolong
    Liang, Yan
    Dong, Yuming
    IEEE SENSORS JOURNAL, 2023, 23 (22) : 27307 - 27315