Reliable self-healing FBG sensor network for improvement of multipoint strain sensing

Autor: Stotaw Talbachew Hayle, Amare Mulatie Dehnaw, Hsing-Chin Liang, Yuan-Ta Hsu, Y. C. Manie, Peng-Chun Peng, Jyun-Wei Li
Rok vydání: 2021
Předmět:
Zdroj: Optics Communications. 499:127286
ISSN: 0030-4018
Popis: In this paper, we proposed and designed reliable self-healing fiber Bragg grating (FBG) sensor network for improvement of multipoint strain sensing. We use an optical switch (OSW) to reconfigure the sensor network and improve the self-healing function during fault happen in the sensor network. In this work, to prove and validate the detection performance of our proposed Bragg wavelength detection technique even when the number of overlap spectra of FBGs increases, we conduct three experiments and collect three different cases of strain data (namely case 1, case 2, and case 3) by applying different strain steps to FBGs. In case 1 experiment, strain was applied to only FBG1 sensor, while the other four FBGs keeps fixed. In case 2 experiment, strain was applied to FBG1 and FBG2 sensors at the same time and with different strain steps. In case 3 experiment, strain was applied to FBG1, FBG2 and FBG3 sensors at the same time and with different strain steps. As a result, in all cases of the experiment, three situations of spectra were introduced between FBGs like non-overlapped, partially overlapped and completely overlapped spectra. To solve this overlap problem, we used deep learning technique to accurately identify the Bragg wavelength of FBGs in the condition of the partially or fully overlapped spectra. Therefore, our proposed FBG sensor system can improve the reliability and detection accuracy of the sensor system even the number of overlaps FBGs spectra increases.
Databáze: OpenAIRE
Externí odkaz: