NIR fibre Bragg grating as dynamic sensor: an application of 1D digital wavelet analysis for signal denoising | Zendy

Z. M. Hafizi | Zendy; Gayan Kahandawa | Zendy; Jayantha Epaarachchi‎ | Zendy; Kin-tak Lau | Zendy; John Canning | Zendy; K. Cook | Zendy

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NIR fibre Bragg grating as dynamic sensor: an application of 1D digital wavelet analysis for signal denoising

Author(s) -

Z. M. Hafizi,

Gayan Kahandawa,

Jayantha Epaarachchi‎,

Kin-tak Lau,

John Canning,

K. Cook

Publication year - 2013

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.2026668

Subject(s) - fiber bragg grating , wavelet , dynamic range , noise reduction , signal (programming language) , signal processing , computer science , noise (video) , materials science , detector , digital signal processing , wavelength , wavelet transform , signal to noise ratio (imaging) , optics , acoustics , optoelectronics , telecommunications , artificial intelligence , physics , computer vision , computer hardware , image (mathematics) , programming language

During the past decade, many successful studies have evidently shown remarkable capability of Fiber Bragg Gratings (FBG) sensor for dynamic sensing. Most of the research works utilized the 1550 nm wavelength range of FBG sensors. However near infra-red (NIR) FBG sensors can offer the lower cost of Structural health Monitoring (SHM) systems which uses cheaper silicon sources and detectors. Unfortunately, the excessive noise levels that experienced in NIR wavelengths have caused the rejection of sensor that operating in this range of wavelengths for SHM systems. However, with the appropriate use of signal processing tools, these noisy signals can be easily 'cleaned'. Wavelet analysis is one of the powerful signal processing tools nowadays, not only for time-frequency analysis but also for signal denoising. This present study revealed that the NIR FBG range gave good response to impact signals. Furthermore, these 'noisy' signals' response were successfully filtered using one dimensional wavelet analysis.

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