Denoising of fiber grating sensor signals based on threshold retention orthogonal matching pursuit

Xiangxin Shao; Qing Lei; Hong Jiang; Hanbo Ye

doi:10.1117/12.2687099

6 August 2023 Denoising of fiber grating sensor signals based on threshold retention orthogonal matching pursuit

Xiangxin Shao, Qing Lei, Hong Jiang, Hanbo Ye

Proceedings Volume 12781, International Conference on Optoelectronic Information and Functional Materials (OIFM 2023); 1278126 (2023) https://doi.org/10.1117/12.2687099
Event: 2023 International Conference on Optoelectronic Information and Functional Materials (OIFM 2023), 2023, Guangzhou, JS, China

Abstract

Aiming at the noise signal caused by external environment and sensor reuse in the demodulation system of large capacity fiber grating sensor network, a Threshold Retained Orthogonal Matching Pursuit (TROMP) reconstruction algorithm is proposed based on compressed sensing theory. In this algorithm, the useful signal can be effectively recovered from the noise signal by improving the threshold setting, atom selection and iteration stop condition. Experiments show that: TROMP algorithm can achieve ideal denoising and reconstruction effect under less observation value, the SNR of the system is increased by 10 dB, the root mean square error is less than 0.0071, and the number of cross-relations can reach 0.9999. Compared with similar algorithms, the running time is shortened by more than half, and the comprehensive performance of noise signal processing for FBG sensor system is better than other reconstruction algorithms.

Citation Download Citation

Xiangxin Shao, Qing Lei, Hong Jiang, and Hanbo Ye "Denoising of fiber grating sensor signals based on threshold retention orthogonal matching pursuit", Proc. SPIE 12781, International Conference on Optoelectronic Information and Functional Materials (OIFM 2023), 1278126 (6 August 2023); https://doi.org/10.1117/12.2687099

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KEYWORDS

Reconstruction algorithms

Signal to noise ratio

Denoising

Interference (communication)

Sensors

Matrices

Signal processing

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