Peak-Detection Algorithm in the Demodulation for the Fiber Bragg Grating Sensor System

Haohan, 朱浩瀚 Zhu; Haikun, 秦海琨 Qin; Min, 张敏 Zhang; Shurong, 赖淑蓉 Lai; Yanbiao, 廖延彪 Liao

doi:10.3788/cjl20083506.0893

Cited by 7 publications

(2 citation statements)

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“…Currently, there are several peak detection algorithms for FBG including direct peak detection, general polynomial fitting algorithm, centroid method, Gaussian fitting algorithm, genetic algorithm, and Steger-based peak detection algorithm. [5][6][7] Among them, direct peak detection and centroid method have low computational complexity and short response time, but their applicability is limited, and they have weak noise resistance. The general polynomial fitting algorithm is simple to implement, but it has limited peak detection accuracy and requires high spectral shape requirements.…”

Section: Introductionmentioning

confidence: 99%

Adaptive multi-peak demodulation algorithm for distributed fiber Bragg grating sensing systems based on Hilbert transform

Wan,

Yang,

Lou

et al. 2023

AOPC 2023: Optic Fiber Gyro

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To mitigate the failure of a Hilbert transform-based fixed-threshold multi-peak demodulation algorithm in distributed Fiber Bragg Grating (FBG) sensing systems with light noise, an adaptive multi-peak demodulation algorithm based on the Hilbert transform is proposed in this paper. The algorithm adopts the thought of Divide and Conquer, including reflection spectrum segmentation and single peak detection. Multiple sub-spectra of the FBG multi-peak spectrum is segmented by the Hilbert transform and calculating adaptive threshold method, and then the Gaussian fitting algorithm is used to achieve the precise positioning of the spectral peaks. Theoretical analyses and simulation results show that the algorithm using an adaptive threshold as a threshold of splitter can greatly improve the portability of the algorithm in complex situations, and improve the algorithm's noise resistance, demodulation speed, and accuracy. It shows that the algorithm provides a new way of demodulation for distributed FBG sensing systems.

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Section: Introductionmentioning

confidence: 99%

Adaptive multi-peak demodulation algorithm for distributed fiber Bragg grating sensing systems based on Hilbert transform

Wan,

Yang,

Lou

et al. 2023

AOPC 2023: Optic Fiber Gyro

View full text Add to dashboard Cite

show abstract

“…To solve the problem, several demodulation algorithms such as the broadband light source/broadband filter or edge filter, broadband light source/tunable filter, broadband light source/interferometric detection and tunable narrowband light source/broadband receiving have been proposed and discussed. Related algorithms including edge filtering method [2], tunable Fabry-Perot cavity filter method [3] and other methods [4][5][6][7][8]. Nevertheless, there are still some drawbacks of the present demodulation algorithms.…”

Section: Introductionmentioning

confidence: 99%

Wavelength Shift Detection Methods Based on Cross-Correlation Analysis for Signal Demodulation of Fiber Bragg Grating Sensing System

Yang

Wei

2012

AMM

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In order to improve the signal demodulation performance of fiber Bragg grating (FBG) sensing system, a wavelength shift detection method based on cross-correlation analysis is proposed to improve the accuracy of the measurement. The simulation results indicate that the absolute error of the measurement can be between 2 pm - 3 pm within the range of SNR of 14 dB-7 dB. Under the condition with high SNR, the absolute error can be approximately reduced to 0.5 pm. Hence, this demodulation algorithm can reduce the influences of the noises effectively and help to further study the features of the FBG sensor demodulation system.

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Research progress based on FBG burst pressure detection

Wang,

Dong,

et al. 2023

2023 3rd International Conference on Frontiers of Electronics, Information and Computation Technologies (ICFEICT)

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Peak-Detection Algorithm in the Demodulation for the Fiber Bragg Grating Sensor System

Cited by 7 publications

References 0 publications

Adaptive multi-peak demodulation algorithm for distributed fiber Bragg grating sensing systems based on Hilbert transform

Adaptive multi-peak demodulation algorithm for distributed fiber Bragg grating sensing systems based on Hilbert transform

Wavelength Shift Detection Methods Based on Cross-Correlation Analysis for Signal Demodulation of Fiber Bragg Grating Sensing System

Research progress based on FBG burst pressure detection

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