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A High-Resolution Demodulation Algorithm for FBG-FP Static-Strain Sensors Based on the Hilbert Transform and Cross
Wenzhu Huang1, Tengkun Zhen2,3, Wentao Zhang4
1Optoelectronic System Laboratory, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China. hwzhu@semi.ac.cn.
Sensors (Basel, Switzerland)
|April 30, 2015
Summary
This study introduces a new algorithm for static strain measurement using fiber Bragg gratings (FBGs). The novel method significantly enhances resolution by suppressing Gaussian noise, achieving a 0.9 nε static-strain resolution.
Area of Science:
- Optoelectronics
- Fiber Optics Sensing
- Metrology
Background:
- Static strain detection commonly uses cross-correlation of reflection spectra from two fiber Bragg gratings (FBGs).
- Traditional methods face resolution limitations due to dominant Gaussian noise in spectral measurements.
- FBG-based Fabry-Perot interferometers (FBG-FPs) offer potential for enhanced strain sensing.
Purpose of the Study:
- To develop a novel static-strain demodulation algorithm for FBG-FPs.
- To improve the resolution of static strain measurements by overcoming Gaussian noise limitations.
- To validate the proposed algorithm through theoretical modeling, simulation, and experimental implementation.
Main Methods:
- Application of the Hilbert transform to alter the Gaussian distribution of FBG-FPs reflection spectra.
- Utilizing a cross third-order cumulant with Hilbert-transformed spectra to generate noise-vanished signals.
- Accurate calculation of wavelength difference between two FBGs using the processed signals.
- Theoretical modeling, simulation analysis, and experimental verification of the algorithm's performance.
Main Results:
- The proposed algorithm theoretically suppresses Gaussian noise completely.
- A static-strain resolution of 0.9 nε was achieved under laboratory conditions.
- The novel method demonstrates a higher resolution compared to traditional cross-correlation techniques.
Conclusions:
- The developed static-strain demodulation algorithm for FBG-FPs effectively suppresses Gaussian noise.
- The algorithm offers significantly improved strain measurement resolution.
- This advancement holds promise for more precise applications in fiber optic sensing.
