Pink noise removal and spectral distortion correction based fiber Bragg grating demodulation algorithm.

Area of Science:

• Optical Engineering
• Signal Processing
• Metrology

Background:

• Fiber Bragg gratings (FBGs) are susceptible to noise and spectral distortions, impacting demodulation accuracy.
• Accurate demodulation is crucial for applications relying on FBG sensors, such as temperature and strain monitoring.

Purpose of the Study:

• To develop and validate a robust noise reduction algorithm for FBGs.
• To improve the accuracy and reliability of FBG demodulation in the presence of noise and distortions.
• To enhance the resolution and precision of FBG peak detection.

Main Methods:

• A noise reduction algorithm combining CEEMDAN decomposition with Savitzky-Golay filtering of intrinsic mode functions.
• Signal reconstruction from filtered components to preserve FBG signal details.
• A resolution-enhanced peak detection algorithm incorporating distortion spectrum correction.

Main Results:

• Simulations demonstrated effective suppression of white and pink noise without significant signal distortion.
• The algorithm successfully retained FBG signal details, avoiding errors from over-smoothing.
• Experimental results showed a significant improvement in the goodness of fit (R²) for the FBG temperature-wavelength curve from 0.9826 to 0.9999.

Conclusions:

• The proposed CEEMDAN-Savitzky-Golay filtering approach offers a superior method for noise reduction in FBGs.
• The enhanced peak detection algorithm provides high accuracy and computational simplicity.
• The combined techniques significantly improve FBG demodulation accuracy and measurement reliability.