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Optimization of the phase generated carrier demodulation algorithm based on support vector regression.

Huyong Ma, Binai Li, Min Xue

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    |November 22, 2021
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    Support vector regression (SVR) compensates for distortions in phase generated carrier (PGC) demodulation for optical fiber sensors. This SVR method improves accuracy and performance over traditional PGC and back propagation algorithms.

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    Area of Science:

    • Optical Fiber Sensing
    • Signal Processing
    • Machine Learning

    Background:

    • Phase generated carrier (PGC) is a key algorithm for demodulating interference signals in optical fiber sensors.
    • PGC offers high sensitivity, linearity, and a large dynamic range.
    • PGC demodulation can be distorted by signal amplitude and modulation depth.

    Purpose of the Study:

    • To investigate the use of support vector regression (SVR) for compensating PGC demodulation distortions.
    • To evaluate the effectiveness of SVR in improving the accuracy and reliability of optical fiber sensor systems.

    Main Methods:

    • Employing the support vector regression (SVR) algorithm to compensate for PGC demodulation distortions.
    • Conducting simulations to assess the nonlinear error reduction and fitting accuracy of the SVR algorithm.
    • Building and testing a vibration monitoring system using the SVR-based algorithm.

    Main Results:

    • SVR effectively reduced nonlinear errors in PGC demodulation systems.
    • SVR achieved fitting accuracies of 97.5% (noiseless) and >90% (noisy systems), outperforming the back propagation (BP) neural network.
    • The SVR-based algorithm demonstrated superior amplitude restoration with lower mean square error and better correlation.

    Conclusions:

    • SVR is a highly effective method for compensating PGC demodulation distortions in optical fiber sensors.
    • The SVR-based approach significantly enhances system performance compared to direct PGC and BP algorithms.
    • Experimental results validated the SVR algorithm's superior performance in a practical vibration monitoring application.