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Related Concept Videos

IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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Related Experiment Video

Updated: Mar 19, 2026

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station
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SFOA-VMD-PE algorithm for a φ-OTDR detection system.

Bo Liu, Mingxuan Wang, Feng Xia

    Applied Optics
    |March 17, 2026
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    Summary

    This study introduces an enhanced Variational Mode Decomposition (VMD) method using permutation entropy and starfish optimization for noise reduction in distributed acoustic sensing systems. The novel approach significantly improves signal-to-noise ratio (SNR) for accurate disturbance detection.

    Area of Science:

    • Acoustic Sensing
    • Signal Processing
    • Optical Metrology

    Background:

    • Distributed acoustic sensing (DAS) systems face challenges with random and fading noise.
    • Manual parameter tuning in Variational Mode Decomposition (VMD) limits its application.
    • Accurate noise suppression is crucial for reliable disturbance detection in DAS.

    Purpose of the Study:

    • To develop an automated VMD approach for effective noise suppression in DAS.
    • To enhance VMD performance using permutation entropy and starfish optimization.
    • To validate the proposed method in a phase-sensitive optical time-domain reflectometry (OTDR) system.

    Main Methods:

    • Proposed a VMD approach integrated with permutation entropy.
    • Utilized the starfish optimization algorithm for automatic VMD parameter selection.

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  • Validated the method on a phase-sensitive OTDR system with simulated disturbance signals.

    • Main Results:

    • The enhanced VMD algorithm achieved significant noise suppression.
    • Consistent Signal-to-Noise Ratio (SNR) improvements exceeding 14 dB were observed across different frequencies.
    • Demonstrated robustness and effectiveness in suppressing random and fading noise.

    Conclusions:

    • The proposed VMD method with permutation entropy and starfish optimization effectively addresses noise in DAS.
    • Automatic parameter selection enhances the practicality and performance of VMD.
    • The technique offers a robust solution for improving the accuracy of acoustic sensing systems.