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    This study introduces a new method to reduce false alarms in distributed fiber optic sensing systems. The technique improves accuracy by filtering unnecessary phase data, requiring fewer traces for reliable event detection.

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    Area of Science:

    • Optical Engineering
    • Signal Processing
    • Fiber Optic Sensing

    Background:

    • Distributed fiber optic sensing, specifically phase-sensitive Optical Time Domain Reflectometry (ϕ-OTDR), faces challenges with nuisance alarm rates (NAR).
    • Previous research often neglected ephemeral events and prioritized classification accuracy, leading to excessive data acquisition and a different source of NAR.
    • Existing methods for feature extraction in ϕ-OTDR systems can be data-intensive and may not effectively handle all types of events.

    Purpose of the Study:

    • To develop a novel technique for reducing the nuisance alarm rate (NAR) in ϕ-OTDR pattern recognition systems.
    • To address the neglect of ephemeral events in prior research and mitigate the NAR introduced by data-intensive classification algorithms.
    • To improve the efficiency of feature extraction and event detection in direct-detected ϕ-OTDR systems.

    Main Methods:

    • A novel correlation-based wrapper is applied to differential signals derived from direct-detected ϕ-OTDR systems.
    • The technique filters out the influence of irrelevant phase information present in the differential signals.
    • It exploits the utility of otherwise unnecessary phase data for more effective signal processing.

    Main Results:

    • The proposed method effectively filters out irrelevant phase effects, reducing the NAR.
    • It avoids the use of extraneous data within the differential signals by better utilizing phase information.
    • The technique achieves improved intensity translation and requires significantly fewer acquired traces compared to contemporary feature extraction methods.

    Conclusions:

    • The developed correlation-based wrapper offers a significant improvement in reducing NAR for ϕ-OTDR systems, particularly for ephemeral events.
    • This approach enhances the efficiency of data processing by requiring fewer traces while maintaining or improving detection accuracy.
    • The findings suggest a more robust and practical solution for real-world applications of distributed fiber optic sensing.