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Related Experiment Video

Updated: Aug 30, 2025

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
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Optical Fiber Vibration Signal Recognition Based on the Fusion of Multi-Scale Features.

Xinrong Ma1, Jiaqing Mo1, Jiangwei Zhang1

  • 1Key Laboratory of Signal Detection and Processing, College of Information Science and Engineering, Xinjiang University, Urumqi 830017, China.

Sensors (Basel, Switzerland)
|August 26, 2022
PubMed
Summary

This study introduces an improved method for detecting intrusion vibration events using optical fiber sensing. The novel approach enhances recognition accuracy for fiber vibration signals, achieving 98.75% precision.

Keywords:
2DCNNdifferential pooling featuresdistributed optical fiber sensingendpoint detectionfeature fusion

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Area of Science:

  • Fiber Optic Sensing
  • Signal Processing
  • Machine Learning

Background:

  • Distributed Sagnac type optical fiber sensing systems face challenges with low recognition accuracy for intrusion vibration events.
  • Traditional methods often struggle with effective feature extraction and signal endpoint detection.

Purpose of the Study:

  • To develop a novel method for recognizing fiber vibration signals with improved accuracy.
  • To enhance the endpoint detection and feature extraction processes in optical fiber sensing systems.

Main Methods:

  • A new endpoint detection algorithm combining spectral centroid and energy spectral entropy product was developed.
  • Convolutional Neural Networks (CNNs) with multi-scale feature fusion and differential pooling were employed for feature extraction.
  • A Multi-Layer Perceptron (MLP) was used for the final recognition of vibration signals.

Main Results:

  • The proposed method achieved an average recognition accuracy of 98.75% for four types of vibration signals.
  • The approach demonstrated higher accuracy compared to traditional Empirical Mode Decomposition (EMD), Variational Mode Decomposition (VMD), and 1D-CNN methods.

Conclusions:

  • The combined endpoint detection and multi-scale feature fusion CNN method significantly improves the recognition accuracy of intrusion vibration events in optical fiber sensing systems.
  • This advanced technique offers a more robust solution for monitoring and security applications utilizing fiber optic sensors.