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Related Experiment Video

Updated: Sep 11, 2025

Design, Instrumentation and Usage Protocols for Distributed In Situ Thermal Hot Spots Monitoring in Electric Coils using FBG Sensor Multiplexing

Design, Instrumentation and Usage Protocols for Distributed In Situ Thermal Hot Spots Monitoring in Electric Coils using FBG Sensor Multiplexing

Published on: March 8, 2020

Multi-peak detection algorithm for FBG array sensing based on self-adaptive thresholding.

Xuanwei Xiong, Xiyuan Zhang, Sen Ma

|August 13, 2025

Summary

This summary is machine-generated.

A new self-adaptive algorithm improves optical fiber sensing by reducing noise in fiber Bragg grating signals. This enhances demodulation speed and stability for precise multi-peak signal detection in sensing networks.

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Last Updated: Sep 11, 2025

Design, Instrumentation and Usage Protocols for Distributed In Situ Thermal Hot Spots Monitoring in Electric Coils using FBG Sensor Multiplexing

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Area of Science:

Optical Fiber Sensing
Signal Processing
Photonics

Background:

Conventional multi-peak detection algorithms for fiber Bragg gratings (FBGs) struggle with noise interference, leading to demodulation failures.
Accurate signal demodulation is crucial for effective quasi-distributed sensing networks.

Purpose of the Study:

To develop a robust, self-adaptive multi-peak detection algorithm for FBG signals.
To enhance the stability, speed, and noise resistance of FBG demodulation.

Main Methods:

Signal normalization and wavelet transform denoising with an improved thresholding function.
Spectrum segmentation using Hilbert transform and a self-adaptive threshold mathematical model.
Spectrum expansion for stable 3 dB bandwidth segmentation and Bragg wavelength extraction.

Main Results:

The proposed algorithm effectively reduces high-frequency noise in FBG signals.
Self-adaptive spectral segmentation significantly improves algorithm portability and demodulation stability.
Experimental results validate enhanced demodulation speed and precision.

Conclusions:

The self-adaptive multi-peak detection algorithm offers a precise and noise-resistant solution for FBG sensing.
This method enhances the reliability of quasi-distributed sensing networks by improving signal demodulation.
The algorithm demonstrates significant advancements in handling complex multi-peak signals in noisy environments.