An SNR Enhancement Method for Φ-OTDR Vibration Signals Based on the PCA-VSS-NLMS Algorithm

Area of Science:

• Optical Engineering
• Signal Processing
• Fiber Optic Sensing

Background:

• Phase-sensitive optical time-domain reflectometer (Φ-OTDR) systems are crucial for long-distance vibration detection.
• Improving the signal-to-noise ratio (SNR) of vibration signals in Φ-OTDR is essential for accurate analysis.
• Existing denoising methods may have limitations in effectively enhancing SNR for Φ-OTDR systems.

Purpose of the Study:

• To propose and validate a novel denoising method, principal component analysis variable step-size normalized least mean square (PCA-VSS-NLMS), for Φ-OTDR systems.
• To enhance the signal-to-noise ratio (SNR) of vibration signals detected by Φ-OTDR.
• To provide an effective and hardware-independent solution for improving long-distance vibration signal detection and recognition.

Main Methods:

• Mathematical principle of the PCA-VSS-NLMS algorithm was constructed, allowing dynamic adjustment of input signals for optimal filtering.
• The algorithm's effectiveness was verified through simulations, comparing it against wavelet denoising (WD), Wiener filtering, variational mode decomposition (VMD), and variable step-size normalized least mean square (VSS-NLMS).
• The PCA-VSS-NLMS algorithm was implemented in a Φ-OTDR system to measure an 11.22 km fiber with induced vibration disturbances.

Main Results:

• Simulations demonstrated that PCA-VSS-NLMS improved SNR from -1.23 dB to 30.68 dB, outperforming other tested algorithms.
• Experimental results showed an SNR improvement from 8.77 dB to 26.17 dB (a 17.40 dB increase) for a 100 Hz vibration signal at 0.07 s.
• The method successfully enhanced the SNR of positional information in the Φ-OTDR system.

Conclusions:

• The PCA-VSS-NLMS algorithm is a highly effective method for denoising vibration signals in Φ-OTDR systems.
• This technique significantly improves the SNR without requiring modifications to existing hardware.
• PCA-VSS-NLMS offers a promising new approach for the detection and recognition of long-distance vibration signals.