Phase unwrapping error identification and suppression method in φ-OTDR systems based on PELT-VMD-ARIMA.

Area of Science:

• Optical Engineering
• Signal Processing
• Geophysics

Background:

• Phase-sensitive optical time-domain reflectometer (φ-OTDR) systems are crucial for distributed acoustic sensing.
• Phase unwrapping errors in φ-OTDR systems can significantly distort vibration information, impacting signal quality and accuracy.
• Accurate vibration detection is essential for various applications, including seismic monitoring.

Purpose of the Study:

• To propose and validate a novel method for identifying and suppressing phase unwrapping errors in φ-OTDR systems.
• To enhance the vibration recognition capability and signal quality of φ-OTDR systems.
• To demonstrate the method's effectiveness in real-world seismic applications.

Main Methods:

• A combined approach termed PELT-VMD-ARIMA was developed, integrating pruned exact linear time (PELT) changepoint detection, variational mode decomposition (VMD), and autoregressive integrated moving average (ARIMA) models.
• Numerical simulations were conducted to verify the method's principle and effectiveness.
• Experimental validation involved using piezoelectric transducers (PZTs) as seismic sources for single-frequency and chirp signals, and testing in an active source seismic application.

Main Results:

• The PELT-VMD-ARIMA method demonstrated significant efficacy in identifying and suppressing phase unwrapping errors.
• Compared to the mean-shift method, the proposed approach reduced the average root mean square error (RMSE) by 70.36% within the 2δ range around changepoints.
• Validation in an active source seismic application confirmed the method's ability to enhance signal quality and vibration recognition.

Conclusions:

• The PELT-VMD-ARIMA method provides a robust solution for mitigating phase unwrapping errors in φ-OTDR systems.
• This advancement significantly improves the accuracy and reliability of distributed acoustic sensing, particularly in seismic applications.
• The enhanced vibration recognition capability facilitates more precise and effective distributed acoustic sensing applications.