Interference fading suppression with fault-tolerant Kalman filter in phase-sensitive OTDR

Area of Science:

• Optoelectronics
• Signal Processing
• Sensor Technology

Background:

• Phase-sensitive optical time-domain reflectometer (Φ-OTDR) systems are crucial for distributed vibration sensing.
• Traditional methods suffer from interference fading and demodulation errors, limiting accuracy and stability.
• Achieving fading-free and highly accurate vibration sensing remains a significant challenge.

Purpose of the Study:

• To propose a multi-sensor information fusion algorithm based on a fault-tolerant Kalman filter for Φ-OTDR systems.
• To achieve fading-free distributed vibration sensing with enhanced accuracy and stability.
• To overcome limitations of classical demodulation methods, particularly demodulation errors and interference fading.

Main Methods:

• Designed a fault-tolerant dual-core complementary array model for Rayleigh scattering signal denoising and vibration judgment.
• Employed a fault-tolerant control strategy to determine sensor weight and vibration judgment coefficients for data fusion.
• Utilized Kalman filter for time-series data fusion, enabling error identification and filling to improve system stability.

Main Results:

• The proposed system demonstrated a frequency response from 10 Hz to 2400 Hz with 98.33% localization accuracy.
• Fusion error of demodulation frequency was reduced to 0.25 Hz, achieving 100% frequency demodulation accuracy.
• Demodulation errors caused by interference attenuation were completely eliminated, outperforming classical methods with an 89.18% error probability.

Conclusions:

• The fault-tolerant Kalman filter algorithm significantly improves the stability and accuracy of distributed vibration sensing in Φ-OTDR systems.
• The fusion of redundant complementary data enhances system robustness against interference fading.
• This approach offers a simple multiplexing structure and stable demodulation performance, making it suitable for various applications.