Distributed optical fiber sensing in coherent Φ-OTDR with a broadband chirped-pulse conversion algorithm.

We propose a broadband chirped-pulse conversion algorithm (BCPCA) to convert a finite-step scanning probe pulse into an equivalent broadband chirped probe pulse by convolving a chirp factor on the received signal in coherent phase-sensitive optical time domain reflectometry (Φ-OTDR). Combined with Rayleigh interference pattern (RIP) demodulation in chirped-pulse Φ-OTDR (CP-ΦOTDR), environmental perturbations, such as strain and temperature along the sensing fiber, can be quantitatively measured. The equivalent broadband chirped pulse is generated by digital processing, and its bandwidth can be increased by changing the composition of the scanning pulse. Thus, the measurable perturbation range of the system can be expanded. As a proof-of-concept experiment, a high-performance distributed strain measurement was realized on a 10 km fiber, the frequency response was 5 kHz, which is only limited by the fiber length, and the strain resolution was 8.04 p ε/H z. The proposed method of generating equivalent broadband chirped pulse through the digital domain can be used as a supplement to CP-ΦOTDR.

Traffic Vibration Signal Analysis of DAS Fiber Optic Cables with Different Coupling Based on an Improved Wavelet Thresholding Method.

Distributed Acoustic Sensing (DAS) is a novel technology that uses fiber optics to sense and monitor vibrations. It has demonstrated immense potential for various applications, including seismology research, traffic vibration detection, structural health inspection, and lifeline engineering. DAS technology transforms long sections of fiber optic cables into a high-density array of vibration sensors, providing exceptional spatial and temporal resolution for real-time monitoring of vibrations. Obtaining high-quality vibration data using DAS requires a robust coupling between the fiber optic cable and the ground layer. The study utilized the DAS system to detect vibration signals generated by vehicles operating on the campus road of Beijing Jiaotong University. Three distinct deployment methods were employed: the uncoupled fiber on the road, the underground communication fiber optic cable ducts, and the cement-bonded fixed fiber optic cable on the road shoulder, and compared for their outcomes. Vehicle vibration signals under the three deployment methods were analyzed using an improved wavelet threshold algorithm, which was verified to be effective. The results indicate that for practical applications, the most effective deployment method is the cement-bonded fixed fiber optic cable on the road shoulder, followed by the uncoupled fiber on the road, and the underground communication fiber optic cable ducts are the least effective. This has important implications for the future development of DAS as a tool for various fields.

Signal Activity Detection for Fiber Optic Distributed Acoustic Sensing with Adaptive-Calculated Threshold.

The key point on analyzing the data stream measured by fiber optic distributed acoustic sensing (DAS) is signal activity detection separating measured signals from environmental noise. The inability to calculate the threshold for signal activity detection accurately and efficiently without affecting the measured signals is a bottleneck problem for current methods. In this article, a novel signal activity detection method with the adaptive-calculated threshold is proposed to solve the problem. With the analysis of the time-varying random noise's statistical commonality and the short-term energy (STE) of real-time data stream, the top range of the total STE distribution of the noise is found accurately for real-time data stream's ascending STE, thus the adaptive dividing level of signals and noise is obtained as the threshold. Experiments are implemented with simulated database and urban field database with complex noise. The average detection accuracies of the two databases are 97.34% and 90.94% only consuming 0.0057 s for a data stream of 10 s, which demonstrates the proposed method is accurate and high efficiency for signal activity detection.

Watt-level L band superfluorescent fiber source.

An L band superfluorescent fiber source (SFS) with output power of 0.94W is presented, under 4.4W 976nm pump power. The optical conversion efficiency is about 21%. The spectrum covers the broad wavelength range from 1560nm to 1615nm. The high power L band SFS is constructed by a low power L band amplified spontaneous emission (ASE) seed source and a high power erbium-ytterbium co-doped fiber (EYDF) amplifier in double pass forward pumping configuration.