This paper extends the capabilities of chirped-pulse phase-sensitive optical time-domain reflectometry to the measurement of large dynamic strains over hundreds of meters of standard single-mode fiber. Benefitting from single-shot strain measurements, this technique has already demonstrated dynamic strains of the order of submicrostrains with a sensitivity of picostrains-per-root-Hertz. Yet, for large dynamic strains, it relies on the accumulation of incremental measurements, where each trace is cross correlated with its predecessor to determine the relative change of strain. However, practical time records of measured high slew-rate applied perturbations contain disturbing outliers. We then detail and analyze a post-processing strategy to mitigate this limitation. Through this strategy, we are able to achieve for the first time (to our knowledge) high signal-to-noise Rayleigh-backscattering-based distributed measurements of large and fast dynamic strains of a longitudinally vibrating 4 m section at the end of 210 m of a single-mode fiber: from peak to peak 150-1190 με at vibration frequency of 400 Hz and 50 Hz, respectively.

The development of advanced distributed optical fiber sensing systems that are capable of performing accurate and spatially resolved multiparameter measurements is of great interest to a wide range of scientific and industrial applications. Here, we propose and experimentally demonstrate a wavelength diversity based advanced distributed optical fiber sensor system to accomplish multiparameter sensing while greatly enhancing measurement accuracy. A suite of deep neural network (DNN) algorithms are developed and verified for data denoising, rapid Brillouin frequency shift estimation, and vibration data event classification. As a proof-of-concept, we demonstrate the effectiveness of the proposed advanced wavelength diversity distributed fiber sensor system assisted by DNN for simultaneous, independent measurements of static strain, temperature, and acoustic vibrations over a 25 km long sensing fiber at 3 m spatial resolution. These results suggest the potential for an intelligent multiparameter monitoring system with enhanced performance in advanced structural health monitoring applications.

Slope-assisted Brillouin optical time domain analysis (SA-BOTDA) is a fast and distributed sensing technique that interrogates the Brillouin gain spectrum (BGS) near the middle of the linear region of its slope, allowing the measurement of high frequency vibrations. However, environmentally-induced deviations of the interrogation point from the rather small linear region around the optimum frequency position, result in harmonic distortion and changes in the slope value, which determines the gain-to-frequency conversion factor. Engineering the BGS by adding a loss probe, we propose a novel and improved version of SA-BOTDA, having a significantly wider drift tolerance for the interrogation point. Here, using a 14 ns pump pulse and a judicious choice of the frequency of the loss probe, we demonstrate an engineered BGS having a 70% wider frequency range (as compared with the conventional BGS), where the interrogation point can drift without compromising either the prescribed level of harmonic distortion or the given slope tolerance, further benefiting the flexibility and usage of SA-BOTDA.

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This paper presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDA) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/με and 0.9 MHz/°C for peak 1; and 47.2 kHz/με, and 1.11 MHz/°C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber on a 1-inch steel pipe under pressure up to 1,000 psi at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-inch outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 με was observed, and the sensitivity was calculated as 0.28με/psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

It is experimentally demonstrated that a chirped pulse phase-sensitive OTDR can measure large and fast dynamic strains (~100’s of με, ~100’s of Hz) with SNR of > 24dB. Signal smoothing and impact of error accumulation are also discussed.

Fiber-optic dynamic interrogators, which use periodic frequency scanning, actually sample a time-varying measurand on a non-uniform time grid. Commonly, however, the sampled values are reported on a uniform time grid, synchronized with the periodic scanning. It is the novel and noteworthy message of this paper that this artificial assignment may give rise to significant distortions in the recovered signal. These distortions increase with both the signal frequency and measurand dynamic range for a given sampling rate and frequency scanning span of the interrogator. They may reach disturbing values in dynamic interrogators, which trade-off scanning speed with scanning span. The paper also calls for manufacturers of such interrogators to report the sampled values along with their instants of acquisition, allowing interpolation algorithms to substantially reduce the distortion. Experimental verification of a simulative analysis includes: (i) a commercial dynamic interrogator of ‘continuous’ FBG fibers that attributes the measurand values to a uniform time grid; as well as (ii) a dynamic Brillouin Optical time Domain (BOTDA) laboratory setup, which provides the sampled measurand values together with the sampling instants. Here, using the available measurand-dependent sampling instants, we demonstrate a significantly cleaner signal recovery using spline interpolation.