Towards large dynamic range and ultrahigh measurement resolution in distributed fiber sensing based on multicore fiber

Abstract

Featuring a dependence of Brillouin frequency shift (BFS) on temperature and strain changes over a wide range, Brillouin distributed optical fiber sensors are however essentially subjected to the relatively poor temperature/strain measurement resolution. On the other hand, phase-sensitive optical time-domain reflectometry (Φ-OTDR) offers ultrahigh temperature/strain measurement resolution, but the available frequency scanning range is normally narrow thereby severely restricts its measurement dynamic range. In order to achieve large dynamic range and high measurement resolution simultaneously, we propose to employ both the Brillouin optical time domain analysis (BOTDA) and Φ-OTDR through space-division multiplexed (SDM) configuration based on the multicore fiber (MCF), in which the two sensors are spatially separately implemented in the central core and a side core, respectively. As a proof of concept, the temperature sensing has been performed for validation with 2.5 m spatial resolution over 1.565 km MCF. Large temperature range (10 °C) has been measured by BOTDA and the 0.1 °C small temperature variation is successfully identified by Φ-OTDR with ~0.001 °C resolution. Moreover, the temperature changing process has been recorded by continuously performing the measurement of Φ-OTDR with 80 s frequency scanning period, showing about 0.02 °C temperature spacing at the monitored profile. The proposed system enables the capability to see finer and/or farther upon requirement in distributed optical fiber sensing.

Recent developments in fibre optic shape sensing

“…In recent years, advancement of research on effect of bend on Brillouin scattering frequency shift in multicore fibres has introduced a novel principle for FOSSs, promising long range full 3D shape sensing [61][62][63][64]. The latest research study has experimentally demonstrated use of conventional Brillouin optical time-domain analysis (BOTDA) for a 1 kilometre long multicore fibre bend sensing; however, further work is required to develop it to a FOSS [61].…”

Fast information acquisition using spectra subtraction for Brillouin distributed fiber sensors

“…In previous research, the sensing information, i.e., the Brillouin gain peak along the fiber is obtained by curve fitting the gain profile point by point from one end to the other [3,[5][6][7][9][10][11]14,15,[20][21][22][23][24][26][27][28][29][30], and that profile ideally follows a Lorentzian shape as described below [31]…”

“…practice, the Brillouin gain spectrum is normally obtained by Lorentzian curve fitting point by point and then the sensing information is retrieved from the central Brillouin frequency [20]. However, on the way to a higher solution, especially with 1 million points and beyond [21][22][23][24], to in-site real-time dynamic measurements [25][26][27], and to extra fine frequency resolution [28][29][30], the curve fitting process takes a very long time and it is neither target oriented nor effective, which makes those goals hard to achieve and some even unrealistic. Actually, not every single point along the fiber needs to be curve fitted, because a large range of the fiber's Brillouin frequency may only have jitters in a measurement, which is not necessary to be calculated, and only those points with frequency changes carries information and need be fitted and calculated.…”

Long-range distributed optical fiber hot-wire anemometer based on chirped-pulse ΦOTDR

“…However, this technique necessarily multiplies the acquisition time, limiting the dynamic performance of the sensor. In addition, there exist in the state of the art other high performance temperature DOFS based on different sensing principles, such as Raman scattering [40,41], Brillouin scattering [42], or even combinations of multiple techniques [43]. While these techniques may be able to provide absolute temperature measurements, they generally provide low resolution temperature measurements, and are not well adapted to dynamic monitoring.…”