Extensive research on Brillouin- and Raman-based distributed optical fibre sensors over the past two decades has resulted in the commercialization of distributed sensors capable of measuring static and quasi-static phenomena such as temperature and strain. Recently, the focus has been shifted towards developing distributed sensors for measurement of dynamic phenomena such as dynamic strain and sound waves. This article reviews the current state of the art distributed optical fibre sensors capable of quantifying dynamic vibrations. The most important aspect of Rayleigh and Brillouin scattering processes which have been used for distributed dynamic measurement are studied. The principle of the sensing techniques used to measure dynamic perturbations are analyzed followed by a case study of the most recent advances in this field. It is shown that the Rayleigh-based sensors have longer sensing range and higher frequency range, but their spatial resolution is limited to 1 m. On the other hand, the Brillouin-based sensors have shown a higher spatial resolution, but relatively lower frequency and sensing ranges.

A distributed optical fiber dynamic strain sensor with high spatial and frequency resolution is demonstrated. The sensor, which uses the $\varphi$-OTDR interrogation technique, exhibited a higher sensitivity thanks to an improved optical arrangement and a new signal processing procedure. The proposed sensing system is capable of fully quantifying multiple dynamic perturbations along a 5 km long sensing fiber with a frequency and spatial resolution of 5 Hz and 50 cm, respectively. The strain resolution of the sensor was measured to be 40 nε.

A distributed optical fibre acoustic sensor is numerically modelled. To increase the flexibility of the model, the building blocks of the sensing system are modelled separately and later combined to form the numerical model. This approach is adopted to facilitate the evaluation of each of the individual building blocks and their effects on the output of the sensor. The numerical model is used to assess the effect of parameters such as the linewidth of the laser source, the width of the probe pulse, and the frequency and amplitude of perturbation on the response of the sensing system. It is shown that the precision and accuracy of the sensing system are affected by the frequency and amplitude of perturbation as well as the pulse width and linewidth of the probe pulse.

A novel subsea cable condition monitoring technique based on embedded optical fibre inside the cable is demonstrated. It is shown that a distributed optical fibre vibration sensor can be used to map dynamic strains all along the cable simultaneously. It is experimentally shown that such system can fully quantify the location and strain level at each point on the cable as a function of time for both abrupt impact and cyclical loading. The sensing system demonstrated a spatial and strain resolution of 1 ${m}$ and 4 ${\mu \epsilon}$ , respectively, over a 10 ${km}$ sensing range.

We present a low-noise distributed acoustic sensor using enhanced backscattering fiber with a series of localized reflectors. The point reflectors were inscribed in a standard telecom fiber in a fully automated system by focusing an ultra-fast laser through the fiber cladding. The inscribed reflectors provided a reflectance of −53 dB, significantly higher than the Rayleigh backscattering level of −70 dB/m, despite adding only 0.01 dB of loss per 100 reflection points. We constructed a coherent φ-OTDR system using a double-pulse architecture to probe the enhanced backscattering fiber. Using this system, we found that the point reflectors enabled an average phase noise of −91 dB (re rad²/Hz), 20 dB lower than sensors formed using Rayleigh backscattering in the same fiber. The sensors are immune to interference fading, exhibit a high degree of linearity, and demonstrate excellent non-local signal suppression (>50 dB). This work illustrates the potential for low-cost enhanced backscattering fiber to enable low-noise, long-range distributed acoustic sensing.