A Comprehensive Study of Optical Fiber Acoustic Sensing

Abstract

The optical fiber acoustic sensing system is suitable for long-distance monitoring of the acoustic signals generated by the external disturbances. According to the continuity of sensing units, quasi-distributed and distributed optical fiber acoustic sensing technologies are differentiated to meet different application requirements. On the one hand, the recent progress of Fabry-Perot interferometer (FPI) focusing on the diaphragm material, and the research hotspots in the field of the continuous Fiber Bragg grating (FBG) array are firstly reviewed. On the other hand, Mach-Zehnder interferometry (MZI), Michelson interferometry (MI), and Sagnac interferometry (SI) have rapidly developed in the aspect of the demodulation algorithm optimization with the purpose of the sensing performance improvement. Moreover, the current primary research works of the phase-sensitive optical time-domain reflectometer (ϕ-OTDR) are the signalto-noise ratio improvement and the mixed optical structure design. Finally, this paper presents an overview of the recent advances of optical fiber acoustic sensing system in the application domains of military defense, structural health monitoring, petroleum exploration, and development. INDEX TERMS Acoustic detection, distributed acoustic sensing, optical fiber sensing, ϕ-OTDR, structural health monitoring.

Optical Fiber Vibration Sensor Using Least Mean Square Error Algorithm

“…The amplitude curve A LI (l 0 ,∆t) at the vibration position l 0 and the phase curve Φ LI (l 0 ,∆t) at the vibration position l 0 could be obtained. Firstly, we use the conventional IQ demodulation method to process the small part of beat signal, and obtain the amplitude of light intensity ALI(t) from the Equation (4) and the phase of light intensity ΦLI(t) from Equation (5). According to the time interval between two adjacent optical pulses Δt, we could construct the time-space amplitude matrix ALI(l,Δt) and the time-space phase matrix ΦLI(l,Δt).…”

“…Vibration signal detection is critical for fault diagnosis of electromechanical devices, such as railway roller bearings [1] and internal combustion engines [2]. Owing to the ability of distributed sensing and transmission [3], anti-electromagnetic interference [4], and convenient installation, the optical fiber vibration sensor has grown significantly and has great potential in the field of fault diagnosis [5]. In practical application, because the position information and time-frequency characteristics of vibration signal need to be obtained simultaneously, the optical fiber vibration sensor based on coherent optical time domain reflectometry (COTDR) becomes an important choice, which is suitable for long-distance vibration positioning [6] and vibration phase recovery [7].…”

Variational Mode Decomposition-Based Threat Classification for Fiber Optic Distributed Acoustic Sensing

“…Interrogating these fluctuations then enable to detect and classify such activities. In this context, phase-sensitive optical time-domain reflectometry (phase-OTDR) technique has been developed for DAS during the last two decades [2,3]. Unlike conventional OTDR, in phase-OTDR, pulses of highly coherent lights are used to transmit into a fiber optic cable, and for this reason, it is sensitive to relative phases of reflected fields from the scattering centers.…”

Co-Processing Parallel Computation for Distributed Optical Fiber Vibration Sensing

“…As one typical distributed optical fiber vibration sensing system, a phase-sensitive optical time domain reflectometer (Φ-OTDR) can achieve simultaneously multi-point vibration detection and location. Because of the benefits of its high sensitivity, good spatial resolution and long detecting distance [4,5], Φ-OTDR has broad application prospects in long-distance oil and gas pipelines [6], border security intrusion detection and smart grids [7,8]. The current research hotspot of Φ-OTDR is the improvement of its sensing performance, such as a sensing distance up to even hundreds of kilometers [9,10], and a spatial resolution of a sub-meter magnitude [11], which leads to a huge amount of sensing data and a growing demand for computation resources.…”