Phase-sensitive optical time-domain reflectometry (Φ-OTDR) has attracted numerous attention due to its superior performance in detecting the weak perturbations along the fiber. Relying on the ultra-sensitivity of light phase to the tiny deformation of optical fiber, Φ-OTDR has been treated as a powerful technique with a wide range of applications. It is fundamental to extract the phase of scattering light wave accurately and the methods include coherent detection, I/Q demodulation, 3 by 3 coupler, dual probe pulses, and so on. Meanwhile, researchers have also made great efforts to improve the performance of Φ-OTDR. The frequency response range, the measurement accuracy, the sensing distance, the spatial resolution, and the accuracy of event discrimination, all have been enhanced by various techniques. Furthermore, lots of researches on the applications in various kinds of fields have been carried out, where certain modifications and techniques have been developed. Therefore, Φ-OTDR remains as a booming technique in both researches and applications.

The overhead power transmission line, as an important component of equipment for long-distance power transmission, is threatened by icing and galloping, which will lead to equipment troubles and cause huge economic loss. Thus, there is a great need for on-line monitoring for transmission lines. Because the photoelectric composite cable, such as optical fiber composite overhead ground wire (OPGW) is widely used, it is possible to introduce distributed optical fiber sensors (DOFS) into transmission line status monitoring. Common schemes based on DOFS usually offer low sensing density and are hard to realize global awareness, while phase sensitive optical time domain reflectometry (Φ-OTDR), as a DOFS that has the characteristic of distributed sensing, is hoping to address the limitation. In this paper, by establishing mathematical models, proposing analytical method, and building demonstration devices to analyze the dynamic strain characteristics of overhead power transmission line, an Φ-OTDR based on-line monitoring scheme of transmission line status is presented and experimentally proved for the first time. The estimation error of sag is less than 5.8% on centimeter scale, and the estimation error of ice thickness is no more than 10.84% on sub-millimeter scale, which gives an accurate description of transmission line status and provides strong support for early warning of transmission line failures.

The demand for distributed acoustic sensors, which are capable of reconstructing the amplitude, frequency, and phase of an acoustic field, is increasing. These sensors are typically realized by phase-sensitive optical time domain reflectometry ( $\Phi$ -OTDR). However, common $\Phi$ -OTDR systems suffer from a fading phenomenon, which causes amplitude fluctuation on Rayleigh backscattering traces, and the scattered light may not have enough intensity in some regions. These areas have low amplitude backscattering that may be even lower than the system noise floor during some periods of time. Therefore, we cannot reconstruct the phase signal properly in such low intensity areas. Systems with multiple frequencies have been proposed to achieve fading suppression. However, online data processing of such schemes remains a challenge, especially for continuous in-field applications. Prediction of fading must be performed in real time. Any delay caused by massive calculations is not acceptable. In this paper, a continuous fading suppression method based on a $\Phi$ -OTDR system with three different probe frequencies is presented as well as a tracking algorithm for selecting the optimum probe signal for any time, which predicts the occurrence of fading before it actually occurs. The performance of the proposed method has been experimentally evaluated and statistically analyzed. The distortion induced by the fading effect could be suppressed to 1.15% under continuous real-time running. The method is highly effective and repeatable, which makes it suitable for practical online purposes.

The frequency-drift of laser source is a crucial factor for influencing the performance of the phase–sensitive optical time domain reflectometer (Φ-OTDR). It induces signal fluctuation and severely limits the measurement capacity for low frequency. In this paper, a twice differential method is proposed to compensate for the influence of the laser-frequency-drift in Φ-OTDR. It uses the differential signal between two points on the sensing fiber as a reference signal and then subtracts the reference signal from the main signal to obtain the final result. In the experiment, the signal fluctuation induced by laser-frequency-drift is decreased by more than 95%. A vibration with a 0.1 Hz frequency on a 6 km sensing fiber is detected with 10 m spatial resolution and sensitivity is estimated to be 5.9 nε. With this method we also successfully measured the process of a stepper motor stretching a fiber section. This method will expand the scope of application of Φ-OTDR in the fields, which require high sensitivity and low frequency response.

This paper proposes a real-time multi-class disturbance detection algorithm based on YOLO for distributed fiber vibration sensing. The algorithm achieves real-time detection of event location and classification on external intrusions sensed by distributed optical fiber sensing system (DOFS) based on phase-sensitive optical time-domain reflectometry (Φ-OTDR). We conducted data collection under perimeter security scenarios and acquired five types of events with a total of 5787 samples. The data is used as a spatial–temporal sensing image in the training of our proposed YOLO-based model (You Only Look Once-based method). Our scheme uses the Darknet53 network to simplify the traditional two-step object detection into a one-step process, using one network structure for both event localization and classification, thus improving the detection speed to achieve real-time operation. Compared with the traditional Fast-RCNN (Fast Region-CNN) and Faster-RCNN (Faster Region-CNN) algorithms, our scheme can achieve 22.83 frames per second (FPS) while maintaining high accuracy (96.14%), which is 44.90 times faster than Fast-RCNN and 3.79 times faster than Faster-RCNN. It achieves real-time operation for locating and classifying intrusion events with continuously recorded sensing data. Experimental results have demonstrated that this scheme provides a solution to real-time, multi-class external intrusion events detection and classification for the Φ-OTDR-based DOFS in practical applications.

Phase-sensitive optical time-domain reflectometry (Φ-OTDR) has been proposed for distributed vibration sensing purpose over recent years. Emerging applications, including seismic and hydroacoustic wave detection, demand accurate low-frequency vibration reconstruction capability. We propose to use the direct-detection Φ-OTDR configuration to achieve quantitative demodulation of external low-frequency vibrations by phase-shifted dual-pulse probes. Simultaneous pulsing and phase shifting modulation is realized with a single acousto-optic modulator to generate such probes, relaxing the need for an additional optical phase modulator. In the experiments, vibrations with frequency as low as 0.5 Hz are successfully reconstructed with 10 m spatial resolution and 35 dB signal-to-noise ratio. Excellent linearity and repeatability are demonstrated between the optical phase demodulation results and the applied vibration amplitudes. The proposed method is capable of quantitative demodulation of low-frequency vibrations with a cost-effective system configuration and high computation efficiency, showing potential for commercial applications of distributed seismic or hydroacoustic wave acquisition.