Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach–Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications.

In the past two decades Brillouin-based sensors have emerged as a newly-developed optical fiber sensing technology for distributed temperature and strain measurements. Among these, the Brillouin optical time domain reflectometer (BOTDR) has attracted more and more research attention, because of its exclusive advantages, including single-end access, simple system architecture, easy implementation and widespread field applications. It is realized mainly by injecting optical pulses into the fiber and detecting the Brillouin frequency shift (BFS), which is linearly related to the change of ambient temperature and axial strain of the sensing fiber. In this paper, the authors provide a review of new progress on performance improvement and applications of BOTDR in the last decade. Firstly, the recent advances in improving the performance of BOTDRs are summarized, such as spatial resolution, signal-to-noise ratio and measurement accuracy, measurement speed, cross sensitivity and other properties. Moreover, novel-type optical fibers bring new characteristics to optic fiber sensors, hence we introduce the different Brillouin sensing features of special fibers, mainly covering the plastic optical fiber, photonic crystal fiber, few-mode fiber and other special fibers. Additionally, we present a brief overview of BOTDR application scenarios in many industrial fields and intelligent perception, including structural health monitoring of large-range infrastructure, geological disaster prewarning and other applications. To conclude, we discuss several challenges and prospects in the future development of BOTDRs.

Super-resolution imaging has been revolutionizing technical analysis in various fields from biological to physical sciences. However, many objects are hidden by strongly scattering media such as biological tissues that scramble light paths, create speckle patterns and hinder object’s visualization, let alone super-resolution imaging. Here, we demonstrate non-invasive super-resolution imaging through scattering media based on a stochastic optical scattering localization imaging (SOSLI) technique. After capturing multiple speckle patterns of photo-switchable point sources, our computational approach utilizes the speckle correlation property of scattering media to retrieve an image with a 100-nm resolution, an eight-fold enhancement compared to the diffraction limit. More importantly, we demonstrate our SOSLI to do non-invasive super-resolution imaging through not only static scattering media, but also dynamic scattering media with strong decorrelation such as biological tissues. Our approach paves the way to non-invasively visualize various samples behind scattering media at nanometer levels of detail.

In the application of the fire prevention, the sensor is expected to alarm before the occurrence of fire. We propose and experimentally demonstrate a long-range Raman distributed fiber temperature sensor (RDFTS) and a temperature early warning model (TEWM) for fire detection and prevention. The TWEM includes first-order and second-order moving average method. And the second-order moving average method is suitable for prediction based on trends with significant temperature changes. The RDFTS achieved a spatial resolution of 3.0 and 28.6 m for the sensing range of 1.38 and 28.9 km, respectively. In experiment, the sensing fiber is placed in the temperature-controlled chamber and outdoor building (Boxue Building, Taiyuan University of Technology, China) for detecting and predicting the temperature. The experimental results show that the TEWM can predict the temperature trend in advance of 46 s. Simultaneously, the mean absolute errors of prediction temperature are 0.33 °C (temperature-controlled chamber) and 0.31 °C (Boxue Building). The experimental results are in accordance with the China-National Standard System for fire detection and prevention.

Partial discharge detection is crucial for electrical cable safety evaluation. The ultrasonic signals frequently generated in the partial discharge process contains important characteristic information. However, traditional ultrasonic transducers are easily subject to strong electromagnetic interference in environments with high voltages and strong magnetic fields. In order to overcome this problem, an optical fiber Sagnac interferometer system is proposed for partial discharge ultrasound detection. Optical fiber sensing and time-frequency analysis of the ultrasonic signals excited by the piezoelectric ultrasonic transducer is realized for the first time. The effective frequency band of the Sagnac interferometer system was up to 175 kHz with the help of a designed 10 kV partial discharge simulator device. Using the cumulative histogram method, the characteristic ultrasonic frequency band of the partial discharges was between 28.9 kHz and 57.6 kHz for this optical fiber partial discharge detection system. This new ultrasound sensor can be used as an ideal ultrasonic source for the intrinsically safe detection of partial discharges in an explosive environment.

Single-pixel imaging (SPI) uses a single-pixel detector instead of a detector array with a lot of pixels in traditional imaging techniques to realize two-dimensional or even multi-dimensional imaging. For SPI using compressed sensing, the target to be imaged is illuminated by a series of patterns with spatial resolution, and then the reflected or transmitted intensity is compressively sampled by the single-pixel detector to reconstruct the target image while breaking the limitation of the Nyquist sampling theorem. Recently, in the area of signal processing using compressed sensing, many measurement matrices as well as reconstruction algorithms have been proposed. It is necessary to explore the application of these methods in SPI. Therefore, this paper reviews the concept of compressive sensing SPI and summarizes the main measurement matrices and reconstruction algorithms in compressive sensing. Further, the performance of their applications in SPI through simulations and experiments is explored in detail, and then their advantages and disadvantages are summarized. Finally, the prospect of compressive sensing with SPI is discussed.