简要回顾了从基于传统机器学习的普通感知型分布式光纤声波传感器（DAS）到基于深度学习的全智能化DAS的转变历程，深入分析了基于多维信息提取的DAS监督学习及半监督、无监督和跨场景迁移等深度学习方法的研究现状，概括了不同识别模型的构建思路、特点，及其识别性能、处理时间等评价指标，也论述了DAS从单源检测到多源混叠检测、从单任务到多任务处理等智能感知能力提升面临的新挑战，最后对全智能化DAS的信号处理发展方向及新趋势进行了展望。

我国大型基础设施的建设规模已多年位居世界之首，分布式光纤传感技术（DOFS）作为大型基础设施健康状态实时监测最有潜力的技术，近年来得到了迅速发展。针对DOFS在技术和应用的突破上面临的挑战，在介绍DOFS各技术基本工作原理、发展历史、现状以及典型应用原理和方案等的基础上，对其工作新机理、系统设计方案、研究发展方向等进行了阐述和讨论。

电石渣的排放及贮存量日益递增, 电石渣硅铁的资源化利用也成为亟待解决的难题。为实现电石渣硅铁的高值化应用, 以干法电石渣中分离出的磁性硅铁为加重质配制重介质悬浮液, 并探究了悬浮液密度、黏土含量和硅铁粒度等因素对其粘度及沉降特性的影响。结果表明, 增大悬浮液密度或黏土用量以及减小硅铁粒度均会使悬浮液的粘度提高, 从而使加重质颗粒的沉降速度下降, 稳定性得到提升。此外, 为了进一步验证该悬浮液体系用于实际分选的可行性, 将不同密度的悬浮液用于选煤浮沉试验分选混合煤样, 在密度为1.30 g/cm3和1.40 g/cm3的重介质悬浮液中, 浮煤产率高且灰分含量较初始煤样大幅降低, 说明该悬浮液体系具有良好的分选性能。

Phase-sensitive optical time domain reflectometry (Ф-OTDR) is an effective way to detect vibrations and acoustic waves with high sensitivity, by interrogating coherent Rayleigh backscattering light in sensing fiber. In particular, fiber-optic distributed acoustic sensing (DAS) based on the Ф-OTDR with phase demodulation has been extensively studied and widely used in intrusion detection, borehole seismic acquisition, structure health monitoring, etc., in recent years, with superior advantages such as long sensing range, fast response speed, wide sensing bandwidth, low operation cost and long service lifetime. Significant advances in research and development (R&D) of Ф-OTDR have been made since 2014. In this review, we present a historical review of Ф-OTDR and then summarize the recent progress of Ф-OTDR in the Fiber Optics Research Center (FORC) at University of Electronic Science and Technology of China (UESTC), which is the first group to carry out R&D of Ф-OTDR and invent ultra-sensitive DAS (uDAS) seismometer in China which is elected as one of the ten most significant technology advances of PetroChina in 2019. It can be seen that the Ф-OTDR/DAS technology is currently under its rapid development stage and would reach its climax in the next 5 years.

High sensitivity of a distributed optical-fiber vibration sensing (DOVS) system based on the phase-sensitivity optical time domain reflectometry (Φ-OTDR) technology also brings in high nuisance alarm rates (NARs) in real applications. In this paper, feature extraction methods of wavelet decomposition (WD) and wavelet packet decomposition (WPD) are comparatively studied for three typical field testing signals, and an artificial neural network (ANN) is built for the event identification. The comparison results prove that the WPD performs a little better than the WD for the DOVS signal analysis and identification in oil pipeline safety monitoring. The identification rate can be improved up to 94.4%, and the nuisance alarm rate can be effectively controlled as low as 5.6% for the identification network with the wavelet packet energy distribution features.

A real-time intelligent fiber-optic perimeter intrusion detection system (PIDS) based on the fiber Bragg grating (FBG) sensor network is presented in this paper. To distinguish the effects of different intrusion events, a novel real-time behavior impact classification method is proposed based on the essential statistical characteristics of signal’s profile in the time domain. The features are extracted by the principal component analysis (PCA), which are then used to identify the event with a K-nearest neighbor classifier. Simulation and field tests are both carried out to validate its effectiveness. The average identification rate (IR) for five sample signals in the simulation test is as high as 96.67%, and the recognition rate for eight typical signals in the field test can also be achieved up to 96.52%, which includes both the fence-mounted and the ground-buried sensing signals. Besides, critically high detection rate (DR) and low false alarm rate (FAR) can be simultaneously obtained based on the autocorrelation characteristics analysis and a hierarchical detection and identification flow.

A fiber-optic humidity sensor has been fabricated by coating a moisture sensitive polymer film to the fiber Bragg grating (FBG). The Bragg wavelength of the polyimide-coated FBG changes while it is exposed to different humidity conditions due to the volume expansion of the polyimide coating. The characteristics of sensors, including sensitivity, temporal response, and hysteresis, were improved by controlling the coating thickness and the degree of imidization during the thermal curing process of the polyimide. In the relative humidity (RH) condition ranging from 11.3% RH to 97.3% RH, the sensitivity of the sensor was about 13.5 pm/% RH with measurement uncertainty of ±1.5% RH.

A novel multi-channel distributed optical fiber intrusion monitoring system with smart fiber link backup and on-line fault diagnosis functions was proposed. A 1×N optical switch was intelligently controlled by a peripheral interface controller (PIC) to expand the fiber link from one channel to several ones to lower the cost of the long or ultra-long distance intrusion monitoring system and also to strengthen the intelligent monitoring link backup function. At the same time, a sliding window auto-correlation method was presented to identify and locate the broken or fault point of the cable. The experimental results showed that the proposed multi-channel system performed well especially whenever any a broken cable was detected. It could locate the broken or fault point by itself accurately and switch to its backup sensing link immediately to ensure the security system to operate stably without a minute idling. And it was successfully applied in a field test for security monitoring of the 220-km-length national borderline in China.

Few-mode fiber Bragg grating (FM-FBG) has wide applications in the field of multi-wavelength fiber lasers and fiber-optic sensing. In this letter, FBG is successfully written in a novel type of FM fiber (FMF) based on 248-nm excimer laser and a uniform phase mask. A low-loss coupling between the FMF to a singlemode fiber is realized by a graded-index multi-mode fiber with a length of about a quarter pitch. The sensing properties of the FMF grating are further investigated. The experimental results indicate that the novel FM-FBG has sensitivities of temperature, strain, and bending of 11.2 pm/oC, 1.3 pm/\mu \varepsilon, and 636.9 pm/m-1, respectively.