This paper presents a systematic review of the research available on salinity optic fiber sensors (OFSs) for seawater based on the refractive index (RI) measurement principle for the actual measurement demand of seawater salinity in marine environmental monitoring, the definition of seawater salinity and the correspondence between the seawater RI and salinity. To further investigate the progress of in situ measurements of absolute salinity by OFSs, the sensing mechanisms, research progress and measurement performance indices of various existing fiber optic salinity sensors are summarized. According to the Thermodynamic Equation of Seawater-2010 (TEOS-10), absolute salinity is recommended for sensor calibration and measurement. Comprehensive domestic and international research progress shows that fiber-optic RI sensors are ideal for real-time, in situ measurement of the absolute salinity of seawater and have excellent potential for application in long-term in situ measurements in the deep ocean. Finally, based on marine environmental monitoring applications, a development plan and the technical requirements of salinity OFSs are proposed to provide references for researchers engaged in related industries.

Fiber optic sensors are expected to be an auxiliary measurement tool in the field of ocean observation due to their small size, easy networking, intrinsic immunity to electromagnetic interference, and many other advantages. In recent years, the research around fiber optic sensing technology in the field of physical ocean observation has received increasing attention from researchers. According to the different measurement objects and measurement principles, the focus is on the seawater temperature sensor based on fiber grating, seawater salinity sensor, seawater pressure sensor, seawater salinity sensor based on multi-core optical fiber, seawater salinity sensor based on Michelson and Mach-Zehnder interferometry, seawater pressure sensor based on Fabry-Perot cavity, fiber optic temperature salinity and depth sensors based on resonant and coupling technology, flow velocity sensor based on multi-core optical fiber and fiber optic turbulence sensors based on thermal dissipation and turbulent kinetic energy dissipation. The test methods and test results of various sensors are analyzed, and the advantages and disadvantages of the technologies are pointed out. Prospects for the application of fiber optic sensors in physical ocean observation are presented.

This paper proposes an approach for acoustic emission (AE) source localization in a large marble stone using distributed feedback (DFB) fiber lasers. The aim of this study is to detect damage in structures such as those found in civil applications. The directional sensitivity of DFB fiber laser is investigated by calculating location coefficient using a method of digital signal analysis. In this, autocorrelation is used to extract the location coefficient from the periodic AE signal and wavelet packet energy is calculated to get the location coefficient of a burst AE source. Normalization is processed to eliminate the influence of distance and intensity of AE source. Then a new location algorithm based on the location coefficient is presented and tested to determine the location of AE source using a Delta (Δ) DFB fiber laser rosette configuration. The advantage of the proposed algorithm over the traditional methods based on fiber Bragg Grating (FBG) include the capability of: having higher strain resolution for AE detection and taking into account two different types of AE source for location.

Infrared and visible images are fused to obtain a high-quality visible image with salient infrared targets that can be used in other vision tasks. The fusion strategy is key to achieving efficient image fusion. The strategies currently used in deep learning-based image fusion methods are based on manual computation and are unlearnable, limiting further improvements in infrared and visible image fusion. In this paper, FusionGRAM, a novel end-to-end infrared and visible image fusion framework, is proposed. It adaptively fuses visible detail information and infrared thermal information. The framework is fully convolutional, and the parameters of each part can be learned. The proposed method applied dense connections with an attention mechanism and gradient residual, thereby improving the network’s ability to obtain critical information during feature extraction. Further, pixel intensity loss and detail loss functions were used to train FusionGRAM. Fused features were reconstructed using four convolution layers to obtain an informative fused image. Ablation experiments and comparisons on public datasets showed that FusionGRAM outperformed current state-of-the-art fusion methods in subjective and objective evaluations.

The train-induced vibration response provides a flexible solution for the real-time monitoring deformation of high-speed railway track slab in actual operation. This paper proposes a long-term real-time monitoring method for track slab deformation based on wavelet packet energy (WPE) using fiber optic accelerometers to record train-induced vibration. We found that the vibration response law of track slab deformation could be established by using the WPE of the frequency band covering the first- and second-order frequencies induced by the adjacent carriages. A field test was carried out for more than one year on the Beijing–Shanghai high-speed railway to investigate the train-induced vibration response law of track slab that was continuously deformed under a long-term temperature load. The maximum values of the WPE characteristic index appeared in winter and summer, and they were positively correlated with the temperature difference between the air environment and the track slab under the daily temperature load. These results were demonstrated to be consistent with the track slab deformation law for long-term and daily temperature loads. The novel method based on fiber optic accelerometers and WPE provides a new method for the long-term and real-time monitoring of track slab deformation.

Fiber optic seismic sensors have important application prospects in the field of earthquake science research and underground structure detection, due to their strong adaptability in harsh environments such as deep wells, seabeds, and glaciers. It has always been one of the key problems to achieve ultra-low noise levels over a wide measurement frequency band for fiber optic seismic sensors. This article reviews two typical low-noise broadband fiber optic seismic sensing techniques, including narrow-linewidth laser frequency scanning and frequency locking sensing technique, laser interferometric phase interrogation technique. The principles are given. The measurement frequency band and noise level are tested and discussed. Recent progresses on crustal deformation observation, earthquake monitoring, water temperature solid tide detection and deep earth structure exploration based on fiber optic seismic sensors are introduced. Finally, the possible research trends are discussed.