We demonstrate a fiber Bragg grating (FBG) pressure sensor based on a spring-diaphragm elastic structure (SDES) for measuring ultimate pressure. The spring-diaphragm elastic structure model can effectively prevent the fiber Bragg grating from being broken under large pressure situations. The geometrical parameters of the sensor are optimally optimized by analyzing the structure of the spring and the diaphragm. By analyzing the results based on the spring-diaphragm elastic structure, the pressure sensor is manufactured and experimentally verified for extreme pressure conditions. For the first time, the fiber Bragg grating pressure sensor was operated at the ultimate pressure. The ultimate pressure experiment demonstrates a stable linear relationship between the fiber Bragg grating central wavelength and external pressure in the range of 0–100 MPa, and the sensitivity of the pressure sensor is 79.7 pm/MPa with a linear correlation coefficient of 0.9998. In addition, the relative temperature sensitivity coefficients of the FBGs were obtained as ${K}_{P} =5.99 \times 10^{-6}/^{\circ }\text{C}$ and ${K}_{T} =6.265 \times 10^{-6}/^{\circ }\text{C}$ respectively to eliminate the temperature cross-sensitivity effect. The pressure sensor can be used for ultimate pressure detection, especially for deep sea detection, oil exploration, and chemical monitoring.

When light traverses through water, it undergoes influence from the absorption and scattering of particles, resulting in diminished contrast and color distortion within underwater imaging. These effects further constrain the observation of underwater environments and the extraction of features from submerged objects. To address these challenges, we introduce an underwater color image processing approach, which amalgamates the frequency and spatial domains, enhancing image contrast in the frequency domain, adaptively refining image color within the spatial domain, and ultimately merging the contrast-enhanced image with the color-corrected counterpart within the CIE L*a*b* color space. Experiments conducted on standard underwater image benchmark datasets highlight the significant improvements our proposed method achieves in terms of enhancing contrast and rendering more natural colors compared to several state-of-the-art methods. The results are further evaluated using four commonly used image metrics, consistently showing that our method yields the highest average value. The proposed method effectively addresses challenges related to low contrast, color distortion, and obscured details in underwater images, a fact especially evident in various scenarios involving color-affected underwater imagery.

In this paper we present a magnetic probe structure based on magneto-fluidic and laser internal cavity modulation. We used a single-mode-no-core-single-mode fiber structure coated by a magnetic fluid as a sensing element, and inserted the sensing element in the inner cavity of a laser. Highly sensitive, high signal-to-noise ratio (SNR), narrow half-height width (FWHM) sensing signals have been obtained using intra-laser cavity modulation. The magnetic detection sensitivity of the sensor was improved, and a sensing system with a magnetic detection sensitivity of 1.76 × 10⁻³ mw/Oe and a linearity of 99.709% was achieved. The temperature sensitivity is 0.035 μW/°C. The limit error of the magnetic field sensor is ±0.006035%. Meanwhile, output signal index of the sensing system is FWHM<40pm.

Underwater Wireless Optical Communication (UWOC) plays a crucial role in marine exploration and observation due to its high speed and low latency characteristics, while research on underwater time and frequency transfer (UTFT) is relatively lacking. The complicated underwater environments, absorption and scattering effects severely degrade signal stability and signal-to-noise-ratio (SNR). In response to this issue, a photon packet transmission model is established based on the Monte Carlo simulation (MCS). The effects of different parameters, including water conditions, divergence angles, receiving apertures, are systematically analyzed, with key indicators such as phase noise and Allan deviation, identified as performance measures. An experimental platform is also built using kaolin turbidity to obtain experimental results corresponding to different frequencies and turbidity levels, which are then compared with simulation results. The high consistency between simulation and experimental results verifies the reliability of the proposed model. This research provides a feasible method for performance prediction and tolerance design of UTFT networks.

Optical-carried microwave interferometry (OCMI) has attracted increasing attention in recent years, as it combines the ease of phase extraction and manipulation of microwave techniques with the low-loss transfer of optical fibers. Conventional OCMI implementations typically employ broadband light sources and coherent photodetection, which inevitably suffer from dispersion, polarization fading, and phase drift, severely limiting the achievable sensing distance. In this work, we proposed an optimized OCMI architecture that adopts incoherent photodetection combined with electric-domain microwave interferometry. Comprehensive theoretical analysis and systematic experiments demonstrate that the proposed system enables robust, dynamic, and long-haul fiber transfer delay (FTD) measurements, no less than in 15 km length, with improved resolution and stability. It provides new insight for building long-haul FTD sensor networks.