Search Results (9)

The aim of this study was to prepare and characterize thin hybrid films on polyurethane-coated knitted fabrics and to achieve satisfactory color fastness to artificial light. Sol–gel-derived hybrid thin films were deposited via the dip-coating of 3-glycidoxypropiltrimethoxysilane. Titanium dioxide (TiO₂) and zinc oxide (ZnO) nanopowders were added to compensate for the insufficient aging resistance, which manifests itself in low color fastness and is one of the most frequent complaints from manufacturers of coated marine fabrics (yachts, boats, etc.). The optimum processing conditions were determined by varying the concentration of precursors and auxiliaries, the mass concentration of TiO₂ and ZnO nanopowders, the drawing speed, and the methods and process of fabric treatment. The hybrid films were also characterized using scanning electron microscopy and Fourier transform infrared spectroscopy with attenuated total internal reflection, while Spectraflash SF 300 investigated color fastness. After 300 h of exposure in a xenon chamber, the thin hybrid films showed good color fastness and good resistance to washing cycles. The sol–gel treatment proved to be a successful answer to the manufacturers’ need for the post-treatment of polyurethane-coated knitted fabrics against UV radiation for use in the marine sector (yachts, speedboats, etc.). Full article

To analyze the induced electric field characteristics generated by the rotation and shaking of underwater metal vehicles, a mathematical model of the induced electric field generated by the underwater metal vehicles was derived using Faraday’s electromagnetic induction law. A mathematical model of the induced electric field on the electrode pairs of metal vehicles shaking in different coordinate system planes was established through in-depth analysis. Based on this, a three-component output model of the induced electric field output by the three-axis sensor was obtained when the measurement system was shaking at all three angles. At a constant speed, the induced electric field interference output by the measurement system is a static signal. The value of the static electric field is proportional to the vehicle’s speed and the value of the geomagnetic field, and the value of each component is related to the direction of movement and the value of the geomagnetic field component. The simulation results show that when the navigation body is moving at a constant speed, the induced electric field is a static electric field with a magnitude of mV/m. In a stable state, the induced electric field noise generated by changes in pitch, roll, and heading sway is at the nV/m level and does not have a significant impact on detection. The correctness of the theoretical model has been verified through experiments on offshore speedboat platforms, and it is feasible to use metal navigation bodies for ship electric field detection. Full article

This paper addresses the challenge of reduced tracking accuracy in maritime electro-optical tracking equipment when dealing with high-mobility targets like speedboats and aircraft due to off-target error delays. We propose an innovative technique that leverages inertial navigation data to enhance target prediction and tracking control. Our approach involves the real-time integration of high-frequency inertial navigation-derived attitude information into the tracking system. By combining off-target error information with angular measurements from the tracking mechanism, we project the vector of the tracked target into multiple coordinate systems, including the imaging coordinate system, carrier coordinate system, and geographic coordinate system. Subsequently, we model and predict the target’s motion trajectory in the relatively slow-changing geographic coordinate system. This transformation process increases the update frequency and real-time performance of the tracking control position loop command angle. Unlike traditional control methods that heavily rely on the model of the controlled object, our approach significantly improves tracking accuracy and engineering applicability. It offers a technology-based optimization of tracking and control performance through an interdisciplinary theoretical fusion, deeply integrating inertial navigation technology with tracking control technology. Experimental results with maritime electro-optical tracking equipment demonstrate that our proposed control technique increases tracking accuracy for high-speed targets by approximately threefold compared to traditional methods. Under the same experimental conditions, the off-target error statistics are reduced from 1.8 mrad to 633 μrad. Full article

In the shallow-water waveguide environment, the tonal signals radiated by moving targets carry modal interference and Doppler shift information. The modal interference can be used to obtain the time of the closest point of approach ($t_{CPA}$) and the ratio of the range at the closest point of approach to the velocity of the source ($r_{CPA}/v$). However, parameters $r_{CPA}$ and v cannot be solved separately. When $t_{CPA}$ is known, the $r_{CPA}$ and the v of the target can be obtained theoretically by using the Doppler information. However, when the Doppler frequency shift is small or at a low signal-to-noise ratio, there will be a strong parametric coupling between $r_{CPA}$ and v. In order to solve the above parameter coupling problem, a target motion parameter estimation method from tonal signals with a single hydrophone is proposed in this paper. The method uses the Doppler and modal interference information carried by the tonal signals to obtain two different parametric coupling curves. Then, the parametric coupling curves can be used to estimate the two motion parameters. Simulation experiments verified the rationality of this method. The proposed method was applied to the SWellEx-96 and speedboat experiments, and the estimation errors of the motion parameters were within 10%, which shows the method is effective in its practical applications. Full article

In order to realize the real-time detection of an unmanned fishing speedboat near a ship ahead, a perception platform based on a target visual detection system was established. By controlling the depth and width of the model to analyze and compare training, it was found that the 5S model had a fast detection speed but low accuracy, which was judged to be insufficient for detecting small targets. In this regard, this study improved the YOLOv5s algorithm, in which the initial frame of the target is re-clustered by K-means at the data input end, the receptive field area is expanded at the output end, and the loss function is optimized. The results show that the precision of the improved model’s detection for ship images was 98.0%, and the recall rate was 96.2%. Mean average precision (mAP) reached 98.6%, an increase of 4.4% compared to before the improvements, which shows that the improved model can realize the detection and identification of multiple types of ships, laying the foundation for subsequent path planning and automatic obstacle avoidance of unmanned ships. Full article

Marine target detection technology plays an important role in sea surface monitoring, sea area management, ship collision avoidance, and other fields. Traditional marine target detection algorithms cannot meet the requirements of accuracy and speed. This article uses the advantages of deep learning in big data feature learning to propose the YOLOv4 marine target detection method fused with a convolutional attention module. Marine target detection datasets were collected and produced and marine targets were divided into ten categories, including speedboat, warship, passenger ship, cargo ship, sailboat, tugboat, and kayak. Aiming at the problem of insufficient detection accuracy of YOLOv4’s self-built marine target dataset, a convolutional attention module is added to the YOLOv4 network to increase the weight of useful features while suppressing the weight of invalid features to improve detection accuracy. The experimental results show that the improved YOLOv4 has higher detection accuracy than the original YOLOv4, and has better detection results for small targets, multiple targets, and overlapping targets. The detection speed meets the real-time requirements, verifying the effectiveness of the improved algorithm. Full article

With the growing need to understand our surroundings and improved means of sensor manufacturing, the concept of Internet of Things (IoT) is becoming more interesting. To enable continuous monitoring and event detection by IoT, the development of low power sensors and interfaces is required. In this work we present a novel, switched inductor based acoustic sensor interface featuring a bandpass filter and envelope detector, perform a sensitivity, frequency selectivity, and power consumption analysis of the circuit, and present its design parameters and their qualitative influence on circuit characteristics. We develop a prototype and present experimental characterization of the interface and its operation with input signals up to 20 mV peak-to-peak, at low acoustic frequencies from 100 Hz to 1 kHz. The prototype achieves a sensitivity of approximately 2 mV/mV in the passband, a four times lower sensitivity in the stopband, and a power consumption of approximately 3.31 µW. We compare the prototype interface to an interface consisting of an active bandpass filter and a passive voltage doubler using a prerecorded speedboat signal. Full article

Smoothed particle hydrodynamics (SPH) and the finite element method (FEM) are often combined with the scope to model the interaction between structures and the surrounding fluids (FSI). There is the case, for instance, of aircrafts crashing on water or speedboats slamming into waves. Due to the high computational complexity, the influence of air is often neglected, limiting the analysis to the interaction between structure and water. On the contrary, this work aims to specifically investigate the effect of air when merged inside the fluid–structure interaction (FSI) computational models. Measures from experiments were used as a basis to validate estimations comparing results from models that include or exclude the presence of air. Outcomes generally showed a great correlation between simulation and experiments, with marginal differences in terms of accelerations, especially during the first phase of impact and considering the presence of air in the model. Full article

Vehicle simulators are multimodal interactive applications used in many human activities with different purposes. However, they are sometimes expensive systems that need to be carefully studied before they are designed and built, since some simulators can actually be much more expensive than the simulated vehicle. This is an important issue, although it is sometimes overlooked in scientific research. This paper proposes four different setups (with a variety of visual, sound, motion generation, and user-input interfaces) for non-aerial vehicle simulation, using a speedboat simulator as a case study. These setups are analysed in terms of their cost and their effectiveness is discussed. Rough figures are provided to give a comparative insight into the economic order of magnitude necessary to design and build a vehicle simulator. Full article