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The aim of this paper is to create a combined machine for planning the soil for sowing cotton on the edges. A total for the execution of the innovation of planning the soil for sowing cotton on the edges was developed, which comprises of a dump deep-dredger with a slanted rack and a comb-maker. The essential standards and strategies of classical mechanics, numerical examination and measurements were utilized in this paper. The plan conspire of the combined unit is advocated. The following results were obtained from the outcomes of multivariate tests set up: the width of the ripper within the extend of 10.5-11.03 cm, the disintegrating point of 27°, the point of establishment of the plowshare edge to the heading of movement of 31°. The arrangement of edges of the desired degree with negligible vitality utilization is given with a width and length of the deep-dredger bit, separately, of 5 and 20 cm, edge hold width of 21 cm, the length of its wing within the run of 47-49 cm, and a least longitudinal.

The dredging pump is the most critical dredging equipment for the cutter suction dredger, and its performance is one of the decisive factors for the cutter suction dredger productivity. Relying on the Xiamen New Airport Phase II Project, a comparative analysis of the dredging pump performance before and after impeller wear was carried out under medium-coarse sand conveying conditions. The results show that impeller wears will cause the dredging pump head to fall and performance degradation. In the range of normal construction process parameters, the larger the impeller rotational speed is or the smaller the concentration of medium-coarse sand conveying is, the more significant the decline in dredging pump performance will be. The research results can provide guidance for the cutter suction dredger pump working point adjustment and process optimization in the dredging pump wear condition.

With the continuous development of the shipping industry, suction dredgers play a crucial role as functional vessels for channel dredging. The reamer, as the core component of a cutter suction dredger, significantly impacts the energy consumption of the entire vessel. Most suction dredger reamers are powered by three-phase asynchronous motors. To fully utilize the motor’s output power, there is an urgent need to design a constant power control system to ensure stable and consistent power output despite variations in system parameters. This paper proposes a fuzzy PID control algorithm to address the limitations of traditional PID control, such as slow and insufficient response times, in order to achieve smoother and faster reamer power regulation. The proposed control strategy is validated through both simulations and experiments. Results show that the fuzzy PID algorithm reduces overshoot by an average of 9.85%, rise time by 38.58%, and regulation time by 42%, compared to traditional PID control. Additionally, the fuzzy PID control demonstrates superior robustness in dynamic responses to system changes. Overall, the fuzzy PID control system outperforms traditional PID in maintaining constant power control of the reamer.

During the continuous operation of trailing suction hopper dredger (TSHD), equipment workload exhibits significant time-varying characteristics. Maintaining dynamic symmetry between power generation and consumption is crucial for ensuring system stability and preventing power supply failures. Key challenges lie in dynamic perception, accurate prediction, and real-time power management to achieve this equilibrium. To address this issue, this paper proposes and constructs a “prediction-driven dynamic power management method.” Firstly, to model the complex temporal dependencies of the workload sequence, we introduce and improve a dilated convolutional long short-term memory network (Dilated-LSTM) to build a workload prediction model with strong long-term dependency awareness. This model significantly improves the accuracy of workload trend prediction. Based on the accurate prediction results, a dynamic power management strategy is developed: when the predicted total power consumption is about to exceed a preset margin threshold, the Power Management System (PMS) automatically triggers power reduction operations for adjusfigure loads, aiming to maintain grid balance without interrupting critical loads. If the power that the generator can produce is still less than the required power after the power is reduced, and there is still a risk of supply-demand imbalance, the system uses an Improved Grey Wolf Optimization (IGWO) algorithm to automatically disconnect some non-critical loads, achieving real-time dynamic symmetry matching of generation capacity and load demand. Experimental results show that this mechanism effectively prevents generator overloads or ship-wide power failures, significantly improving system stability and the reliability of power supply to critical loads. The research results provide effective technical support for intelligent energy efficiency management and safe operation of TSHDs and other vessels with complex working conditions.

Rake suction dredgers are specialized vessels used for dredging projects in water bodies. Power positioning refers to the precise control of the vessel’s position in the water using power systems to complete operational tasks or maintain specific positions. This paper proposes a PID control algorithm based on reinforcement learning to address the accuracy and stability issues of power positioning in rake suction dredgers. The algorithm utilizes a deep Q-network as the core of reinforcement learning, combined with PID control principles, to enable the intelligent agent to control the vessel in real time. In algorithm design, the problem of overestimation is effectively addressed through a dual neural network structure, and an experience replay mechanism is introduced to enhance training efficiency and stability. In the reinforcement learning process, a reward function suitable for the characteristics of rake suction dredgers is designed, considering the balance between path-tracking accuracy and vessel stability. Experimental results demonstrate that the proposed algorithm can achieve power positioning control of rake suction dredgers under different sea conditions, with high path tracking accuracy and stability, providing an effective solution for the autonomous navigation and operation of rake suction dredgers.

Trailing suction hopper dredgers are usually equipped with high-pressure-jet pumps, which provide high pressure water to improve dredging efficiency. In a newly built trailing suction hopper dredger, the high-pressure-jet pump encountered serious vibration problem. In this study, unsteady Reynolds-averaged Navier-Stokes equations were solved with Shear Stress Transport k-ω turbulence model to carry out pump-pipeline matching analysis, and the causes of flow-induced vibration were discussed. The impeller was correspondingly optimized by increasing the blade number and moderately decreasing the blade inlet setting angle and wrap angle. The optimization results show that the high-pressure-jet pump works in the high-efficiency zone both for the high-speed dredging process and low-speed hopper discharging process, and the time-average value and amplitude of the hydraulic radial force drops by more than 30% under the required working condition, which effectively mitigates the flow-induced vibration.

Trailing suction hopper dredgers (TSHDs) are widely used in port subgrade reinforcement and land reclamation layered backfilling, with construction quality relying on sediment settling paths and deposition characteristics. To tackle the lack of guidance on key parameters like bottom door opening, sailing speed, and related problems, a multiphase settling model based on coupled CFD–DEM is developed. This model analyzes sediment particle settling trajectories, distribution patterns, and uniformity responses under different conditions. Through orthogonal simulations of bottom door openings (22%, 50%, 100%) and sailing speeds (0.02, 0.045, 0.07 kn), the coupling relationships among particle settling velocity, main deposition layer thickness, and spatial extension are revealed, clarifying how parameter variations affect deposition uniformity and coverage. The results indicate that, relative to a small opening (22%), a moderate bottom door opening (50%) simultaneously increases layer thickness and markedly improves deposition uniformity (minimum uniformity index), whereas a very large opening (100%) further increases thickness at the expense of a modest loss of uniformity relative to the moderate case; higher sailing speeds cause long-range migration and local deposition irregularities. Engineering validation using field data from the Junyang 1 TSHD in the Manila Pasay project shows that a moderate bottom door opening of about 15% (selected based on the 22–50% simulation trend), combined with a medium sailing speed of about 0.4 kn, achieves a good balance between thickness control and uniformity. A coupled multi-physics analysis framework and a parameter–response map are established, systematically revealing the influence of operational parameters on sediment settling and deposition uniformity and providing quantitative support for TSHD backfilling operations.

The increasing adoption of Maritime Autonomous Surface Ships (MASS) poses significant challenges to the safe operation of maritime infrastructure. As most maritime accidents occur in port and coastal areas, there is a pressing need to address the limitations of MASS navigation in these environments. This paper proposes a novel concept for MASS-ready ports, utilizing shore-mounted sensors to mitigate blind spots caused by infrastructure and traffic density. Drawing inspiration from the automotive domain’s Manage Automated Driving (MAD) concept, our approach integrates LiDAR, RADAR, and camera sensors to create a safe and reliable navigation system for MASS in port areas. A case study on the operation of an autonomous dredger in the Port of Emden (NPorts) in northern Germany demonstrates the feasibility of our concept, using historical maneuver data and sensor simulation. Our research highlights the importance of shore-based sensor technology in supporting MASS navigation in port waters, paving the way for safer and more efficient maritime operations.

Maritime traffic is undergoing a transformation from on-board navigation towards highly automated, remotely controlled operations. Given the constrained and well-defined area of operation, port maintenance is a predestined use case for a highly automated vessel. In combination with alternative driving systems, maritime automation technologies hold a great potential of increasing efficiency and sustainability in port maintenance. To achieve this goal, this paper describes the concept of a highly automated hopper-dredger for port maintenance, proposing assistance systems for navigation in different automation stages according to the definition of the International Maritime Organization (IMO). Commercial off-the-shelf technologies are employed to realize assistance systems, transferring also solutions to the maritime environment that are already established in other industrial domains. A method for Verification and Validation of the proposed concept is presented and applied in sea trials with a research vessel. Regulatory aspects are considered as well. The study concludes that a remotely operated dredger can be realized based on State-of-the-Art sensor systems, enabling sustainable, efficient and cost-saving port maintenance. Based on the presented results, clear recommendations are derived for automation concepts and suitable technologies at different IMO automation level. The need for a legal framework to utilize the potential of the proposed concept in regular operations is pointed out.

The results of experimental testing of methods for remote control of underwater walking mini-dredgers are discussed. Tests were carried out in real water conditions on the basis of a prototype of a 6-legged underwater walking vehicle. During the tests, technological operations for clearing and deepening small channels and eriks, as well as the extraction of sapropel from the bottom of the lake, were simulated. During the experiments, a mini-dredger has been controlled using video information of on-board video cameras. Due to poor visibility in the zone of hydraulic erosion of bottom soil, management was carried out in conditions of an incomplete and ambiguous understanding of the external environment. Local positioning was carried out according to natural landmarks. It is shown that fairly accurate remote control of the movement of a mini-dredger can be organized on the basis of public satellite maps of the area, even in conditions of a lack of sensory information. Moreover, the operation of an underwater dredger can be realized with minimal external control influences. The research results may be demanded in the development of walking robotic systems intended for the rehabilitation of degrading small water bodies and for other underwater technical work.