Height optimization system for trailing suction dredger-mounted energy dissipation device

Abstract

The invention provides a height optimization system for a trailing suction dredger-mounted energy dissipation device. The optimization system comprises a core parameter input module, a loading process simulation and prediction module, a loading efficiency analysis module, a design optimization output module and an automatic height adjustment module. In the construction process, the height of the energy dissipation device can be automatically and accurately adjusted in real time according to different soil texture and different slurry concentration requirements. The energy dissipation device cannot be too low to cause quick settling coarse particle sediment to block an outlet of the energy dissipation device, and cannot be too high to cause cabin entering water flow to disturb sediment to increase overflow loss of suspended sediment. By accurately controlling the height of the energy dissipation device, the construction efficiency of the trailing suction dredger is improved, meanwhile, the adverse effect of loading overflow on the construction water area environment can be reduced, and the engineering application value is achieved. The height of the energy dissipation device can be automatically and flexibly adjusted, and the loading efficiency and the loading flatness of silt in the cabin are improved by reducing overflow loss.

Description

[0001] This application is a divisional application with the application date of October 10, 2024, application number 202411411313.6, and invention name "A method for optimizing the automatic adjustment of the height of the energy dissipation device of a bucket suction dredger". Technical Field

[0002] The invention belongs to the technical field of dredging engineering, and in particular relates to a height optimization system of an energy dissipation device carried by a trailing suction dredger. Background Art

[0003] Trailing suction hopper dredger is the main ship in the dredging industry, and plays an important role in waterway dredging, land reclamation, port maintenance and other projects. The mud tank system is an important part of the trailing suction hopper dredger, which is responsible for the important functions of dredging loading and flushing. The loading construction process of the trailing suction hopper dredger can be divided into two parts: loading and overflow according to the characteristics of different stages. According to the characteristics of the target soil, the mud (water and sediment mixture) continuously flows into the mud tank through the tank inlet pipe. Part of the sediment is deposited on the bottom of the tank under the action of gravity, and the other part of the sediment is mixed with water in the tank in a suspended state. When the liquid level of this part of the water-sand mixture exceeds the height of the overflow tube, overflow losses of varying degrees occur.

[0004] The loading overflow construction efficiency of a trailing suction hopper dredger is directly related to the design and layout of the energy dissipation device. At present, the energy dissipation devices of most domestic trailing suction hopper dredgers are of fixed design, and cannot adjust the height of the energy dissipation device according to various complex working conditions such as different soil types and mud concentrations, so as to reduce the disturbance of the inflow water to the silt in the cabin in a targeted manner. When the silt particles are coarse, the silt is deposited quickly, and the installation height of the energy dissipation device is too low to easily block the outlet; when the silt particles are fine, the installation height of the energy dissipation device is too high, and the fine silt will be disturbed by the inflow water, causing most of it to be suspended, increasing the overflow loss, reducing the loading efficiency, and at the same time having an adverse impact on the surrounding construction water environment. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides an energy dissipation device of a trailing suction hopper dredger with adjustable height, an automatic height adjustment optimization method and a ship-borne system, which can realize automatic and flexible adjustment of the height of the energy dissipation device during the construction of the trailing suction hopper dredger, and improve the loading flatness and loading efficiency of the sediment in the cabin by minimizing the disturbance of the sediment in the cabin and reducing the overflow loss, and can meet the needs of various working conditions such as different soil types, inlet concentrations, inlet flow rates, and structural dimensions of the mud cabin of the trailing suction hopper dredger.

[0006] Technical Solution One of the purposes of the present invention is to provide a method for optimizing the automatic height adjustment of an energy dissipation device of a trailing suction dredger, comprising: Process 1: constructing an adjustable height energy dissipation device in the cabin of the suction dredger; Process 2 determines the optimal energy dissipation height; Step 1: Determine the core parameters through the existing trailing suction hopper construction related data, geological survey report of the construction area, soil condition data, etc. The core parameters include: geometric model, boundary conditions, grid conditions, initial conditions, fluid movement and sediment movement. The details are as follows: (1) The geometric model mainly includes: the dimensions of the mud tank structure, the dimensions of the transverse and longitudinal triangular tanks, the dimensions of the overflow equipment, the dimensions and height of the energy dissipation equipment, and the positions of the transverse and longitudinal triangular tanks and the energy dissipation overflow equipment relative to the mud tank; (2) Boundary conditions include: the inlet boundary is the loading flow rate and loading mud concentration, the overflow boundary is the free outflow boundary, the upper boundary of the mud tank is the atmospheric pressure boundary, and the bulkhead boundary is the wall boundary with a certain roughness material; (3) Grid conditions include: grid range in the x, y, and z directions and unit grid size.

[0007] (4) Initial conditions include: initial water level H0 and loading simulation time T; (5) Fluid motion parameters include: fluid temperature T, fluid viscosity, and fluid motion equation.

[0008] (6) The fluid motion equation uses the RNG k−ε equation according to the characteristics of the tank, as follows: Where: - turbulent kinetic energy; - velocity component; , - coordinate components; ——molecular viscosity coefficient; ——turbulent viscosity coefficient; —— term of turbulent energy generation; ——turbulent energy dissipation rate; , —— , The turbulent Prandtl number; ,in , , ; ,in , .

[0009] Sediment movement parameters mainly include sediment particle size, sediment density, sediment porosity, critical Shields number, underwater angle of repose, displacement motion coefficient and scour coefficient, involving four types of movement: sediment suspension, sediment deposition, sediment scour and sediment displacement. The following sediment empirical formula is used to automatically calculate the movement form of each sediment particle during the simulation process.

[0010] Among them, the empirical formula of Mastbergen and Von den Berg is used to calculate the sediment initiation and scouring process.

[0011] In the formula, Refers to the entrainment coefficient, is the external normal direction of the bed surface, Refers to the Shields number of sediment particles. Refers to the critical Shields number of sediment particles, g The acceleration due to gravity, is the dynamic viscosity of the fluid, d s Refers to the sand particle size, is the density of sediment, is the fluid density.

[0012] Shields number of sediment particles The expression is: In the formula, is the shear stress on the riverbed surface.

[0013] In non-horizontal bed areas, considering the influence of the sediment repose angle, the critical Shields number correction value is θ cr,i ’ for In the formula, is the perpendicular to the sedimentation surface and the gravitational acceleration g The angle of φ It is the angle of repose of the sediment; ψ It is the angle between the uphill direction of the fluid and the flow direction.

[0014] The empirical formula of Meyer-Peter&Műller equati was used to calculate the bed load transport process in the simulation process.

[0015] Where, bed load sediment thickness δ The calculation formula is: Therefore, the calculation formula for the bed load transport velocity is: Step 2: Carry out simulation prediction of the loading process, including two steps: establishing a loading numerical model and loading simulation prediction.

[0016] Establishing a numerical model for loading: refers to establishing a numerical model capable of simulating the loading construction process based on the input core parameters using CFD software (existing technology) to achieve loading simulation function.

[0017] Loading simulation prediction: Use the above loading numerical model to set different energy dissipation device height position working conditions, perform numerical simulation, simulate the entire loading process, realize the simulation prediction of loading capacity, earthwork volume, total overflow loss and sediment height in the cabin as the loading time changes, and obtain multiple sets of numerical simulation calculation results corresponding to different energy dissipation device height positions. The height position of the energy dissipation device needs to be set manually.

[0018] The numerical simulation results also include: t (3D grid point cloud of flow at time t); ρ t (3D grid point cloud of density at time t); v x (3D grid point cloud of velocity in x direction at time t); v y (3D grid point cloud of the y-direction velocity component at time t). The numerical calculation results are provided to step 3.

[0019] Step 3: Based on the numerical simulation results, the evaluation criteria are set according to the four indicators of loading capacity, earthwork volume, overflow loss, and sediment flatness to obtain the optimal recommended height of the energy dissipation device; In multiple sets of numerical simulation results, different energy dissipation device heights correspond to different four indicators, namely, loading capacity, earthwork volume, overflow loss, and sediment flatness. The evaluation basis sequence is set, and the recommended value for the optimal design of the energy dissipation device height is determined according to the evaluation basis sequence (first gradient, second gradient). Usually, the loading efficiency represented by loading capacity, earthwork volume, and overflow loss is used as the first gradient judgment standard, and the flatness of sediment is used as the second gradient judgment standard. Among them, the larger the loading capacity and earthwork volume, the smaller the overflow loss, and the higher the flatness of the mud tank, indicating that the height of the energy dissipation device under this working condition has a better effect on the loading effect.

[0020] Preferably, the optimization goal is to set the sediment flatness α to be optimal and the earthwork volume D to be maximum, then the optimization model objective function is: Set constraints ( x . t .): in, The length of the time period for calculating the amount of deposited earthwork; For Outflow volume during the time period; For Outflow concentration during the time period; x i Belongs to [0,H], H represents the height of the mud tank, x (it) As a parameter for calculating flatness, it represents the height of sediment deposited at sampling position i at time t, It represents the average height of sediment deposited in the longitudinal centerline section of the mud chamber.

[0021] Where T is the maximum time set initially.

[0022] Set the heights of multiple energy dissipation devices and use the numerical calculation model in step 2 to calculate q t , ρ t , v x and v y , and then calculate the flatness of the deposited sediment and the amount of earthwork. According to the above optimization objectives (optimal flatness and maximum earthwork volume), the best group is selected, and the corresponding energy dissipation equipment height is the optimal energy dissipation equipment height.

[0023] Taking into account time and computing power, and based on relevant numerical calculation and prediction experience, the recommended number of energy dissipation device height groups is 12 to 20, with an interval of 0.25 to 0.5 m between each group and a height variation range of 5 to 6 m.

[0024] Process 3: Loading at the optimal energy dissipation height Step 4: According to the optimal height of the energy dissipation device obtained in step 3, adjust the hydraulic support rod of the adjustable height energy dissipation device to raise or lower the height of the energy dissipation device to the optimal height.

[0025] Furthermore, in step 3, in order to avoid complex numerical calculation process, neural network is introduced to predict sediment height and earthwork volume. As follows: A sediment height prediction model is established to predict sediment height as follows: X is calculated by establishing a prediction model for the X(t) value and the initial and boundary conditions of the numerical simulation as follows: Input value: q t is the three-dimensional grid point cloud of the flow at time t; ρ t is the three-dimensional grid point cloud with density at time t; vx is the three-dimensional grid point cloud of the velocity in the x direction at time t; v y It is the three-dimensional grid point cloud of the y-direction velocity at time t.

[0026] Output value: X (t+Δt) represents the sediment height matrix of the flatness section calculated at the next Δt moment as the label item of the sediment height prediction model. Among them, the three-dimensional position of the energy dissipation equipment is set to 0, which is used to characterize the spatial characteristics of the energy dissipation equipment.

[0027] The q values ​​calculated by numerical simulation are extracted at time intervals of Δt. t , t , v x , v y The q corresponding to each time t , t , v x , v y The convolution kernel feature extraction of the three-dimensional grid data generates a feature matrix, and the corresponding t+Δt moment, which is used to calculate the sediment height in the cabin, is combined into a label matrix X to train the network. Through the above operations, the sediment height prediction model of the calculation point of the flatness calculation plane is obtained by numerical simulation data training.

[0028] In the training phase, the input and label are calculated by the loading process simulation prediction model in step 2; after the training is completed, the actual q t , t , v x , v y Predict the height of sediment at each point, and then reflect the flatness of the sediment.

[0029] The earthwork volume prediction model is established to predict the earthwork volume in the cabin, as follows: As above, dt is the three-dimensional grid point cloud of earthwork volume at time t, and d(t+Δt) represents the earthwork volume calculated at the next Δt time as the label item of the earthwork volume prediction model. t , t , v x , v y The network of the data and the three-dimensional data of the earthwork volume in the mud tank at time t+Δt is trained to obtain the earthwork volume prediction model.

[0030] The order of the two evaluation criteria, earthwork volume and flatness, is set according to the prediction model to obtain the recommended optimized height.

[0031] The second object of the present invention is to provide a height optimization system for an energy dissipation device on a trailing suction dredger, which is characterized by comprising a core parameter input module, a loading process simulation prediction module, a design optimization output module, and a height automatic adjustment module, and these software modules are embedded in and called by the ship-borne loading control system; Among them, the core parameter input module: The core parameters include geometric model, boundary conditions, grid conditions, initial conditions, fluid movement and sediment movement; the geometric model includes: mud tank structure size, transverse and longitudinal triangular tank size, overflow equipment size, energy dissipation equipment size and height, and the position of transverse and longitudinal triangular tanks and energy dissipation overflow equipment relative to the mud tank; the boundary conditions include the inlet boundary as the loading flow and loading mud concentration, the overflow boundary as the free outflow boundary, the upper boundary of the mud tank as the atmospheric pressure boundary, and the bulkhead boundary as the wall boundary with a certain roughness material; the grid conditions include: the grid range in the three directions of x, y, and z and the unit grid size; the initial conditions include the initial water level H 0 , loading simulation time t; the fluid motion parameters include fluid temperature T, fluid viscosity , fluid motion equation; the sediment movement parameters mainly include sediment particle size, sediment density, sediment porosity, critical Shields number, underwater repose angle, displacement motion coefficient and scour coefficient, involving four movement forms of sediment suspension, sediment deposition, sediment scour and sediment displacement; Among them, the loading process simulation prediction module: The core parameter input module uses the various parameters input to perform numerical calculations to simulate the loading process under different working conditions. The loading process simulation prediction module implements loading process simulation prediction, including the establishment of loading numerical model and loading simulation prediction.

[0032] Establish a numerical model for loading: Based on the input core parameters, use CFD software (existing technology) to establish a numerical model that can simulate the loading construction process to achieve loading simulation function.

[0033] Loading simulation prediction: Use the above loading numerical model to set different energy dissipation device height position working conditions, perform numerical simulation, simulate the entire loading process, realize the simulation prediction of loading capacity, earthwork volume, total overflow loss and sediment height in the cabin as the loading time changes, and obtain multiple sets of numerical simulation calculation results corresponding to different energy dissipation device height positions. The height position of the energy dissipation device needs to be set manually.

[0034] The numerical simulation results also include: t (3D grid point cloud of flow at time t); ρt (3D grid point cloud of density at time t); v x (3D grid point cloud of velocity in x direction at time t); v y (3D grid point cloud of the y-direction velocity component at time t). The results of the numerical calculation are provided to the design optimization output module.

[0035] This module can display various data in the calculation process in real time and present the simulation results in a visual way in the 3D model. Users can have a more intuitive and in-depth understanding of the loading process by viewing the specific flow rate, concentration and earthwork volume output results during the loading process under various working conditions. It helps users analyze various phenomena in the loading process, such as flow rate distribution, sediment concentration changes, etc., and then optimize the loading plan.

[0036] Among them, the design optimization output module: Based on the numerical simulation results output by the loading process simulation prediction module, the evaluation criteria are set in order with four indicators, namely loading capacity, earthwork volume, overflow loss, and sediment flatness, to obtain the optimized recommended height of the energy dissipation device; users can click to select the order of evaluation criteria (loading efficiency, flatness) according to actual needs; the system will automatically output the optimized recommended value of the height of the energy dissipation equipment based on the evaluation criteria selected by the user.

[0037] Specifically, in multiple sets of numerical simulation results, different energy dissipation device heights correspond to different four indicators, namely, mud tank loading capacity, earthwork volume, overflow loss, and sediment flatness. The evaluation basis sequence is set, and the recommended value for the optimal design of the energy dissipation device height is generated according to the evaluation basis sequence (first gradient, second gradient). Usually, the loading efficiency represented by loading capacity, earthwork volume and overflow loss is used as the first gradient judgment standard, and the flatness of sediment is used as the second gradient judgment standard. Among them, the larger the loading capacity and earthwork volume, the smaller the overflow loss, and the higher the mud tank flatness, indicating that the height of the energy dissipation device under this working condition has a better effect on the loading effect.

[0038] Among them, the automatic height adjustment module: Based on the recommended value of the optimized height of the energy dissipation device output by the design optimization output module, a control signal is sent through the shipboard loading control system to automatically control the hydraulic struts on the adjustable height energy dissipation device. By accurately controlling the extension and retraction of the hydraulic struts, the height of the energy dissipation device can be adjusted automatically and precisely. In addition, users can also manually determine the soil conditions of the construction area through existing geological survey data, and input the appropriate height of the energy dissipation device through the loading control system based on engineering experience. After receiving the command, the system will send a control signal to the hydraulic struts to realize the lifting and lowering adjustment of the manually assisted energy dissipation device. This adjustment method is more flexible and can adapt to different construction environments and needs.

[0039] The beneficial effect of the present invention is to provide a method and system for automatically adjusting the height of the energy dissipation device of a trailing suction dredger, which can automatically and accurately adjust the height of the energy dissipation device in real time according to different soil qualities and different mud concentration requirements during the construction process. The energy dissipation device will not be too low, causing the rapidly settling coarse-grained sediment to block the outlet of the energy dissipation device, nor will it be too high, causing the inflow of water to disturb the sediment and increase the overflow loss of suspended sediment. By accurately controlling the height of the energy dissipation device, the construction efficiency of the trailing suction dredger can be improved, and at the same time, the adverse effects of the loading overflow on the construction water environment can be reduced, which has engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a front view of an adjustable height energy dissipation device of a trailing suction dredger according to an embodiment; Figure 2 It is a side view of the adjustable height energy dissipation device of the trailing suction dredger of the embodiment; Figure 3 It is a schematic diagram of the retractable pipeline structure of the embodiment; Figure 4 This is a schematic diagram of the structure of the hydraulic support rod for lifting in the embodiment; Figure 5 It is a three-dimensional modeling diagram of the mud tank of the trailing suction dredger of the embodiment; Figure 6 The grid division of the three-dimensional model of the mud tank of the trailing suction dredger in the embodiment; Figure 7 It is a three-dimensional numerical simulation diagram of the mud tank of the trailing suction dredger of the embodiment; Figure 8 The embodiment is a flow chart of the sediment height prediction model; Fig. 9 It is a flow chart of the earthwork volume prediction model of the embodiment; Fig.10 Optimizing the height prediction flow chart of the energy dissipation device for the embodiment; Fig.11 A simple artificial neural network predictive model for optimizing the height of energy dissipation equipment; Fig.12 Highly optimized system software module for the energy dissipation device on the trailing suction hopper dredger; Fig.13 It is a highly automated adjustment process for the energy dissipation device of the trailing suction dredger during construction; Reference numerals 1- telescopic main pipe, 2- transverse pipe, 3- connecting steel plate, 4- hydraulic support rod, 5- cross beam in mud tank, 6- mud tank side wall; 11-inner pipe, 12-outer pipe, 13-filler, 14-limiting block, 15-main pipe connecting flange; 21-outlet, 22-lateral pipe connection flange; 41-rear cylinder head, 42-cylinder barrel, 43-piston, 44-piston rod, 45-guide sleeve, 46-sealing ring, 47-front cylinder head. DETAILED DESCRIPTION

[0041] The adjustable height energy dissipation device, the automatic height adjustment optimization method and the system of the trailing suction hopper dredger of the present invention are further described in detail below with reference to the accompanying drawings by way of specific embodiments.

[0042] Preparation process When the trailing suction dredger is modified, the structural part of the adjustable height energy dissipation device is as follows Figures 1 to 4 shown.

[0043] The energy dissipation device is height-adjustable and is embedded in and controlled by the shipboard loading control system so as to make timely adjustments for optimal loading operations.

[0044] The adjustable height energy dissipation device of the trailing suction dredger consists of a telescopic main pipe 1, a transverse pipe 2, a connecting steel plate 3, a hydraulic support rod 4, and a cross beam 5 in the mud chamber; the cross beam 5 in the mud chamber is fixed to the side wall 6 of the mud chamber by welding technology, four lifting hydraulic support rods 4 are fixed to the cross beam 5 in the mud chamber by bolts, a connecting steel plate 3 is placed above the hydraulic support rod 4, and is fixed to the upper end of the hydraulic support rod 4 by bolts, and the connecting steel plate 3 is connected to the outer pipe 12 of the telescopic main pipe 1 by welding.

[0045] The telescopic main pipe 1 is a sleeve structure, the inner pipe 11 and the outer pipe 12 are sealed by a filler 13 without affecting relative sliding, the limit block 14 limits the telescopic amount of the telescopic main pipe 1, and the telescopic main pipe 1 can be freely extended within a certain limit under the action of the hydraulic support rod 4. The outer pipe 12 is connected to the transverse pipe 2 through the main pipe connection flange 15.

[0046] The transverse pipe 2 is divided into three parts, namely, left, middle and right parts, which are connected in sequence through flanges. The transverse pipe 2 is provided with a total of 8 outlets 21 for dissipating energy and loading the mud into the chamber.

[0047] The hydraulic strut 4 is composed of a rear cylinder cover 41, a cylinder barrel 42, a piston 43, a piston rod 44, a guide sleeve 45, a sealing ring 46, and a front cylinder cover 47. The rear cylinder cover 41 is connected to the cross beam 5 in the mud tank by bolts, and at the same time closes the rear part of the cylinder barrel 42; the piston 43 is subjected to force in the cylinder barrel, and is transmitted to the upper connecting steel plate 3 through the piston rod 44; the guide sleeve 45 supports and ensures the coaxiality of the piston rod 44 and the cylinder barrel 42; the front cylinder cover 46 and the piston rod 44 are sealed by the sealing ring 46 to prevent water, mud and sand from affecting the normal operation of various components in the cylinder barrel 42 during the loading process.

[0048] When adjusting the height of the energy dissipation device, the shipboard loading control system controls the lifting and lowering of the four hydraulic support rods 4 in the embodiment, and drives the outer pipe 12 and the transverse pipe 2 of the telescopic main pipe 1 to rise or fall through the connecting steel plate 3, and the mud is discharged into the mud tank along the inner pipe 11, the outer pipe 12, the transverse pipe 2, and the outlet 21 to carry out the loading operation.

[0049] Example 1 Optimization method for automatic height adjustment of energy dissipation device of trailing suction dredger Process 1: Complete the facility modification of the trailing suction dredger by referring to the preparatory work.

[0050] Process 2 determines the optimal adjustment height value, including the following steps: Step 1: Determine the core parameters, including the key parameters of six parts: geometric model, boundary conditions, grid conditions, initial conditions, fluid motion and sediment motion, which are used to automatically establish the three-dimensional model of the mud tank system and set the scenario constraints of the loading simulation.

[0051] (1) Geometric model parameters, including the setting of mud tank structure dimensions, transverse and longitudinal triangular tank dimensions, overflow equipment dimensions, energy dissipation equipment dimensions, and the positions of transverse and longitudinal triangular tanks and energy dissipation overflow equipment relative to the mud tank, are used to establish a three-dimensional structural model of the mud tank system. Figure 5 shown.

[0052] (2) The boundary conditions include setting the inlet boundary as the loading flow rate and loading mud concentration, selecting the overflow boundary as the free outflow boundary, the upper boundary of the mud tank as the atmospheric pressure boundary, and the bulkhead boundary as the wall boundary with a certain roughness material; (3) If Figure 6 As shown, the grid is divided according to the three-dimensional model. The grid conditions include setting the total grid range in three directions to include the mud tank system structure model, and setting the unit grid size to a suitable length, width and height size for identifying the mud tank structure in the simulation calculation; (4) Initial conditions include setting the initial water level and loading simulation duration; (5) Fluid motion parameters include setting fluid temperature and fluid viscosity, and selecting the fluid motion equation as the RNG k−ε equation; (6) Sediment movement parameters include setting sediment particle size, sediment density, sediment porosity, critical Shields number, underwater angle of repose, displacement coefficient and scour coefficient. The empirical formula of Mastbergen and Von den Berg is used to calculate the sediment start-up and scour process, and the empirical formula of Meyer-Peter & Műller equati is used to calculate the bedload transport process in the simulation process.

[0053] Step 2: Establish a loading numerical model and loading simulation prediction; Establishing a numerical model for loading: This means using CFD software to establish a numerical model that can simulate the loading construction process based on the input core parameters, so as to realize the loading simulation function; Loading simulation prediction: Use the above loading numerical model to set different energy dissipation device height position working conditions, perform numerical simulation, simulate the entire loading process, realize the simulation prediction of the loading capacity, earthwork volume, total overflow loss and sediment height in the cabin as the loading time changes, and obtain multiple sets of numerical simulation calculation results corresponding to different energy dissipation device height positions; the energy dissipation device height position needs to be set manually; The numerical simulation results also include: t (3D grid point cloud of flow at time t); ρ t (3D grid point cloud of density at time t); v x (3D grid point cloud of velocity in x direction at time t); v y (Three-dimensional grid point cloud of the y-direction velocity component at time t); the results of the numerical calculation are provided to step 3.

[0054] The embodiment uses CFD software, structured multi-block grid technology, and finite volume method to automatically establish a numerical model of the loading construction process based on the input core parameters, and realizes the simulation of the loading construction changing with time. The simulation results are as follows: Figure 7 As shown in the figure, different energy dissipation device heights are set, and the loading control system sets different sediment movement parameters according to the geological survey report of the construction area and the existing construction experience data for different soil types, and performs loading simulation calculations under multiple working conditions.

[0055] Step 3: Energy dissipation device highly optimizes output. The optimization goal is to optimize the sediment flatness α and maximize the earthwork volume D, then the objective function of the optimization model is: Set constraints ( x . t .): in, The length of the time period for calculating the amount of deposited earthwork; For Outflow volume during the time period; For Outflow concentration during the time period; x i Belongs to [0,H], H represents the height of the mud tank, x (it)As a parameter for calculating flatness, it represents the height of sediment deposited at sampling position i at time t, It represents the average height of sediment deposited in the longitudinal centerline section of the mud chamber.

[0056] Where T is the maximum time set initially.

[0057] Set the heights of multiple energy dissipation devices and use the numerical calculation model in step 2 to calculate q t , ρ t , v x and v y , and then calculate the flatness of the deposited sediment and the amount of earthwork. According to the above optimization objectives (optimal flatness and maximum earthwork volume), the best group is selected, and the corresponding energy dissipation equipment height is the optimal energy dissipation equipment height.

[0058] Optionally, the recommended value for the optimized design of the energy dissipation equipment height can also be determined according to the evaluation order (first gradient, second gradient) of the four indicators of loading capacity, earthwork volume, overflow loss, and sediment flatness. Usually, the loading efficiency represented by loading capacity, earthwork volume, and overflow loss is used as the first gradient judgment standard, and the sediment flatness is used as the second gradient judgment standard. Among them, the larger the loading capacity and earthwork volume, the smaller the overflow loss, and the higher the flatness of the mud tank, indicating that the height of the energy dissipation equipment under this working condition has a better effect on the loading effect.

[0059] Furthermore, in construction conditions where higher requirements are placed on loading flatness, the evaluation criteria sequence may be adjusted to take the deposited silt flatness as the first gradient.

[0060] In step 3, in order to avoid complex numerical calculation process, neural network is introduced to predict sediment height and earthwork volume. As follows: Combination Figure 8 As shown, four variables are input into the input layer: qt (flow), ρt (density), vxt (x-direction velocity) and vyt (y-direction speed), these input features are input into the target Transformer neural network model after feature selection and standardization preprocessing to obtain the sediment height prediction results.

[0061] The target Transformer neural network model includes Embedding Layer, Multi-headAttention and Softmax (probability distribution output). Embedding Layer vectorizes the input features and converts them into vector representations suitable for network processing. This process maps high-dimensional input features to low-dimensional vector space for subsequent processing. Multi-head Attention captures different feature information through multiple sets of attention heads, integrates this information, and performs weighted processing on the input features. Softmax calculates the probability distribution of each output through the results of multi-head attention mechanism processing: The output values ​​are mapped to [0, 1], and the sum of all output probabilities is 1, which helps the model learn the nonlinear relationship between input features and output results. Finally, the predicted sediment deposition height sequence (x 1 ,x 2 ,...,x n ).

[0062] The Transformer neural network model (sedimentation sediment height prediction model) uses four input variables as training data and sediment deposition height sequences as labels to train it. After each iteration, the validation data and its labels are used to calculate the loss function, with the mean square error (MSE) as the loss function: In the formula, are the sediment height obtained by iterative calculation and the actual sediment height as the label value, respectively.

[0063] The model adjusts the network weights through the backpropagation algorithm to minimize the loss function. In each training iteration, the gradient of the loss function is calculated and the network weights are updated until the model reaches the preset convergence condition and the target neural network model is obtained.

[0064] Combination Fig. 9 As shown, four variables are input into the input layer: qt (flow), ρt (density), vxt (x-direction velocity) and vyt(y-direction speed), the input features are preprocessed (normalized) and then input into the network. The BatchNorm layer calculates the mean and variance of all values ​​in a mini-batch, and uses the calculated mean and variance to normalize each batch of data, so that the input of each layer maintains a relatively stable distribution, which is used to accelerate training and improve the stability of the model. The PointNet layer is a deep learning framework that specializes in processing point cloud data. In this model, it is used to extract high-dimensional feature representations of input features. The fully connected layer further processes the features extracted from the PointNet layer, and can map high-dimensional features to the target output space, thereby realizing the prediction of earthwork volume.

[0065] Optionally, the present invention also provides another simpler and faster method for recommending parameters for height optimization of energy dissipation equipment, combining Fig.10 The figure shows the optimal energy dissipation equipment height prediction process. The prediction process includes 10 parts: data input, data preprocessing, training set and test set division, neural network model construction, forward propagation, loss function calculation, back propagation, parameter update, model evaluation, and optimal value recommendation.

[0066] (1) Data input: As the starting point of the entire prediction model, the data of the mud entering the mud tank at time t, such as qt (flow rate), ρt (density), vxt (x-direction velocity), vyt (y-direction velocity), and h (height of the energy dissipation device), are input in a tabular form.

[0067] (2) Data preprocessing: In this stage, the data described in (1) will be standardized. The earthwork volume D and sediment flatness α are calculated, a new parameter λ (0<λ<1) is set, and λD−(1−λ)α is calculated for each set of data. Where: The length of the time period for calculating the amount of deposited earthwork; For Outflow volume during the time period; For Outflow concentration during the time period (3) Training set and test set division: Data such as qt (flow), ρt (density), vxt (x-direction velocity), vyt (y-direction velocity), and h (height of energy dissipation device) will be divided into training set and test set. The training set is used to train the model, and the test set is used to evaluate the performance of the model. The division ratio is set to 8:2 or 7:3.

[0068] (4) Neural network model construction: Combination Fig.11As shown in the figure, a simple artificial neural network (MLP) model is built. The neural network consists of multiple layers of neurons (nodes), with several neurons in each layer. The layer structure includes an input layer (receiving processed input data), a hidden layer (performing complex calculations and extracting high-order features of the input data), and an output layer (producing the final prediction result, i.e., the objective function λD−(1−λ)α).

[0069] (5) Forward propagation: Data passes through the neurons of each layer from the input layer, calculates the activation function and outputs until it reaches the output layer. The calculation formula for each layer is as follows: Where: l is the number of activation layers; is the weight matrix; is the bias vector; and are the activation values ​​of this layer and the previous layer respectively. The corresponding input data qt (flow), ρt (density), vxt (speed in the x direction), vyt (speed in the y direction), h (height of the energy dissipation device), etc. can be taken for calculation; is the activation function.

[0070] Furthermore, the activation function selects the ReLU function: (6) Loss function calculation: Select the common mean square error (MSE) as the loss function: Where: is the true value, is the predicted value, where y=λD−(1−λ)α, is the sample size.

[0071] (7) Back propagation: By calculating the gradient of the loss function with respect to each parameter, the parameters are updated to minimize the loss function. The gradient calculation formula is as follows: Where: is the error term, which is the difference between the network prediction value and the true label value.

[0072] (8) Parameter update: Use the gradient descent optimization algorithm to update the weight matrix and bias vector. The gradient descent update formula is as follows: Where: is the learning rate.

[0073] (9) Model evaluation: Use the test set to evaluate model performance using indicators such as accuracy, precision, and recall.

[0074] (10) Optimal value recommendation: After the model training is completed, predictions can be made for the input parameters qt (flow), ρt (density), vxt (x-direction speed), vyt (y-direction speed), h (energy dissipation device height), etc. In order to find the maximum value of the model, the model parameters are fixed, and the derivatives of each parameter in each layer are calculated using the chain rule to make them equal to zero, and the extreme value candidates within a certain range are obtained. The maximum value is selected and back propagated to obtain the optimal energy dissipation device height. h .

[0075] Process 3: Loading at the optimal energy dissipation height Step 4: According to the optimal height of the energy dissipation device obtained in step 3, adjust the hydraulic support rod of the adjustable height energy dissipation device to raise or lower the height of the energy dissipation device to the optimal height.

[0076] Example 2 A height optimization system for energy dissipation device on a trailing suction dredger It includes 4 developed software modules: core parameter input module, loading process simulation prediction module, design optimization output module, and height automatic adjustment module. These software modules are embedded in the ship-borne loading control system and are called by it; Fig.12 ; Among them, the core parameter input module: The core parameters include geometric model, boundary conditions, grid conditions, initial conditions, fluid movement and sediment movement; the geometric model includes: mud tank structure size, transverse and longitudinal triangular tank size, overflow equipment size, energy dissipation equipment size and height, and the position of transverse and longitudinal triangular tanks and energy dissipation overflow equipment relative to the mud tank; the boundary conditions include the inlet boundary as the loading flow and loading mud concentration, the overflow boundary as the free outflow boundary, the upper boundary of the mud tank as the atmospheric pressure boundary, and the bulkhead boundary as the wall boundary with a certain roughness material; the grid conditions include: the grid range in the three directions of x, y, and z and the unit grid size; the initial conditions include the initial water level H 0 , loading simulation time T; the fluid motion parameters include fluid temperature T, fluid viscosity , fluid motion equation; the sediment movement parameters mainly include sediment particle size, sediment density, sediment porosity, critical Shields number, underwater repose angle, displacement motion coefficient and scour coefficient, involving four movement forms of sediment suspension, sediment deposition, sediment scour and sediment displacement; Among them, the loading process simulation prediction module: The core parameter input module uses the various parameters input to perform numerical calculations to simulate the loading process under different working conditions. The loading process simulation prediction module implements loading process simulation prediction, including the establishment of loading numerical model and loading simulation prediction.

[0077] Establishing a numerical model for loading: refers to establishing a numerical model capable of simulating the loading construction process based on the input core parameters using CFD software (existing technology) to achieve loading simulation function.

[0078] Loading simulation prediction: Use the above loading numerical model to set different energy dissipation device height position working conditions, perform numerical simulation, simulate the entire loading process, realize the simulation prediction of loading capacity, earthwork volume, total overflow loss and sediment height in the cabin as the loading time changes, and obtain multiple sets of numerical simulation calculation results corresponding to different energy dissipation device height positions. The height position of the energy dissipation device needs to be set manually.

[0079] The numerical simulation results also include: t (3D grid point cloud of flow at time t); ρ t (3D grid point cloud of density at time t); v x (3D grid point cloud of velocity in x direction at time t); v y (3D grid point cloud of the y-direction velocity component at time t). The results of the numerical calculation are provided to the design optimization output module.

[0080] This module can display various data in the calculation process in real time and present the simulation results in a visual way in the 3D model. Users can have a more intuitive and in-depth understanding of the loading process by viewing the specific flow rate, concentration and earthwork volume output results during the loading process under various working conditions. It helps users analyze various phenomena in the loading process, such as flow rate distribution, sediment concentration changes, etc., and then optimize the loading plan.

[0081] Among them, the design optimization output module: Based on the numerical simulation results output by the loading process simulation prediction module, the evaluation criteria are set in order with four indicators, namely loading capacity, earthwork volume, overflow loss, and sediment flatness, to obtain the optimized recommended height of the energy dissipation device; users can click to select the order of evaluation criteria (loading efficiency, flatness) according to actual needs; the system will automatically output the optimized recommended value of the height of the energy dissipation equipment based on the evaluation criteria selected by the user.

[0082] Specifically, in multiple sets of numerical simulation results, different energy dissipation device heights correspond to different four indicators, namely, loading capacity, earthwork volume, overflow loss, and sediment flatness. The evaluation basis sequence is set, and the recommended value for the optimal design of the energy dissipation device height is determined according to the evaluation basis sequence (first gradient, second gradient). Usually, the loading efficiency represented by loading capacity, earthwork volume, and overflow loss is used as the first gradient judgment standard, and the flatness of sediment is used as the second gradient judgment standard. Among them, the larger the loading capacity and earthwork volume, the smaller the overflow loss, and the higher the flatness of the mud tank, indicating that the height of the energy dissipation device under this working condition has a better effect on the loading effect.

[0083] Among them, the automatic height adjustment module: Based on the recommended value of the optimized height of the energy dissipation device output by the design optimization output module, a control signal is sent through the shipboard loading control system to automatically control the hydraulic struts on the adjustable height energy dissipation device. By accurately controlling the extension and retraction of the hydraulic struts, the height of the energy dissipation device can be adjusted automatically and precisely. In addition, users can also manually determine the soil conditions of the construction area through existing geological survey data, and input the appropriate height of the energy dissipation device through the loading control system based on engineering experience. After receiving the command, the system will send a control signal to the hydraulic struts to realize the lifting and lowering adjustment of the manually assisted energy dissipation device. This adjustment method is more flexible and can adapt to different construction environments and needs.

[0084] The modules are as follows: The simulation and prediction module of the loading process uses the various parameters input in the core parameter input module to perform numerical simulation calculations on the loading process: the silt is regarded as solid particles, and the fluid model and silt particle model are used to simulate the four states of silt suspension, deposition, resuspension and displacement. The energy dissipation device outlet is partitioned separately by using a partitioned block structured grid and the grid is doubled. The inlet boundary is the loading flow and loading mud concentration, the overflow boundary is the free outflow boundary, the upper boundary of the mud tank is the atmospheric pressure boundary, and the bulkhead boundary is the wall boundary with a certain roughness material. The finite volume method is used to perform numerical simulation calculations on the loading process.

[0085] During the simulation process, the module can display various data in the calculation process in real time, such as flow rate, concentration, earthwork volume, etc., and present the simulation results in a visual way in the 3D model. Users can have a deeper and more comprehensive understanding of the loading process through these intuitive data and images. In addition, users can also view the output results under various working conditions and analyze various phenomena in the loading process, such as flow rate distribution, sediment concentration changes, etc., so as to further optimize the loading plan.

[0086] Furthermore, the loading volume, earthwork volume, overflow loss and sediment flatness at different times during the loading process are calculated using the following formula: Loading capacity: refers to the total mass of mud mixture loaded into the mud tank without overflowing.

[0087] Where: M Indicates the loading capacity, M f represents the mass of the fluid in the cabin, M ss Indicates the mass of suspended sediment particles in the cabin, M sd Indicates the mass of sediment particles deposited in the cabin.

[0088] Earthwork volume: refers to the volume of original soil loaded into the mud tank without overflowing.

[0089] In the formula, represents the density of sediment particles, represents the porosity of the original soil, represents the fluid density, Represents the original soil density.

[0090] Overflow loss: refers to the total mass of mud mixture loaded into the mud tank but overflowed.

[0091] In the formula, It is the total mass of the mud mixture flowing out from the outlet of the energy dissipation equipment.

[0092] Flatness inside the cabin: It is expressed by the standard deviation of the height of deposited mud in the section of the longitudinal centerline of the mud cabin.

[0093] In the formula, Indicates the flatness of the cabin. Indicates the cross-sectional position of the longitudinal centerline of the mud tank i The height of sediment deposits at It represents the average height of sediment deposited in the longitudinal centerline section of the mud chamber. n It indicates the height of deposited sediment calculated on the longitudinal centerline section of the mud chamber.

[0094] The height automatic adjustment module is a concrete embodiment of the automation of the shipboard loading control system, eliminating the process of manually adjusting the height of the energy dissipation device. The module will automatically control the hydraulic strut 4 set on the adjustable height energy dissipation device according to the recommended value of the optimized height of the energy dissipation device obtained by the design optimization output module. By accurately controlling the extension and retraction of the hydraulic strut 4, the height of the energy dissipation device can be adjusted in real time, automatically, and precisely. This automatic adjustment method not only improves the accuracy and efficiency of the adjustment, but also reduces the difficulty and error of manual operation.

[0095] Furthermore, the user can also input the appropriate height of the energy dissipation device through the shipboard loading control system according to his own judgment and experience. After receiving the command, the system will send a corresponding control signal to the hydraulic support rod 4 to realize the lifting and lowering adjustment of the manual auxiliary energy dissipation device. This flexible adjustment method can adapt to different construction environments and needs, and improve the adaptability and practicality of the system.

[0096] Example 3 A new type of trailing suction hopper dredger with automatically adjustable height of energy dissipation device and a loading construction method thereof: by modifying the original trailing suction hopper dredger or building a new ship, the hardware is equipped with an energy dissipation device with adjustable height, and the preparation work is done, which will not be repeated in the previous text.

[0097] The height-adjustable energy dissipation device is managed by the shipboard loading control system, which has been introduced in Example 2.

[0098] Loading operation method for automatic height adjustment of energy dissipation device of trailing suction dredger Specific process, such as Fig.13 , including the following steps: Step 1: The suction dredger enters the construction area; before the construction starts, the core parameters are manually input, which mainly include six parts: geometric model, boundary conditions, grid conditions, initial conditions, fluid movement and sediment movement. The specific contents of the parameters are as introduced in Example 1.

[0099] Step 2: The shipboard loading control system automatically establishes a numerical model of the loading construction process based on the input core parameters, realizing the simulation function of the loading construction changing over time.

[0100] Step 3: Set different heights of energy dissipation equipment in the shipboard loading control system and perform loading simulation calculations under multiple working conditions.

[0101] Step 4: Recommend the height parameters of the energy dissipation equipment through the design optimization parameter output module of the shipboard loading control system. According to user needs, select and set the evaluation basis order (first gradient, second gradient) and the number of recommended values, and automatically generate the recommended values ​​for the height optimization design of the energy dissipation equipment. The core parameter recommendation basis for the height position of the energy dissipation equipment, in the default state, uses the first gradient judgment standard of the loading efficiency represented by the loading capacity, earthwork volume and overflow loss, and the flatness of the deposited sediment as the second gradient judgment standard.

[0102] Furthermore, in construction conditions where higher requirements are placed on loading flatness, the evaluation criteria sequence may be adjusted to take the deposited silt flatness as the first gradient.

[0103] Step 5: When the location and excavation depth of the ship construction area change significantly, refer to the geological survey report, the corresponding excavation soil changes, and repeat step 4 based on the updated input values ​​of qt, ρt, vxt and vyt to recommend new optimized values ​​for the height of the energy dissipation equipment.

[0104] Specifically, as excavation progresses, the excavation position and depth change, and the soil conditions change. In order to improve the overall loading efficiency, the loading control system changes the sediment movement parameters according to the geological survey data, re-performs the numerical calculation and neural network training process such as loading simulation prediction, automatic optimization and recommendation of height parameters under multiple working conditions, and uses the loading control system to automatically re-control the height of the hydraulic support rod, thereby adjusting the height of the energy dissipation device to always ensure a high loading efficiency. When the number of fine particles in the excavated soil increases, the height of the energy dissipation device is automatically and accurately lowered to reduce the disturbance of the inflowing water to the fine particles of sediment, so that the fine particles are quickly deposited and the overflow loss of loading is reduced; when the number of coarse particles in the loading mud increases, the particles settle faster, and the height of the energy dissipation device is automatically and accurately increased to prevent soil particles from blocking the outlet 21 of the energy dissipation device.

[0105] Step 6: When the trailing suction dredger is working at different construction positions and excavation depths, the above-mentioned corresponding energy dissipation equipment height optimization recommended value is called in combination with the ship position and the lowering depth of the rake arm, and a command is sent to the hydraulic support rod 4 provided on the adjustable height energy dissipation device to realize real-time height adjustment of the energy dissipation device.

Claims

1. A system for optimizing the height of energy dissipation device on a trailing suction dredger, characterized in that: The height optimization system includes a core parameter input module, a loading process simulation prediction module, a design optimization output module, and a height automatic adjustment module. These software modules are embedded in and called by the ship-borne loading control system.

2. The system for optimizing the height of the energy dissipation device on a trailing suction hopper dredger according to claim 1, characterized in that: The core parameter input module includes geometric model, boundary conditions, grid conditions, initial conditions, fluid motion and sediment motion; the geometric model includes: mud tank structure size, transverse and longitudinal triangular tank size, overflow equipment size, energy dissipation equipment size and height, and the position of transverse and longitudinal triangular tanks and energy dissipation overflow equipment relative to the mud tank; the boundary conditions include the inlet boundary as the loading flow and loading mud concentration, the overflow boundary as the free outflow boundary, the upper boundary of the mud tank as the atmospheric pressure boundary, and the bulkhead boundary as the wall boundary with a certain roughness material; the grid conditions include: the grid range in the three directions of x, y, and z and the unit grid size; the initial conditions include the initial water level H0 and the loading simulation time T; the fluid motion parameters include fluid temperature T, fluid viscosity, and fluid motion equation; the sediment motion parameters mainly include sediment particle size, sediment density, sediment porosity, critical Shields number, underwater repose angle, push motion coefficient and scour coefficient, involving four motion forms of sediment suspension, sediment deposition, sediment scour and sediment push.

3. The height optimization system of the energy dissipation device on a trailing suction hopper dredger according to claim 1, characterized in that: The loading process simulation prediction module uses the various parameters input by the core parameter input module to perform numerical calculations and simulate the loading process under different working conditions. The loading process simulation prediction module realizes loading process simulation prediction, including establishing a loading numerical model and loading simulation prediction.

4. The system for optimizing the height of the energy dissipation device on a trailing suction hopper dredger according to claim 3, characterized in that: The said establishment of the loading numerical model refers to establishing a numerical model capable of simulating the loading construction process by using CFD software according to the input core parameters, so as to realize the loading simulation function.

5. The system for optimizing the height of the energy dissipation device on a trailing suction hopper dredger according to claim 3, characterized in that: The loading simulation prediction: using the loading numerical model, setting different energy dissipation device height position working conditions, performing numerical simulation, simulating the entire loading process, realizing the simulation prediction of the loading capacity, earthwork volume, total overflow loss and sediment height in the cabin changing with the loading time, and obtaining multiple groups of numerical simulation calculation results corresponding to different energy dissipation device height positions. The energy dissipation device height position needs to be set manually.

6. The system for optimizing the height of the energy dissipation device on a trailing suction hopper dredger according to claim 5, characterized in that: The numerical simulation calculation results also include: t (3D grid point cloud of flow at time t); ρ t (3D grid point cloud of density at time t); v x (3D grid point cloud of velocity in x direction at time t); v y (3D grid point cloud of the y-direction velocity component at time t), the numerical calculation results are provided to the design optimization output module; This module can display various data in the calculation process in real time and present the simulation results in a visual way in the three-dimensional model. Users can have a more intuitive and in-depth understanding of the loading process by viewing the specific flow rate, concentration and earthwork volume output results during the loading process under various working conditions. It helps users analyze various phenomena in the loading process, flow rate distribution, sediment concentration changes, and optimize the loading plan.

7. The system for optimizing the height of the energy dissipation device on a trailing suction hopper dredger according to claim 1, characterized in that: The design optimization output module: based on the numerical simulation results output by the loading process simulation prediction module, sets the evaluation basis sequence according to four indicators, namely, loading capacity, earthwork volume, overflow loss, and sediment flatness, to obtain the optimized recommended height of the energy dissipation device; Users can click to select the order of evaluation criteria (loading efficiency, flatness) according to actual needs; the system will automatically output the optimized recommended value for the height of the energy dissipation equipment based on the evaluation criteria selected by the user.

8. The system for optimizing the height of the energy dissipation device on a trailing suction hopper dredger according to claim 1, characterized in that: The automatic height adjustment module: based on the recommended value of the optimized height of the energy dissipation device output by the design optimization output module, sends a control signal through the ship-borne loading control system, thereby automatically controlling the hydraulic support rod on the adjustable height energy dissipation device, and realizing automatic and precise adjustment of the height of the energy dissipation device by accurately controlling the extension and retraction of the hydraulic support rod; in addition, the user can also manually determine the soil conditions of the construction area through the existing geological survey data, and input the appropriate height of the energy dissipation device through the loading control system according to engineering experience. After receiving the command, the system will send a control signal to the hydraulic support rod to realize the manual auxiliary lifting and lowering adjustment of the energy dissipation device. This adjustment method is more flexible and can adapt to different construction environments and needs.

9. The system for optimizing the height of the energy dissipation device on a trailing suction hopper dredger according to claim 8, characterized in that: The ship-borne loading control system manages the energy dissipation device with adjustable height, which is based on the modification of the original ship of the trailing suction dredger or the new ship under construction; The height-adjustable energy dissipation device is designed to include a retractable main pipe (1), a transverse pipe (2), a connecting steel plate (3), a hydraulic support rod (4), and a crossbeam (5) in the mud tank; The retractable main pipe (1) is a sleeve-type structure. The retractable main pipe (1) comprises an inner pipe (11), an outer pipe (12), a filler (13), a limit block (14), and a main pipe connecting flange (15). The inner pipe (11) and the outer pipe (12) are sealed by the filler (13). The limit block (14) limits the retractable range of the retractable main pipe (1). The inner pipe (11) is connected to the dredging pipeline of the trailing suction dredger. The outer pipe (12) is connected to the transverse pipe (2) via the main pipe connecting flange (15). The transverse pipe (2) is divided into three parts: left, middle and right parts, which are connected in sequence through the transverse pipe connecting flange (22) and are provided with a total of 8 outlets (21); The mud tank inner cross beam (5) is fixed to the mud tank side wall (6) by welding technology, four lifting hydraulic support rods (4) are fixed to the mud tank inner cross beam (5) by bolts, a connecting steel plate (3) is placed above the hydraulic support rod (4) and fixed to the upper end of the hydraulic support rod (4) by bolts, and the connecting steel plate (3) is connected to the outer pipe (12) of the telescopic main pipe (1) by welding technology; Four hydraulic support rods (4) are evenly arranged on the cross beam (5) in the mud tank, so as to provide sufficient force and ensure that the cross beam (5) in the mud tank and the connecting steel plate (3) are evenly stressed; The hydraulic support rod (4) is composed of a rear cylinder cover (41), a cylinder barrel (42), a piston (43), a piston rod (44), a guide sleeve (45), a sealing ring (46), and a front cylinder cover (47); the rear cylinder cover (41) is connected to the cross beam (5) in the mud tank by bolts, and at the same time closes the rear part of the cylinder barrel (42); the piston (43) is subjected to force in the cylinder barrel, and the force is transmitted to the upper connecting steel plate (3) through the piston rod (44); the guide sleeve (45) supports and ensures the coaxiality of the piston rod (44) and the cylinder barrel (42); the front cylinder cover (46) and the piston rod (44) are sealed by the sealing ring (46) to prevent water, mud and sand, etc. from affecting the normal operation of various components in the cylinder barrel (42) during the loading process.

10. The system for optimizing the height of the energy dissipation device on a trailing suction hopper dredger according to claim 9, characterized in that: Obtain the optimized recommended height of the energy dissipation device, adjust the hydraulic support rod of the adjustable height energy dissipation device, raise or lower the height of the energy dissipation device to the optimal height, and perform loading operations at the optimal energy dissipation height.

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