Arrangement ship steering oar and side thrust system interactive collaborative operation simulation method

Abstract

The invention discloses an arrangement ship steering oar and side thrust system interactive collaborative operation simulation method, and relates to the technical field of ship operation. The problems that in the prior art, a steering oar and a side thrust system are independently controlled, an effective collaborative operation strategy is lacked, consequently, the operation efficiency is low, and under the complex sea condition, the ship control difficulty is large, and safety accidents are likely to happen are solved. Through cooperative control of the steering oar and the side thrust system, the motion trail of the geotextile laying ship can be more accurately controlled, the geotextile laying precision and the operation efficiency are improved, the thrust distribution strategy is optimized, the energy consumption of the geotextile laying ship is reduced, the economic benefit is improved, the dynamic delay factor and the interference compensation strategy are introduced, and the working efficiency of the geotextile laying ship is improved. Specialized labor division of each level is realized through a layered control framework, the control efficiency and accuracy are improved, a case database and a strategy library are constructed, rapid calling and self-adaptive correction of historical strategies are realized, a closed-loop verification process is formed, and reliable theoretical support and technical guarantee are provided for actual operation.

Description

Technical Field

[0001] The present invention relates to the field of ship operation technology, and in particular to a simulation method for interactive collaborative operation of a rudder propeller and a thruster system. Background Art

[0002] When performing marine engineering operations such as laying submarine pipelines and laying submarine cables, the laying ship needs to accurately control the position and heading of the hull. Traditional laying ships are mainly operated by rudder propellers and thrust systems. For example, the Chinese patent with the announcement number: CN103306239B discloses a system for controlling the lateral contraction of the row body, including guide rails, supports, steel cables, row bodies, mooring ropes and steel cable hooks; transverse guide rails are loaded on both sides of the laying ship, the guide rails are fixed to the supports by welding, the supports are fixed to the steel cable hooks, the laying ship deck, and the laying ship slide by welding, the steel cables are connected to the supports and the laying ship by steel cable hooks, and the row body and the guide rails are tied and fixed by mooring ropes to form a whole. The laying vessel loading transverse guide operation system loads transverse guides on both sides of the laying vessel, and then connects the row body to the guides through tying ropes, thereby controlling the lateral contraction of the row body and improving the effective utilization rate of the overlapping width of the above-water row body. It is widely used in underwater laying construction under different working conditions, while reducing construction costs and improving construction efficiency.

[0003] In the prior art, the rudder propeller system is responsible for the ship's steering, and the thruster system is responsible for the ship's lateral movement. In actual operations, the rudder propeller and thruster system often need to work together to improve operating efficiency and accuracy. However, the rudder propeller and thruster system are independently controlled and lack an effective collaborative operation strategy, resulting in low operating efficiency. In addition, in complex sea conditions, the ship is difficult to operate and is prone to safety accidents. Summary of the invention

[0004] The purpose of the present invention is to provide a simulation method for the interactive and collaborative operation of the rudder propeller and thruster system of a laying vessel, so as to realize the interactive and collaborative operation of the rudder propeller and thruster system, improve the maneuvering efficiency and accuracy of the laying vessel, reduce the safety risks in the actual operation process through simulation, and provide a theoretical basis and technical support for the optimization of the rudder propeller and thruster system to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: The method for simulating the interactive collaborative operation of the rudder propeller and thruster system comprises the following steps: Step 1: Establish a dynamic model of the rudder propeller and thruster system of the laying ship, and couple the dynamic model with the control system model to generate a rudder propeller-thruster joint dynamic model, in which the thrust output of the rudder propeller and thruster is used as the input signal of the control system model, and the control command of the control system model is used as the input signal of the dynamic model to realize the interaction between the dynamic model and the control system model; Step 2: Build a multi-device interactive collaborative control architecture model based on the dynamic model and control system model, and define the thrust distribution constraint rules and interference compensation strategy according to the collaborative control relationship between the rudder propeller and the thruster; Step 3: Set the simulation scene and simulation parameters, perform simulation calculations according to the simulation scene and simulation parameters, and simulate the motion state and force conditions of the laying ship, rudder propeller and thrust system; Step 4: Based on the thrust distribution constraint rules and interference compensation strategy, the thrust distribution weight and control response priority are adjusted in the simulation cycle, and the motion state and force conditions in the simulation process are verified by deviation spectrum analysis with the preset path; Step 5: Generate a visual simulation report based on the analysis and verification results, and mark the key collaborative control nodes and performance bottlenecks. At the same time, build a case database to store the optimized parameter combinations of typical operation scenarios, and use a similarity matching algorithm to quickly call and adaptively correct historical strategies.

[0006] Furthermore, the dynamic model in step 1 specifically includes: Collect the design drawings of the laying ship and build a three-dimensional dynamic model of the hull, rudder propeller and thruster system based on the principles of fluid dynamics; Based on the three-dimensional dynamic model of the rudder propeller, the nonlinear variation characteristics of the rudder propeller thrust vector with the rudder angle and the rotation speed are obtained, and based on the nonlinear variation characteristics, the rudder propeller thrust vector model is constructed, and the rudder propeller thrust vector model is coupled with the hull model to simulate the influence of the rudder propeller on the hull motion; Based on the three-dimensional dynamic model of the thrust system, the thrust data of the thrust system at different speeds are obtained, the relationship between the thrust and speed of the thrust system is established, and a discretized thrust model is formed.

[0007] Furthermore, the discretized thrust model also includes introducing a dynamic delay factor to characterize the instantaneous lag effect of propeller speed and thrust, specifically including: Conduct at least one actual test on the thrust system, collect time series data of speed change and thrust response under different working conditions, and determine the dynamic delay factor τ; The thrust model calculation formula is as follows:

[0008] In the formula, T ( t ) is expressed as the thrust value at time t; T ( t-Δt ) represents the thrust value at the previous moment; ΔT ( t ) is expressed as the thrust change; T new ( n (t )) indicates that the current speed n ( t ) The thrust value calculated without considering the delay effect; Δt It represents the time step of simulation calculation; τ represents the dynamic delay factor.

[0009] Furthermore, in step 2, a multi-device interactive collaborative control architecture model is constructed, which specifically includes: Establish a hierarchical control architecture model, including path planning layer, motion control layer and actuator layer; The path planning layer collects environmental data in real time, generates a reference trajectory of the ship's motion in combination with a preset layout path, fuses the environmental data through an environmental disturbance observer, calculates the motion trajectory compensation, and compensates the reference trajectory of the ship's motion; The motion control layer spatially synthesizes the propeller thrust vector output by the dynamic model and the thrust of the thrust system through the conversion matrix between the hull coordinate system and the local equipment coordinate system to generate a unified control input vector; The motion control layer is also used to input the compensated hull motion reference trajectory into the rudder propeller-thruster joint dynamics model, predict the future state of the hull, and optimize the unified control input vector based on the prediction result; The actuator layer calculates the combined torque deviation of the rudder propeller and the thruster in real time based on the discretized thrust model, and feeds it back to the motion control layer for thrust redistribution.

[0010] Furthermore, the thrust distribution constraint rules include: a thrust direction conflict detection mechanism, a power distribution weight function, a thrust limit constraint rule and a torque balance constraint rule.

[0011] Furthermore, the interference compensation strategy includes: a wake interference compensation strategy, an environmental interference feedforward compensation strategy, a model prediction error feedback compensation strategy and a dynamic delay compensation strategy.

[0012] Furthermore, the step three also includes: configuring the ship load distribution parameters, configuring the operation task path planning data, establishing the equipment status monitoring logic, collecting the rudder angle, rotation speed, and thrust deviation in real time as the simulation feedback signal, monitoring and controlling the status of the rudder propeller and thrust system, and ensuring that the control strategy in the simulation process can be effectively executed.

[0013] Furthermore, the simulation scenario in step 3 is generated based on the actual operation type, water conditions, and equipment status of the ship, and specifically includes: According to different layout training subjects, combined with corresponding layout strategies, layout characteristics are determined to build a preliminary task framework; Retrieve the corresponding water area map according to the paving location, and determine the environmental parameters corresponding to the paving operation training subject according to the characteristics of the water area map; Load environmental parameters, water map and paving locations into the preliminary operation task framework to form an operation scenario framework; Obtain the key features of the equipment, build the equipment operation scenario based on the key features of the equipment, and superimpose the equipment operation scenario with the operation scenario framework to form a complete simulation scenario; Perform three-dimensional modeling on the complete simulation scene to generate a first simulation scene, perform pre-simulation in the first simulation scene, obtain a simulation data sequence, and establish a data cycle analysis mechanism; Analyze the abnormal data points that appear in the simulation process based on the data cycle analysis mechanism to determine the abnormal situation and impact degree corresponding to the abnormal data; Evaluate the reliability and accuracy of the first simulation scenario based on the abnormal data situation and impact degree, and obtain an evaluation score; Compare the evaluation score with a preset evaluation threshold to determine whether the first simulation scenario needs to be optimized. When the evaluation score is equal to or greater than the preset evaluation threshold, it is determined that the first simulation scenario meets the requirements and does not need to be optimized. Otherwise, the optimization criteria are determined according to the target difference between the evaluation score and the preset evaluation threshold, the optimization strategy is set, the first simulation scenario is optimized, and the second simulation scenario is generated.

[0014] Furthermore, the method further comprises: Collect the ship's draft, water velocity, water direction and weather parameters, including wind speed and direction; Based on the three-dimensional dynamic model of the ship, according to the draft, water velocity, water direction and weather parameters, the interactive collaborative operation simulation analysis of the rudder propeller and thruster system of the laying ship is carried out, and the first plan for the thrust and rudder propeller control of the laying ship is formed according to the simulation analysis results; The deep Q-network (DQN) algorithm is used to train the reinforcement learning model, and the optimal collaborative control strategy is obtained through interactive learning with the environment. The draft, water velocity, water direction and weather parameters are used as input data of the trained reinforcement learning model, and the reinforcement learning model outputs the collaborative control strategy. According to the collaborative control strategy, the second scheme of the thrust and rudder propeller control of the laying ship is obtained. Corresponding parameters related to the thrust and rudder propeller control of the laying vessel are extracted from the first scheme and the second scheme, and the corresponding parameters are compared. If the deviations of the corresponding parameters of the two schemes do not exceed the set corresponding parameter thresholds, the first scheme or the second scheme is adopted to implement control; if the deviations of the corresponding parameters of the two schemes exceed the set corresponding parameter thresholds, confidence assessments are performed on the first scheme and the second scheme respectively, and the scheme with higher corresponding confidence among the first scheme and the second scheme is adopted as the scheme for implementing control.

[0015] Furthermore, the confidence assessment specifically includes: Defining confidence evaluation indicators of parameters for the first solution and the second solution respectively, wherein the confidence evaluation indicators include data source confidence and external link scale confidence, and the relevant parameters include source parameters and external link parameters; The confidence values ​​of the first or second solution are calculated using the following formulas:

[0016] Wherein, C is the confidence value of the first solution or the second solution, k i The first or second option i The indicator weight of each source parameter, n is the number of source parameters of the first or second scheme, C 1i The first or second option i The data source confidence corresponding to each source parameter; m is the number of external link parameters of the first or second solution, oh j is the index weight of the jth external link parameter of the first or second solution, C 2j It is the confidence level of the external link scale corresponding to the j-th external link parameter of the first solution or the second solution.

[0017] Compared with the prior art, the present invention has the following beneficial effects: Through the coordinated control of the rudder propellers and the thruster system, the motion trajectory of the laying vessel can be controlled more accurately, thereby improving the laying accuracy and operating efficiency, optimizing the thrust distribution strategy, reducing the energy consumption of the laying vessel, and thus improving the economic benefits. The introduction of dynamic delay factors and interference compensation strategies can more realistically simulate the actual operating conditions, and through a hierarchical control architecture, professional division of labor at all levels can be achieved, improving control efficiency and accuracy, building a case database and strategy library, realizing rapid calling and adaptive correction of historical strategies, forming a closed-loop verification process, and providing reliable theoretical support and technical guarantees for actual operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a flow chart of the simulation method for interactive collaborative operation of the rudder propeller and thruster system of the laying ship. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] In order to solve the technical problems in the existing technology that the rudder propeller and thruster system are independently controlled and lack effective collaborative operation strategies, resulting in low operation efficiency, and in complex sea conditions, the ship is difficult to operate and prone to safety accidents, please refer to Figure 1 , this embodiment provides the following technical solutions: The method for simulating the interactive collaborative operation of the rudder propeller and thruster system comprises the following steps: Step 1: Establish a dynamic model of the rudder propeller and thruster system of the laying ship, including the rudder propeller thrust vector model and the thruster system discretized thrust model, and couple the dynamic model with the control system model to generate a rudder propeller-thruster joint dynamic model, wherein the thrust output of the rudder propeller and thruster is used as the input signal of the control system model, and the control command of the control system model is used as the input signal of the dynamic model, so as to realize the interaction between the dynamic model and the control system model; Step 2: Build a multi-device interactive collaborative control architecture model based on the dynamic model and control system model, and define the thrust distribution constraint rules and interference compensation strategy according to the collaborative control relationship between the rudder propeller and the thruster; Step 3: Set the simulation scene and simulation parameters, including environmental parameters, initial state parameters, control parameters, etc., perform simulation calculations based on the simulation scene and simulation parameters, and simulate the motion state and force conditions of the laying ship, rudder propeller and thrust system; The step three also includes: configuring the ship load distribution parameters, including the cargo weight distribution in the cabin, the fuel tank level data (collected through the tank level sensor) and the ballast water distribution (based on the real-time data of the ballast system), and at the same time, configuring the operation task path planning data, including the layout path coordinate sequence, the operation speed profile and the turning point information (imported through the task planning system), generating a dynamic reference trajectory in combination with the environmental parameters, ensuring that the simulation results can reflect the ship performance under actual operating conditions, establishing the equipment status monitoring logic, collecting the rudder angle, speed, and thrust deviation in real time as the simulation feedback signal, monitoring and controlling the status of the rudder propeller and the thrust system, and ensuring that the control strategy in the simulation process can be effectively executed; Step 4: Based on the thrust distribution constraint rules and interference compensation strategy, the thrust distribution weight and control response priority are adjusted in the simulation cycle, and the optimal solution set that meets the layout accuracy and energy consumption constraints is iteratively calculated. The motion state and force conditions in the simulation process are compared with the preset path through deviation spectrum analysis to verify the suppression effect of the collaborative control strategy on nonlinear interference. Step 5: Generate a visual simulation report based on the analysis and verification results, output a multi-dimensional visual report including space-time motion trajectory, equipment operating condition thermal diagram, and energy consumption distribution, and mark the key collaborative control nodes and performance bottlenecks. At the same time, build a case database to store the optimized parameter combinations of typical operating scenarios, covering dynamic model-related parameters, thrust distribution weights, control parameters, etc. Use a similarity matching algorithm to quickly call and adaptively correct historical strategies, compare new simulation results with historical cases, further improve the strategy library, and complete the simulation closed-loop verification process.

[0021] In this embodiment, by establishing a dynamic model and coupling the dynamic model with the control system model to generate a rudder-thrust joint dynamics model, the coordinated control of the rudder and thrust system is realized; based on the multi-device interactive collaborative control architecture model, the thrust distribution constraint rules and interference compensation strategies are defined to solve the problem of low operating efficiency caused by independent control of the rudder and thrust system; by configuring the ship load distribution parameters, the operation task path planning data and the environmental parameters, and combining the equipment status monitoring logic to collect feedback signals in real time, it is ensured that the simulation results can accurately reflect the ship performance under actual operating conditions; in the simulation cycle, based on the thrust distribution constraint rules and the interference compensation strategy, the thrust distribution weight and the control response priority are dynamically adjusted, the optimal solution set that meets the layout accuracy and energy consumption constraints is iteratively calculated, and the suppression effect of the collaborative control strategy on nonlinear interference is verified by deviation spectrum analysis; finally, a multi-dimensional visual simulation report is generated, a case database is constructed, and a similarity matching algorithm is used to realize the rapid call and adaptive correction of historical strategies, forming a closed-loop verification process, which significantly improves the maneuvering accuracy and safety of the layout ship in complex sea conditions, reduces energy consumption, and provides reliable theoretical support and technical guarantee for actual operations.

[0022] In this embodiment, the dynamic model in step 1 specifically includes: Collect design drawings of the layout ship, including the ship type line drawing, cabin layout, installation position and size of the rudder propeller and thruster, so as to determine the model's outline and the relative position relationship of each component. According to the principles of ship engineering, the hull is abstracted as a rigid body, and its physical parameters such as mass, center of gravity, moment of inertia, etc. are defined. Based on the principles of fluid dynamics, a three-dimensional dynamic model of the hull, rudder propeller and thruster system is constructed to simulate the movement and force of the hull in the water, describe the geometric characteristics of the blades such as shape, pitch, diameter, etc., and characterize the nonlinear change characteristics of the rudder propeller thrust vector with the rudder angle and rotation speed; Based on the three-dimensional dynamic model of the rudder propeller, the nonlinear variation characteristics of the rudder propeller thrust vector with the rudder angle and the rotation speed are obtained, and based on the nonlinear variation characteristics, the rudder propeller thrust vector model is constructed, and the rudder propeller thrust vector model is coupled with the hull model to simulate the influence of the rudder propeller on the hull motion; Based on the three-dimensional dynamic model of the thrust system, the thrust data of the thrust system at different speeds are obtained, and the relationship between the thrust and speed of the thrust system is established to form a discretized thrust model. The discretized thrust model also includes introducing a dynamic delay factor to characterize the instantaneous lag effect of the propeller speed and thrust, specifically including: Conduct at least one actual test on the thrust system, collect time series data of speed change and thrust response under different operating conditions, and determine the dynamic delay factor τ related to factors such as propeller characteristics, fluid viscosity and system response time; The thrust model calculation formula is as follows:

[0023] In the formula, T ( t ) is expressed as the thrust value at time t; T ( t-Δt ) represents the thrust value at the previous moment; ΔT ( t ) is expressed as the thrust change; T new ( n ( t )) indicates that the current speed n ( t ) The thrust value calculated without considering the delay effect; Δt It represents the time step of simulation calculation; τ represents the dynamic delay factor.

[0024] In this embodiment, by collecting drawing information to build a three-dimensional dynamic model, the movement and force of the hull and equipment in the water can be accurately simulated, providing a reliable basis for subsequent simulations. The rudder propeller thrust vector model and the discretized thrust model effectively characterize the equipment characteristics. By introducing a dynamic delay factor, the instantaneous lag effect of the propeller speed and thrust is more realistically reflected, making the simulation results more in line with the actual operating conditions, greatly improving the accuracy and practicality of the simulation.

[0025] In this embodiment, the multi-device interactive collaborative control architecture model is constructed in step 2, specifically including: Establish a hierarchical control architecture model, including path planning layer, motion control layer and actuator layer; The path planning layer collects environmental data in real time, such as wind speed, wave angle, current speed, etc., through onboard wind sensors, wave height meters, current meters and other equipment, generates a reference trajectory of the hull motion in combination with a preset layout path, and fuses the environmental data through an environmental disturbance observer, calculates the motion trajectory compensation, and compensates the hull motion reference trajectory; The motion control layer spatially synthesizes the propeller thrust vector output by the dynamic model and the thrust of the thrust system through the conversion matrix between the hull coordinate system and the local equipment coordinate system to generate a unified control input vector; The motion control layer is also used to input the compensated hull motion reference trajectory into the rudder propeller-thruster joint dynamics model, predict the future state of the hull, and optimize the unified control input vector based on the prediction result to achieve optimization of laying accuracy and energy consumption; The actuator layer calculates the combined torque deviation of the rudder propeller and the thruster in real time based on the discretized thrust model, and feeds it back to the motion control layer for thrust redistribution, so that the simulated thrust curve is consistent with the actual equipment response characteristics.

[0026] In this embodiment, the thrust distribution constraint rules include: Thrust direction conflict detection mechanism: Based on the real-time thrust vector of the rudder propeller and the thruster, the transverse projection angle θ is calculated by the vector dot product. When |cosθ|<δ, it is determined as a direction conflict, triggering the priority arbitration logic; the conflict threshold δ is calibrated by actual ship test data, and the value range is 0.1≤δ≤0.3; Power allocation weight function: define dynamic weight coefficients , where n is the cumulative working time of the equipment, which is read in real time by the actuator layer PLC, n max is the maximum continuous working time of the equipment (set according to the equipment technical manual), k is the weight decay rate coefficient, determined by regression analysis of historical fault data, and automatically switches to the backup equipment when γ(n)<0.5; Thrust limit constraint rule: Set the rudder propeller thrust limit |F0|≤F 0max (F0 max Calculated based on the rated power of the rudder propeller motor), thrust limit of the thruster |F1|≤F 1max (F 1max Determined based on hydraulic system pressure threshold); Torque balance constraint rule: The combined torque of the rudder propeller and the thruster must satisfy ||F0×r0+F1×r1||≤τ max , where r0 and r1 are the force arm vectors extracted from the design drawing in step 1, τ max It is the maximum allowable rotational moment of the hull structure.

[0027] In this embodiment, the interference compensation strategy includes: Wake disturbance compensation strategy: The disturbance of the propeller wake to the thruster inlet velocity is collected in real time through the bow Doppler flow meter, and the thrust efficiency loss is calculated based on the Bernoulli equation, the compensation amount is generated and the control command is injected; Environmental disturbance feedforward compensation strategy: Real-time environmental data is obtained through ship-borne wind sensors, wave height meters and ADCP, and the environmental disturbance force is calculated based on the fluid mechanics formula and superimposed on the control input vector as a feedforward item; Model prediction error feedback compensation strategy: The actual resultant torque deviation Δτ is calculated in real time through the thrust space coupling observer at the actuator layer. When Δτ is greater than the allowable error threshold, the adaptive compensation algorithm is triggered to correct the thrust distribution weights α and β. Dynamic delay compensation strategy: embed the dynamic delay factor τ in the discretized thrust model to correct the thrust output timing in real time.

[0028] In this embodiment, the hierarchical control architecture model realizes the specialized division of labor at each level. The path planning layer combines environmental data to accurately plan the trajectory, the motion control layer optimizes the control input, and the actuator layer ensures that the thrust curve is consistent with the actual situation, thereby improving the efficiency and accuracy of the control. The thrust distribution constraint rules can effectively avoid thrust conflicts, reasonably distribute power, ensure the safe operation of equipment, and maintain the hull torque balance; the interference compensation strategy compensates and corrects interference factors such as wake, environment, model errors and dynamic delays in real time, thereby improving the stability and reliability of the system under complex working conditions and greatly enhancing the practicality and accuracy of the laying operation simulation.

[0029] In this embodiment, the simulation scenario in step 3 is generated based on the actual operation type of the ship, water conditions, and equipment status, and specifically includes: According to different laying operation training subjects, such as conventional laying, complex terrain laying, emergency rescue laying, etc., the laying characteristics are determined in combination with the corresponding laying strategies, and a preliminary operation task framework is established. For example, conventional laying focuses on the balance between laying speed and accuracy; complex terrain laying needs to focus on the impact of terrain on the ship's posture and equipment operation; emergency rescue laying emphasizes rapid response and efficient coordination; Retrieve the corresponding water map according to the paving location, such as different water maps of ports, inland rivers, offshore, etc. According to the characteristics of the water map, such as the width of the channel, water flow characteristics, seabed topography, etc., determine the environmental parameters corresponding to the paving operation training subjects, including water flow speed, direction, wave height, tidal changes, etc.; Load environmental parameters, water map and paving locations into the preliminary operation task framework to form an operation scenario framework; Obtain the key features of the equipment, such as the thrust characteristics of the rudder propeller and the response time of the thrust system, build the equipment operation scenario based on the key features of the equipment, and superimpose the equipment operation scenario with the operation scenario framework to form a complete simulation scenario; Perform three-dimensional modeling on the complete simulation scene to generate a first simulation scene, perform pre-simulation in the first simulation scene, obtain a simulation data sequence, and establish a data cycle analysis mechanism; Analyze abnormal data points that appear in the simulation process based on the data loop analysis mechanism to determine the abnormal situation and impact degree corresponding to the abnormal data, such as equipment response delay, force calculation deviation, etc. Evaluate the reliability and accuracy of the first simulation scenario based on the abnormal data situation and impact degree, and obtain an evaluation score; Compare the evaluation score with a preset evaluation threshold to determine whether the first simulation scenario needs to be optimized. When the evaluation score is equal to or greater than the preset evaluation threshold, it is determined that the first simulation scenario meets the requirements and does not need to be optimized. Otherwise, the optimization criteria are determined according to the target difference between the evaluation score and the preset evaluation threshold, the optimization strategy is set, the first simulation scenario is optimized, and the second simulation scenario is generated.

[0030] In this embodiment, according to the actual operation type, water conditions and equipment status, the diversity of laying operations, the complexity of the water environment and the characteristics of the equipment are fully considered, so that the constructed simulation scene is highly close to the actual operation situation, providing a reliable realistic basis for subsequent simulation calculations. Through pre-simulation, data loop analysis and comparison with preset evaluation thresholds, abnormal situations in the scene can be discovered in time and optimized in a targeted manner, thereby improving the reliability and accuracy of the simulation scene, thereby ensuring that the simulation results based on the scene are more valuable for reference, providing strong support for the research and training of laying ship operations.

[0031] Based on the above embodiment, the method further includes: Collect the ship's draft, water velocity, water direction and weather parameters, including wind speed and direction; Based on the three-dimensional dynamic model of the ship, according to the draft, water velocity, water direction and weather parameters, the interactive collaborative operation simulation analysis of the rudder propeller and thruster system of the laying ship is carried out, and the first plan for the thrust and rudder propeller control of the laying ship is formed according to the simulation analysis results; The deep Q-network (DQN) algorithm is used to train the reinforcement learning model, and the optimal collaborative control strategy is obtained through interactive learning with the environment. The draft, water velocity, water direction and weather parameters are used as input data of the trained reinforcement learning model, and the reinforcement learning model outputs the collaborative control strategy. According to the collaborative control strategy, the second scheme of the thrust and rudder propeller control of the laying ship is obtained. Corresponding parameters related to the thrust and rudder propeller control of the laying vessel are extracted from the first scheme and the second scheme, and the corresponding parameters are compared. If the deviations of the corresponding parameters of the two schemes do not exceed the set corresponding parameter thresholds, the first scheme or the second scheme is adopted to implement control; if the deviations of the corresponding parameters of the two schemes exceed the set corresponding parameter thresholds, confidence assessments are performed on the first scheme and the second scheme respectively, and the scheme with higher corresponding confidence among the first scheme and the second scheme is adopted as the scheme for implementing control.

[0032] Specifically, by collecting the draft, water velocity, water direction and weather parameters of the hull, an interactive collaborative operation simulation analysis is carried out based on the three-dimensional dynamic model of the hull to form a first scheme for the thrust and rudder propeller control of the laying ship; in addition, the deep Q network (DQN) algorithm is used to train the reinforcement learning model, and the reinforcement learning model outputs the collaborative control strategy to obtain the second scheme for the thrust and rudder propeller control of the laying ship; the corresponding parameters related to the thrust and rudder propeller control of the laying ship in the two schemes are determined, and a comparison is carried out. If the deviations are all within an acceptable range, it means that the analysis results of different methods are basically consistent, and any execution scheme can be selected; if there is a large deviation, it means that the analysis results of different methods are inconsistent, that is, there will be analysis results with insufficient accuracy. At this time, a confidence assessment is implemented to identify which scheme is credible and reliable, and the reliable scheme will be selected for execution; this scheme examines the reliability of two different schemes by implementing a confidence assessment, thereby ensuring the execution of a reliable scheme. The adoption of this scheme is conducive to improving control accuracy.

[0033] Based on the above embodiment, the confidence evaluation specifically includes: Defining confidence evaluation indicators of parameters for the first solution and the second solution respectively, wherein the confidence evaluation indicators include data source confidence and external link scale confidence, and the relevant parameters include source parameters and external link parameters; The confidence values ​​of the first or second solution are calculated using the following formulas:

[0034] Wherein, C is the confidence value of the first solution or the second solution, k i The first or second option i The indicator weight of each source parameter, n is the number of source parameters of the first or second scheme, C 1i The first or second option i The data source confidence corresponding to each source parameter; m is the number of external link parameters of the first or second solution, oh jis the index weight of the jth external link parameter of the first or second solution, C 2j It is the confidence level of the external link scale corresponding to the j-th external link parameter of the first solution or the second solution.

[0035] Specifically, this scheme provides a usable scheme confidence assessment method. On the basis of considering the confidence of the data source and the confidence of the external link scale, the above formula is used to calculate the confidence assessment value to obtain the comprehensive confidence value of two different schemes, thereby determining the reliability of the scheme; this scheme is based on the confidence assessment of different parameters in the same scheme, and cooperates with setting the parameter weight data in the assessment, thereby calculating a more reasonable comprehensive confidence value; wherein, the sum of the indicator weights of all source parameters used in the calculation and the indicator weights of the external link parameters is equal to 1; the present invention adopts this scheme to achieve high-precision and reliable collaborative operation simulation analysis.

[0036] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A simulation method for interactive collaborative operation of a rudder propeller and a thruster system, characterized in that: The following steps are involved: Establish a dynamic model of the rudder propeller and thruster system of the laying ship, and couple the dynamic model with the control system model to generate a rudder propeller-thruster joint dynamic model, in which the thrust output of the rudder propeller and thruster is used as the input signal of the control system model, and the control command of the control system model is used as the input signal of the dynamic model; A multi-device interactive collaborative control architecture model is constructed based on the dynamic model and control system model, and thrust distribution constraint rules and interference compensation strategies are defined according to the collaborative control relationship between the rudder propeller and the thruster. Set simulation scenarios and simulation parameters, perform simulation calculations based on the simulation scenarios and simulation parameters, and simulate the motion state and force conditions of the laying ship, rudder propeller and thrust system; Based on the thrust distribution constraint rules and interference compensation strategy, the thrust distribution weight and control response priority are adjusted in the simulation cycle, and the motion state and force conditions in the simulation process are verified by deviation spectrum analysis with the preset path; Based on the analysis and verification results, a visual simulation report is generated, and key collaborative control nodes and performance bottlenecks are marked. A case database is built to store optimized parameter combinations for typical operating scenarios, and a similarity matching algorithm is used to quickly call and adaptively correct historical strategies.

2. The interactive collaborative operation simulation method of the laying ship rudder propeller and thruster system according to claim 1 is characterized in that: Dynamic model, including: Collect the design drawings of the laying ship and build a three-dimensional dynamic model of the hull, rudder propeller and thruster system based on the principles of fluid dynamics; Based on the three-dimensional dynamic model of the rudder propeller, the nonlinear variation characteristics of the rudder propeller thrust vector with the rudder angle and the rotation speed are obtained, and based on the nonlinear variation characteristics, the rudder propeller thrust vector model is constructed, and the rudder propeller thrust vector model is coupled with the hull model to simulate the influence of the rudder propeller on the hull motion; Based on the three-dimensional dynamic model of the thrust system, the thrust data of the thrust system at different speeds are obtained, the relationship between the thrust and speed of the thrust system is established, and a discretized thrust model is formed.

3. The interactive collaborative operation simulation method of the laying ship rudder propeller and thruster system according to claim 2 is characterized in that: The discretized thrust model also includes introducing a dynamic delay factor to characterize the instantaneous lag effect of propeller speed and thrust, specifically including: Conduct at least one actual test on the thrust system, collect time series data of speed change and thrust response under different working conditions, and determine the dynamic delay factor τ; The thrust model calculation formula is as follows: ； In the formula, T ( t ) is expressed as the thrust value at time t; T ( t-Δt ) represents the thrust value at the previous moment; ΔT ( t ) is expressed as the thrust change; T new ( n ( t )) indicates that the current speed n ( t ) The thrust value calculated without considering the delay effect; Δt It represents the time step of simulation calculation; τ represents the dynamic delay factor.

4. The interactive collaborative operation simulation method of the rudder propeller and thruster system of the laying ship as claimed in claim 3 is characterized in that: Construct a multi-device interactive collaborative control architecture model, including: Establish a hierarchical control architecture model, including path planning layer, motion control layer and actuator layer; The path planning layer collects environmental data in real time, generates a reference trajectory of the ship's motion in combination with a preset layout path, fuses the environmental data through an environmental disturbance observer, calculates the motion trajectory compensation, and compensates the reference trajectory of the ship's motion; The motion control layer spatially synthesizes the propeller thrust vector output by the dynamic model and the thrust of the thrust system through the conversion matrix between the hull coordinate system and the local equipment coordinate system to generate a unified control input vector; The motion control layer is also used to input the compensated hull motion reference trajectory into the rudder propeller-thruster joint dynamics model, predict the future state of the hull, and optimize the unified control input vector based on the prediction result; The actuator layer calculates the combined torque deviation of the rudder propeller and the thruster in real time based on the discretized thrust model, and feeds it back to the motion control layer for thrust redistribution.

5. The interactive collaborative operation simulation method of the rudder propeller and thruster system of the laying ship according to claim 4 is characterized in that: The thrust distribution constraint rules include: thrust direction conflict detection mechanism, power distribution weight function, thrust limit constraint rules and torque balance constraint rules.

6. The interactive collaborative operation simulation method of the rudder propeller and thruster system of the laying ship as claimed in claim 5 is characterized in that: The interference compensation strategies include: wake interference compensation strategy, environmental interference feedforward compensation strategy, model prediction error feedback compensation strategy and dynamic delay compensation strategy.

7. The interactive collaborative operation simulation method of the rudder propeller and thruster system of the laying ship as claimed in claim 6 is characterized in that: Set simulation scenarios and simulation parameters, perform simulation calculations according to the simulation scenarios and simulation parameters, simulate the motion state and force conditions of the laying ship, rudder propeller and thruster system, and also include: configure ship load distribution parameters. At the same time, configure the operation task path planning data, establish equipment status monitoring logic, collect rudder angle, speed, and thrust deviation in real time as simulation feedback signals, monitor and control the status of the rudder propeller and thruster system, and ensure that the control strategy in the simulation process can be effectively executed.

8. The interactive collaborative operation simulation method of the laying ship rudder propeller and thruster system according to claim 7 is characterized in that: The simulation scenario is generated based on the actual operation type, water conditions, and equipment status of the ship, and specifically includes: According to different layout training subjects, combined with corresponding layout strategies, layout characteristics are determined to build a preliminary task framework; Retrieve the corresponding water area map according to the paving location, and determine the environmental parameters corresponding to the paving operation training subject according to the characteristics of the water area map; Load environmental parameters, water map and paving locations into the preliminary operation task framework to form an operation scenario framework; Obtain the key features of the equipment, build the equipment operation scenario based on the key features of the equipment, and superimpose the equipment operation scenario with the operation scenario framework to form a complete simulation scenario; Perform three-dimensional modeling on the complete simulation scene to generate a first simulation scene, perform pre-simulation in the first simulation scene, obtain a simulation data sequence, and establish a data cycle analysis mechanism; Analyze the abnormal data points that appear in the simulation process based on the data cycle analysis mechanism to determine the abnormal situation and impact degree corresponding to the abnormal data; Evaluate the reliability and accuracy of the first simulation scenario based on the abnormal data situation and impact degree, and obtain an evaluation score; Compare the evaluation score with a preset evaluation threshold to determine whether the first simulation scenario needs to be optimized. When the evaluation score is equal to or greater than the preset evaluation threshold, it is determined that the first simulation scenario meets the requirements and does not need to be optimized. Otherwise, the optimization criteria are determined according to the target difference between the evaluation score and the preset evaluation threshold, the optimization strategy is set, the first simulation scenario is optimized, and the second simulation scenario is generated.

9. The interactive collaborative operation simulation method of the laying ship rudder propeller and thruster system according to claim 2 is characterized in that: Also includes: Collect the ship's draft, water velocity, water direction and weather parameters, including wind speed and direction; Based on the three-dimensional dynamic model of the ship, according to the draft, water velocity, water direction and weather parameters, the interactive collaborative operation simulation analysis of the rudder propeller and thruster system of the laying ship is carried out, and the first plan for the thrust and rudder propeller control of the laying ship is formed according to the simulation analysis results; The deep Q-network (DQN) algorithm is used to train the reinforcement learning model, and the optimal collaborative control strategy is obtained through interactive learning with the environment. The draft, water velocity, water direction and weather parameters are used as input data of the trained reinforcement learning model, and the reinforcement learning model outputs the collaborative control strategy. According to the collaborative control strategy, the second scheme of the thrust and rudder propeller control of the laying ship is obtained. Corresponding parameters related to the thrust and rudder propeller control of the laying vessel are extracted from the first scheme and the second scheme, and the corresponding parameters are compared. If the deviations of the corresponding parameters of the two schemes do not exceed the set corresponding parameter thresholds, the first scheme or the second scheme is adopted to implement control; if the deviations of the corresponding parameters of the two schemes exceed the set corresponding parameter thresholds, confidence assessments are performed on the first scheme and the second scheme respectively, and the scheme with higher corresponding confidence among the first scheme and the second scheme is adopted as the scheme for implementing control.

10. The interactive collaborative operation simulation method of the laying ship rudder propeller and thruster system according to claim 9, characterized in that: The confidence assessment specifically includes: Defining confidence evaluation indicators of parameters for the first solution and the second solution respectively, wherein the confidence evaluation indicators include data source confidence and external link scale confidence, and the relevant parameters include source parameters and external link parameters; The confidence values ​​of the first or second solution are calculated using the following formulas: ； Wherein, C is the confidence value of the first solution or the second solution, k i The first or second option i The indicator weight of each source parameter, n is the number of source parameters of the first or second scheme, C 1i The first or second option i The data source confidence corresponding to each source parameter; m is the number of external link parameters of the first or second solution, ω j is the index weight of the jth external link parameter of the first or second solution, C 2j It is the confidence level of the external link scale corresponding to the j-th external link parameter of the first solution or the second solution.

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