Seabed polymetallic nodule mechanical and hydraulic collaborative collection method

Abstract

The invention discloses a seabed polymetallic nodule mechanical and hydraulic collaborative acquisition method, which comprises the following steps: acquiring real-time topographic data and nodule distribution density of a seabed polymetallic nodule acquisition area, and acquiring topographic height change and nodule adhesion information through sonar scanning and an image sensor to obtain a topographic feature distribution diagram and a density distribution matrix; according to the topographic feature distribution diagram and the density distribution matrix, a preset deep learning model is adopted to analyze topographic complexity and tuberculosis distribution uniformity, the applicability proportion of mechanical collection and hydraulic collection is judged, and a collaborative operation initial weight is obtained; real-time cooperative parameters of mechanical and hydraulic means are calculated through the cooperative operation initial weight in combination with the mechanical arm movement range and the water jet injection capacity of the collection device, and a power distribution scheme and a water jet initial pressure value are determined. Intelligent cooperation of mechanical and hydraulic means in the seabed polymetallic nodule collection process is achieved, and the collection efficiency and adaptability are improved.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular discloses a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules. Background Art

[0002] The collection of polymetallic nodules from the deep seabed is an important topic in the field of marine resource development.

[0003] Current methods for collecting polymetallic nodules rely primarily on single mechanical or hydraulic means. Mechanical collection methods lack adaptability in complex terrain and are easily limited by seafloor undulations and uneven nodule distribution. While hydraulic collection can cover a larger area, the excessive intensity of the water jet leads to energy waste and disturbance of the seafloor ecosystem, and efficiency is difficult to guarantee. These limitations indicate that existing technologies have significant shortcomings in terms of synergy, adaptability, and efficiency optimization, making it difficult to meet the actual needs of deep-sea mining. How to achieve effective synergy between mechanical and hydraulic collection, improve the adaptability of the device to complex seafloor terrain, and optimize the control accuracy of the water jet are currently difficult problems that need to be solved urgently.

[0004] Due to the failure to achieve efficient integration of mechanical and hydraulic means, the collection process often faces the dilemma of low efficiency or excessive energy consumption; at the same time, the diversity of deep-sea topography and changes in nodule adhesion place higher demands on the intelligent response capabilities of the device; in addition, the precise adjustment of the pressure, angle and flow of the water jet directly affects the collection effect and energy utilization. Failure to resolve the technical difficulties caused by these factors makes it difficult for the device to operate stably in extreme environments.

[0005] Therefore, how to achieve the synergy between mechanical and hydraulic means through intelligent control methods in a hydraulic-mechanical hybrid collection device, and at the same time adjust the water jet parameters according to the real-time terrain and nodule distribution to balance efficiency and energy consumption, has become a key issue that needs to be overcome in this research. Solving this problem will provide a new path and breakthrough for the efficient collection of deep-sea polymetallic nodules. Summary of the Invention

[0006] The present invention provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, aiming to address at least one of the defects of the above-mentioned prior art.

[0007] The present invention relates to a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, comprising the following steps: Acquire real-time topographic data and nodule distribution density in the seabed polymetallic nodule collection area. Use sonar scanning and image sensors to collect information on terrain height changes and nodule adhesion, and obtain a topographic feature distribution map and density distribution matrix. Based on the terrain feature distribution map and density distribution matrix, a preset deep learning model was used to analyze the terrain complexity and nodule distribution uniformity, determine the applicability ratio of mechanical and hydraulic collection, and obtain the initial weight of the collaborative operation; By combining the initial weight of collaborative operation with the range of motion of the acquisition device's robotic arm and the water jet's spraying capacity, the real-time collaborative parameters of the mechanical and hydraulic means are calculated, and the power distribution plan and the initial water jet pressure value are determined. After obtaining the power distribution plan and the initial water jet pressure value, the real-time sensor is used to monitor the seabed topography change trend and nodule stripping effect while the acquisition device is running, obtaining dynamic topography update data and effect feedback data; Based on the terrain dynamic update data and effect feedback data, a reinforcement learning algorithm is used to adjust the movement trajectory of the robot arm and the spray angle of the water jet to determine whether the preset efficiency threshold is met, and the optimized trajectory parameters and angle parameters are obtained; By combining the optimized trajectory and angle parameters with the current energy consumption monitoring data, the adjustment range of the water jet flow and pressure is calculated, and the refined water jet control parameters and the operating speed of the robotic arm are determined; After obtaining refined water jet control parameters and the robot arm's operating speed, the embedded control system adjusts the acquisition device's power output and jetting behavior in real time, obtaining adjusted operating status data and energy consumption trends. Based on the adjusted operating status data and energy consumption change trends, if the operating efficiency is lower than the preset threshold, the terrain dynamic update data is smoothed through the adaptive filtering algorithm to determine the abnormal fluctuation area and obtain the revised terrain feature distribution map; Based on the revised terrain feature distribution map, the particle swarm optimization algorithm is used to redistribute the collaborative weights of mechanical and hydraulic means, determine the final power distribution plan and water jet parameters, and obtain stable acquisition operation output data.

[0008] Furthermore, the steps of obtaining real-time topographic data and nodule distribution density of the seabed polymetallic nodule collection area, collecting terrain height changes and nodule adhesion information through sonar scanning and image sensors, and obtaining a terrain feature distribution map and density distribution matrix include: Sonar scanning is used to obtain terrain height and height change data within the acquisition area to generate preliminary terrain feature distribution; Image sensors are used to collect information on nodule distribution and adhesion to obtain raw data on nodule distribution. Extract the distribution density from the original data of tuberculosis distribution and construct the density distribution matrix; The terrain height and height change data are fused and processed to generate an optimized terrain feature distribution map; If the distribution density of a certain area in the density distribution matrix exceeds a preset threshold, the nodule distribution state is adjusted in combination with the adhesion information to obtain a corrected distribution density; Through the overlay analysis of the optimized terrain feature distribution map and the corrected distribution density, the spatial correspondence between feature distribution and density is determined; Obtain the overlay analysis results and jointly output the terrain feature distribution map and density distribution matrix.

[0009] Furthermore, based on the terrain feature distribution map and density distribution matrix, a preset deep learning model is used to analyze the terrain complexity and nodule distribution uniformity, determine the applicability ratio of mechanical collection and hydraulic collection, and obtain the initial weight of the collaborative operation. The steps include: Through terrain characteristics and density distribution, a deep learning model is used to analyze terrain complexity and distribution uniformity, and a preliminary applicability ratio is obtained; Extract the preference data for mechanical and hydraulic collection from the preliminary applicability ratio to determine the allocation basis for collaborative operations. Based on this allocation basis, adjust the operating range of mechanical collection in combination with terrain complexity to obtain an optimized range division. If the distribution uniformity of a certain area in the optimized range division is lower than the preset threshold, the priority of hydraulic acquisition is adjusted according to the density distribution to obtain the adjusted priority sequence; Based on the adjusted priority sequence, the distribution matrix is ​​fused to generate the weight distribution of collaborative tasks and the spatial consistency of the weight distribution is determined; Through the spatial consistency of weight distribution, the preset logistic regression model is used to analyze the stability of the initial weight and obtain the revised collaborative operation weight; Obtain the revised collaborative work weights, superimpose the feature analysis results, and determine the final work allocation plan.

[0010] Furthermore, the steps of calculating the real-time coordination parameters of the mechanical and hydraulic means by combining the initial weight of the collaborative operation with the range of motion of the robotic arm of the acquisition device and the water jet spraying capacity, and determining the power distribution scheme and the initial pressure value of the water jet include: Calculate the operation boundary of the mechanical collection through the initial weight and the range of the robot arm, and determine the boundary division data; Based on the boundary division data, the injection capacity is integrated and the coverage of hydraulic acquisition is adjusted to obtain the range optimization sequence; Through the range optimization sequence, the dynamic distribution of the synergy parameters is obtained and the preliminary ratio of power distribution is determined; If the initial ratio of power distribution exceeds the preset threshold, the real-time calculation results are integrated, the coordination parameters are adjusted, and the revised ratio sequence is determined; Based on the corrected scale sequence and combined with the job fusion data, a spatial mapping of the distribution scheme is generated to obtain the mapping adjustment value; By mapping the adjustment values, the logistic regression model is used to analyze the fluctuation trend of the pressure value and obtain the optimized pressure of the water jet; The final power distribution plan is determined by optimizing the water jet pressure and superimposing the parameter adjustment results.

[0011] Furthermore, after obtaining the power distribution plan and the initial water jet pressure value, the steps of monitoring the seabed topography change trend and the nodule stripping effect through real-time sensors while the acquisition device is running to obtain dynamic topography update data and effect feedback data include: Real-time sensors are used to collect seabed topography change trends and nodule stripping effects, obtaining dynamic topography update data and effect feedback data; Based on the dynamic update data of terrain, the trend analysis method is used to determine the distribution characteristics of the changing trend and obtain the trend distribution sequence; By integrating the trend distribution sequence and the effect feedback data, the dynamic adjustment range of tuberculosis peeling is determined and the adjustment range value is obtained; If the adjustment range value exceeds the preset threshold, the parameters are corrected according to the operating state to obtain the corrected operating parameters; Based on the corrected operating parameters and combined with the monitoring system data, the optimal configuration plan of the acquisition device is obtained and the configuration adjustment sequence is determined; By configuring the adjustment sequence and overlaying the terrain data analysis results, the real-time adaptability of the device operation is determined and the adaptability distribution is obtained; According to the adaptive distribution, the support vector machine algorithm is used to determine the power optimization scheme of the acquisition device and obtain the final allocation parameters.

[0012] Furthermore, based on the terrain dynamic update data and effect feedback data, a reinforcement learning algorithm is used to adjust the movement trajectory of the robot arm and the spray angle of the water jet, and whether a preset efficiency threshold is met is determined. The steps of obtaining optimized trajectory parameters and angle parameters include: Through terrain data and feedback data, the reinforcement learning algorithm is used to adjust the movement trajectory and injection angle to obtain preliminary parameter values; Based on the preliminary parameter values, the real-time monitoring data is integrated to determine the adjustment range and obtain the range sequence; If the range sequence exceeds the preset threshold, the moving trajectory is corrected through data fusion to obtain the corrected trajectory parameters; By correcting the trajectory parameters and superimposing the dynamically updated data, the adaptability of the injection angle is judged and the angle adjustment value is obtained.

[0013] Furthermore, the steps of calculating the adjustment range of the water jet flow and pressure by combining the optimized trajectory parameters and angle parameters with the current energy consumption monitoring data and determining the refined water jet control parameters and the operating speed of the robotic arm include: The embedded control system acquires real-time adjustment data, integrates control parameters and operating speed, and obtains the power output sequence; According to the power output sequence, the injection behavior of the acquisition device is adjusted to obtain the adjusted operation status data; By integrating the data fusion results with the adjusted operation status data, the dynamic sequence of energy consumption changes is determined and a trend acquisition set is obtained; Obtain a set based on the trend, adjust the control parameters, and obtain an updated sequence after the parameters are adjusted; By updating the sequence and integrating the running speed data, the matching degree of the injection behavior is determined and the power output correction value is obtained; According to the power output correction value, the real-time adjustment range of the acquisition device is adjusted to obtain a stable operating state sequence; Through a stable sequence of operating states, the energy consumption change data is integrated to determine the completeness of trend acquisition and obtain the final adjustment configuration.

[0014] Furthermore, based on the adjusted operating status data and energy consumption change trend, if the operating efficiency is lower than a preset threshold, the terrain dynamic update data is smoothed by an adaptive filtering algorithm to determine the abnormal fluctuation area, and the steps of obtaining a revised terrain feature distribution map include: The terrain dynamic update data is smoothed by an adaptive filtering algorithm. If the operating status is lower than the preset threshold, the abnormal fluctuation area is determined to obtain a corrected terrain feature distribution map; According to the modified terrain feature distribution map, the mean filter algorithm is used to perform secondary smoothing on the abnormal fluctuation area to obtain the smoothed terrain feature sequence; By integrating the smoothed terrain feature sequence with the energy consumption change data, the fluctuation range of the dynamic sequence is determined and the fluctuation constraint set is obtained. According to the fluctuation constraint set, the real-time adjustment range of the job status is obtained, and the adjusted status update sequence is obtained; By integrating the terrain dynamic data through the adjusted state update sequence, the matching degree of the feature distribution is judged and the distribution correction value is obtained; According to the distribution correction value, the filter parameters of the smoothing process are adjusted to obtain the optimized terrain feature distribution map; By optimizing the terrain feature distribution map and integrating dynamic sequence data, the stability of the operating status is judged and the final adjustment configuration is obtained.

[0015] Furthermore, based on the revised terrain feature distribution map, the particle swarm optimization algorithm is used to reallocate the coordination weights of mechanical and hydraulic means, determine the final power distribution plan and water jet parameters, and obtain stable acquisition operation output data. The steps include: Based on the revised terrain feature distribution map, the particle swarm optimization algorithm was used to adjust the coordination weights of mechanical and hydraulic means, determine the power distribution plan and water jet parameters, and obtain stable data output from the acquisition operation. Based on the stable data output from the acquisition operation, the terrain feature distribution map is integrated to determine the matching degree of the power distribution plan and obtain the weight correction value; Through the weight correction value, the iterative parameters of the particle swarm optimization algorithm are adjusted to obtain the optimized collaborative weight sequence; Based on the optimized synergy weight sequence, the water jet parameters are integrated to determine the dynamic balance range of mechanical and hydraulic means and determine the adjusted power distribution plan; Through the adjusted power distribution plan, the real-time status data of the acquisition operation is obtained to obtain the status update sequence; According to the status update sequence, the terrain feature data is integrated to determine the fluctuation range of the output data and obtain the final operation configuration parameters; Through the final operation configuration parameters, the operating modes of the water jet and mechanical means are adjusted to determine a stable acquisition operation output sequence.

[0016] The beneficial effects achieved by the present invention are: The present invention provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules. By acquiring seabed topography data and nodule distribution density in real time, a deep learning model is used to analyze the terrain complexity and nodule distribution uniformity, and the collaborative operation weights of mechanical collection and hydraulic collection are determined. During the collection process, the present invention monitors the changes in seabed topography and the nodule stripping effect in real time, and uses a reinforcement learning algorithm to dynamically adjust the trajectory of the robotic arm and the water jet parameters. When the operating efficiency is lower than the preset threshold, the abnormal fluctuation area is processed by an adaptive filtering algorithm, and the particle swarm optimization algorithm is used to redistribute the collaborative weights. The present invention realizes the intelligent coordination of mechanical and hydraulic means in the process of collecting seabed polymetallic nodules, improves the collection efficiency and adaptability, and provides an innovative solution for deep-sea resource development. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The figure is a flow chart of an embodiment of a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules according to the present invention. DETAILED DESCRIPTION

[0018] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0019] like Figure 1 As shown, the first embodiment of the present invention provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, comprising the following steps: Step S100: Acquire real-time terrain data and nodule distribution density of the seabed polymetallic nodule collection area, collect terrain height changes and nodule adhesion information through sonar scanning and image sensors, and obtain a terrain feature distribution map and density distribution matrix.

[0020] Seabed polymetallic nodules are mineral samples collected from the bottom of the Pacific Ocean at a depth of 5,364 meters.

[0021] Nodule distribution density refers to the total mass of polymetallic nodules per unit area of ​​seabed surface (usually 1 square meter).

[0022] Nodule adhesion information is the information about the bonding strength and interaction mechanism between polymetallic nodules and seabed sediments.

[0023] A terrain feature distribution map is a professional map that systematically presents the surface or seabed terrain types, spatial distribution, and morphological parameters of a certain area in a visual manner.

[0024] The density distribution matrix is ​​a spatial distribution pattern that quantifies regional density parameters in a matrix structure and is used to systematically analyze the aggregation characteristics of geological, resource or environmental elements.

[0025] Step S200: Based on the terrain feature distribution map and density distribution matrix, a preset deep learning model is used to analyze the terrain complexity and the uniformity of nodule distribution, determine the applicability ratio of mechanical collection and hydraulic collection, and obtain the initial weight of the collaborative operation.

[0026] The suitability ratio refers to the percentage of nodule distribution areas or resources within a target exploration area that meet specific mining conditions (such as economic value, technical feasibility, and environmental impact thresholds) compared to the total area or total resources within the target exploration area. This ratio, which comprehensively considers resource distribution characteristics, engineering constraints, and environmental risks, guides the delineation of mining priority blocks.

[0027] The initial weight of collaborative operation refers to the pre-set task priority allocation parameter in the deep-sea polymetallic nodule mining system to achieve collaborative control of multiple subsystems (such as ore collection, lifting, monitoring, etc.), which is used to optimize resource scheduling and overall operation efficiency.

[0028] Step S300: Calculate the real-time coordination parameters of the mechanical and hydraulic means by combining the initial weight of the collaborative operation with the range of motion of the robotic arm of the acquisition device and the water jet injection capability, and determine the power distribution scheme and the initial pressure value of the water jet.

[0029] A robotic arm's range of motion refers to the set of all positions its end effector can reach in three-dimensional space, also known as its workspace. This range is determined by the arm's structural design, joint degrees of freedom, and drive system, directly impacting its operational capabilities and applicable scenarios.

[0030] Water jetting capability refers to the ability of a jet formed by a high-pressure nozzle to cut, crush, or strip a target medium (such as seabed sediments, nodules, or crusts) under specific working conditions. It is determined by the jet's kinetic energy, range, and stability, and is a core performance indicator in deep-sea mining, rock cutting, and other fields.

[0031] Real-time coordination parameters are key control variables used to dynamically coordinate the operating states of multiple subsystems (such as ore collection, hoisting, and dynamic positioning) in deep-sea mining systems. Through priority allocation, resource scheduling, and dynamic feedback mechanisms, they ensure the system's response speed, operational efficiency, and safety under complex working conditions.

[0032] The power distribution scheme is a dynamic energy flow scheduling rule designed for multi-power source systems. Its core goal is to achieve an optimal balance between energy efficiency, system stability, and equipment lifespan while meeting load requirements. In fields such as deep-sea mining and electric vehicles, this scheme must adapt to complex operating conditions (such as sudden changes in seabed topography and the coordinated operation of multiple robotic arms).

[0033] The initial waterjet pressure value refers to the initial pressure setting benchmark determined during the waterjet system design phase, based on target operating conditions (cutting / crushing medium characteristics, jet distance, nozzle parameters, etc.) through theoretical calculations or empirical models. Its core function is to provide a quantitative starting point for high-pressure pump selection, piping design, and dynamic pressure control, taking into account system energy consumption, equipment tolerance, and operational efficiency.

[0034] Step S400: After obtaining the power distribution plan and the initial water jet pressure value, when the acquisition device is running, the seabed topography change trend and the nodule stripping effect are monitored through real-time sensors to obtain dynamic topography update data and effect feedback data.

[0035] Nodule stripping effect refers to the comprehensive performance index that quantitatively characterizes the separation efficiency and integrity of nodules and sediments when using water jet technology to physically separate seabed polymetallic nodules. It includes three core dimensions: stripping efficiency, nodule breakage rate, and environmental adaptability.

[0036] Step S500: Based on the terrain dynamic update data and effect feedback data, a reinforcement learning algorithm is used to adjust the movement trajectory of the robot arm and the spray angle of the water jet, and whether the preset efficiency threshold is met is determined to obtain optimized trajectory parameters and angle parameters.

[0037] Step S600: Calculate the adjustment range of the water jet flow and pressure by combining the optimized trajectory parameters and angle parameters with the current energy consumption monitoring data, and determine the refined water jet control parameters and the operating speed of the robotic arm.

[0038] Water jet flow rate refers to the volume or mass of water passing through the nozzle cross section per unit time, which represents the kinetic energy output intensity of the jet.

[0039] Water jet control parameters are the core regulating variables for achieving precise operations. They mainly include four categories: pressure, flow, nozzle characteristics and motion parameters. Their synergistic effect determines the energy output and processing effect of the jet.

[0040] Step S700: After obtaining refined water jet control parameters and the operating speed of the robotic arm, the power output and injection behavior of the acquisition device are adjusted in real time through the embedded control system to obtain adjusted operation status data and energy consumption change trends.

[0041] Step S800: Based on the adjusted operating status data and energy consumption change trend, if the operating efficiency is lower than the preset threshold, the terrain dynamic update data is smoothed by an adaptive filtering algorithm to determine the abnormal fluctuation area and obtain a corrected terrain feature distribution map.

[0042] The abnormal fluctuation region refers to a continuous spatial range in a specific medium (such as a geological body, fluid, or gas-liquid two-phase flow) where physical parameters (pressure, density, element concentration, etc.) deviate significantly from the baseline value due to external excitation or internal nonlinear effects.

[0043] Step S900: Based on the corrected terrain feature distribution map, a particle swarm optimization algorithm is used to redistribute the coordination weights of mechanical and hydraulic means, determine the final power distribution plan and water jet parameters, and obtain stable acquisition operation output data.

[0044] The synergy weight of mechanical and hydraulic means refers to a quantitative evaluation indicator of the dynamic contribution ratio of mechanical action (such as robot arm movement, gear transmission) and hydraulic action (such as fluid pressure, jet cutting) to the overall performance of the composite system.

[0045] Acquisition operation output data refers to the structured data set reflecting the operation process and results obtained through sensors and / or monitoring equipment during engineering operations (such as underwater jetting operations).

[0046] Furthermore, this embodiment provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, wherein step S100 includes: Step S110: Acquire terrain height and height change data within the acquisition area through sonar scanning to generate a preliminary terrain feature distribution.

[0047] In the generated preliminary terrain feature distribution, the terrain height distribution function is: (1) In formula (1), represents the terrain height distribution function, represents sonar scanning data, σ represents Gaussian smoothing parameter, and Represent the length and width of the sampling area, Indicates that the calculation is a point with dot The square of the Euclidean distance between them.

[0048] Step S120: Using an image sensor to collect information on nodule distribution and adhesion, and obtaining raw data on nodule distribution.

[0049] In the original data of tuberculosis distribution, the tuberculosis distribution density function is: (2) In formula (2), represents the nodule distribution density function, Indicates the number of tuberculosis, represents the adhesion coefficient, represents the statistical area, represents the statistical radius, represents the double summation symbol, from arrive 、 from arrive Perform traversal and summation.

[0050] Step S130: extracting the distribution density from the original tuberculosis distribution data and constructing a density distribution matrix.

[0051] Step S140: performing fusion processing on the terrain height and height change data to generate an optimized terrain feature distribution map.

[0052] In the generated optimized terrain feature distribution map, the optimized terrain feature distribution function is: (3) In formula (3), represents the optimized terrain feature distribution function, represents the terrain height distribution function, represents the gradient operator, represents the Laplace operator, 、 、 are the weight coefficients of terrain height, first-order derivative and second-order derivative respectively.

[0053] Step S150: If the distribution density of a certain area in the density distribution matrix exceeds a preset threshold, the nodule distribution state is adjusted in combination with the adhesion information to obtain a corrected distribution density.

[0054] The corrected distribution density is: (4) In formula (4), represents the corrected distribution density, represents the nodule distribution density function, represents the density threshold, Indicates the correction factor based on adhesion.

[0055] Step S160 : performing overlay analysis on the optimized terrain feature distribution map and the corrected distribution density to determine the spatial correspondence between the feature distribution and the density.

[0056] Step S170: Obtain the overlay analysis results and jointly output the terrain feature distribution map and the density distribution matrix.

[0057] The final overlay analysis results are: (5) In formula (5), represents the final overlay analysis result, represents one of the input functions, Represents the second input function, Represents the third input function, represents the spatial correlation weight function, and is the integration variable.

[0058] Furthermore, this embodiment provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, wherein step S200 includes: Step S210: Using the terrain features and density distribution, a deep learning model is used to analyze the terrain complexity and distribution uniformity to obtain a preliminary applicability ratio.

[0059] Step S220: Extract the tendency data of mechanical collection and hydraulic collection from the preliminary applicability ratio to determine the allocation basis of the collaborative operation; based on the allocation basis, adjust the operating range of the mechanical collection in combination with the terrain complexity to obtain an optimized range division.

[0060] Step S230: If the distribution uniformity of a certain area in the optimized range division is lower than a preset threshold, the priority of hydraulic acquisition is adjusted according to the density distribution to obtain an adjusted priority sequence.

[0061] Step S240: Based on the adjusted priority sequence, the distribution matrix is ​​integrated to generate the weight distribution of the collaborative task, and the spatial consistency of the weight distribution is determined.

[0062] Step S250: Analyze the stability of the initial weights using a preset logistic regression model based on the spatial consistency of the weight distribution to obtain a revised collaborative task weight.

[0063] Step S260: Obtain the corrected collaborative task weights, superimpose the feature analysis results, and determine the final task allocation plan.

[0064] Preferably, the present embodiment provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, wherein step S300 includes: Step S310: Calculate the operation boundary of the mechanical collection by using the initial weight and the range of the robot arm, and determine the boundary division data.

[0065] Step S320: Based on the boundary division data, the injection capacity is integrated, and the coverage of the hydraulic acquisition is adjusted to obtain a range optimization sequence.

[0066] Step S330: Obtain the dynamic distribution of the coordination parameters through the range optimization sequence and determine the preliminary ratio of power distribution.

[0067] Step S340: If the preliminary ratio of power distribution exceeds the preset threshold, the real-time calculation results are integrated, the coordination parameters are adjusted, and a corrected ratio sequence is determined.

[0068] Step S350: Generate a spatial mapping of the distribution scheme based on the corrected ratio sequence and combined with the job fusion data to obtain a mapping adjustment value.

[0069] Step S360 : By mapping the adjustment value, a logistic regression model is used to analyze the fluctuation trend of the pressure value to obtain the optimized pressure of the water jet.

[0070] Step S370: Determine the final power distribution plan based on the optimized pressure of the water jet and the result of parameter adjustment.

[0071] Furthermore, this embodiment provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, wherein step S400 includes: Step S410: collecting seabed topography change trends and nodule stripping effects through real-time sensors to obtain dynamic topography update data and effect feedback data.

[0072] Step S420: Based on the terrain dynamic update data, a trend analysis method is used to determine the distribution characteristics of the change trend and obtain a trend distribution sequence.

[0073] Step S430: Determine the dynamic adjustment range of nodule peeling by integrating the effect feedback data through the trend distribution sequence and obtain the adjustment range value.

[0074] Step S440: If the adjustment range value exceeds the preset threshold, the parameters are corrected according to the operating state to obtain corrected operating parameters.

[0075] Step S450: According to the corrected operating parameters and in combination with the monitoring system data, an optimized configuration scheme of the acquisition device is obtained, and a configuration adjustment sequence is determined.

[0076] Step S460: By configuring the adjustment sequence and superimposing the terrain data analysis results, the real-time adaptability of the device operation is determined to obtain the adaptability distribution.

[0077] Step S470: Based on the adaptive distribution, a support vector machine algorithm is used to determine the power optimization scheme of the acquisition device and obtain the final allocation parameters.

[0078] Furthermore, this embodiment provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, wherein step S500 includes: Step S510: Using terrain data and feedback data, a reinforcement learning algorithm is used to adjust the movement trajectory and injection angle to obtain preliminary parameter values.

[0079] In the moving trajectory, the moving trajectory function is: (6) In formula (6), represents the moving trajectory function, represents the terrain feature weight, represents the feedback data vector, represents the learning rate parameter, Represents the terrain gradient function. The formula is used to calculate the preliminary movement trajectory parameters.

[0080] In the injection angle, the injection angle adjustment amount is: (7) In formula (7), Indicates the amount of spray angle adjustment, represents the adjustment coefficient, Indicates the monitoring data weight, Indicates real-time monitoring data. Represents the reference state vector. Formula (7) is used to calculate the adjustment range of the injection angle.

[0081] Step S520: Based on the preliminary parameter values, the real-time monitoring data is integrated to determine the adjustment range and obtain a range sequence.

[0082] Step S530: If the range sequence exceeds the preset threshold, the movement trajectory is corrected by data fusion to obtain corrected trajectory parameters.

[0083] In the corrected trajectory parameters, the corrected trajectory function is: (8) In formula (8), represents the corrected trajectory function, represents the integral weight coefficient, represents the velocity vector, represents the correction factor, Denotes the deviation vector. The formula is used to calculate the corrected trajectory parameters.

[0084] Step S540: By correcting the trajectory parameters and superimposing the dynamically updated data, the adaptability of the injection angle is determined to obtain an angle adjustment value.

[0085] In the angle adjustment value, the final injection angle is: (9) In formula (9), represents the final injection angle, represents the initial angle, represents the dynamic adjustment coefficient, represents the fitness evaluation vector, represents the environment state vector, Is the sum index, indicating from 1 to Integer loop variable used to iterate through each item one by one Formula (9) is used to calculate the final injection angle adjustment value. Based on the angle adjustment value and real-time monitoring data, an optimization scheme is determined to obtain an optimized parameter set. By optimizing the parameter set and combining it with the trend judgment results, the final configuration sequence is obtained and the configuration adjustment value is determined. Based on the configuration adjustment value, the terrain data is integrated to determine the matching degree of the operating state and obtain the matching distribution.

[0086] Furthermore, this embodiment provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, wherein step S600 includes: Step S610: By integrating the optimized trajectory parameters and angle parameters with the energy consumption monitoring data, the adjustment range of the water jet flow rate and pressure is calculated to determine the initial control parameters and the operating speed.

[0087] In the energy consumption monitoring data, the optimized energy consumption value is: (10) In formula (10), Represents the optimized energy consumption value, Indicates the water jet pressure, Indicates flow rate, Indicates the time interval, represents the efficiency coefficient, Indicates the number of sampling points.

[0088] The angle adjustment amount is: (11) In formula (11), Indicates the angle adjustment amount, represents the amplitude coefficient, represents the angular velocity, Indicates time, represents the phase adjustment coefficient, represents the initial phase angle.

[0089] Control speed: (12) In formula (12), Indicates control speed, represents the pressure influence coefficient, Indicates the pressure difference, represents the fluid density, represents the speed correction factor, Indicates the maximum flow rate, represents the jet cross-sectional area.

[0090] The flow adjustment amount is: (13) In formula (13), Indicates the flow adjustment amount, represents the flow regulation coefficient, Indicates the water head height, represents the time constant, Indicates the adjustment time.

[0091] Step S620: According to the initial control parameters and in combination with the monitoring data, a dynamic change sequence of the running speed is obtained to obtain a speed adjustment value.

[0092] The speed adjustment value is superimposed on the data fusion results to determine the degree of water jet flow matching and determine the flow correction value. The flow correction value is then integrated with the pressure adjustment data to obtain the updated control parameter sequence and the optimized parameter set. The optimized parameter set, combined with the dynamic calculation results, determines the adaptability of the operating speed and determines the optimized speed value. The optimized speed value is then integrated with the trajectory parameters to determine the adjustment range of the angle parameters and obtain the final configuration parameters. The final configuration parameters are then superimposed with the monitoring data to determine the stability of the pressure adjustment and obtain a stable control sequence.

[0093] Furthermore, this embodiment provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, wherein step S700 includes: Step S710: Acquire real-time adjustment data through the embedded control system, integrate control parameters and operating speed, and obtain a power output sequence.

[0094] Step S720: Adjust the spraying behavior of the acquisition device according to the power output sequence to obtain adjusted operation status data.

[0095] Step S730: By fusing the data fusion results with the adjusted operation status data, the dynamic sequence of energy consumption changes is determined to obtain a trend acquisition set.

[0096] Step S740: According to the trend acquisition set, the control parameters are adjusted to obtain an update sequence after the parameters are adjusted.

[0097] Step S750: By updating the sequence and integrating the operating speed data, the matching degree of the injection behavior is determined to obtain a power output correction value.

[0098] Step S760: Adjust the real-time adjustment range of the acquisition device according to the power output correction value to obtain a stable operating state sequence.

[0099] Step S770: Through the stable operation state sequence, the energy consumption change data is integrated to determine the completeness of the trend acquisition and obtain the final adjustment configuration.

[0100] Furthermore, this embodiment provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, wherein step S800 includes: Step S810: Smoothing the terrain dynamic update data through an adaptive filtering algorithm. If the operating status is lower than a preset threshold, the abnormal fluctuation area is determined to obtain a corrected terrain feature distribution map.

[0101] Step S820: Based on the corrected terrain feature distribution map, a mean filter algorithm is used to perform secondary smoothing on the abnormal fluctuation area to obtain a smoothed terrain feature sequence.

[0102] Step S830: By integrating the smoothed terrain feature sequence with the energy consumption change data, the fluctuation range of the dynamic sequence is determined to obtain a fluctuation constraint set.

[0103] Step S840: According to the fluctuation constraint set, obtain the real-time adjustment range of the job status and obtain the adjusted status update sequence.

[0104] Step S850: By using the adjusted state update sequence, the terrain dynamic data is integrated to determine the matching degree of the feature distribution and obtain a distribution correction value.

[0105] Step S860: Adjust the filter parameters of the smoothing process according to the distribution correction value to obtain an optimized terrain feature distribution map.

[0106] Step S870: By integrating the optimized terrain feature distribution map with the dynamic sequence data, the stability of the operation status is determined to obtain the final adjustment configuration.

[0107] Furthermore, this embodiment provides a method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules, wherein step S900 includes: Step S910: Using the corrected terrain feature distribution map, a particle swarm optimization algorithm is used to adjust the coordination weights of mechanical and hydraulic means, determine the power distribution scheme and water jet parameters, and obtain stable acquisition operation output data.

[0108] For example, using a modified terrain feature distribution map to adjust the coordination weights between mechanical and hydraulic means, and then determining the power distribution scheme and water jet parameters, can be considered a dynamic optimization approach. The core of the particle swarm optimization algorithm is to simulate swarm behavior and find the optimal solution through collaboration between individuals.

[0109] For example, in a collection operation, mechanical methods might be responsible for breaking up the terrain, while hydraulic methods might flush the material with water jets. Assuming an initial weight of 70% for mechanical and 30% for hydraulic, the algorithm adjusts the weights based on the hardness distribution of the terrain. After iteration, this weighting might become 60% and 40% to accommodate unevenly hard and soft terrain.

[0110] Specifically, mechanical weight is increased in hard areas, while water jet parameters are increased in soft areas, such as pressure from 5MPa to 7MPa, to ensure stable output. This adjustment effectively balances energy consumption and efficiency.

[0111] Step S920: Based on the stable data output from the acquisition operation, the terrain feature distribution map is integrated to determine the matching degree of the power distribution scheme and obtain a weight correction value.

[0112] In one embodiment, the process of collecting the output data of the operation, fusing it with the terrain feature distribution map, judging the matching degree of the power distribution scheme, and obtaining the weight correction value can be regarded as a feedback adjustment mechanism.

[0113] For example, if output data indicates that the material collection rate in a certain area is lower than expected, for example, only 10 tons per hour compared to the target of 15 tons, combined with topographic map analysis, this could be due to a power distribution bias toward machinery, resulting in insufficient hydraulic power. The weight correction might suggest increasing the hydraulic power weight by another 5% to optimize the match. This step allows for timely identification of deviations and dynamic adjustments.

[0114] Step S930: Adjust the iteration parameters of the particle swarm optimization algorithm by using the weight correction value to obtain an optimized collaborative weight sequence.

[0115] It should be noted that adjusting the iterative parameters of the particle swarm optimization algorithm through the weight correction value to obtain the optimized collaborative weight sequence emphasizes the algorithm's adaptability. For example, if the initial iteration step size is set to 0.1 and the correction value shows that the adjustment is too slow, it can be increased to 0.15 to speed up convergence.

[0116] Optimally, after 10 iterations in a given operation, the weight sequence stabilizes at 55% mechanical and 45% hydraulic, the water jet pressure is locked at 6.5 MPa, and output data fluctuations decrease. This approach improves the algorithm's adaptability to complex terrain.

[0117] Step S940: Based on the optimized synergy weight sequence, the water jet parameters are integrated to determine the dynamic balance range of the mechanical and hydraulic means, and determine the adjusted power distribution plan.

[0118] In one possible implementation, water jet parameters are integrated to determine the dynamic balance range of mechanical and hydraulic means, and the adjusted power distribution plan is determined, focusing on the overall coordination of the system.

[0119] For example, when adjusting the water jet flow rate from 20L / s to 25L / s, the mechanical power needs to be reduced by 10% to avoid overload. This adjustment might lock the power distribution at 50 / 50, ensuring smooth operation. This reduces equipment wear and maintains long-term stability.

[0120] Step S950: Acquire real-time status data of the acquisition operation through the adjusted power distribution plan to obtain a status update sequence.

[0121] Specifically, the adjusted power distribution scheme captures real-time status data, generating a status update sequence similar to a real-time monitoring application. For example, during a certain operation, the status data indicates a sudden 5% drop in collection efficiency. Analysis of terrain characteristics suggests this may be due to localized uplift. The status update sequence records this change and triggers subsequent adjustments. This real-time nature enables rapid response to terrain changes.

[0122] Step S960: According to the state update sequence, the terrain feature data is integrated, the fluctuation range of the output data is determined, and the final operation configuration parameters are obtained.

[0123] For example, by integrating terrain feature data with the status update sequence, the fluctuation range of the output data can be determined to determine the final operation configuration parameters. This allows for refined management through data analysis. If the fluctuation range is narrowed from ±10% to ±5%, the final configuration might adjust the water jet angle from 30° to 45° and reduce the machine speed to 80 rpm. This configuration can significantly improve operation consistency.

[0124] Step S970: Adjust the operation modes of the water jet and mechanical means through the final operation configuration parameters to determine a stable acquisition operation output sequence.

[0125] In one embodiment, adjusting the operating modes of the water jet and mechanical means through the final operation configuration parameters and determining a stable acquisition operation output sequence is the implementation link of the entire process.

[0126] For example, water jetting takes precedence in soft terrain, while mechanical extraction takes precedence in hard terrain. The output sequence shows a stable daily collection volume of around 200 tons. This flexibility helps cope with changing environments and optimize resource utilization.

[0127] Compared with the existing technology, the method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules provided in this embodiment obtains seabed topography data and nodule distribution density in real time, uses a deep learning model to analyze the terrain complexity and nodule distribution uniformity, and determines the collaborative operation weights of mechanical collection and hydraulic collection. During the collection process, this embodiment monitors the changes in seabed topography and the nodule stripping effect in real time, and uses a reinforcement learning algorithm to dynamically adjust the trajectory of the robotic arm and the water jet parameters. When the operating efficiency is lower than the preset threshold, the abnormal fluctuation area is processed by an adaptive filtering algorithm, and the particle swarm optimization algorithm is used to redistribute the collaborative weights. This embodiment realizes the intelligent collaboration of mechanical and hydraulic means in the process of collecting seabed polymetallic nodules, improves the collection efficiency and adaptability, and provides an innovative solution for deep-sea resource development.

[0128] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the invention. Thus, the present invention is intended to include such changes and modifications as fall within the scope of the claims and their equivalents.

Claims

1. A method for the coordinated collection of submarine polymetallic nodules by mechanical and hydraulic means, characterized in that: The following steps are involved: Acquire real-time topographic data and nodule distribution density in the seabed polymetallic nodule collection area. Use sonar scanning and image sensors to collect information on terrain height changes and nodule adhesion, and obtain a topographic feature distribution map and density distribution matrix. Based on the terrain feature distribution map and density distribution matrix, a preset deep learning model is used to analyze the terrain complexity and nodule distribution uniformity, determine the applicability ratio of mechanical collection and hydraulic collection, and obtain the initial weight of the collaborative operation; By using the initial weight of the collaborative operation, combined with the range of motion of the robotic arm of the acquisition device and the injection capacity of the water jet, the real-time collaborative parameters of the mechanical and hydraulic means are calculated to determine the power distribution plan and the initial pressure value of the water jet; After obtaining the power distribution scheme and the initial water jet pressure value, the seabed topography change trend and the nodule stripping effect are monitored by real-time sensors while the acquisition device is running, and dynamic topography update data and effect feedback data are obtained; Based on the terrain dynamic update data and effect feedback data, a reinforcement learning algorithm is used to adjust the movement trajectory of the robotic arm and the spray angle of the water jet, determine whether the preset efficiency threshold is met, and obtain optimized trajectory parameters and angle parameters; By combining the optimized trajectory and angle parameters with the current energy consumption monitoring data, the adjustment range of the water jet flow and pressure is calculated, and the refined water jet control parameters and the operating speed of the robotic arm are determined; After obtaining refined water jet control parameters and the robot arm's operating speed, the embedded control system adjusts the acquisition device's power output and jetting behavior in real time, obtaining adjusted operating status data and energy consumption trends. Based on the adjusted operating status data and energy consumption change trends, if the operating efficiency is lower than the preset threshold, the terrain dynamic update data is smoothed through the adaptive filtering algorithm to determine the abnormal fluctuation area and obtain the revised terrain feature distribution map; Based on the revised terrain feature distribution map, the particle swarm optimization algorithm is used to redistribute the collaborative weights of mechanical and hydraulic means, determine the final power distribution plan and water jet parameters, and obtain stable acquisition operation output data.

2. The method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules according to claim 1, characterized in that: The steps of obtaining real-time terrain data and nodule distribution density of the seabed polymetallic nodule collection area, collecting terrain height changes and nodule adhesion information through sonar scanning and image sensors, and obtaining a terrain feature distribution map and a density distribution matrix include: Sonar scanning is used to obtain terrain height and height change data within the acquisition area to generate preliminary terrain feature distribution; Image sensors are used to collect information on nodule distribution and adhesion to obtain raw data on nodule distribution. Extract the distribution density from the original data of tuberculosis distribution and construct the density distribution matrix; Performing fusion processing on the terrain height and height change data to generate an optimized terrain feature distribution map; If the distribution density of a certain area in the density distribution matrix exceeds a preset threshold, the nodule distribution state is adjusted in combination with the adhesion information to obtain a corrected distribution density; Through the overlay analysis of the optimized terrain feature distribution map and the corrected distribution density, the spatial correspondence between feature distribution and density is determined; Obtain the overlay analysis results and jointly output the terrain feature distribution map and density distribution matrix.

3. The method for the coordinated mechanical and hydraulic collection of seabed polymetallic nodules according to claim 1, characterized in that: The steps of analyzing terrain complexity and nodule distribution uniformity using a preset deep learning model based on the terrain feature distribution map and density distribution matrix, determining the applicability ratio of mechanical collection and hydraulic collection, and obtaining the initial weight of the collaborative operation include: Through terrain characteristics and density distribution, a deep learning model is used to analyze terrain complexity and distribution uniformity, and a preliminary applicability ratio is obtained; Extracting the tendency data of mechanical collection and hydraulic collection from the preliminary applicability ratio to determine the allocation basis of the collaborative operation; adjusting the operation range of the mechanical collection based on the allocation basis and taking into account the complexity of the terrain to obtain an optimized range division; If the distribution uniformity of a certain area in the optimized range division is lower than the preset threshold, the priority of hydraulic acquisition is adjusted according to the density distribution to obtain the adjusted priority sequence; Based on the adjusted priority sequence, the distribution matrix is ​​fused to generate the weight distribution of collaborative tasks and the spatial consistency of the weight distribution is determined; Through the spatial consistency of weight distribution, the preset logistic regression model is used to analyze the stability of the initial weight and obtain the revised collaborative operation weight; Obtain the revised collaborative work weights, superimpose the feature analysis results, and determine the final work allocation plan.

4. The method for cooperative mechanical and hydraulic collection of seabed polymetallic nodules according to claim 1, characterized in that: The steps of calculating the real-time coordination parameters of the mechanical and hydraulic means by combining the initial weight of the collaborative operation with the range of motion of the robotic arm of the acquisition device and the spraying capacity of the water jet, and determining the power distribution scheme and the initial pressure value of the water jet include: Calculate the operation boundary of the mechanical collection through the initial weight and the range of the robot arm, and determine the boundary division data; According to the boundary division data, the injection capacity is integrated, and the coverage range of the hydraulic acquisition is adjusted to obtain a range optimization sequence; By means of the range optimization sequence, the dynamic distribution of the coordination parameters is obtained and the preliminary proportion of the power distribution is determined; If the initial ratio of power distribution exceeds the preset threshold, the real-time calculation results are integrated, the coordination parameters are adjusted, and the revised ratio sequence is determined; Based on the corrected scale sequence and combined with the job fusion data, a spatial mapping of the distribution scheme is generated to obtain the mapping adjustment value; By using the mapping adjustment value, a logistic regression model is used to analyze the fluctuation trend of the pressure value to obtain the optimized pressure of the water jet; The final power distribution plan is determined by optimizing the water jet pressure and superimposing the parameter adjustment results.

5. The method for cooperative mechanical and hydraulic collection of seabed polymetallic nodules according to claim 1, characterized in that: After obtaining the power distribution scheme and the initial water jet pressure value, the steps of monitoring the seabed topography change trend and the nodule stripping effect through real-time sensors while the acquisition device is running to obtain dynamic topography update data and effect feedback data include: Real-time sensors are used to collect seabed topography change trends and nodule stripping effects, obtaining dynamic topography update data and effect feedback data; According to the terrain dynamic update data, a trend analysis method is used to determine the distribution characteristics of the change trend and obtain a trend distribution sequence; By integrating the trend distribution sequence and the effect feedback data, a dynamic adjustment range of tuberculosis peeling is determined to obtain an adjustment range value; If the adjustment range value exceeds the preset threshold, the parameters are corrected according to the operating state to obtain the corrected operating parameters; Based on the corrected operating parameters and combined with the monitoring system data, the optimal configuration plan of the acquisition device is obtained and the configuration adjustment sequence is determined; By configuring the adjustment sequence and overlaying the terrain data analysis results, the real-time adaptability of the device operation is determined and the adaptability distribution is obtained; According to the adaptive distribution, the support vector machine algorithm is used to determine the power optimization scheme of the acquisition device and obtain the final allocation parameters.

6. The method for cooperative mechanical and hydraulic collection of seabed polymetallic nodules according to claim 1, characterized in that: The steps of using a reinforcement learning algorithm to adjust the movement trajectory of the robotic arm and the spray angle of the water jet based on the terrain dynamic update data and the effect feedback data, and determining whether a preset efficiency threshold is met to obtain optimized trajectory parameters and angle parameters include: Through terrain data and feedback data, the reinforcement learning algorithm is used to adjust the movement trajectory and injection angle to obtain preliminary parameter values; Based on the preliminary parameter values, the real-time monitoring data is integrated to determine the adjustment range and obtain the range sequence; If the range sequence exceeds the preset threshold, the moving trajectory is corrected through data fusion to obtain the corrected trajectory parameters; By correcting the trajectory parameters and superimposing the dynamically updated data, the adaptability of the injection angle is judged and the angle adjustment value is obtained.

7. The method for cooperative mechanical and hydraulic collection of seabed polymetallic nodules according to claim 1, characterized in that: The steps of calculating the adjustment range of the water jet flow rate and pressure by combining the optimized trajectory parameters and angle parameters with the current energy consumption monitoring data, and determining the refined water jet control parameters and the operating speed of the robotic arm include: By integrating the optimized trajectory and angle parameters with the energy consumption monitoring data, the adjustment range of the water jet flow and pressure is calculated to determine the initial control parameters and operating speed. According to the initial control parameters and in combination with monitoring data, a dynamic change sequence of the operating speed is obtained to obtain a speed adjustment value.

8. The method for cooperative mechanical and hydraulic collection of seabed polymetallic nodules according to claim 1, characterized in that: After obtaining the refined water jet control parameters and the robot arm operating speed, the steps of adjusting the power output and spraying behavior of the acquisition device in real time through the embedded control system to obtain the adjusted operation status data and energy consumption change trend include: The embedded control system acquires real-time adjustment data, integrates control parameters and operating speed, and obtains the power output sequence; According to the power output sequence, the injection behavior of the acquisition device is adjusted to obtain adjusted operation status data; By integrating the data fusion results with the adjusted operation status data, the dynamic sequence of energy consumption changes is determined and a trend acquisition set is obtained; Acquire a set according to the trend, adjust control parameters, and obtain an updated sequence after the parameters are adjusted; By updating the sequence and integrating the running speed data, the matching degree of the injection behavior is determined and the power output correction value is obtained; According to the power output correction value, the real-time adjustment range of the acquisition device is adjusted to obtain a stable operating state sequence; Through a stable sequence of operating states, the energy consumption change data is integrated to determine the completeness of trend acquisition and obtain the final adjustment configuration.

9. The method for cooperative mechanical and hydraulic collection of seabed polymetallic nodules according to claim 1, characterized in that: The step of smoothing the terrain dynamic update data using an adaptive filtering algorithm based on the adjusted operation status data and energy consumption change trend, determining abnormal fluctuation areas, and obtaining a revised terrain feature distribution map includes: The terrain dynamic update data is smoothed by an adaptive filtering algorithm. If the operating status is lower than the preset threshold, the abnormal fluctuation area is determined to obtain a corrected terrain feature distribution map; According to the modified terrain feature distribution map, the mean filter algorithm is used to perform secondary smoothing on the abnormal fluctuation area to obtain the smoothed terrain feature sequence; By integrating the smoothed terrain feature sequence with the energy consumption change data, the fluctuation range of the dynamic sequence is determined and the fluctuation constraint set is obtained. According to the fluctuation constraint set, a real-time adjustment range of the job status is obtained to obtain an adjusted status update sequence; By integrating the terrain dynamic data through the adjusted state update sequence, the matching degree of the feature distribution is judged and the distribution correction value is obtained; According to the distribution correction value, the filter parameters of the smoothing process are adjusted to obtain an optimized terrain feature distribution map; By optimizing the terrain feature distribution map and integrating dynamic sequence data, the stability of the operating status is judged and the final adjustment configuration is obtained.

10. The method for cooperative mechanical and hydraulic collection of seabed polymetallic nodules according to claim 1, characterized in that: The steps of using the particle swarm optimization algorithm to redistribute the coordination weights of mechanical and hydraulic means based on the modified terrain feature distribution map, determining the final power distribution plan and water jet parameters, and obtaining stable acquisition operation output data include: Based on the revised terrain feature distribution map, the particle swarm optimization algorithm was used to adjust the coordination weights of mechanical and hydraulic means, determine the power distribution plan and water jet parameters, and obtain stable data output from the acquisition operation. Based on the stable data output from the acquisition operation, the terrain feature distribution map is integrated to determine the matching degree of the power distribution plan and obtain the weight correction value; Adjusting the iterative parameters of the particle swarm optimization algorithm by using the weight correction value to obtain an optimized collaborative weight sequence; Based on the optimized synergy weight sequence, the water jet parameters are integrated to determine the dynamic balance range of mechanical and hydraulic means and determine the adjusted power distribution plan; Through the adjusted power distribution plan, the real-time status data of the acquisition operation is obtained to obtain the status update sequence; According to the status update sequence, the terrain feature data is integrated to determine the fluctuation range of the output data and obtain the final operation configuration parameters; Through the final operation configuration parameters, the operating modes of the water jet and mechanical means are adjusted to determine a stable acquisition operation output sequence.

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