Positioning control method, device and equipment for fan-shaped bow jet of trailing suction hopper dredger and medium

Abstract

The invention relates to a fan-shaped bow jet positioning control method, device, equipment and medium for a trailing suction hopper dredger, and the method comprises the steps: obtaining sea condition data and distribution characteristic data in a spraying area in real time, analyzing the sea condition data based on an established first response model, and obtaining a first response model; according to the ship attitude control strategy, a corresponding ship attitude control strategy is generated; based on an established second response model, performing data fusion on the ship attitude control strategy and the distribution characteristic data to generate corresponding fusion data, and generating a corresponding spraying control strategy according to the fusion data; not only can uniform spraying of silt be ensured, but also the working efficiency and the safety are remarkably improved. Through real-time feedback and optimization of a control strategy, high efficiency and accuracy of operation can be continuously kept, and the problems of response lag, tedious operation, uneven spraying and the like in a traditional control method are fundamentally solved.

Description

Technical Field

[0001] The invention relates to the technical field of trailing suction hopper dredger control, and in particular to a method, device, equipment and medium for positioning control of a fan-shaped bow jet of a trailing suction hopper dredger. Background Art

[0002] At present, the existing positioning control methods of the fan-shaped bow spray of the trailing suction hopper dredger often rely on manual adjustment or a dynamic positioning system with a low level of automation. Although attempts are made to improve the efficiency of dredging operations by adjusting the thrust distribution and bow control, these methods perform poorly in response to changes in sea conditions due to the lack of refined control and rapid response mechanisms. Specifically, the existing systems are usually unable to quickly adapt to dynamic sea conditions such as wind, waves, and tides, resulting in a lag in the adjustment of the ship's attitude and the inability to achieve accurate positioning. Therefore, the distribution of sediment during the spraying process is often uneven, and mud accumulation occurs frequently, which seriously affects the operating efficiency. Especially in complex marine environments, the stability and operational safety of the ship are further threatened, which not only increases the construction period, but also increases the operational risk, restricting the application effect of the trailing suction hopper dredger in dredging projects. The existing control methods lack sufficient intelligence and adaptive capabilities, and fail to effectively solve the negative impact of changes in sea conditions on the positioning accuracy and spraying effect of the ship. Summary of the invention

[0003] In order to solve the problem that the existing control methods lack sufficient intelligence and adaptability and fail to effectively solve the negative impact of sea conditions changes on ship positioning accuracy and spraying effect, the present application provides a fan-shaped bow spray positioning control method, device, equipment and medium for a trailing suction dredger.

[0004] The above-mentioned invention objective of the present application is achieved through the following technical solutions: A method for controlling the positioning of a fan-shaped bow jet of a trailing suction hopper dredger, the method comprising: Acquire sea condition data and distribution characteristic data in the spraying area in real time, wherein the sea condition data at least includes wind condition data and water condition data; Based on the established first response model, the sea condition data is analyzed to generate a corresponding ship attitude control strategy, and a corresponding ship attitude control operation is performed according to the ship attitude control strategy; Based on the established second response model, data fusion is performed on the ship attitude control strategy and the distribution characteristic data to generate corresponding fusion data, and a corresponding spraying control strategy is generated according to the fusion data; According to the spraying control strategy, corresponding spraying control parameters are determined, wherein the spraying control parameters at least include a range parameter and a power parameter, and corresponding spraying control operations are performed according to the spraying control parameters.

[0005] By adopting the above technical solution, the sea condition data is analyzed based on the first response model to generate the corresponding ship attitude control strategy, ensuring that the ship can adjust the attitude parameters such as heading, tilt angle and speed in a timely and accurate manner when facing a complex marine environment, so as to maintain stability during the operation. In addition, the ship attitude control strategy and the sediment distribution characteristic data in the spraying area are fused through the second response model to generate an optimized spraying control strategy. This data fusion process ensures that the spraying path and spraying intensity can be dynamically adjusted according to the ship attitude and real-time sea conditions, avoiding the problem of sediment accumulation or uneven spraying caused by the failure to adjust the spraying parameters in time in the traditional method. Finally, according to the generated spraying control strategy, the method calculates accurate spraying control parameters, such as spraying range and power, and performs spraying control operations. Under complex sea conditions, this dynamic adjustment capability can not only ensure uniform spraying of sediment, but also significantly improve the operation efficiency and safety. Through real-time feedback and optimization of control strategies, the method can continuously maintain the efficiency and accuracy of the operation, fundamentally solving the problems of response lag, cumbersome operation, and uneven spraying in traditional control methods.

[0006] In a preferred example, the present application may be further configured as follows: the step of acquiring sea condition data and spraying area distribution characteristic data in real time, wherein the sea condition data at least includes wind condition data and water condition data, comprises: Obtain ship position information; Based on underwater imaging sensors, the distribution characteristic data in the spraying area is obtained; Substituting the ship position information and the distribution characteristic data into the established demand data identification model to determine the corresponding demand data results, wherein the demand data results are used to determine the complexity of the relationship between the ship attitude control strategy and the sediment distribution data; According to the required data result, the corresponding sea condition sensor element is determined, and based on the sea condition sensor element, the corresponding sea condition data is acquired.

[0007] By adopting the above technical solutions, it is possible to ensure that the ship can accurately adjust the operating parameters under dynamic sea conditions. By obtaining the ship's position information and combining it with the distribution characteristic data of the underwater imaging sensor, the sediment distribution status in the spraying area and the real-time position of the ship can be effectively grasped, thereby providing accurate data support for subsequent attitude control and spraying control. Substituting the ship's position information and distribution characteristic data into the established demand data recognition model can determine the complexity of the relationship between the ship's attitude control strategy and the sediment distribution, thereby optimizing the selection of sea condition sensor elements, so that different sea condition sensor elements can obtain accurate sea condition data according to specific needs, such as wind speed, wind direction, water flow status, etc. This process of real-time acquisition and precise matching ensures the accuracy and relevance of sea condition data, thereby improving the stability and efficiency of ship operations.

[0008] In a preferred example, the present application may be further configured as follows: the step of determining the corresponding sea condition sensor element according to the required data result, and obtaining the corresponding sea condition data based on the sea condition sensor element includes: According to the demand data results, matching corresponding scenario conditions; Determine the corresponding sea condition sensing element based on the mapping relationship determined by the scene conditions; If the sea condition sensing element is an anemometer, wind speed data is obtained; If the sea condition sensing element is a wind direction sensor, obtaining wind direction data; If the sea condition sensing element is a water flow sensor, obtaining water flow state data; If the sea condition sensing element is a wave sensor, wave state data is obtained.

[0009] By adopting the above technical solution, different scene conditions can be intelligently matched according to the required data results, and then suitable sensors can be selected to obtain relevant sea condition data. This intelligent matching mechanism can flexibly adjust the selection of sensor elements according to the specific working environment, improve the pertinence and accuracy of data acquisition, and avoid invalid or erroneous data collection caused by improper sensor selection in traditional methods, thereby ensuring the accuracy and response speed of ship operations, especially in complex sea conditions, and can quickly obtain accurate wind speed, wind direction, water flow and wave state data, providing strong data support for subsequent ship attitude and spraying control strategies.

[0010] In a preferred example, the present application may be further configured as follows: the step of fusing the ship attitude control strategy and the distribution characteristic data based on the established second response model to generate corresponding fused data includes: Selecting key data in the ship attitude control strategy; Determine a corresponding data fusion algorithm according to the required data result; Based on the data fusion algorithm, the key data and the distribution characteristic data are fused to generate corresponding fused data.

[0011] By adopting the above technical solution, it is possible to comprehensively consider the ship attitude control strategy and the real-time characteristics of the sediment distribution in the spraying area through precise data fusion analysis, thereby ensuring the optimized control of the spraying operation. Data fusion can effectively eliminate the limitations of a single data source, combine the characteristic information of ship attitude adjustment and sediment distribution, and generate a more comprehensive and accurate fusion data, so that the control strategy is more in line with actual operation needs. Through this fusion method, the relationship between the ship attitude control strategy and the sediment distribution in the spraying area is effectively modeled and optimized, which greatly improves the control accuracy and spraying effect during the ship operation process and reduces unnecessary errors and deviations.

[0012] In a preferred example, the present application may be further configured as follows: the step of generating a corresponding spraying control strategy according to the fusion data includes: Checking whether the ship attitude after executing the ship attitude control operation maintains the optimal attitude, if not, re-determining the ship attitude control strategy to perform the ship attitude control operation until the ship attitude maintains the optimal attitude; If yes, determine a spraying control target according to the fused data, and determine a control range of the spraying control target, wherein the spraying control target includes a spraying angle, a spraying radius, a spraying intensity and a spraying frequency; Determine the error tolerance interval corresponding to the control interval according to the demand data result; The spraying control target, the control interval and the error tolerance interval are packaged to form a corresponding spraying control strategy.

[0013] By adopting the above technical solutions, it is possible to detect and correct potential attitude deviations in a timely manner by checking whether the ship's attitude is in the best attitude, ensuring that the ship is always in the best operating attitude. If the ship's attitude is not in the best state, the system can automatically recalculate and adjust the attitude control strategy until the ship returns to the ideal state, ensuring the stability and accuracy of the spraying operation. Through this process, each operation cycle of the ship can be optimized based on real-time feedback, thereby improving the reliability and operation efficiency of spraying control. At the same time, by setting the spraying control target and determining the control range based on the fused data, the error range during the operation process is effectively limited, ensuring the stability and uniformity of the spraying operation under different environmental conditions, and greatly improving the safety and operability of the construction process.

[0014] In a preferred example, the present application may be further configured as follows: the step of determining the corresponding spraying control parameters according to the spraying control strategy includes: Determine a spraying range according to the control range and the allowable error range of the spraying angle, and the control range and the allowable error range of the spraying radius; According to the overlap degree generated after comparing the spraying range with the spraying area, determine whether to modify the spraying range, if yes, push an interactive window for modifying the spraying range, if no, determine the corresponding range parameters according to the spraying range; The power parameter is determined according to the control interval and the error tolerance interval of the spraying intensity, and the control interval and the error tolerance interval of the spraying frequency.

[0015] By adopting the above technical solutions, the spraying range and power parameters can be accurately determined by combining the control intervals and error tolerance intervals such as spraying angle, spraying radius, and spraying intensity. By comparing with the spraying area, the overlap of the spraying range is determined, and dynamic adjustments are made according to the actual situation to ensure that the spraying range accurately covers the target area. If the overlap is insufficient, the system will prompt the operator to modify the spraying range through an interactive window. This feedback mechanism improves the flexibility and adaptability of the spraying control process and avoids the problem of excessive or insufficient spraying deviation in traditional methods. At the same time, the power parameters are determined based on the control interval and error range of the spraying intensity and spraying frequency to ensure energy efficiency optimization of the spraying operation. This dynamic adjustment capability can maintain operating efficiency and accuracy under different sea conditions, reduce energy waste, and further improve the overall effect of the spraying operation.

[0016] The second object of the invention is achieved by the following technical solutions: A fan-shaped bow jet positioning control device for a trailing suction hopper dredger, the fan-shaped bow jet positioning control device for a trailing suction hopper dredger comprising: An acquisition module, used for acquiring sea condition data and distribution characteristic data in the spraying area in real time, wherein the sea condition data at least includes wind condition data and water condition data; A first analysis module is used to analyze the sea condition data based on the established first response model to generate a corresponding ship attitude control strategy, and perform a corresponding ship attitude control operation according to the ship attitude control strategy; A second analysis module is used to perform data fusion on the ship attitude control strategy and the distribution characteristic data based on the established second response model to generate corresponding fusion data, and generate a corresponding spraying control strategy according to the fusion data; The determination module is used to determine corresponding spraying control parameters according to the spraying control strategy, wherein the spraying control parameters at least include a range parameter and a power parameter, and perform corresponding spraying control operations according to the spraying control parameters.

[0017] The third objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned method for controlling the positioning of a fan-shaped bow jet of a trailing suction dredger are implemented.

[0018] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for controlling the positioning of a fan-shaped bow jet of a trailing suction dredger are implemented.

[0019] In summary, the present application includes at least one of the following beneficial technical effects: The positioning control method for the fan-shaped bow spray of a trailing suction dredger solves the problems of the traditional method in responding to changes in sea conditions, complex operation, and inaccurate positioning by combining real-time sea condition data and distribution characteristic data of the spraying area. First, the method can obtain sea condition data including wind speed, wind direction, water flow rate, wave height, etc. in real time, so that the control system can respond quickly to environmental changes and dynamically adjust the ship's attitude. Traditional methods often rely on manual adjustment or low-automation systems, which make it difficult to quickly adjust the ship's attitude and spraying path when sea conditions change, resulting in reduced operation accuracy and low efficiency.

[0020] By analyzing the sea condition data based on the first response model, the corresponding ship attitude control strategy is generated to ensure that the ship can adjust the attitude parameters such as heading, tilt angle and speed in a timely and accurate manner when facing a complex marine environment, so as to maintain stability during the operation. In addition, the ship attitude control strategy and the sediment distribution characteristic data in the spraying area are fused through the second response model to generate an optimized spraying control strategy. This data fusion process ensures that the spraying path and spraying intensity can be dynamically adjusted according to the ship's attitude and real-time sea conditions, avoiding the problem of sediment accumulation or uneven spraying caused by the failure to adjust the spraying parameters in time in the traditional method.

[0021] Finally, according to the generated spraying control strategy, the method calculates accurate spraying control parameters, such as spraying range and power, and performs spraying control operations. Under complex sea conditions, this dynamic adjustment capability can not only ensure uniform spraying of sediment, but also significantly improve operation efficiency and safety. Through real-time feedback and optimization of control strategies, the method can continuously maintain the efficiency and accuracy of operations, fundamentally solving the problems of response lag, cumbersome operation, and uneven spraying in traditional control methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1The present invention is a flow chart of a method for controlling the positioning of a fan-shaped bow jet of a trailing suction dredger in one embodiment of the present application.

[0023] Figure 2 It is a flowchart for realizing step S10 in a method for controlling the positioning of a fan-shaped bow jet of a trailing suction dredger in one embodiment of the present application; Figure 3 It is a flow chart for realizing step S104 in a method for controlling the positioning of a fan-shaped bow jet of a trailing suction dredger in one embodiment of the present application; Figure 4 It is a flow chart for realizing step S30 in a method for controlling the positioning of a fan-shaped bow jet of a trailing suction dredger in one embodiment of the present application; Figure 5 It is another implementation flow chart of step S30 in a method for controlling the positioning of a fan-shaped bow jet of a trailing suction dredger in one embodiment of the present application; Figure 6 It is a flowchart for realizing step S40 in a method for controlling the positioning of a fan-shaped bow jet of a trailing suction dredger in one embodiment of the present application; Figure 7 It is a principle block diagram of a fan-shaped bow jet positioning control device of a trailing suction dredger in one embodiment of the present application; Figure 8 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application is further described in detail below in conjunction with the accompanying drawings.

[0025] In one embodiment, if Figure 1 As shown, the present application discloses a method for controlling the positioning of a fan-shaped bow jet of a trailing suction dredger, which specifically comprises the following steps: S10, acquiring sea condition data and distribution characteristic data in the spraying area in real time, the sea condition data at least including wind condition data and water condition data; In this embodiment, key data of the current operating environment are continuously collected, including wind speed, wind direction, wave height, water flow rate, etc. These sea condition data can reflect the dynamic changes of the environment in which the ship is located, so that the system can respond to every change in the marine environment. The acquisition of sea condition data includes using an anemometer to measure the current wind speed, a wind direction sensor to record changes in wind direction, and a water flow sensor to monitor the speed and direction of the water flow. At the same time, underwater imaging sensors or other detection equipment are used to monitor the sediment distribution characteristics in the spraying area. These data provide the necessary basis for subsequent ship attitude control and spraying control strategies, and can ensure that under complex sea conditions, the ship can accurately adjust the operating state to avoid uneven spraying operations or imbalanced ship attitudes due to changes in external conditions, thereby improving spraying efficiency and accuracy.

[0026] S20, analyzing the sea condition data based on the established first response model to generate a corresponding ship attitude control strategy, and executing a corresponding ship attitude control operation according to the ship attitude control strategy; In this embodiment, by inputting the real-time acquired sea condition data into the established first response model, the system can dynamically calculate the optimal attitude control strategy of the ship based on these data. Specifically, the first response model can deduce the attitude adjustment requirements of the ship, including heading angle, tilt angle, thrust distribution, etc., by analyzing factors such as wind speed, wave height, and water flow speed. These attitude control strategies directly affect the stability and spraying accuracy of the ship. For example, in strong winds and high waves, the ship may need to adjust its course to resist the influence of wind and waves, or increase propulsion to maintain the operational stability of the ship. Based on the generated attitude control strategy, the system will perform corresponding control operations and automatically adjust the ship's rudder angle, propeller speed, etc., so as to ensure that the ship remains in the best operating state, avoid attitude imbalance or drift, and ensure the accuracy and safety of the spraying operation.

[0027] S30, based on the established second response model, performing data fusion on the ship attitude control strategy and the distribution characteristic data to generate corresponding fusion data, and generating a corresponding spraying control strategy according to the fusion data; In this embodiment, the second response model is used for data fusion by combining the ship attitude control strategy with the sediment distribution characteristic data of the spraying area. Specifically, the ship attitude control strategy provides the current state and adjustment requirements of the ship, while the sediment distribution characteristic data reflects the real-time distribution of sediment in the spraying area. By fusing these two types of data, the system can generate a comprehensive control strategy to ensure the coordination of the spraying operation and the ship attitude. For example, if the ship's attitude needs to be adjusted to adapt to strong winds and waves, and the sediment in the spraying area is unevenly distributed, data fusion can provide feedback to guide the adjustment of the spraying path and the change of the spraying intensity. This data fusion not only optimizes the stability of the ship, but also effectively avoids sediment accumulation or uneven spraying, improving operation efficiency and spraying accuracy.

[0028] S40. Determine corresponding spraying control parameters according to the spraying control strategy, where the spraying control parameters at least include a range parameter and a power parameter, and perform corresponding spraying control operations according to the spraying control parameters.

[0029] In this embodiment, the generated spraying control strategy will be used to calculate specific spraying control parameters. The spraying range parameter determines the coverage area of ​​the nozzle, while the power parameter affects the intensity of the sediment spraying. These parameters are crucial to the accuracy and effectiveness of the spraying operation. For example, if the ship is in complex sea conditions, the spraying range may need to be adjusted appropriately to cope with the impact of hull swaying or ocean currents. In addition, the spraying intensity should also be adjusted according to the distribution of sediment in the spraying area to ensure that the sediment is evenly distributed during the spraying process and will not deviate from the target area due to strong winds or water currents. By accurately calculating and executing these spraying control parameters, the system can dynamically adjust each parameter in the spraying process to ensure the efficiency and accuracy of the spraying operation and avoid deviations or waste of resources during the spraying process.

[0030] In summary, by analyzing the sea state data based on the first response model and generating the corresponding ship attitude control strategy, it is ensured that the ship can adjust the attitude parameters such as heading, tilt angle and speed in a timely and accurate manner when facing a complex marine environment, so as to maintain stability during the operation process. In addition, the ship attitude control strategy and the sediment distribution characteristic data of the spraying area are fused through the second response model to generate an optimized spraying control strategy. This data fusion process ensures that the spraying path and spraying intensity can be dynamically adjusted according to the ship attitude and real-time sea conditions, avoiding the problem of sediment accumulation or uneven spraying caused by the failure to adjust the spraying parameters in time in the traditional method. Finally, according to the generated spraying control strategy, the method calculates the precise spraying control parameters, such as spraying range and power, and performs the spraying control operation. Under complex sea conditions, this dynamic adjustment capability can not only ensure the uniform spraying of sediment, but also significantly improve the operation efficiency and safety. Through real-time feedback and optimization of the control strategy, the method can continuously maintain the efficiency and accuracy of the operation, fundamentally solving the problems of response lag, cumbersome operation, and uneven spraying in the traditional control method.

[0031] In one embodiment, if Figure 2 As shown, in step S10, the step of acquiring sea condition data and spraying area distribution characteristic data in real time, wherein the sea condition data at least includes wind condition data and water condition data, comprises: S101, obtaining ship location information; In this embodiment, the precise position information of the ship during the operation is obtained in real time through the global positioning system (GPS) or other positioning equipment on the ship. The ship's position information is the basic data for subsequent control operations, ensuring that the ship is in the correct position in the operation area. Especially in the case of changing sea conditions, the precise positioning of the ship is crucial for subsequent spraying control and attitude adjustment. By accurately obtaining the longitude, latitude and heading data of the ship, the system can promptly determine whether the ship deviates from the predetermined path, thereby performing necessary adjustments to ensure that the ship can accurately perform the spraying operation. S102, acquiring distribution characteristic data in the spraying area based on the underwater imaging sensor; In this embodiment, underwater imaging technology is used to obtain the real-time sediment distribution in the spraying area. The underwater imaging sensor can obtain detailed images or depth information of the underwater area through ultrasonic or laser scanning technology. This information can help the system accurately identify the distribution characteristics of sediment in the spraying area, such as the thickness, distribution density and unevenness of the sediment. Based on this data, the system can determine the specific needs of the spraying operation, including whether the range and intensity of the spraying need to be adjusted. The data provided by the underwater imaging sensor can reflect the changes of sediment in the spraying process in real time, thereby improving the efficiency and accuracy of the spraying operation.

[0032] S103, substituting the ship position information and distribution characteristic data into the established demand data identification model to determine the corresponding demand data results, which are used to determine the complexity of the relationship between the ship attitude control strategy and the sediment distribution data; In this embodiment, the real-time collected ship position and sediment distribution data in the spraying area are input into a pre-established model, which generates corresponding demand data results by analyzing the relationship between the two types of data. The demand data results reflect the complexity of the ship's current attitude adjustment requirements and the distribution of sediment in the spraying area. Through model calculation, the system can judge the difficulty and complexity of the ship's attitude control strategy under the current operating environment, and then determine the adjustment strategy to be adopted. This step can help the system understand the relationship between sea conditions and sediment in the operating area, ensure that the ship's attitude control and spraying operations are coordinated with each other, and avoid operation failure or inefficiency due to changes in sea conditions; specifically, the ship's position information provides the precise position of the ship during the operation, including the ship's longitude, latitude and current heading (direction). This information is used to determine the position of the ship in the spraying operation area and its angle and distance relative to the spraying area. In the demand data recognition model, the position of the ship can help the system determine the relative position of the spraying area, thereby determining the priority of the ship's attitude control and the target that needs to be adjusted. For example, whether the ship has deviated from the predetermined spraying path, or whether it needs to adjust its course or speed to adapt to the needs of the spraying area. The distribution characteristic data of the spraying area is obtained through underwater imaging sensors and other equipment. These data include the thickness, density, uniformity, etc. of the sediment. The complexity of the sediment distribution will directly affect the formulation of the spraying strategy. The demand data recognition model evaluates the sediment situation in the spraying area based on these distribution data, helping the system to determine whether there is an uneven distribution or an area that needs special attention in the spraying area. The difficulty of the spraying operation will increase with the increase of the uneven distribution of sediment. For example, when the sediment accumulation is more concentrated, the spraying angle and intensity may need to be adjusted to avoid excessive spraying. The demand data recognition model is built based on machine learning or optimization algorithms. Its purpose is to comprehensively analyze the ship position information and the distribution characteristic data of the spraying area, evaluate the relationship between these data, and output the demand data results. This model will judge the complexity of the current operating environment and the control strategy that needs to be adopted based on real-time input data. Specifically, the demand data recognition model will calculate the complexity between the ship attitude control strategy and the sediment distribution characteristics based on the input ship position information and the sediment distribution in the spraying area. For example, if the ship is at the edge of the spraying area and the sediment is unevenly distributed in the area, the model may output demand data results that require complex posture adjustments; if the ship is at the center of the spraying area and the sediment is evenly distributed, the model may output a simpler control strategy requirement. The generation of demand data results is based on the model's analysis of the relationship between the input data (ship position and sediment distribution data).This output is a data set that reflects the current operational needs, including specific requirements for ship attitude control and spraying operation adjustments. For example, the model may output "the ship needs to adjust its course by 30 degrees to avoid deviating from the spraying path and increase thrust to maintain stability", or "the sediment distribution is relatively uneven, and the spraying intensity needs to be increased and the spraying angle needs to be adjusted to ensure the uniformity of the coverage area"; assuming that the position of the ship on the sea surface is located by the sensor at the edge of a spraying area, and the sediment distribution characteristic data in the area shows that the sediment is unevenly distributed, and the sediment in some areas is more concentrated. The demand data identification model analyzes the relationship between the ship's position information and the sediment distribution, and evaluates whether the ship needs to adjust its course to adapt to the current spraying needs. At the same time, the model also considers the need to increase the spraying intensity in areas with concentrated sediment. Based on these analyses, the model may generate demand data results, indicating that the ship needs to adjust its course by 45 degrees and increase the spraying intensity until the ship enters the optimal position in the spraying area and can spray the sediment evenly.

[0033] S104. Determine a corresponding sea condition sensor element according to the required data result, and obtain corresponding sea condition data based on the sea condition sensor element.

[0034] In this embodiment, the real-time collected data on the ship's position and the sediment distribution in the spraying area are input into a pre-established model, which generates corresponding demand data results by analyzing the relationship between these two types of data. The demand data results reflect the complexity of the ship's current attitude adjustment requirements and the distribution of sediment in the spraying area. Through model calculation, the system can determine the difficulty and complexity of the ship's attitude control strategy under the current operating environment, and then determine the adjustment strategy to be adopted. This step can help the system understand the relationship between sea conditions and sediment in the operating area, ensure that the ship's attitude control and spraying operations are coordinated with each other, and avoid operation failure or inefficiency due to changes in sea conditions.

[0035] In summary, it is possible to ensure that the ship can accurately adjust its operating parameters under dynamic sea conditions. By obtaining the ship's position information and combining it with the distribution characteristic data of the underwater imaging sensor, the sediment distribution status in the spraying area and the real-time position of the ship can be effectively grasped, thereby providing accurate data support for subsequent attitude control and spraying control. Substituting the ship's position information and distribution characteristic data into the established demand data recognition model can determine the complexity of the relationship between the ship's attitude control strategy and the sediment distribution, thereby optimizing the selection of sea condition sensor elements, so that different sea condition sensor elements can obtain accurate sea condition data according to specific needs, such as wind speed, wind direction, water flow status, etc. This process of real-time acquisition and precise matching ensures the accuracy and relevance of sea condition data, thereby improving the stability and efficiency of ship operations.

[0036] In one embodiment, if Figure 3As shown, in step S104, that is, according to the required data result, the corresponding sea state sensor element is determined, and based on the sea state sensor element, the step of obtaining the corresponding sea state data includes: S1041. Match corresponding scenario conditions according to the demand data results; In this embodiment, based on the demand data results, the system will automatically determine the specific sea condition scenario of the current operating environment. The demand data results include information such as the current position of the ship, sea conditions, and sediment distribution in the spraying area. This information is used to analyze the working environment of the ship. Scenario conditions refer to the actual sea conditions of the operation inferred from these data, such as whether there are strong winds, big waves or other complex currents. The core purpose of this step is to identify the specific characteristics of the current sea conditions by analyzing the demand data results, and then determine the appropriate sea condition sensors, so as to ensure that subsequent data collection can accurately reflect the environmental data required for the actual operation of the ship. For example, if the demand data indicates that the wind speed in the area where the ship is operating is high, the system will determine that wind speed data needs to be obtained to further optimize the spraying control strategy.

[0037] S1042, determining a corresponding sea condition sensing element based on the mapping relationship determined based on the scene conditions; In this embodiment, based on the scene conditions, the system will select the appropriate sea condition sensor element according to the established mapping relationship. The mapping relationship is a predefined set of rules for matching different sea conditions (such as wind speed, waves, current speed, etc.) with corresponding sensors. For example, in a strong wind environment, the system will select an anemometer as a sensor to obtain wind speed data; in an operating area with strong water flow, the system will select a water flow sensor to monitor the water flow state. The purpose of this step is to ensure that the collected sea condition data can fully and accurately reflect the current operating environment by accurately matching the scene conditions with the sensors, thereby optimizing the adjustment of the ship's attitude control and spraying strategy.

[0038] S1043. If the sea condition sensing element is an anemometer, obtaining wind speed data; In this embodiment, when the mapping relationship determines that an anemometer is needed to obtain sea condition data, the system will enable the anemometer for real-time measurement to obtain the current wind speed data. The anemometer is a device used to measure the speed of air flow, and its data is crucial to the ship's heading adjustment, the accuracy of spraying operations, and the stability of the ship. Wind speed data can help the system determine the impact of wind on the ship's attitude, especially in severe sea conditions. Changes in wind speed may cause the ship to deviate from the predetermined position, thereby affecting the effect of the spraying operation. Therefore, accurate wind speed data can guide the ship's control system to adjust the thrust distribution and rudder angle to ensure operation accuracy.

[0039] S1044. If the sea condition sensing element is a wind direction sensor, obtain wind direction data; In this embodiment, when the mapping relationship determines that the wind direction sensor is the required sea condition sensing element, the system will start the wind direction sensor to obtain wind direction data. The wind direction sensor is used to accurately measure the direction of the wind. Especially in ship attitude control, wind direction is a very important factor, which directly affects the ship's heading adjustment. In the spraying operation, the wind direction data can help the system calculate the interference of the wind on the ship's heading, and adjust the ship's attitude accordingly, so that the spraying operation is kept in the best state and the wind force is prevented from causing the sediment spraying to deviate from the target area.

[0040] S1045. If the sea condition sensing element is a water flow sensor, obtain water flow state data; In this embodiment, if it is determined in the mapping relationship that a water flow sensor is needed to monitor the water flow state, the system will enable the water flow sensor to collect the current water flow speed and direction data. The water flow sensor can monitor the flow of water in real time, especially in complex waters, where changes in water flow will affect the ship's posture and spraying effect. The speed and direction of the water flow determine the possible drift direction of the ship. Timely acquisition of water flow state data enables the control system to automatically adjust its posture when the ship drifts or stability is affected, avoiding uneven spraying or errors due to interference from the water flow, thereby ensuring operational efficiency and safety.

[0041] S1046: If the sea condition sensing element is a wave sensor, obtain wave state data.

[0042] In this embodiment, when the mapping relationship determines that the wave sensor is the required sea condition sensing element, the system will activate the wave sensor and obtain the wave status data in real time. The wave sensor is mainly used to measure the height, period, direction and other parameters of the sea surface waves, which are crucial to the stability of the ship and the spraying accuracy. The size and direction of the waves directly affect the attitude of the ship, especially in large waves or complex sea conditions, the stability of the ship may be significantly affected, thereby affecting the uniformity during the spraying process. By acquiring the wave status data in real time, the system can make real-time adjustments according to the changes in the waves, such as increasing the thrust to maintain the stability of the ship, or adjusting the spraying angle and frequency to ensure that the mud and sand are accurately sprayed to the target area.

[0043] Preferably, the corresponding sea condition sensing element is determined according to the required data results to ensure that the ship operation can be accurately and adaptively adjusted according to the real-time environmental conditions. This process is crucial for optimizing the spraying operation and improving the stability of the ship operation. Specifically, the reasons for doing so include the following: First, ensure accurate collection of data that matches the environment. Sea condition data (such as wind speed, wind direction, water current, waves, etc.) directly affects the ship's attitude control and spraying operations. Under different sea conditions, different sensor elements can provide specific environmental data, which helps the system to accurately adjust the ship's operations. By determining the sensor element based on the required data results, the system can select the most suitable sensor according to the specific operating environment and task requirements. For example, when the wind speed is high or the wind direction changes frequently, the use of an anemometer or wind direction sensor can provide accurate wind speed and wind direction data, which helps to dynamically adjust the ship's heading and avoid the impact of wind on spraying operations. In areas with strong water flow, the use of water flow sensors can accurately capture the speed and direction of the water flow, help the ship remain stable, and ensure spraying accuracy.

[0044] Second, improve the adaptability and flexibility of the system. Different operating areas will face different sea conditions. The demand data results include an assessment of the current operating environment, which can help the system dynamically identify the most suitable sensor. For example, some areas may be more affected by waves, while other areas may be mainly affected by water currents. If the system can intelligently select the corresponding sensor elements (such as wave sensors or water flow sensors) based on the demand data results, it can respond more flexibly to different changes in sea conditions and ensure that the most appropriate real-time data can be obtained under all environmental conditions. This mechanism of intelligent selection of sensor elements improves the system's adaptability and avoids invalid sensor data collection or the use of inappropriate equipment.

[0045] Third, improve the accuracy of data and the precision of operations. The design and working principle of each sea condition sensor element are targeted at specific environmental conditions and can provide more accurate data. For example, anemometers are specially designed to measure wind speed and can provide more accurate wind speed data than other devices; water flow sensors can efficiently capture changes in water flow with higher accuracy than other sensors. By selecting appropriate sensors based on the required data results, the system can ensure that the collected sea condition data is more accurate, making subsequent ship attitude adjustments, spraying control, and operation optimization more accurate. The accuracy of this process directly affects the operation results and avoids uneven or unstable operations due to data errors or improperly selected sensors.

[0046] Fourth, optimize operational efficiency and safety. Sea conditions are complex and changeable. Ships may face multiple influences such as wind, waves, and currents during operations. Choosing appropriate sensors can help ships quickly respond to changes in sea conditions and make appropriate adjustments. By determining the corresponding sea condition sensing elements based on the required data results, the system can capture changes in the marine environment in a timely and accurate manner, thereby responding quickly. This can not only improve the uniformity of spraying and the stability of the ship, but also effectively prevent potential risks caused by changes in sea conditions and ensure operational safety. For example, in an environment with high wind speeds, timely collection of wind speed data and adjustment of the ship's attitude can avoid the impact of wind on the hull, ensure the stability of the ship, reduce tilting and drifting, and improve operational efficiency.

[0047] Fifth, reduce unnecessary sensor usage and costs. Each sea condition sensor has its specific role and application range. Reasonable selection of sensors based on the required data results can avoid the use of irrelevant or redundant sensors when not needed, saving unnecessary hardware costs. Through intelligent judgment and matching of scene conditions, the system can optimize the use of equipment and reduce energy and resource waste. For example, in an environment with calmer waves, there is no need to enable wave sensors. Instead, enable current sensors or anemometers, which can effectively reduce the complexity and cost of the system.

[0048] Assuming that the ship is operating in an area with strong water flow, the demand data results show that the change in water flow has the greatest impact on the ship's operation. Based on this result, the system will select a water flow sensor to monitor the speed and direction of the water flow in real time. The water flow data helps the ship adjust the propulsion and heading to maintain the accuracy of the operation. If the system determines that the wind speed in the operation area has a greater impact on the operation, it will switch to anemometers and wind direction sensors to obtain accurate wind speed and direction data to ensure the accuracy of the spraying control strategy. In this process, the system accurately selects sensors based on the demand data results to ensure the efficiency and safety of the operation.

[0049] In summary, it is possible to intelligently match different scenario conditions according to the required data results, and then select suitable sensors to obtain relevant sea condition data. This intelligent matching mechanism can flexibly adjust the selection of sensor elements according to the specific working environment, improve the pertinence and accuracy of data acquisition, and avoid invalid or erroneous data collection caused by improper sensor selection in traditional methods, thereby ensuring the accuracy and response speed of ship operations, especially in complex sea conditions, and can quickly obtain accurate wind speed, wind direction, water flow and wave state data, providing strong data support for subsequent ship attitude and spraying control strategies.

[0050] In one embodiment, if Figure 4As shown, in step S30, that is, based on the established second response model, the ship attitude control strategy and the distribution characteristic data are fused to generate corresponding fused data, including: S3011. Select key data in the ship attitude control strategy; In this embodiment, parameters and data that are critical to the accuracy and stability of the operation are extracted from the ship's attitude control strategy. These key data usually include the ship's heading, tilt angle, speed, propulsion, rudder angle, etc. These data are crucial for adjusting the ship's attitude and maintaining stability, especially in complex sea conditions, where the accuracy of the ship's attitude control strategy directly affects the effect of the spraying operation. For example, in strong winds or high waves, the ship may need to adjust its heading and thrust to maintain stability, and the selection of these key data will provide the necessary basis for subsequent dynamic adjustments. By accurately selecting and analyzing these key data, the system can determine the operating status of the ship in real time and make the most appropriate attitude adjustment, thereby ensuring accuracy and safety during the operation.

[0051] S3012. Determine a corresponding data fusion algorithm according to the required data results; In this embodiment, based on the previously generated demand data results, the system selects a suitable data fusion algorithm to better integrate and analyze the ship attitude control data and the spraying area distribution characteristic data. The demand data results include the demand for ship attitude control and the distribution of sediment in the spraying area. These data need to be fused through a specific algorithm to generate a comprehensive control output. Specifically, the system can select different data fusion algorithms according to the complexity of the operating environment, such as Kalman filtering, particle filtering or weighted averaging. If the operating environment is more complex, the data relationship may be more nonlinear, and nonlinear algorithms such as particle filtering will be selected; if the data relationship is relatively simple, linear algorithms such as Kalman filtering may be more efficient. Depending on the different demand data results, the system can flexibly select the most appropriate algorithm to ensure the accuracy and efficiency of the data fusion process.

[0052] S3013. Based on the data fusion algorithm, perform data fusion on the key data and the distribution characteristic data to generate corresponding fused data.

[0053] In this embodiment, the step of fusing key data and distribution characteristic data based on a data fusion algorithm refers to using a previously determined fusion algorithm to combine key data in the ship's attitude control strategy with the sediment distribution characteristic data in the spraying area to generate a comprehensive fused data. The data fusion process integrates the ship's attitude adjustment requirements with the real-time sediment distribution in the spraying area to provide a global view, ensuring that the ship's attitude adjustment and spraying operations can be optimized based on real-time data. For example, if the ship's heading adjustment does not match the sediment distribution characteristics of the spraying area, a new adjustment strategy will be generated after data fusion to ensure that the spraying angle, spraying range, etc. can adapt to the needs of the current operation. This fused data can provide precise input for subsequent spraying control strategies, ensuring the efficiency and accuracy of spraying operations under different sea conditions and sediment distribution conditions; The core of the data fusion process of key data and distribution characteristic data based on the data fusion algorithm is to integrate the key data in the ship attitude control strategy with the sediment distribution characteristic data in the spraying area to generate a unified and accurate fusion data. The working principle of this process relies on the selected fusion algorithm (such as Kalman filter, particle filter or weighted average method, etc.) to optimize and coordinate the inputs from different data sources to ensure that the final output data can reflect the complexity of the operating environment and provide a reliable basis for control decisions. Specifically, first, the ship attitude control data (such as heading, speed, thrust, rudder angle, etc.) and the sediment distribution data in the spraying area (such as sediment thickness, distribution density, uniformity, etc.) are input into the fusion algorithm. These data come from different sources and may also be in different forms, so they need to be converted into standardized data that can be compared and calculated with each other through algorithms. The algorithm analyzes the correlation and influence of these two types of data and merges them according to the preset weights or prediction models. For example, in this scenario, the Kalman filter will optimize the current data based on the estimated value of the current attitude of the ship and the distribution of the spraying area, using the estimated results of the previous moment, so as to generate more accurate fusion data. If there is a certain time delay between the ship's attitude data and the sediment distribution data, the particle filter can sample in multiple possible states through the Monte Carlo method, thereby effectively estimating the current optimal state. Through this process, the fused data can better represent the actual situation of the ship's attitude changes and sediment distribution during operation, thereby guiding the ship's attitude adjustment and spraying operations. The fused data not only improves the accuracy of the control strategy, but also optimizes the ship's operating parameters in real time under changing sea conditions to ensure the uniformity and stability of the spraying operation. For example, if the ship's attitude control data does not match the sediment distribution in the spraying area, data fusion will automatically adjust the spraying path, spraying intensity and spraying angle to ensure the best operation effect.

[0054] In summary, accurate data fusion analysis can be used to comprehensively consider the ship attitude control strategy and the real-time characteristics of the sediment distribution in the spraying area, thereby ensuring the optimal control of the spraying operation. Data fusion can effectively eliminate the limitations of a single data source, combine the characteristic information of ship attitude adjustment and sediment distribution, and generate a more comprehensive and accurate fusion data, so that the control strategy is more in line with actual operation needs. Through this fusion method, the relationship between the ship attitude control strategy and the sediment distribution in the spraying area is effectively modeled and optimized, which greatly improves the control accuracy and spraying effect during the ship operation process and reduces unnecessary errors and deviations.

[0055] In one embodiment, if Figure 5 As shown, in step S30, i.e., the step of generating a corresponding spraying control strategy according to the fusion data, it includes: S3021, checking whether the ship attitude after executing the ship attitude control operation maintains the optimal attitude, if not, re-determining the ship attitude control strategy to execute the ship attitude control operation until the ship attitude maintains the optimal attitude; In this embodiment, after the ship performs the attitude control operation, the system will check whether the current attitude state of the ship meets the preset "optimal attitude" standard through real-time feedback data (such as the ship's tilt angle, heading, ship speed, etc.). The optimal attitude refers to the most stable and most suitable heading and angle required by the ship during the spraying operation, which helps to improve the operation accuracy and avoid waste. If the inspection results show that the ship's attitude has not reached the optimal state, the system will automatically recalculate the attitude control strategy and adjust the ship's heading, rudder angle or thrust and other control parameters until the ship reaches the ideal operating attitude. For example, in strong winds or high waves, the ship may tilt to a certain extent due to the influence of the waves. The system will make timely adjustments to ensure the stable operation of the ship and avoid uneven spraying or deviation from the target area due to attitude imbalance.

[0056] S3022: If yes, determine the spraying control target and the control range of the spraying control target according to the fused data. The spraying control target includes spraying angle, spraying radius, spraying intensity and spraying frequency. In this embodiment, if the ship's posture has maintained the optimal posture, the system will determine the spraying control target based on the fusion data generated in the previous step. The spraying control target includes parameters such as spraying angle, spraying radius, spraying intensity and spraying frequency, which directly affect the effect of the spraying operation. The fusion data contains the integrated information of the ship's posture and the distribution of sediment in the spraying area. Through this data, the system can determine the optimal spraying angle and radius. For example, if the ship is at the edge of the spraying area and the sediment is unevenly distributed, the system may adjust the spraying angle to cover a wider area. The spraying intensity and frequency are set according to the density of the sediment distribution and the requirements of the working environment to ensure the uniformity of the spraying. By setting the spraying target reasonably, the system can ensure that the sediment is accurately sprayed to the predetermined area to avoid waste and unevenness.

[0057] S3023. Determine the error tolerance range corresponding to the control range according to the demand data result; In this embodiment, after the system generates the spraying control target according to the demand data results, it will further analyze the error tolerance range of the control interval. The demand data results usually provide ideal values ​​of target parameters such as spraying angle, spraying radius, spraying intensity, and restrictions on the operating environment. The system will set an error tolerance range for each control target based on these data. This range defines the acceptable error range for the spraying operation. For example, the spraying angle may allow a certain deviation (such as ±2 degrees), and the spraying intensity and frequency will also have a certain error tolerance (such as ±5%). The determination of the error tolerance range ensures the flexibility and fault tolerance of the spraying operation, so that even in complex sea conditions, the system can still effectively adjust the spraying parameters to ensure the operation effect.

[0058] Specifically, the system will set a tolerance for each control target based on the spraying targets provided in the demand data results, such as spraying angle, spraying radius, spraying intensity and spraying frequency, combined with the characteristics of the current operating environment (such as sea conditions, wind speed, wave height, water flow, etc.). This tolerance reflects the maximum deviation that the spraying parameters can accept during the actual operation. For example, the spraying angle may need to be kept within a certain range, and a deviation of ±2 degrees is usually allowed. This is mainly because the ship may tilt or sway to a certain extent under the influence of waves or wind. Therefore, the control system needs to set a reasonable angle error range so that the accuracy of the spraying operation can be maintained when the ship's attitude changes. The system will set a tolerance for each control target based on the spraying targets provided in the demand data results, such as spraying angle, spraying radius, spraying intensity and spraying frequency, combined with the characteristics of the current operating environment (such as sea conditions, wind speed, wave height, water flow, etc.). This tolerance reflects the maximum deviation that the spraying parameters can accept during the actual operation. For example, the spraying angle may need to be kept within a certain range, and a deviation of ±2 degrees is usually allowed. This is mainly because the ship may tilt or sway to a certain extent under the influence of waves or wind. Therefore, the control system needs to set a reasonable angle error range so that the accuracy of the spraying operation can be maintained when the ship's attitude changes. In addition, the determination of the error tolerance range also takes into account the ship's control accuracy and real-time feedback capabilities. In some complex sea conditions, the ship may not be able to spray completely according to the predetermined trajectory. At this time, the control system will adjust the spraying parameters in real time according to the actual feedback data (such as ship attitude, spraying effect, etc.) to ensure that the operation target is achieved within the error range. For example, when the ship's attitude fluctuates in a small range, the system can automatically adjust the spraying angle and intensity to ensure the uniformity of the spraying area. Finally, the system will set the error tolerance range according to the measurement accuracy of the equipment. The adjustment of the spraying parameters depends on the accuracy of the sensor and controller, and the accuracy of the equipment itself has a certain tolerance range. Therefore, when setting the error tolerance range, the technical performance of the equipment is also an important reference factor. If the equipment's spraying control accuracy is high, the allowable error range can be relatively small; conversely, if the equipment's accuracy is low, a larger error tolerance range needs to be set to ensure that there is sufficient flexibility during operation to cope with fluctuations in equipment and sea conditions.

[0059] S3024. Package the spraying control target, control interval and error tolerance interval to form a corresponding spraying control strategy.

[0060] In this embodiment, after the above steps, the system will package the spraying control target, control interval and error tolerance interval into a complete spraying control strategy. This spraying control strategy includes all necessary parameters and conditions to ensure that the execution of the spraying operation meets the predetermined goals. For example, the spraying control target may include: a spraying angle of 30 degrees, a spraying radius of 50 meters, a spraying intensity of 10 cubic meters per minute, and a spraying frequency of 5 times per minute. The control interval defines the allowable error range of these parameters. The error tolerance interval clarifies the maximum deviation range of the spraying parameters that may occur in actual operation. By packaging this information, the system can integrate all parameters and constraints into an overall strategy to ensure that the operations of each link in the spraying operation process can be closely coordinated and ultimately achieve the best operation results.

[0061] In summary, by checking whether the ship's posture maintains the optimal posture, potential posture deviations can be discovered and corrected in a timely manner to ensure that the ship is always in the optimal operating posture. If the ship's posture does not maintain the optimal state, the system can automatically recalculate and adjust the posture control strategy until the ship returns to the ideal state to ensure the stability and accuracy of the spraying operation. Through this process, each operation cycle of the ship can be optimized based on real-time feedback, thereby improving the reliability and operation efficiency of spraying control. At the same time, by setting the spraying control target and determining the control range based on the fused data, the error range during the operation process is effectively limited, ensuring the stability and uniformity of the spraying operation under different environmental conditions, and greatly improving the safety and operability of the construction process.

[0062] In one embodiment, if Figure 6 As shown, in step S40, i.e., the step of determining the corresponding spraying control parameters according to the spraying control strategy, the steps include: S401, determining a spraying range according to a control range and an allowable error range of a spraying angle, and a control range and an allowable error range of a spraying radius; In this embodiment, based on the control interval and error tolerance interval of the spraying angle, as well as the control interval and error tolerance interval of the spraying radius, the system will calculate a spraying range suitable for the current operating environment. The spraying angle control interval defines the upper and lower limits of the spraying angle, while the spraying radius control interval limits the maximum range of the spraying. In actual operation, these two intervals will be combined with the error tolerance interval, which is used to consider the impact of the external environment and equipment accuracy on the spraying effect. For example, the spraying angle may have an error range of ±2 degrees, and the control interval of the spraying radius may be set to 30 to 50 meters, with an allowable error of ±5 meters. The system calculates the actual spraying range based on these restrictions to ensure that the spraying operation can cover the predetermined area, while avoiding spraying deviations caused by changes in the ship's attitude or sea conditions, thereby ensuring operation accuracy and uniformity.

[0063] S402, judging whether to modify the spraying range according to the overlap degree generated after comparing the spraying range and the spraying area, and if so, pushing an interactive window for modifying the spraying range, and if not, determining the corresponding range parameters according to the spraying range; In this embodiment, after the system calculates the spraying range, it compares it with the actual spraying area to evaluate the overlap between the spraying range and the target spraying area. If the calculated spraying range has a low overlap with the predetermined spraying area, it means that the actual spraying area fails to cover the target area, and the system will determine that the spraying range needs to be adjusted. At this time, the system will push an interactive window, allowing the operator to manually or automatically adjust the spraying range to ensure that the spraying operation can accurately cover the target area. If the overlap is high, it means that the spraying range is as expected, and the system will further calculate the range parameters based on the current spraying range. These parameters include the actual radius and angle of the spraying, thereby optimizing subsequent spraying operations. This process can ensure the accuracy of the spraying operation, and can also quickly adjust the operating range under dynamic sea conditions to prevent the spraying from deviating from the target area.

[0064] S403: Determine the power parameter according to the control interval and the allowable error interval of the spraying intensity, and the control interval and the allowable error interval of the spraying frequency.

[0065] In this embodiment, the system determines the power parameters of the spraying according to the control interval of the spraying intensity and the control interval of the spraying frequency. The spraying intensity control interval defines the amount of sediment delivered per unit time, while the spraying frequency control interval limits the frequency of the spraying operation. Combined with the error tolerance interval, these control intervals provide flexible adjustment space for the spraying operation. The error tolerance intervals of the spraying intensity and the spraying frequency are usually set based on the variability of the equipment performance and the operating environment. For example, the error tolerance interval of the spraying intensity may be set to ±5%, while the tolerance of the spraying frequency may be ±10%. Based on these parameters, the system will calculate the appropriate power parameters, which directly affect the working efficiency and energy consumption of the spraying system, ensuring that the equipment will not be overloaded while ensuring the spraying effect, avoiding energy waste or equipment damage. By accurately calculating the power parameters, the system can ensure the stability and efficiency of the spraying operation, especially in complex or changeable sea conditions, and can automatically adjust the spraying intensity and frequency to adapt to different work requirements.

[0066] In summary, the spraying range and power parameters can be accurately determined by combining the control intervals and error tolerance intervals such as spraying angle, spraying radius, and spraying intensity. By comparing with the spraying area, the overlap of the spraying range is determined, and dynamic adjustments are made according to the actual situation to ensure that the spraying range accurately covers the target area. If the overlap is insufficient, the system will prompt the operator to modify the spraying range through an interactive window. This feedback mechanism improves the flexibility and adaptability of the spraying control process and avoids the problem of excessive or small spraying deviations in traditional methods. At the same time, the power parameters are determined based on the control interval and error range of the spraying intensity and spraying frequency to ensure energy efficiency optimization of the spraying operation. This dynamic adjustment capability can maintain operating efficiency and accuracy under different sea conditions, reduce energy waste, and further improve the overall effect of the spraying operation.

[0067] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0068] In one embodiment, a fan-shaped bow jet positioning control device for a trailing suction hopper dredger is provided, and the fan-shaped bow jet positioning control device for a trailing suction hopper dredger corresponds one-to-one to a fan-shaped bow jet positioning control method for a trailing suction hopper dredger in the above embodiment. The fan-shaped bow jet positioning control device for a trailing suction hopper dredger includes an acquisition module, a first analysis module, a second analysis module, and a determination module. Each functional module is described in detail as follows: An acquisition module, used for acquiring sea condition data and distribution characteristic data in the spraying area in real time, wherein the sea condition data at least includes wind condition data and water condition data; A first analysis module is used to analyze the sea condition data based on the established first response model to generate a corresponding ship attitude control strategy, and perform a corresponding ship attitude control operation according to the ship attitude control strategy; A second analysis module is used to perform data fusion on the ship attitude control strategy and the distribution characteristic data based on the established second response model to generate corresponding fusion data, and generate a corresponding spraying control strategy according to the fusion data; The determination module is used to determine corresponding spraying control parameters according to the spraying control strategy, wherein the spraying control parameters at least include a range parameter and a power parameter, and perform corresponding spraying control operations according to the spraying control parameters.

[0069] Optionally, the acquisition module includes: A first acquisition unit, used to acquire ship position information; A second acquisition unit is used to acquire distribution characteristic data in the spraying area based on an underwater imaging sensor; A first determination unit is used to substitute the ship position information and the distribution characteristic data into the established demand data recognition model to determine the corresponding demand data result, and the demand data result is used to determine the complexity of the relationship between the ship attitude control strategy and the sediment distribution data; A second determination unit is used to determine a corresponding sea condition sensor element according to the required data result, and obtain corresponding sea condition data based on the sea condition sensor element; Optionally, the second determining unit includes: A matching subunit, used to match corresponding scenario conditions according to the demand data result; A determination subunit, used to determine a good mapping relationship based on the scene conditions and determine a corresponding sea condition sensing element; A first acquisition subunit, configured to acquire wind speed data if the sea condition sensing element is an anemometer; A second acquisition subunit is used to acquire wind direction data if the sea condition sensing element is a wind direction sensor; A third acquisition subunit is used to acquire water flow state data if the sea condition sensing element is a water flow sensor; a fourth acquisition subunit, configured to acquire wave state data if the sea state sensing element is a wave sensor; Optionally, the second analysis module includes: A selection unit, used for selecting key data in the ship attitude control strategy; A third determining unit, used to determine a corresponding data fusion algorithm according to the required data result; A generating unit, configured to perform data fusion on the key data and the distribution characteristic data based on the data fusion algorithm to generate corresponding fused data; Optionally, the second analysis module further includes: A checking unit, used to check whether the ship attitude after executing the ship attitude control operation maintains an optimal attitude, and if not, re-determine the ship attitude control strategy to perform the ship attitude control operation until the ship attitude maintains an optimal attitude; a fourth determining unit, configured to determine, if yes, a spraying control target according to the fused data, and determine a control interval of the spraying control target, wherein the spraying control target includes a spraying angle, a spraying radius, a spraying intensity, and a spraying frequency; A fifth determining unit, configured to determine an error tolerance interval corresponding to the control interval according to the demand data result; A packaging unit, used for packaging the spraying control target, the control interval and the error allowable interval to form a corresponding spraying control strategy; Optionally, the determining module includes: a sixth determining unit, configured to determine a spraying range according to the control interval and the error tolerance interval of the spraying angle, and the control interval and the error tolerance interval of the spraying radius; a judgment unit, configured to judge whether to modify the spraying range according to the overlap degree generated after comparing the spraying range with the spraying area, and if so, push an interactive window for modifying the spraying range; if not, determine a corresponding range parameter according to the spraying range; The seventh determination unit is used to determine the power parameter according to the control interval and the error tolerance interval of the spraying intensity, and the control interval and the error tolerance interval of the spraying frequency.

[0070] The specific definition of a fan-shaped bow jet positioning control device for a trailing suction hopper dredger can be found in the above definition of a fan-shaped bow jet positioning control method for a trailing suction hopper dredger, which will not be repeated here. Each module in the above-mentioned fan-shaped bow jet positioning control device for a trailing suction hopper dredger can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0071] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a fan-shaped bow spray positioning control method of a trailing suction dredger is implemented.

[0072] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: S10, acquiring sea condition data and distribution characteristic data in the spraying area in real time, the sea condition data at least including wind condition data and water condition data; S20, analyzing the sea condition data based on the established first response model to generate a corresponding ship attitude control strategy, and executing a corresponding ship attitude control operation according to the ship attitude control strategy; S30, based on the established second response model, performing data fusion on the ship attitude control strategy and the distribution characteristic data to generate corresponding fusion data, and generating a corresponding spraying control strategy according to the fusion data; S40. Determine corresponding spraying control parameters according to the spraying control strategy, where the spraying control parameters at least include a range parameter and a power parameter, and perform corresponding spraying control operations according to the spraying control parameters.

[0073] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: S10, acquiring sea condition data and distribution characteristic data in the spraying area in real time, the sea condition data at least including wind condition data and water condition data; S20, analyzing the sea condition data based on the established first response model to generate a corresponding ship attitude control strategy, and executing a corresponding ship attitude control operation according to the ship attitude control strategy; S30, based on the established second response model, performing data fusion on the ship attitude control strategy and the distribution characteristic data to generate corresponding fusion data, and generating a corresponding spraying control strategy according to the fusion data; S40. Determine corresponding spraying control parameters according to the spraying control strategy, where the spraying control parameters at least include a range parameter and a power parameter, and perform corresponding spraying control operations according to the spraying control parameters.

[0074] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0075] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0076] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for controlling the positioning of a fan-shaped bow jet of a trailing suction hopper dredger, characterized in that: The fan-shaped bow jet positioning control method of a trailing suction dredger comprises: Acquire sea condition data and distribution characteristic data in the spraying area in real time, wherein the sea condition data at least includes wind condition data and water condition data; Based on the established first response model, the sea condition data is analyzed to generate a corresponding ship attitude control strategy, and a corresponding ship attitude control operation is performed according to the ship attitude control strategy; Based on the established second response model, data fusion is performed on the ship attitude control strategy and the distribution characteristic data to generate corresponding fused data, and a corresponding spraying control strategy is generated according to the fused data; According to the spraying control strategy, corresponding spraying control parameters are determined, wherein the spraying control parameters at least include a range parameter and a power parameter, and corresponding spraying control operations are performed according to the spraying control parameters.

2. A method for controlling the positioning of a fan-shaped bow jet of a trailing suction hopper dredger according to claim 1, characterized in that: The step of acquiring sea condition data and spraying area distribution characteristic data in real time, wherein the sea condition data at least includes wind condition data and water condition data, comprises: Obtain ship position information; Based on underwater imaging sensors, the distribution characteristic data in the spraying area is obtained; Substituting the ship position information and the distribution characteristic data into the established demand data identification model to determine the corresponding demand data results, wherein the demand data results are used to determine the complexity of the relationship between the ship attitude control strategy and the sediment distribution data; According to the required data result, the corresponding sea condition sensor element is determined, and based on the sea condition sensor element, the corresponding sea condition data is acquired.

3. A method for controlling the positioning of a fan-shaped bow jet of a trailing suction hopper dredger according to claim 2, characterized in that: The step of determining the corresponding sea condition sensor element according to the required data result, and acquiring the corresponding sea condition data based on the sea condition sensor element comprises: According to the demand data results, matching corresponding scenario conditions; Determine the corresponding sea condition sensing element based on the mapping relationship determined by the scene conditions; If the sea condition sensing element is an anemometer, wind speed data is obtained; If the sea condition sensing element is a wind direction sensor, obtaining wind direction data; If the sea condition sensing element is a water flow sensor, obtaining water flow state data; If the sea condition sensing element is a wave sensor, wave state data is obtained.

4. A method for controlling the positioning of a fan-shaped bow jet of a trailing suction hopper dredger according to claim 2, characterized in that: The step of fusing the ship attitude control strategy and the distribution characteristic data based on the established second response model to generate corresponding fused data includes: Selecting key data in the ship attitude control strategy; Determine a corresponding data fusion algorithm according to the required data result; Based on the data fusion algorithm, the key data and the distribution characteristic data are fused to generate corresponding fused data.

5. A method for controlling the positioning of a fan-shaped bow jet of a trailing suction hopper dredger according to claim 2, characterized in that: The step of generating a corresponding spraying control strategy according to the fused data includes: Checking whether the ship attitude after executing the ship attitude control operation maintains the optimal attitude, if not, re-determining the ship attitude control strategy to perform the ship attitude control operation until the ship attitude maintains the optimal attitude; If yes, determine a spraying control target according to the fused data, and determine a control range of the spraying control target, wherein the spraying control target includes a spraying angle, a spraying radius, a spraying intensity and a spraying frequency; Determine the error tolerance interval corresponding to the control interval according to the demand data result; The spraying control target, the control interval and the error tolerance interval are packaged to form a corresponding spraying control strategy.

6. A method for controlling the positioning of a fan-shaped bow jet of a trailing suction hopper dredger according to claim 5, characterized in that: The step of determining corresponding spraying control parameters according to the spraying control strategy includes: Determine a spraying range according to the control range and the allowable error range of the spraying angle, and the control range and the allowable error range of the spraying radius; According to the overlap degree generated after comparing the spraying range with the spraying area, determine whether to modify the spraying range, if yes, push an interactive window for modifying the spraying range, if no, determine the corresponding range parameters according to the spraying range; The power parameter is determined according to the control interval and the error tolerance interval of the spraying intensity, and the control interval and the error tolerance interval of the spraying frequency.

7. A fan-shaped bow jet positioning control device for a trailing suction dredger, characterized in that: The fan-shaped bow jet positioning control device of a trailing suction dredger comprises: An acquisition module, used for acquiring sea condition data and distribution characteristic data in the spraying area in real time, wherein the sea condition data at least includes wind condition data and water condition data; A first analysis module is used to analyze the sea condition data based on the established first response model to generate a corresponding ship attitude control strategy, and perform a corresponding ship attitude control operation according to the ship attitude control strategy; A second analysis module is used to perform data fusion on the ship attitude control strategy and the distribution characteristic data based on the established second response model to generate corresponding fusion data, and generate a corresponding spraying control strategy according to the fusion data; The determination module is used to determine corresponding spraying control parameters according to the spraying control strategy, wherein the spraying control parameters at least include a range parameter and a power parameter, and perform corresponding spraying control operations according to the spraying control parameters.

8. The fan-shaped bow jet positioning control device of a trailing suction hopper dredger according to claim 7, characterized in that: The acquisition module comprises: A first acquisition unit, used to acquire ship position information; A second acquisition unit is used to acquire distribution characteristic data in the spraying area based on an underwater imaging sensor; A first determination unit is used to substitute the ship position information and the distribution characteristic data into the established demand data recognition model to determine the corresponding demand data result, and the demand data result is used to determine the complexity of the relationship between the ship attitude control strategy and the sediment distribution data; A second determination unit is used to determine a corresponding sea condition sensor element according to the required data result, and obtain corresponding sea condition data based on the sea condition sensor element; The second determining unit includes: A matching subunit, used to match corresponding scenario conditions according to the demand data result; A determination subunit, used to determine a good mapping relationship based on the scene conditions and determine a corresponding sea condition sensing element; A first acquisition subunit, configured to acquire wind speed data if the sea condition sensing element is an anemometer; A second acquisition subunit is used to acquire wind direction data if the sea condition sensing element is a wind direction sensor; A third acquisition subunit is used to acquire water flow state data if the sea condition sensing element is a water flow sensor; a fourth acquisition subunit, configured to acquire wave state data if the sea state sensing element is a wave sensor; The second analysis module comprises: A selection unit, used for selecting key data in the ship attitude control strategy; A third determining unit, used to determine a corresponding data fusion algorithm according to the required data result; A generating unit, configured to perform data fusion on the key data and the distribution characteristic data based on the data fusion algorithm to generate corresponding fused data; The second analysis module also includes: A checking unit, used to check whether the ship attitude after executing the ship attitude control operation maintains an optimal attitude, and if not, re-determine the ship attitude control strategy to perform the ship attitude control operation until the ship attitude maintains an optimal attitude; a fourth determining unit, configured to determine, if yes, a spraying control target according to the fused data, and determine a control interval of the spraying control target, wherein the spraying control target includes a spraying angle, a spraying radius, a spraying intensity, and a spraying frequency; A fifth determining unit, configured to determine an error tolerance interval corresponding to the control interval according to the demand data result; A packaging unit, used for packaging the spraying control target, the control interval and the error allowable interval to form a corresponding spraying control strategy; The determination module comprises: a sixth determining unit, configured to determine a spraying range according to the control interval and the error tolerance interval of the spraying angle, and the control interval and the error tolerance interval of the spraying radius; a judgment unit, configured to judge whether to modify the spraying range according to the overlap degree generated after comparing the spraying range with the spraying area, and if so, push an interactive window for modifying the spraying range; if not, determine a corresponding range parameter according to the spraying range; The seventh determination unit is used to determine the power parameter according to the control interval and the error tolerance interval of the spraying intensity, and the control interval and the error tolerance interval of the spraying frequency.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the positioning control method of the fan-shaped bow jet of a trailing suction hopper dredger as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the positioning control method of the fan-shaped bow jet of a trailing suction hopper dredger as claimed in any one of claims 1 to 6 are implemented.

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