An Automatic Buoy Deployment and Recovery Method, System and Equipment

Abstract

The present application relates to a method, system and device for automatic buoy deployment and recovery. The method includes generating a buoy deployment plan and planning a buoy recovery path. The generation of the buoy deployment plan includes obtaining buoy parameters and sea area information, constructing a sea area image of the target sea area based on the sea area information of the target sea area, meshing the sea area image, taking the center of each grid as an alternative buoy deployment point, and from one end of the target sea area to the other end, with the goal of minimizing the overlapping area of the monitoring areas of adjacent buoy models, successively deploying buoy models at the alternative deployment points to generate several alternative deployment plans, and combining the monitoring coverage rate, total deployment difficulty coefficient and total stability coefficient of each alternative deployment plan to output the optimal alternative deployment plan as the buoy deployment plan. The buoy recovery path planning is based on the positions of each buoy deployment point. The present application can make the generated buoy deployment plan and the planned recovery path more scientific and reasonable, so as to facilitate actual operations.

Description

Technical Field

[0001] The present application relates to the technical field of buoy deployment and recovery, and particularly relates to an automatic buoy deployment and recovery method, system and device. Background Art

[0002] Buoys include monitoring buoys and channel buoys. A variety of sensors are installed on the monitoring buoys, such as temperature and humidity sensors, wind speed sensors, water flow sensors, etc., which are used to be deployed in the target sea area to be monitored, monitor the meteorological information of the target sea area and transmit it back, mainly playing the role of sea area meteorological and hydrological monitoring.

[0003] In the prior art, for the task of deploying monitoring buoys in the target sea area for meteorological and hydrological monitoring, it is necessary for manual workers to monitor buoy parameters, such as the effective monitoring range and the anti-wave coefficient, according to the sea area information of the target sea area, such as the boundary range and hydrological data, and design a deployment plan by the monitoring personnel. This deployment method mainly depends on the experience and subjective judgment of the monitoring personnel, the generation efficiency of the deployment plan is low, and it is highly dependent on human experience, and it is impossible to ensure that the deployment plan has a high buoy utilization rate and rationality.

[0004] Similarly, in the process of buoy recovery after monitoring, mainly by the monitoring personnel according to the deployment positions of each buoy, manually plan the recovery path, and drive the recovery ship along the recovery path during actual recovery to recover the buoys one by one. This manual planning method, on the one hand, is difficult to ensure the rationality of the recovery path, and on the other hand, only considers the position and space information of the buoy single - handedly, without considering the many instabilities existing during the buoy recovery operation at sea, which affects the efficiency and safety of the actual buoy recovery operation. Summary of the Invention

[0005] In order to solve the problems existing in the above - mentioned prior art, the purpose of the present application is to provide an automatic buoy deployment and recovery method, system and device. The present application can avoid the subjective influence of humans in the generation of buoy deployment plans and the planning of recovery paths, improve the scientificity and rationality of the deployment and recovery plans. At the same time, considering the deployment difficulty and stability after deployment in the buoy deployment plan is beneficial to improving the comprehensiveness of the deployment plan, can reduce the deployment difficulty, improve the stability of the buoy after deployment, and make the buoy deployment plan more suitable for the actual offshore scenario.

[0006] An automatic buoy deployment and recovery method described in the present application includes the generation of a buoy deployment plan and the planning of a buoy recovery path;

[0007] The generation of the buoy deployment plan includes the following steps:

[0008] Sa1. Obtain the buoy parameters and the sea area information of the target sea area to be monitored. The buoy parameters include the effective monitoring range and the anti-wind and wave coefficient of the buoy; the sea area information includes the boundary of the target sea area, the hydrological data, and the historical meteorological data.

[0009] Sa2. Construct a sea area image of the target sea area based on the sea area information of the target sea area, grid the sea area image, and use the center of each grid as an alternative placement point for the buoy; construct a buoy model based on the buoy parameters.

[0010] Sa3. Starting from one end of the target sea area to the other end, with the goal of minimizing the overlapping area of the monitoring areas of adjacent buoy models, sequentially place the buoy models at the alternative placement points.

[0011] Sa4. Repeat step Sa3 to generate several alternative placement plans, and calculate the monitoring coverage rates of each alternative placement plan.

[0012] Sa5. Based on the anti-wind and wave coefficient, hydrological data, and historical meteorological data, calculate the placement difficulty coefficient and the stability coefficient after placement of the buoy model at each placement point, and then obtain the total placement difficulty coefficient and the total stability coefficient of each alternative placement plan.

[0013] Sa6. Combining the monitoring coverage rate, the total placement difficulty coefficient, and the total stability coefficient of each alternative placement plan, output the optimal alternative placement plan as the buoy placement plan.

[0014] The buoy recovery path planning includes the following steps:

[0015] Generate a buoy recovery path based on the position information of each buoy placement point in the buoy placement plan and output it.

[0016] Preferably, in step Sa1, the anti-wind and wave coefficient includes one or more of the righting arm, metacentric height, maximum swing angle, swing period, drag coefficient, lift coefficient, anchor holding power, anchor chain tension, maximum wind speed that can be withstood, and maximum wave height that can be withstood.

[0017] Preferably, in step Sa3, the greedy algorithm is used to sequentially place the buoy models at the alternative placement points.

[0018] Preferably, in step Sa5, the placement difficulty coefficient DS of a single placement point i is calculated according to the following formula:

[0019] DS i = ω 1 * Dw i + ω 2 * Suw i + ω 3 * Sbli ;

[0020] Among them, i represents the serial number of the placement point, Dw i represents the water depth of the placement point i, Suw i represents the geomorphic score of the underwater topography at the placement point i, and the geomorphic score is proportional to the complexity of the underwater topography, Sbl i represents the busy degree of commercial and fishing vessels at the placement point i, ω 1 、ω 2 、ω 3 respectively represent the weights of water depth, geomorphic score, and the busy degree of commercial and fishing vessels;

[0021] The total placement difficulty coefficient DS of the alternative placement plan is calculated according to the following formula:

[0022]

[0023] Among them, n represents the total number of placement points;

[0024] The stability coefficient of a single placement point is calculated according to the following formula:

[0025] SS i =-ω 4 *Ssc i -ω 5 *Sbf i +v 6 *Cwr;

[0026] Among them, i represents the serial number of the placement point, Ssc i represents the sea condition score of the placement point i, and the sea condition score is proportional to the intensity of the sea condition change, Sbf i represents the severity of biological attachment at the placement point i, Cwr represents the wind and wave resistance coefficient of the buoy, ω 4 、ω 5 、ω 6 respectively represent the weights of the sea condition score, the severity of biological attachment, and the wind and wave resistance coefficient;

[0027] The total stability coefficient SS of the alternative placement plan is calculated according to the following formula:

[0028]

[0029] Among them, n represents the total number of placement points.

[0030] Preferably, step Sa6 is specifically: numerically comparing the total stability coefficient SS of each alternative placement plan with a preset stability coefficient threshold SS thr respectively, and making the total stability coefficient SS less than the stability coefficient threshold SS thrEliminate the alternative buoy placement plans and retain those with a total stability coefficient SS greater than or equal to the stability coefficient threshold SS thr Alternative buoy placement plans:

[0031] Calculate the selection index Sl of the retained alternative buoy placement plans according to the following formula:

[0032] Sl = a * Cov + b * DS;

[0033] Where cov represents the monitoring coverage rate of the alternative buoy placement plan, and a and b respectively represent the calculation coefficients of the monitoring coverage rate and the total deployment difficulty coefficient DS, satisfying a > 0 and b < 0;

[0034] Among the retained alternative buoy placement plans, select the alternative buoy placement plan with the highest selection index Sl as the buoy deployment plan for output.

[0035] Preferably, the buoy recovery path planning is specifically as follows:

[0036] Set the operation period for performing the buoy recovery task, obtain the monitoring data of each buoy, select the impact indicators that affect the recovery operation from the monitoring data, and based on the obtained impact indicators, predict the change of the impact indicators at each deployment point during the operation period;

[0037] According to the situation of the impact indicators, select the time period suitable for performing the recovery operation at each deployment point as the operation window period;

[0038] Obtain the position information of each buoy, use the operation window period of each obtained deployment point as a constraint condition, and use a path planning algorithm to generate and output the buoy recovery path with the shortest total recovery distance as the goal.

[0039] Preferably, the impact indicators include one or more of the wind speed, wave height, and flow velocity at the deployment point;

[0040] The path planning algorithm selects the genetic algorithm, uses whether the recovery operation period of each buoy is within the operation window period of the corresponding point as the penalty condition of the genetic algorithm, and generates and outputs the buoy recovery path with the shortest total recovery distance as the goal.

[0041] A buoy automatic deployment and recovery system of the present application includes a buoy deployment plan generation module and a buoy recovery path planning module;

[0042] The buoy deployment plan generation module includes:

[0043] An acquisition unit, which is used to obtain buoy parameters and sea area information of the target sea area to be monitored. The buoy parameters include the effective monitoring range and the wind and wave resistance coefficient of the buoy; the sea area information includes the boundary of the target sea area, hydrological data, and historical meteorological data;

[0044] A graphical unit, which is used to construct a sea area image of the target sea area based on the sea area information of the target sea area, grid the sea area image, and use the center of each grid as an alternative placement point for the buoy; construct a buoy model based on the buoy parameters;

[0045] A placement plan generation unit, which is used to place the buoy models on the alternative placement points in sequence from one end of the target sea area to the other end, with the goal of minimizing the overlapping area of the monitoring areas of adjacent buoy models, repeat the placement steps to generate several alternative placement plans, and calculate the monitoring coverage rates of the alternative placement plans;

[0046] A coefficient calculation unit, which is used to calculate the placement difficulty coefficient and the stability coefficient after placement of the buoy model at each placement point based on the wave resistance coefficient, hydrological data, and historical meteorological data, and then obtain the total placement difficulty coefficient and the total stability coefficient of each alternative placement plan;

[0047] An output unit, which is used to combine the monitoring coverage rate, the total placement difficulty coefficient, and the total stability coefficient of each alternative placement plan, and output the optimal alternative placement plan as the buoy placement plan;

[0048] The buoy recovery path planning module is used to generate and output a buoy recovery path based on the position information of each buoy placement point in the buoy placement plan.

[0049] A computer device of the present application includes a processor and a memory connected by a signal. At least one instruction or at least one program segment is stored in the memory. When the at least one instruction or the at least one program segment is loaded by the processor, it executes the buoy automatic placement and recovery method as described above.

[0050] A computer-readable storage medium of the present application stores at least one instruction or at least one program segment thereon. When the at least one instruction or the at least one program segment is loaded by the processor, it executes the buoy automatic placement and recovery method as described above.

[0051] The advantages of a buoy automatic placement and recovery method, system, and device of the present application are as follows:

[0052] 1. This application combines the sea area information of the target sea area and the buoy parameters for deploying buoys, uses the grid method to divide the target sea area, and comprehensively evaluates each alternative deployment plan in combination with the monitoring coverage rate, deployment difficulty, and stability after buoy deployment. The deployment plan with the best comprehensive performance is selected as the final buoy deployment plan for output. This enables this application to avoid subjective human influence when generating the buoy deployment plan, improve the scientificity and rationality of the deployment plan, and at the same time improve the generation efficiency of the buoy deployment plan, reduce the deployment difficulty, improve the stability after buoy deployment, and make the buoy deployment plan more suitable for actual offshore scenarios. In addition, this application generates a buoy recovery path based on the position information of each buoy deployment point, making the planned path more reasonable.

[0053] 2. When this application plans the buoy recovery path, it selects the influencing indicators that affect the recovery operation from the monitored meteorological data and hydrological data of the deployment points, and predicts the changes in the influencing indicators of each deployment point during the operation period. From this, the operation windows suitable for performing the recovery operation at each deployment point during the operation period are selected. Combining the position information and operation windows of each deployment point, the operation windows are used as the constraint conditions for the path planning algorithm, and path planning is carried out from two dimensions of space and time. The planned recovery path not only considers the positions of each deployment point, but also considers the time period suitable for performing the recovery operation, which is more in line with the actual situation of offshore recovery operations and is conducive to improving the efficiency and safety of buoy recovery operations. Description of the Drawings

[0054] Figure 1 is the flowchart of the steps of a buoy automatic deployment and recovery method described in this application;

[0055] Figure 2 is the structural schematic diagram of the computer device described in this embodiment.

[0056] Description of the reference numerals: 101 - processor, 102 - memory. Detailed Embodiment

[0057] As Figure 1 shown, a buoy automatic deployment and recovery method described in this application includes buoy deployment plan generation and buoy recovery path planning;

[0058] The generation of the buoy deployment plan includes the following steps:

[0059] Sa1. Obtain the buoy parameters and the sea area information of the target sea area to be monitored. The buoy parameters include the effective monitoring range and the anti-wind-and-wave coefficient of the buoy; the sea area information includes the boundary of the target sea area, hydrological data, and historical meteorological data. Specifically, the buoy parameters can be obtained according to the model, specifications, and instruction manual of the buoy. The boundary of the target sea area is set according to the monitoring task, and the hydrological data and historical meteorological data can be obtained from the maritime department.

[0060] Sa2. Construct the sea area image of the target sea area based on the sea area information of the target sea area, and grid the sea area image. Take the center of each grid as an alternative placement point for the buoy. Construct a buoy model based on the buoy parameters. Specifically, an electronic sea chart can be obtained, and the target sea area can be selected in the electronic sea chart according to the boundary of the target sea area, which is the sea area image of the target sea area. Using a grid algorithm, for example, a conventional uniform grid algorithm, or a watershed algorithm, a pyramid segmentation algorithm, etc., can all achieve the gridding of the sea area image of the target sea area, and can be selected according to actual requirements and system computing power.

[0061] Sa3. Starting from one end of the target sea area to the other end, with the goal of minimizing the overlapping area of the monitoring areas of adjacent buoy models, place the buoy models on the alternative placement points in sequence. Specifically, use the greedy algorithm to place the buoy models on the alternative placement points in sequence. In a specific embodiment, in order to save computing power and simplify the simulation process, the buoy model can be abstracted as a point model, and the geometric center position of the buoy is used as the coordinate of the point model. In other alternative embodiments, in a scenario with sufficient computing power, a scaled-down model of the buoy can be made to make the presented placement effect more intuitive.

[0062] In an exemplary description, the process of using the greedy algorithm for buoy simulation placement is as follows:

[0063] Step 1: Initialization

[0064] Determine one end of the sea area as the starting point, which can be a specific location geographically, such as the west end of the target sea area.

[0065] Prepare a list of alternative placement points, which are the center points of each grid after the sea area is gridded.

[0066] Step 2: Select the first placement point

[0067] According to the greedy strategy, select the first placement point. This point is usually based on some preliminary evaluation criteria, such as the distance from the starting point, whether the hydrological and meteorological conditions of the grid where the point is located are suitable for buoy placement, etc.

[0068] Step 3: Iterative placement

[0069] Starting from the first deployment point, successively select subsequent deployment points.

[0070] In each step, evaluate all alternative points where buoys have not been deployed yet, and select the next deployment point according to the following strategy:

[0071] Minimum overlap area of monitoring regions: Calculate the overlap area between the monitoring region after deploying a buoy at each alternative point and the monitoring regions of the already deployed buoys. Select the point with the minimum overlap area as the next deployment point.

[0072] Repeat the above steps until the last deployment point is at the farthest end from the starting point, for example, the easternmost end, and this alternative deployment plan generation is completed.

[0073] Sa4. Repeat step Sa3 to generate several alternative deployment plans, and calculate the monitoring coverage rates of each alternative deployment plan;

[0074] Since the greedy algorithm has strong derivativeness, and in the scenario of this embodiment, the center point of each grid is adjacent to multiple other center points, which enables generating multiple different alternative deployment plans by repeatedly using step Sa3 multiple times and adding the constraint that the selected points are not repeated. Subsequently, combining various data, the optimal deployment plan will be selected from multiple alternative deployment plans and output as the final deployment plan.

[0075] Sa5. Based on the anti-wind and wave coefficient, hydrological data, and historical meteorological data, calculate the deployment difficulty coefficient of the buoy model at each deployment point and the stability coefficient after deployment, and then obtain the total deployment difficulty coefficient and total stability coefficient of each alternative deployment plan;

[0076] Specifically, the anti-wind and wave coefficient is used to characterize the ability of the buoy to resist wind and waves in the marine scenario, which is mainly determined by various design parameters of the buoy, such as:

[0077] Stability index:

[0078] Restoring Moment Arm: It refers to the ratio of the restoring moment generated when the buoy returns to the vertical position to the distance between the center of gravity and the center of buoyancy.

[0079] Metacentric Height (GM): It refers to the height from the center of gravity of the buoy to the metacenter (the point where the restoring moment arm acts). The larger the GM value, the more stable the buoy.

[0080] Dynamic response index:

[0081] Pitch and Roll Angles: The maximum swing angles reached by the buoy under the action of wind and waves.

[0082] Period of Oscillation: The time required for the buoy to complete one oscillation cycle.

[0083] Hydrodynamic indicators:

[0084] Drag coefficient: A quantitative indicator of the resistance experienced by the buoy when moving in a fluid.

[0085] Lift Coefficient: A quantitative indicator of the lift force experienced by the buoy when moving in a fluid.

[0086] Anchoring system indicators:

[0087] Holding Power: The ability of the anchor to grip the seabed, usually expressed by the anchor's holding coefficient.

[0088] Chain Tension: The tension borne by the anchor chain under the action of wind and waves.

[0089] Environmental adaptability indicators:

[0090] Maximum Wind Speed: The maximum wind speed at which the buoy can operate safely.

[0091] Maximum Wave Height: The maximum wave height at which the buoy can operate safely.

[0092] Among the above parameters, they are all design parameters of the buoy and can be directly obtained from the buoy instruction manual.

[0093] In a specific embodiment, one or several of them are selected to characterize the wind and wave resistance coefficient of the buoy, which can be designed according to actual needs. Through this step, the wind and wave resistance coefficient of the selected buoy can be represented by quantitative indicators.

[0094] Difficulty coefficient DS of a single deployment point i Calculated according to the following formula:

[0095] DS i = ω 1 * Dw i + ω 2 * Suw i + ω 3 * Sbl i ;

[0096] Where i represents the serial number of the deployment point, Dw i represents the water depth of deployment point i, Suw iDenote the geomorphic score of the underwater geomorphology at the deployment point i, where the geomorphic score is proportional to the complexity of the underwater geomorphology, Sbl i Denote the busy degree of commercial and fishing vessels at the deployment point i, ω 1 、ω 2 、ω 3 respectively denote the weights of water depth, geomorphic score, and the busy degree of commercial and fishing vessels.

[0097] Specifically, the water depth of the deployment point can be obtained from hydrological data. Generally speaking, the deeper the water depth, the greater the deployment difficulty at this deployment point, and the corresponding deployment difficulty coefficient DS i is also greater.

[0098] Since an anchor needs to be dropped for fixation when deploying the buoy, the complexity of the underwater geomorphology will affect the difficulty of dropping the anchor, and thus affect the deployment difficulty. The geomorphic score of the underwater geomorphology adopts the expert scoring method. The deployment personnel score the underwater geomorphology of each deployment point according to the complexity of the underwater geomorphology, for example, the geomorphic flatness, the distribution density of seabed organisms, etc. The higher the score, the more complex the underwater geomorphology, the greater the deployment difficulty, and the greater the corresponding deployment difficulty coefficient.

[0099] The busy degree of commercial and fishing vessels at the deployment point will also affect the deployment difficulty. Specifically, the deployment process of the buoy takes a certain amount of time. If the frequency of commercial and fishing vessels passing by the deployment point is high, it will affect the deployment operation. For example, it may be necessary to adjust the position of the deployment ship to avoid commercial and fishing vessels. In addition, the operations of commercial and fishing vessels will also affect the deployment operation. Therefore, in this embodiment, the busy degree of commercial and fishing vessels is taken as one of the factors to consider the deployment difficulty coefficient. The busy degree of commercial and fishing vessels can be expressed as the passing frequency of commercial and fishing vessels, which is calculated based on the number of commercial and fishing vessels passing by near the deployment point within a certain historical period. For example, a circular area with a radius of 5m centered on the deployment point is used as the statistical area, and the total number of commercial and fishing vessels passing through this statistical area within seven days before the current moment is counted. This number is used as the quantitative index of the busy degree of commercial and fishing vessels. The more the number, the higher the busy degree of commercial and fishing vessels, and the higher the corresponding deployment difficulty coefficient.

[0100] The weights ω 1 、ω 2 、ω 3 can be designed according to the actual situation and the influence of various factors on the deployment difficulty, such as 40%, 40%, 20%.

[0101] In a specific embodiment,

[0102] The total deployment difficulty coefficient DS of the alternative deployment plan is calculated according to the following formula:

[0103]

[0104] Among them, n represents the total number of laying points;

[0105] In this step, the laying difficulty coefficients of all laying points of the alternative laying plan are accumulated to obtain the total laying difficulty coefficient of the alternative laying plan.

[0106] The stability coefficient of a single laying point is calculated according to the following formula:

[0107] SS i = -ω 4 *Ssc i -ω 5 *Sbf i +ω 6 *Cwr;

[0108] Among them, i represents the serial number of the laying point, Ssc i represents the sea condition score of the laying point i, and the sea condition score is proportional to the intensity of the sea condition change. Sbf i represents the severity of biological attachment at the laying point i, Cwr represents the wind and wave resistance coefficient of the buoy, and ω 4 、ω 5 、ω 6 respectively represent the weights of the sea condition score, the severity of biological attachment, and the wind and wave resistance coefficient;

[0109] Specifically, the sea condition score is used to represent the intensity of the sea condition change (whether the sea area is calm). The intensity of the sea condition change will affect the stability of the buoy after laying. When the intensity of the sea condition change is relatively large, it may cause the buoy to be damaged or displaced. The intensity of the sea condition change has a certain regularity. For example, in the absence of sudden weather, the intensity of the sea area within a certain period will not change significantly. At least, for the laying points where the sea condition change degree has always been relatively intense in the past period, it can be predicted that the stability after laying the buoy is poor.

[0110] Therefore, the intensity of the sea area change can be represented by the historical hydrological data and meteorological data of the laying point. For example, the hydrological data and meteorological data within three days before the current moment, specifically reflected in the wind speed, the size of the wind and waves, the wave height, the wave period, and the wave direction. One or more of them are selected to represent the intensity of the sea condition. In specific operations, the expert scoring method can be adopted. For example, the laying personnel combine the data of each laying point to score, or the data summation method can be adopted. For example, several selected data are weighted and summed to obtain a quantitative index representing the intensity of the sea condition change. Through this index, the stability of the laying point can be numerically represented. In this embodiment, the sea condition score is proportional to the intensity of the sea condition change and inversely proportional to the stability coefficient of the laying point. Therefore, the weight ω 4Take a negative sign.

[0111] The degree of biological attachment at the deployment point will also affect the stability of the buoy after deployment. Specifically, if the degree of biological attachment after the buoy is deployed, such as severe attachment of algae plants and shellfish, will greatly increase the weight of the buoy, damage the mechanical structure of the buoy, and may also cause corrosion and damage to the surface of the buoy, affecting the stability of the buoy after deployment. Therefore, the severity of biological attachment at the buoy deployment point is also one of the factors affecting the stability of the buoy after deployment. In this embodiment, mainly in the way of expert evaluation, the specific method is to obtain the environmental factors of each deployment point, such as parameters such as water temperature, salinity, dissolved oxygen, and the type of bottom sediment, such as the bottom sediment is silt, rock or coral reef. At the same time, obtain the biological regional characteristics near the deployment point, mainly obtain the richness of the attached biological community near the deployment point, and let experts estimate and score the severity of biological attachment. Generally speaking, if there is no attached biological community near the deployment point, the severity of this biological attachment is 0. If there is an attached biological community, the higher the richness of the attached biological community and the more suitable the environmental factors are for the growth of attached organisms, the higher the corresponding severity value of biological attachment, and the greater the impact on the stability of the deployment point after deployment. Therefore, the weight ω in the above formula 5 Take a negative sign.

[0112] Based on the aforementioned calculation method of the wind and wave resistance coefficient, an index for characterizing the wind and wave resistance ability of the buoy can be obtained. This index is proportional to the stability of the buoy after deployment. The higher the wind and wave resistance coefficient, the higher the stability of the buoy after deployment. Therefore, the weight ω in the above formula 6 Take a positive sign.

[0113] In this embodiment, in combination with the actual operation process, the influencing factors of the stability of the buoy after deployment are analyzed. The two parameters in the environmental factors that have a greater impact on the stability of the buoy deployment, the intensity of sea condition changes and biological attachment, are taken as consideration factors. At the same time, the wind and wave resistance coefficient of the buoy itself is taken as a consideration factor, which can comprehensively and objectively evaluate the stability of the buoy after deployment, and then conduct a comprehensive and comprehensive evaluation of the selection of the buoy deployment point.

[0114] The total stability coefficient SS of the alternative deployment plan is calculated according to the following formula:

[0115]

[0116] Among them, n represents the total number of deployment points.

[0117] In this step, the total stability coefficients of all deployment points of the alternative deployment plan are accumulated to obtain the total stability coefficient of the alternative deployment plan.

[0118] Sa6. Combine the monitoring coverage rate, total deployment difficulty coefficient, and total stability coefficient of each alternative deployment plan, and output the optimal alternative deployment plan as the buoy deployment plan;

[0119] Specifically, analyze the above three parameters in combination with the actual application process. Based on the deduction of the greedy algorithm, the monitoring coverage rates of each alternative deployment plan are relatively close, with little difference. Comparing the two parameters of the total deployment difficulty coefficient and the total stability coefficient, the total stability coefficient is the core index for selecting the buoy deployment plan. First of all, if the stability is not good after the buoy is deployed, it may affect the monitoring effect and lead to inaccurate data collection. More importantly, it may cause the dislocation or even damage of the buoy, resulting in greater losses. Therefore, among the above three parameters, the total stability coefficient should be the first factor to consider. The specific approach is as follows:

[0120] Compare the total stability coefficient SS of each alternative deployment plan with the preset stability coefficient threshold SS thr numerically. Eliminate the alternative deployment plans with the total stability coefficient SS less than the stability coefficient threshold SS thr , and retain the alternative deployment plans with the total stability coefficient SS greater than or equal to the stability coefficient threshold SS thr ; In this step, first eliminate the plans that do not meet the stability requirements to avoid large instabilities after the buoy is deployed, resulting in losses.

[0121] Calculate the selection index Sl of the retained alternative deployment plans according to the following formula:

[0122] Sl = a * cov + b * DS;

[0123] where cov represents the monitoring coverage rate of the alternative deployment plan, and a and b respectively represent the calculation coefficients of the monitoring coverage rate and the total deployment difficulty coefficient DS, satisfying a > 0 and b < 0;

[0124] The monitoring coverage rate is specifically obtained by dividing the sum of the monitoring areas of each buoy by the total area of the target sea area, and is used to characterize the percentage of the monitoring range of this alternative deployment plan that can cover the target sea area.

[0125] Among the retained alternative deployment plans, select the alternative deployment plan with the highest selection index Sl as the buoy deployment plan output. Specifically, the specific values of the coefficients a and b can be configured according to the degree of emphasis on the two factors, and this embodiment does not limit this.

[0126] The buoy recovery path planning includes the following steps:

[0127] Generate and output the buoy recovery path based on the position information of each buoy deployment point in the buoy deployment plan.

[0128] The buoy recovery path planning is specifically as follows:

[0129] An operation period for executing the buoy recovery task is set, monitoring data of each buoy is obtained, influencing indicators that have an impact on the recovery operation are selected from the monitoring data, and based on the obtained influencing indicators, changes in the influencing indicators of each deployment point during the operation period are predicted; the influencing indicators include one or more of the wind speed, wave height, and flow velocity at the deployment point.

[0130] Taking wind speed as an example, assuming that the operation period is within 1 hour after the current time, the exemplary prediction process is as follows:

[0131] Data collection: Get wind speed data every minute for the past 5 hours.

[0132] Preprocessing: fill missing values, remove outliers, and standardize data.

[0133] Feature extraction: Extract date and time features (hours, minutes).

[0134] Model selection: Select the ARIMA model for preliminary forecasting.

[0135] Model training: Use the previous 4 hours of data to train the ARIMA model.

[0136] Verification and adjustment: Use the data from the 5th hour to verify the model and adjust the model parameters based on the verification results.

[0137] Forecast: Use the final model to predict wind speed changes in the next hour, that is, during the operation period.

[0138] This makes it possible to predict the influencing indicators during the operation period.

[0139] According to the influencing indicators, a time period suitable for the recovery operation at each deployment point is selected as the operation window period. For example, if the wind speed suitable for the recovery operation is no more than 3m / s, then based on the operation time required to recover a single buoy, illustratively, the single operation time is 10 minutes. Then, combined with the predicted wind speed changes during the operation period, a time period with an average wind speed close to 3m / s in the next hour and a length of at least 10 minutes is selected as the operation window period for the buoy at the deployment point.

[0140] The position information of each buoy is obtained, and the operation window period of each deployment point is used as a constraint condition. The buoy recovery path is generated and output using a path planning algorithm with the shortest total recovery journey as the goal.

[0141] The path planning algorithm selects the genetic algorithm. Whether the recovery operation period of each buoy is within the operation window period of the corresponding point is used as the penalty condition of the genetic algorithm. With the goal of the shortest total recovery distance, the buoy recovery path is generated and output.

[0142] In an exemplary description, the specific recovery path planning process is as follows:

[0143] Suppose there are 4 buoys to be recovered in the target sea area. Each buoy has its corresponding deployment point, and the suitable operation window periods of each point are different.

[0144] Encode each buoy:

[0145] The individual encoding represents the recovery path and the time period for carrying out the recovery operation.

[0146] The encoding format can be: [buoy number, time point, buoy number, time point,...].

[0147] Fitness function:

[0148] The fitness function calculates the fitness value of an individual, considering the path length and operability:

[0149] Fitness = path length weight * total path length - operability weight * operability penalty.

[0150] The path length weight and the operability weight are preset parameters used to adjust the relative importance of the path length and operability.

[0151] Path length calculation:

[0152] The path length can be calculated based on the distance between the buoys, for example, using the Euclidean distance or the actual sailing distance.

[0153] Operability penalty calculation:

[0154] The operability penalty is calculated according to whether the period of stay (i.e., the period of performing the recovery operation) at each deployment point on the planned path is within the operation window period of that point:

[0155] If the period of stay at a certain deployment point is not within the corresponding operation window period, a relatively large penalty value is added.

[0156] If the periods of stay at all deployment points are within the operation window periods, the stability penalty is 0.

[0157] Constraint handling:

[0158] Use a penalty function to handle solutions that do not meet the operability conditions, or ensure that the offspring solutions meet the operability conditions through genetic operations.

[0159] Examples of genetic operations are as follows:

[0160] In the crossover and mutation operations, special rules can be designed to maintain or generate solutions that meet the operability conditions. For example:

[0161] Crossover: When selecting the crossover point, ensure that the individuals after crossover still maintain the time periods within the operability window.

[0162] Mutation: In the mutation operation, if the new time period does not meet the operability conditions, it can be adjusted to the nearest operability window.

[0163] Through such design and operation, the genetic algorithm can effectively search for the recovery path that not only satisfies the shortest path but also takes into account the operability matching.

[0164] This embodiment also provides an automatic buoy deployment and recovery system, including a buoy deployment plan generation module and a buoy recovery path planning module;

[0165] The buoy deployment plan generation module includes:

[0166] An acquisition unit, which is used to obtain buoy parameters and sea area information of the target sea area to be monitored. The buoy parameters include the effective monitoring range and the anti-wind and wave coefficient of the buoy; the sea area information includes the boundary of the target sea area, hydrological data, and historical meteorological data;

[0167] A graphical unit, which is used to construct a sea area image of the target sea area based on the sea area information of the target sea area, grid the sea area image, and use the center of each grid as an alternative buoy deployment point; construct a buoy model based on the buoy parameters;

[0168] A deployment plan generation unit, which is used to deploy the buoy models on the alternative deployment points in sequence from one end of the target sea area to the other end, with the goal of minimizing the overlapping area of the monitoring areas of adjacent buoy models, repeat the deployment steps to generate several alternative deployment plans, and calculate the monitoring coverage rates of each alternative deployment plan;

[0169] A coefficient calculation unit, which is used to calculate the deployment difficulty coefficient and the stability coefficient after deployment of the buoy models at each deployment point based on the anti-wind and wave coefficient, hydrological data, and historical meteorological data, and then obtain the total deployment difficulty coefficient and the total stability coefficient of each alternative deployment plan;

[0170] An output unit, which is used to output the optimal alternative deployment plan as the buoy deployment plan by combining the monitoring coverage rate, the total deployment difficulty coefficient, and the total stability coefficient of each alternative deployment plan;

[0171] The buoy recovery path planning module is used to generate and output a buoy recovery path based on the position information of each buoy placement point in the buoy placement plan.

[0172] The system of this embodiment and the above method belong to the same inventive concept and can be understood by referring to the above description, so details are not repeated here.

[0173] As Figure 2 shown, this embodiment also provides a computer device, including a processor 101 and a memory 102 connected by a bus signal. At least one instruction or at least one program segment is stored in the memory 102. When the at least one instruction or the at least one program segment is loaded by the processor 101, the above-mentioned buoy automatic placement and recovery method is executed. The memory 102 can be used to store software programs and modules. The processor 101 executes various functional applications by running the software programs and modules stored in the memory 102. The memory 102 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for functions, etc.; the data storage area can store data created according to the use of the device, etc. In addition, the memory 102 can include high-speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices. Correspondingly, the memory 102 can also include a memory controller to provide the processor 101 with access to the memory 102.

[0174] The method embodiments provided by the embodiments of this application can be executed in a computer terminal, a server, or a similar computing device, that is, the above computer device can include a computer terminal, a server, or a similar computing device. The internal structure of the computer device can include, but is not limited to: a processor, a network interface, and a memory. Among them, the processor, network interface, and memory in the computer device can be connected by a bus or other means.

[0175] Among them, the processor 101 (or CPU (Central Processing Unit)) is the computing core and control core of the computer device. The network interface may optionally include a standard wired interface, a wireless interface (such as WI-FI, a mobile communication interface, etc.). The memory 102 (Memory) is the memory device in the computer device, used to store programs and data. It can be understood that the memory 102 here can be a high-speed RAM storage device, or a non-volatile memory device, such as at least one disk storage device; optionally, it can also be at least one storage device located far from the aforementioned processor 101. The memory 102 provides a storage space, and this storage space stores the operating system of the electronic device, which may include but is not limited to: Windows system (an operating system), Linux (an operating system), Android (a mobile operating system) system, IOS (a mobile operating system) system, etc., and this application does not make any limitations in this regard; and, one or more instructions suitable for being loaded and executed by the processor 101 are also stored in this storage space, and these instructions can be one or more computer programs (including program codes). In the embodiments of this specification, the processor 101 loads and executes one or more instructions stored in the memory 102 to implement the buoy automatic deployment and recovery method described in the above method embodiments.

[0176] The embodiments of this application also provide a computer-readable storage medium, on which at least one instruction or at least one segment of program is stored, and when the at least one instruction or the at least one segment of program is loaded by the processor 101, it executes the buoy automatic deployment and recovery method as described above. The above computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to the embodiments of this application is implemented.

[0177] According to the embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium. For example, it may include but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this application, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or combined with an instruction execution system, device, or component.

[0178] In the description of the present application, it should be understood that the orientation or positional relationship indicated by orientation words such as "front, back, top, bottom, left, right", "lateral, vertical, horizontal" and "top, bottom", etc. is usually based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present application and simplifying the description. Without contrary explanation, these orientation words do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation on the protection scope of the present application.

[0179] For those skilled in the art, according to the technical solutions and concepts described above, various corresponding changes and deformations can be made, and all these changes and deformations should fall within the protection scope of the claims of the present application.

Claims

1. A method for automatically deploying and recovering a buoy, characterized in that: Including buoy deployment plan generation and buoy recovery path planning; The buoy deployment plan generation includes the following steps: Sa1, obtaining buoy parameters and sea area information of the target sea area to be monitored, wherein the buoy parameters include the effective monitoring range and wind and wave resistance coefficient of the buoy; the sea area information includes the boundary, hydrological data and historical meteorological data of the target sea area; Sa2, constructing a sea area image of the target sea area based on the sea area information of the target sea area, gridding the sea area image, and taking each grid center as a candidate deployment point of the buoy; and constructing a buoy model based on the buoy parameters; Sa3, from one end of the target sea area to the other end, with the goal of minimizing the overlapping area of ​​the monitoring areas of adjacent buoy models, deploying the buoy models on the candidate deployment points in sequence; Sa4. Repeat step Sa3 to generate several alternative deployment plans, and calculate the monitoring coverage of each alternative deployment plan; Sa5. Based on the wind and wave resistance coefficient, hydrological data and historical meteorological data, calculate the deployment difficulty coefficient of the buoy model at each deployment point and the stability coefficient after deployment, and then obtain the total deployment difficulty coefficient and total stability coefficient of each alternative deployment scheme; Sa6. Combining the monitoring coverage, total deployment difficulty coefficient and total stability coefficient of each alternative deployment scheme, output the best alternative deployment scheme as the buoy deployment scheme; The buoy recovery path planning comprises the following steps: Based on the position information of each buoy deployment point in the buoy deployment plan, a buoy recovery path is generated and output.

2. The method for automatically deploying and recovering a buoy according to claim 1, characterized in that: In step Sa1, the wind and wave resistance coefficient includes one or more of the righting arm, stability height, maximum swing angle, swing period, drag coefficient, lift coefficient, anchor grip, anchor chain tension, maximum wind speed and maximum wave height.

3. The method for automatically deploying and recovering a buoy according to claim 1, characterized in that: In step Sa3, a greedy algorithm is used to sequentially deploy the buoy models on the candidate deployment points.

4. The method for automatically deploying and recovering a buoy according to claim 1 or 2, characterized in that: In step Sa5, the deployment difficulty coefficient DS of a single deployment point i Calculated as follows: DS i =ω1*Dw i +ω2*Suw i +ω3*Sbl i ; Where i represents the sequence number of the deployment point, Dw i represents the water depth at deployment point i, Suw i represents the landform score of the underwater landform at the deployment point i, which is proportional to the complexity of the underwater landform. i represents the busyness of commercial fishing vessels at the deployment point i, ω1, ω2, and ω3 represent the weights of water depth, landform score, and busyness of commercial fishing vessels, respectively; The total deployment difficulty coefficient DS of the alternative deployment scheme is calculated according to the following formula: Where n represents the total number of deployment points; The stability coefficient of a single deployment point is calculated according to the following formula: SS i =-ω4*Ssc i -ω5*Sbf i +ω6*Husband; Among them, i represents the sequence number of the deployment point, Ssc i represents the sea state score of the deployment point i, which is proportional to the severity of the sea state change, Sbf i represents the severity of biofouling at deployment point i, Cwr represents the wind and wave resistance coefficient of the buoy, ω4, ω5, ω6 represent the weights of sea state score, severity of biofouling and wind and wave resistance coefficient respectively; The total stability coefficient SS of the alternative deployment scheme is calculated according to the following formula: Where n represents the total number of deployment points.

5. The method for automatically deploying and recovering a buoy according to claim 1, characterized in that: Step Sa6 specifically includes: comparing the total stability coefficient SS of each candidate point arrangement scheme with the preset stability coefficient threshold SS thr Perform numerical comparison and set the total stability coefficient SS to be less than the stability coefficient threshold SS thr The alternative point arrangement schemes are eliminated, and the total stability coefficient SS is greater than or equal to the stability coefficient threshold SS thr Alternative deployment plans; The selection index S1 of the retained alternative layout scheme is calculated according to the following formula: Sl = a*Cov+b*DS; Wherein, cov represents the monitoring coverage of the alternative deployment solution, a and b represent the calculation coefficients of the monitoring coverage and the total deployment difficulty coefficient DS, respectively, satisfying a>0, b<0; Among the retained alternative deployment plans, the alternative deployment plan with the highest selection index S1 is selected as the buoy deployment plan output.

6. The method for automatically deploying and recovering a buoy according to claim 1, characterized in that: The buoy recovery path planning is specifically as follows: Setting an operation period for executing the buoy recovery task, obtaining monitoring data of each buoy, selecting influencing indicators that have an impact on the recovery operation from the monitoring data, and predicting changes in the influencing indicators of each deployment point during the operation period based on the obtained influencing indicators; According to the influencing indicators, the time period suitable for performing the recovery operation at each deployment point is selected as the operation window period; The position information of each buoy is obtained, and the operation window period of each deployment point is used as a constraint condition. The buoy recovery path is generated and output using a path planning algorithm with the shortest total recovery journey as the goal.

7. The method for automatically deploying and recovering buoys according to claim 6, wherein the influencing index comprises one or more of wind speed, wave height, and flow velocity at the deployment point; The path planning algorithm uses a genetic algorithm, and whether the recovery operation period of each buoy is within the operation window period of the corresponding point is used as a penalty condition of the genetic algorithm. The buoy recovery path is generated and output with the shortest total recovery journey as the goal.

8. A buoy automatic deployment and recovery system, characterized in that: It includes a buoy deployment plan generation module and a buoy recovery path planning module; The buoy deployment plan generation module includes: A collection unit, which is used to obtain buoy parameters and sea area information of the target sea area to be monitored, wherein the buoy parameters include the effective monitoring range and wind and wave resistance coefficient of the buoy; the sea area information includes the boundary, hydrological data and historical meteorological data of the target sea area; A graphical unit, which is used to construct a sea area image of the target sea area based on the sea area information of the target sea area, grid the sea area image, and use each grid center as a candidate deployment point for the buoy; and construct a buoy model based on the buoy parameters; A deployment scheme generating unit is used to deploy the buoy models on the candidate deployment points in sequence from one end of the target sea area to the other end, with the goal of minimizing the overlapping area of ​​the monitoring areas of adjacent buoy models, repeat the deployment steps to generate a number of candidate deployment schemes, and calculate the monitoring coverage rate of each candidate deployment scheme; A coefficient calculation unit, which is used to calculate the deployment difficulty coefficient of the buoy model at each deployment point and the stability coefficient after deployment based on the wind and wave resistance coefficient, hydrological data and historical meteorological data, so as to obtain the total deployment difficulty coefficient and total stability coefficient of each alternative deployment scheme; An output unit, which is used to combine the monitoring coverage, total deployment difficulty coefficient and total stability coefficient of each alternative deployment scheme, and output the optimal alternative deployment scheme as the buoy deployment scheme; The buoy recovery path planning module is used to generate and output a buoy recovery path based on the position information of each buoy deployment point in the buoy deployment plan.

9. A computer device comprising a processor and a memory connected in a signal connection, characterized in that: The memory stores at least one instruction or at least one program, and when the at least one instruction or the at least one program is loaded by the processor, the method for automatic deployment and recovery of a buoy as described in any one of claims 1 to 7 is executed.

10. A computer-readable storage medium having at least one instruction or at least one program stored thereon, characterized in that: When the at least one instruction or the at least one program is loaded by the processor, the method for automatic deployment and recovery of a buoy as described in any one of claims 1 to 7 is executed.

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