Automatic buoy laying and recovering method, system and equipment

Abstract

The invention relates to an automatic buoy laying and recovery method, system and equipment. The method comprises the steps of buoy laying scheme generation and buoy recovery path planning. The buoy laying scheme generation comprises the steps of obtaining buoy parameters and sea area information, constructing a sea area image of a target sea area based on the sea area information of the target sea area, gridding the sea area image, taking the center of each grid as an alternative laying point of buoys, and laying the buoys from one end of the target sea area to the other end of the target sea area. And with the minimum overlapping area of the monitoring areas of the adjacent buoy models as the target, sequentially laying the buoy models on the alternative laying points to generate a plurality of alternative laying schemes, and outputting the optimal alternative laying scheme as the buoy laying scheme by combining the monitoring coverage rate, the total laying difficulty coefficient and the total stability coefficient of each alternative laying scheme. And the buoy recovery path planning is performed based on the position of each buoy distribution point. According to the method, the generated buoy laying scheme and the planned recovery path can be more scientific and reasonable, so that actual operation is facilitated.

Description

Technical Field

[0001] The present application relates to the technical field of buoy deployment and recovery, and in particular to a method, system and equipment for automatic buoy deployment and recovery. Background Art

[0002] Buoys include monitoring buoys and channel buoys. Monitoring buoys are equipped with various types of sensors, such as temperature and humidity sensors, wind speed sensors, water flow sensors, etc. They are used to be deployed in target sea areas that need to be monitored to monitor the meteorological information of the target sea areas and transmit it back. They mainly play 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 to manually monitor the buoy parameters, such as the effective monitoring range and the wind and wave resistance coefficient, based on the sea area information of the target sea area, such as the boundary range and hydrological data, and the monitoring personnel design the deployment plan. This deployment method mainly relies on the experience and subjective judgment of the monitoring personnel. The deployment plan generation efficiency is low and it is highly dependent on human experience, and it cannot guarantee that the deployment plan has a high buoy utilization rate and rationality.

[0004] Similarly, during the buoy recovery process after the monitoring is completed, the monitoring personnel mainly manually plan the recovery route according to the deployment points of each buoy. During the actual recovery, the recovery ship is driven along the recovery route and recovers the buoys one by one. On the one hand, this manual planning method is difficult to ensure the rationality of the recovery path. On the other hand, it only considers the spatial location information of the buoy, and does not consider the many instabilities that exist when performing buoy recovery operations 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 this application is to provide a method, system and equipment for automatic deployment and recovery of buoys. This application can avoid the subjective influence of human beings in the generation of buoy deployment plan and recovery path planning, improve the scientificity and rationality of the deployment and recovery plan, and at the same time, consider the deployment difficulty and stability after deployment in the buoy deployment plan, which is conducive to improving the comprehensiveness of the deployment plan, reducing the deployment difficulty, and improving the stability of the buoy after deployment, making the buoy deployment plan more suitable for actual marine scenarios.

[0006] A method for automatic buoy deployment and recovery described in the present application includes generating a buoy deployment plan and planning a buoy recovery path;

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

[0008] 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;

[0009] 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;

[0010] 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;

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

[0012] 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;

[0013] 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;

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

[0015] Based on the position information of each buoy deployment point in the buoy deployment plan, a buoy recovery path is generated and output.

[0016] Preferably, 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.

[0017] Preferably, in step Sa3, a greedy algorithm is used to sequentially deploy the buoy models on the candidate deployment points.

[0018] Preferably, in step Sa5, the deployment difficulty coefficient DS of a single deployment point is i Calculated as follows:

[0019] DS i =ω1*Dw i +ω2*Suw i +ω3*Sbl i ;

[0020] 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;

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

[0022]

[0023] Where n represents the total number of deployment points;

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

[0025] SS i =-ω4*Ssc i -ω5*Sbf i +v6*Cwr;

[0026] 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;

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

[0028]

[0029] Where n represents the total number of deployment points.

[0030] Preferably, step Sa6 specifically comprises: comparing the total stability coefficient SS of each candidate point arrangement scheme with a 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 options:

[0031] The selection index S1 of the retained alternative layout scheme is calculated according to the following formula:

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

[0033] 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;

[0034] Among the retained alternative deployment plans, the alternative deployment plan with the highest selection index S1 is selected as the buoy deployment plan output.

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

[0036] 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;

[0037] 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;

[0038] 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.

[0039] Preferably, the influencing index includes one or more of wind speed, wave height, and flow velocity at the deployment point;

[0040] 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.

[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] 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;

[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 each grid center as a candidate deployment point for the buoy; and construct a buoy model based on the buoy parameters;

[0045] 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;

[0046] 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;

[0047] 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;

[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 deployment point in the buoy deployment plan.

[0049] A computer device of the present application includes a processor and a memory connected by signals, wherein 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 automatic buoy deployment and recovery method as described above is executed.

[0050] A computer-readable storage medium of the present application 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 a processor, the automatic buoy deployment and recovery method as described above is executed.

[0051] The advantages of the method, system and equipment for automatically deploying and recovering buoys described in the present application are:

[0052] 1. This application combines the sea area information of the target sea area and the buoy parameters of the deployed buoys, adopts a gridding method to segment the target sea area, and comprehensively evaluates each alternative deployment plan in combination with the monitoring coverage, deployment difficulty and stability of the buoy after deployment. The deployment plan with the best comprehensive performance is selected as the final buoy deployment plan output, so that when generating the buoy deployment plan, this application can avoid human subjective influence, 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, and improve the stability of the buoy after deployment, so that the buoy deployment plan is more suitable for actual marine scenarios. In addition, this application generates a buoy recovery path based on the location information of each buoy deployment point, which can make the planned path more reasonable.

[0053] 2. When planning the buoy recovery path, the present application selects the influencing indicators that have an impact on the recovery operation based on the meteorological and hydrological data of the monitored deployment points, and predicts the changes in the influencing indicators of each deployment point during the operation period. In this way, the operation window period suitable for performing the recovery operation at each deployment point during the operation period is selected. Combined with the location information and operation window period of each deployment point, the operation window period is used as a constraint condition of the path planning algorithm, and path planning is performed from both spatial and temporal dimensions, so that the planned recovery path not only considers the location of each deployment point, but also the time period suitable for 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. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0056] Description of reference numerals: 101 - processor, 102 - memory. DETAILED DESCRIPTION

[0057] like Figure 1 As shown, a method for automatic deployment and recovery of buoys described in the present application includes generating a buoy deployment plan and planning a buoy recovery path;

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

[0059] Sa1. 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; specifically, the buoy parameters can be obtained according to the model, specifications and instructions 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 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 an alternative deployment point for the buoy; construct a buoy model based on the buoy parameters. Specifically, an electronic sea area map can be obtained, and the target sea area can be selected from the electronic sea area map according to the boundary of the target sea area, which is the sea area image of the target sea area. Using a gridding algorithm, for example, a conventional uniform gridding algorithm, or a watershed algorithm, a pyramid segmentation algorithm, etc., can realize the gridding of the sea area image of the target sea area, which can be selected according to actual needs and system computing power.

[0061] 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, the buoy models are deployed on the alternative deployment points in sequence; specifically, a greedy algorithm is used to deploy the buoy models on the alternative deployment 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 optional embodiments, in a scenario with sufficient computing power, a proportional scaled-down model of the buoy can be made to make the deployment presentation more intuitive.

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

[0063] Step 1: Initialization

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

[0065] Prepare a list of candidate deployment 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, the first deployment point is selected. 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 deployment, etc.

[0068] Step 3: Iterative deployment

[0069] Starting from the first placement point, select subsequent placement points in sequence.

[0070] At each step, all candidate sites where buoys have not yet been deployed are evaluated and the next deployment site is selected according to the following strategy:

[0071] Minimum overlapping monitoring area: Calculate the overlapping area between the monitoring area of ​​each candidate point and the monitoring area of ​​the deployed buoys after the buoys are deployed. Select the point with the smallest overlapping area as the next deployment point.

[0072] Repeat the above steps until the last deployment point is located at the other end farthest from the starting point, such as the easternmost end, and the generation of this alternative deployment plan is completed.

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

[0074] Since the greedy algorithm has strong derivative properties, and in the scenario of this embodiment, the center point of each grid is adjacent to multiple other center points, multiple different alternative placement plans can be generated by repeating step Sa3 multiple times and adding the selected points as constraints. Subsequently, the optimal placement plan will be selected from multiple alternative placement plans in combination with various data as the final placement plan output.

[0075] 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;

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

[0077] Stability index:

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

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

[0080] Dynamic response indicators:

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

[0082] Period of Oscillation: The time required for a buoy to oscillate once.

[0083] Fluid dynamics indicators:

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

[0085] Lift Coefficient: A quantitative indicator of the lift force exerted on a buoy when it moves in a fluid.

[0086] Anchoring system indicators:

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

[0088] Chain Tension: The tension on 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] The above parameters are all design parameters of the buoy and can be directly obtained from the buoy manual.

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

[0094] Deployment difficulty coefficient DS of a single deployment point i Calculated as follows:

[0095] DS i =ω1*Dw i +ω2*Suw i +ω3*Sbl i ;

[0096] 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 deployment point i, ω1, ω2, and ω3 represent the weights of water depth, landform score, and busyness of commercial fishing vessels, respectively.

[0097] Specifically, the water depth of the deployment point can be obtained through hydrological data. Generally speaking, the deeper the water depth, the greater the difficulty of deployment of the deployment point. The corresponding deployment difficulty coefficient DS i The bigger it is.

[0098] Since the buoy needs to be anchored for fixation during deployment, the complexity of the underwater topography will affect the difficulty of anchoring, and then affect the deployment difficulty. The underwater topography is scored by an expert scoring method, and the deployment personnel score the underwater topography of each deployment point according to the complexity of the underwater topography, such as the flatness of the topography, the distribution density of seabed organisms, etc. The higher the score, the more complex the underwater topography, the greater the deployment difficulty, and the corresponding deployment difficulty coefficient.

[0099] The busyness of commercial fishing vessels at the deployment point will also affect the deployment difficulty. Specifically, the buoy deployment process takes a certain amount of time. If the commercial fishing vessels at the deployment point have a high frequency of travel, it will affect the deployment operation. For example, the position of the deployment ship may need to be adjusted to avoid commercial fishing vessels. In addition, the operation of commercial fishing vessels will also affect the deployment operation. Therefore, in this embodiment, the busyness of commercial fishing vessels is taken as one of the considerations for the deployment difficulty coefficient. The busyness of commercial fishing vessels can be expressed as the frequency of commercial fishing vessels passing by, which is calculated based on the number of commercial fishing vessels passing by the deployment point within a certain period of time in history. For example, a circular area with a radius of 5m with the deployment point as the center is used as the statistical area. The total number of commercial fishing vessels passing through the statistical area within seven days before the current moment is counted, and the number is used as a quantitative indicator of the busyness of commercial fishing vessels. The larger the number, the busier the commercial fishing vessels are, and the higher the corresponding deployment difficulty coefficient.

[0100] The weights ω1, ω2, and ω3 can be designed according to the actual situation and the influence of various factors on the deployment difficulty, for example, 40%, 40%, and 20%.

[0101] In a specific embodiment,

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

[0103]

[0104] Where n represents the total number of deployment points;

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

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

[0107] SS i =-ω4*Ssc i -ω5*Sbf i +ω6*Cwr;

[0108] 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;

[0109] Specifically, the sea state score is used to indicate the intensity of sea state changes (whether the sea is calm). The intensity of sea state changes will affect the stability of the buoy after deployment. When the sea state changes more drastically, it may cause the buoy to be damaged or dislocated. The intensity of sea state changes has certain regularity. For example, in the absence of sudden weather events, the intensity of the sea will not change significantly within a period of time. At least, for deployment points where the sea state changes have always been more drastic in the past period of time, it can be predicted that the stability after the buoy is deployed will be poor.

[0110] Therefore, the severity of the changes in the sea area can be represented by the historical hydrological and meteorological data of the deployment point, for example, the hydrological and meteorological data within three days before the current moment, which are specifically reflected in wind speed, wave size, wave height, wave period and wave direction, and one or more of them are selected to represent the severity of the sea conditions. In specific operations, the expert scoring method can be adopted, for example, the deployment personnel can score based on the data of each deployment point, or the data summation method can be adopted, for example, the weighted summation of several selected data is performed to obtain a quantitative indicator that characterizes the severity of the sea condition changes. The stability of the deployment point can be numerically expressed by this indicator. In this embodiment, the sea condition score is proportional to the severity of the sea condition changes, and inversely proportional to the stability coefficient of the deployment point. Therefore, the weight ω4 in the above formula takes 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 and shells, it will greatly increase the weight of the buoy and destroy the mechanical structure of the buoy. It may also cause corrosion and damage to the buoy surface, 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, the expert evaluation method is mainly used. The specific method is to obtain the environmental factors of each deployment point, such as water temperature, salinity, dissolved oxygen and other parameters, bottom type, such as mud, rock or coral reef, and 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 the 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 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 biological attachment severity value will be, and the greater the impact on the stability of the deployment point after deployment. Therefore, the weight ω5 in the above formula takes 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 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 ω6 in the above formula takes a positive sign.

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

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

[0115]

[0116] Where n represents the total number of deployment points.

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

[0118] 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;

[0119] Specifically, the above three parameters are analyzed in combination with the actual application process. Based on the deduction of the greedy algorithm, the monitoring coverage of each alternative deployment scheme is relatively close, and the difference is not large. Comparing the two parameters of the total deployment difficulty coefficient and the total stability coefficient, the total stability coefficient is the core indicator for the selection of the buoy deployment scheme. First of all, if the stability of the buoy is not good after deployment, it may affect the monitoring effect and make it impossible to accurately collect data. More importantly, it may cause the buoy to be dislocated or even damaged, causing great losses. Therefore, among the above three parameters, the total stability coefficient should be given priority. The specific approach is as follows:

[0120] The total stability coefficient SS of each alternative layout scheme is compared 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 In this step, the solutions that do not meet the stability requirements are first eliminated to avoid great instability after the buoys are deployed, which may cause losses.

[0121] The selection index S1 of the retained alternative layout scheme is calculated according to the following formula:

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

[0123] 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;

[0124] The monitoring coverage rate is 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 target sea area that can be covered by the monitoring range of the alternative deployment plan.

[0125] Among the reserved alternative deployment schemes, the alternative deployment scheme with the highest selection index S1 is selected as the buoy deployment scheme output. Specifically, the specific values ​​of coefficients a and b can be configured according to the importance of the two factors, and this embodiment does not limit this.

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

[0127] Based on the position information of each buoy deployment point in the buoy deployment plan, a buoy recovery path is generated and output.

[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 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.

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

[0143] Assume that there are 4 buoys that need to be recovered in the target sea area, each buoy has its corresponding deployment point, and the suitable operation window period for each point is different.

[0144] Encode each buoy:

[0145] The individual codes represent the recycling routes and the time periods during which the recycling operations are performed.

[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, taking into account path length and operability:

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

[0150] Path length weight and operability weight are pre-set parameters used to adjust the relative importance of 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 sailed distance.

[0153] Workability penalty calculation:

[0154] The operability penalty is calculated based on whether the time period spent at each deployment point on the planned path (i.e., the time period for performing the recovery operation) is within the operation window of the point:

[0155] If the time period for a deployment point to stay is not within the corresponding operation window, a larger penalty value will be added.

[0156] If the time period for all deployment points to stay is within the operation window, the stability penalty is 0.

[0157] Constraint handling:

[0158] A penalty function is used to deal with solutions that do not meet the workability conditions, or genetic operations are used to ensure that the offspring solutions meet the workability conditions.

[0159] Examples of genetic operations are as follows:

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

[0161] Crossover: When choosing the crossover point, ensure that the individuals after the crossover still remain within the workability window for a period of time.

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

[0163] Through such design and operation, the genetic algorithm can effectively search for a recovery path that satisfies both the shortest path and operability matching.

[0164] This embodiment also provides a buoy automatic 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] 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;

[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 each grid center as a candidate deployment point for the buoy; and construct a buoy model based on the buoy parameters;

[0168] 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;

[0169] 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;

[0170] 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;

[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 deployment point in the buoy deployment plan.

[0172] The system of this embodiment and the above-mentioned method belong to the same inventive concept, which can be understood with reference to the above description and will not be described in detail here.

[0173] like Figure 2 As shown, this embodiment also provides a computer device, including a processor 101 and a memory 102 connected by bus signals, wherein the memory 102 stores at least one instruction or at least one program, and when the at least one instruction or at least one program is loaded by the processor 101, the buoy automatic deployment and recovery method as described above is executed. The memory 102 can be used to store software programs and modules, and the processor 101 executes various functional applications by running the software programs and modules stored in the memory 102. The memory 102 can mainly include a program storage area and a data storage area, wherein 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 a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, 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 in the embodiments of the present application can be executed in a computer terminal, a server or a similar computing device, that is, the above-mentioned computer device can include a computer terminal, a server or a similar computing device. The internal structure of the computer device may 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 via 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 a memory device in the computer device for storing programs and data. It can be understood that the memory 102 here can be a high-speed RAM storage device, or a non-volatile storage device (non-volatile memory), such as at least one disk storage device; optionally, it can also be at least one storage device located away from the aforementioned processor 101. The memory 102 provides a storage space, which 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 (Android, a mobile operating system) system, IOS (a mobile operating system) system, etc., and this application does not limit this; and, in the storage space, one or more instructions suitable for being loaded and executed by the processor 101 are also stored, and these instructions can be one or more computer programs (including program codes). In the embodiment of the present specification, the processor 101 loads and executes one or more instructions stored in the memory 102 to implement the automatic deployment and recovery method of the buoy described in the above method embodiment.

[0176] The embodiment of the present application also provides a computer-readable storage medium, on which at least one instruction or at least one program is stored, and when the at least one instruction or the at least one program is loaded by the processor 101, the above-mentioned buoy automatic deployment and recovery method is executed. The above-mentioned computer-readable storage medium carries one or more programs, and when the above-mentioned one or more programs are executed, the method according to the embodiment of the present application is implemented.

[0177] According to an embodiment of the present application, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0178] In the description of the present application, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction, and therefore cannot be understood as limiting the scope of protection of the present application.

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