Cable Tensioning System Based on Multi-Source Input and Mooring Structure Motion Control Method

Abstract

This application relates to the technical field of mooring control methods, and specifically relates to a cable tensioning system based on multi-source input and a mooring structure motion control method. By integrating various environmental data, this application improves the adaptability and accuracy of the predicted data. Measures are taken in a timely manner by monitoring the tension data to ensure the safety of the mooring structure. A combined model of CNN and GRU or CNN and LSTM is used to obtain mooring motion control reference data. By sampling the continuous attitude data and calculating the difference ratio, the predicted data of the median difference is extracted as the median data, avoiding the influence of extreme values and improving the stability and reliability of the prediction.

Description

Technical Field

[0001] The present application relates to the technical field of mooring control methods, and particularly to a cable tensioning system based on multi-source input and a mooring structure motion control method. Background Art

[0002] In a mooring structure, the stable control of the mooring structure is a complex and crucial issue. Especially when facing severe sea conditions and extreme environmental conditions, the marine environmental forces, including waves, ocean currents, wind forces, and the change of ocean tide levels, all have a significant impact on the mooring structure. The action of these forces will cause the moored ship to produce complex motion responses, such as swaying, heaving, and drifting. In some sea conditions, these forces may cause the mooring cables to break, thus affecting the safety of ship operations. How to predict the ship's attitude based on environmental data and adjust the ship's attitude according to the predicted attitude data to improve the stability of the mooring structure is a technical problem to be solved in this field. Summary of the Invention

[0003] In view of this, the present application provides a cable tensioning system based on multi-source input and a mooring structure motion control method, which can predict the ship's attitude based on environmental data and adjust the ship's attitude according to the predicted attitude data, thereby improving the stability of the mooring structure.

[0004] In a first aspect, a mooring structure motion control method based on multi-source input provided by the present application includes: obtaining tidal data, wind force data, and cable tension data; obtaining the monitored tension values of each cable according to the cable tension data; if it is determined that at least one of the monitored tension values is greater than a preset tension, simultaneously start paying out the ropes of each cable; if it is determined that each of the monitored tension values is less than the preset tension, perform the following steps: stop paying out the ropes of each cable, import the tidal data and the wind force data into an attitude simulation model, calculate attitude prediction data within a preset future time period; sample multiple prediction data from the attitude prediction data; respectively compare the multiple difference ratios between the multiple prediction data and the standard data; extract the prediction data with the median difference ratio among the multiple difference ratios and mark it as the median data; compare the deviation degree between the median data and the standard data to generate attitude compensation data; and pay out and take in the cables according to the attitude compensation data to feedback control the current attitude and change towards the opposite attitude of the deviation attitude of the median data relative to the standard data.

[0005] Combined with the first aspect, in a possible implementation manner, stopping paying out the ropes of each cable, importing the tidal data and the wind power data into the attitude simulation model, and calculating the attitude prediction data within a preset future time period includes: obtaining wave data based on the tidal data and the wind power data; acquiring the historical attitude at a historical preset moment and the current attitude at the current moment; and performing ship attitude prediction based on the wave data, the historical attitude, and the current attitude by using a combined model of CNN and GRU or CNN and LSTM to obtain the attitude prediction data.

[0006] Combined with the first aspect, in a possible implementation manner, it further includes: obtaining loading and unloading data; obtaining ship position lifting data based on the loading and unloading data; converting the length of the ropes paid out and retrieved according to the ship position lifting data and the coefficient of paying out and retrieving the ropes; and paying out and retrieving the ropes of each cable simultaneously based on the length of the ropes paid out and retrieved.

[0007] Combined with the first aspect, in a possible implementation manner, sampling a plurality of prediction data from the attitude prediction data includes: equally dividing the preset future time period at a preset step length to obtain a plurality of time nodes; and extracting the plurality of prediction data corresponding to the plurality of time nodes.

[0008] Combined with the first aspect, in a possible implementation manner, comparing the deviation degree between the median data and the standard data to generate attitude compensation data includes: if the median data is relative to the standard data and the predicted ship heading corresponds to a value higher than the standard attitude of the ship heading, obtaining a first heading deviation degree and generating first compensation data; at this time, according to the attitude compensation data, paying out and retrieving the cables to feedback control the current attitude and changing towards the opposite attitude of the deviation attitude of the median data relative to the standard data includes: according to the first compensation data, tightening the head cable and the head back cable, paying out the tail cable and the tail back cable, and performing feedback control until the ship heading decreases by an amplitude corresponding to the first heading deviation degree within the preset future time period; or; comparing the deviation degree between the median data and the standard data to generate attitude compensation data includes: if the median data is relative to the standard data and the predicted ship heading corresponds to a value lower than the standard attitude of the ship heading, obtaining a second attitude deviation degree and generating second compensation data; at this time, according to the attitude compensation data, paying out and retrieving the cables to feedback control the current attitude and changing towards the opposite attitude of the deviation attitude of the median data relative to the standard data includes: according to the second compensation data, paying out the head cable and the head back cable, tightening the tail cable and the tail back cable, and performing feedback control until the ship heading increases by an amplitude corresponding to the second attitude deviation degree within the preset future time period.

[0009] In combination with the first aspect, in a possible implementation manner, during the execution of tightening the head cable and the head back cable and paying out the tail cable and the tail back cable according to the first compensation data and performing feedback control until the ship's heading decreases by an amplitude corresponding to the first heading deviation within the future preset time period, the method further includes: synchronously tightening the head cross cable based on a first speed proportionality coefficient, and synchronously paying out the tail cross cable based on a second speed proportionality coefficient; wherein, the first speed proportionality coefficient is proportional to the ship-shore rope length ratio of the head cross cable and the head cable, and the second speed proportionality coefficient is proportional to the ship-shore rope length ratio of the tail cross cable and the tail cable.

[0010] In combination with the first aspect, in a possible implementation manner, during the execution of paying out the head cable and the head back cable and tightening the tail cable and the tail back cable according to the second compensation data and performing feedback control until the ship's heading increases by an amplitude corresponding to the second attitude deviation within the future preset time period, the method further includes: synchronously paying out the head cross cable based on a third speed proportionality coefficient, and synchronously tightening the tail cross cable based on a fourth speed proportionality coefficient; wherein, the third speed proportionality coefficient is proportional to the ship-shore rope length ratio of the head cross cable and the head cable, and the fourth speed proportionality coefficient is proportional to the ship-shore rope length ratio of the tail cross cable and the tail cable.

[0011] In combination with the first aspect, in a possible implementation manner, the step of simultaneously paying out each cable when it is determined that at least one of the monitored tension values is greater than the preset tension includes: setting a payout step size; and paying out each cable intermittently at the payout step size.

[0012] In combination with the first aspect, in a possible implementation manner, the step of paying out each cable intermittently at the payout step size includes: when performing a single payout at the payout step size, continuously detecting the cable tension data for a preset detection duration; calculating the average tension of the cable tension data within the preset detection duration; and sampling the average tension and collecting it into the dataset of the monitored tension values.

[0013] Second aspect, the present application provides a cable tensioning system based on multi-source input, including: a data acquisition module configured to: acquire tidal data, wind force data, and cable tension data; obtain the monitored tension values of each cable according to the cable tension data; a tension regulation module communicatively connected to the data acquisition module, the tension regulation module configured to: if it is determined that at least one of the monitored tension values is greater than a preset tension, start paying out the ropes of each cable simultaneously; an attitude control module communicatively connected to the data acquisition module, the attitude control module configured to: if it is determined that each of the monitored tension values is less than the preset tension, perform the following steps: stop paying out the ropes of each cable, import the tidal data and the wind force data into an attitude simulation model, calculate the attitude prediction data within a preset time period in the future; sample multiple prediction data from the attitude prediction data; respectively compare the multiple difference ratios between the multiple prediction data and the standard data; extract the prediction data with the median difference ratio among the multiple difference ratios and mark it as the median data; compare the deviation degree between the median data and the standard data to generate attitude compensation data; and pay in and out the cable according to the attitude compensation data to feedback control the current attitude and change towards the opposite attitude of the deviation attitude of the median data relative to the standard data.

[0014] The present application has the following technical effects when applied: By integrating various environmental and structural data such as tides, wind forces, and cable tensions, the present application improves the adaptability and accuracy of the motion control of the mooring structure. By monitoring the cable tension data, it is possible to determine in real time whether the cable is approaching the preset tension and take timely measures to pay out the cable to avoid cable breakage and ensure the safety of the mooring structure. Using a combined model of CNN and GRU or CNN and LSTM or CNN and LSTM for ship attitude prediction, by sampling continuous attitude data and calculating the difference ratios, the prediction data with the median difference ratio is extracted as the median data, avoiding the influence of extreme values and improving the stability and reliability of the prediction. According to the deviation degree between the median data and the standard data, attitude compensation data is generated, and the cable is adjusted accordingly to realize the pre-adjustment of the feedback control of the ship attitude, enabling it to resist environmental changes and maintain the standard attitude. Combining the loading and unloading data, predicting the lifting and lowering of the ship position, and adjusting the payout length accordingly to avoid changes in the ship attitude caused by cable dragging when the ship position changes. Through the present application, by integrating multi-source data, prediction models, and feedback control technologies, the stable pre-control of the ship attitude is realized, the stability and safety of the mooring structure are improved, and the influence of environmental changes on the ship attitude is reduced. Description of the Drawings

[0015] Figure 1 The figure shows a schematic diagram of the method steps of a mooring structure motion control method based on multi-source input provided by an embodiment of the present application;

[0016] Figure 2 Shown is a schematic diagram of the method steps for predicting attitude based on wave data;

[0017] Figure 3 Shown is a schematic diagram of the method steps for controlling the rope winding and unwinding according to loading and unloading;

[0018] Figure 4 Shown is a schematic diagram of the calculation method for the corresponding relationship between ship position elevation data and rope unwinding length;

[0019] Figure 5 Shown is a schematic diagram of the method steps for dividing a future preset time period into multiple time nodes and extracting corresponding prediction data;

[0020] Figure 6 Shown is a schematic diagram of the method steps for reducing the ship's heading based on median data;

[0021] Figure 7 Shown is a schematic diagram of the ship's cable distribution;

[0022] Figure 8 Shown is a schematic diagram of the method steps for increasing the ship's heading based on median data;

[0023] Figure 9 Shown is a schematic diagram of the method steps for synchronously controlling the transverse cable when reducing the ship's heading;

[0024] Figure 10 Shown is a schematic diagram of the method steps for synchronously controlling the transverse cable when increasing the ship's heading;

[0025] Figure 11 Shown is a schematic diagram of the method steps for step-by-step rope unwinding;

[0026] Figure 12 Shown is a schematic diagram of the method steps for using the average tension as the monitored tension value when unwinding the rope;

[0027] Figure 13 Shown is a schematic diagram of the system structure of a cable tensioning system based on multi-source input;

[0028] Figure 14 Shown is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0029] Figure 7 Among them: 701, head cable; 702, head back cable; 703, tail cable; 704, tail back cable; 705, head transverse cable; 706, tail transverse cable. Detailed implementation manners

[0030] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without making creative efforts belong to the scope of protection of the present application.

[0031] Figure 1 The following is a schematic diagram of the method steps of a mooring structure motion control method based on multi-source input provided by an embodiment of the present application. The present application provides a mooring structure motion control method based on multi-source input. In one embodiment, as Figure 1 shown, the mooring structure motion control method based on multi-source input includes: Step 110, obtaining tidal data, wind data, and cable tension data.

[0032] In this step, the tidal data and wind data for a future period can be monitored through the weather system of the shore control center.

[0033] Step 120, obtaining the monitored tension values of each cable according to the cable tension data.

[0034] In Steps 110 and 120, capstans are provided at the bow and the ship position of the ship. The cables are wound around the capstans. The capstans can wind up the cables, and one end of the cable extends and is fixed on the shore. The capstans can monitor the tension values of each cable, or a tension detector can be independently set to monitor.

[0035] Step 130, determining whether at least one monitored tension value is greater than a preset tension. If the determination result of Step 130 is yes, then execute Step 140; if not, then start to execute Step 150 and subsequent steps. The preset tension can be set to be less than the breaking tension by 200N - 400N.

[0036] Step 140, simultaneously starting to pay out the ropes of each cable.

[0037] In Step 140, when at least one cable is approaching breakage, the ropes of each cable are simultaneously paid out to reduce the tension of the cables, and simultaneously paying out the ropes of each cable can avoid changes in the ship's attitude caused by asynchronous rope payout. For example, if there are 2 head ropes, 2 head back ropes, 2 head transverse ropes, 2 tail ropes, 2 tail back ropes, and 2 tail transverse ropes on the ship, then the above 12 cables are simultaneously paid out. A minimum tension limit can be set, and the rope payout stops until the tension of the cable reaches the minimum set range value. For example, if the breaking tension is 1300N and the preset tension is set to 1100N, the minimum set range value can be set to 600N - 900N.

[0038] Step 150: Stop paying out each cable, import the tidal data and wind data into the attitude simulation model, and calculate the attitude prediction data for a preset future time period.

[0039] In this step, an existing ship attitude prediction model can be used. For example, ADCIRC (An Advanced Circulation Model For Oceanic, Coastal and Estuarine Waters) or MATLAB can be used to model the wave data and simulate the waves, convert the tidal data and wind data into wave data, and then predict the ship attitude based on a combined model of CNN (Convolutional Neural Network) and GRU (Gated Recurrent Unit) to obtain the attitude prediction data. Alternatively, a combined model of CNN and LSTM (Long Short-Term Memory Network) can be used for attitude prediction. The CNN performs convolutional operations for feature extraction. Both the tidal data and wind data are environmental parameters in the model. The output of the CNN is used as the input of the LSTM for temporal feature learning, and finally the attitude prediction data is obtained. The preset future time period can be set to 3 minutes, 10 minutes, 15 minutes, etc. in the future.

[0040] Step 160: Sample multiple prediction data from the attitude prediction data.

[0041] Since the attitude prediction data obtained in Step 150 is continuous attitude data for a preset future time period, in Step 160, the continuous attitude data is sampled to obtain multiple discrete attitudes as multiple prediction data.

[0042] Step 170: Compare the multiple difference ratios between the multiple prediction data and the standard data respectively.

[0043] In this step, the standard data corresponding to the standard attitude of the ship is set in advance. For example, when the ship's deck is kept horizontal, it is set as the standard attitude. The attitude gaps between the attitudes corresponding to each sampled prediction data and the standard attitude are compared respectively, and the attitude gap is recorded as the difference ratio in this step. For example, 10 prediction data are sampled. Calculate the height difference between the ship's heading corresponding to the 3rd prediction data and the standard head attitude, and then calculate the ratio of this height difference to the deck-bottom distance as 1 / 25, and this ratio is recorded as the difference ratio, where the deck-bottom distance is the vertical distance from the deck to the bottom of the ship; calculate the height difference between the ship's heading corresponding to the 5th prediction data and the standard head attitude, and then calculate the ratio of this height difference to the deck-bottom distance as 1 / 28, and this ratio is recorded as the difference ratio.

[0044] Step 180: Extract the prediction data with the median difference ratio from the multiple difference ratios and mark it as the median data.

[0045] In this step, considering that the attitude prediction data obtained in step 150 is only through algorithms, the median prediction data is taken in this step to avoid too large or too small values. The prediction data corresponding to the median is relatively objective. Specifically, among all the sampled prediction data, one or two values of the difference ratio at the middle position are used as the median difference. For example, when sampling 10 prediction data, the prediction data is sorted according to the difference ratio from large to small: serial number 1, serial number 2, serial number 3, serial number 4, serial number 5, serial number 6, serial number 7, serial number 8, serial number 9, serial number 10. Serial number 5 and serial number 6 are the median differences, and any one of the prediction data of serial number 5 and serial number 6 is selected as the median data. Another example: the prediction data is sorted according to the difference ratio from large to small: serial number 1, serial number 2, serial number 3, serial number 4, serial number 5, serial number 6, serial number 7, serial number 8, serial number 9, serial number 10, serial number 11. Serial number 6 is the median difference, and the prediction data of serial number 6 is used as the median data.

[0046] Step 190: Compare the deviation degree between the median data and the standard data to generate attitude compensation data.

[0047] In this step, the median data and the standard data are used as the data comparison objects to obtain the deviation degree of the corresponding attitudes of the two, and the attitude compensation data is generated accordingly. For example, the height difference between the ship's bow direction corresponding to the median data and the standard head attitude, and the ratio to the deck-bottom distance is 4 / 25, then the deviation degree is 4 / 25, and the corresponding attitude compensation data is generated. Subsequently, the ship's attitude needs to be corrected according to the deviation degree.

[0048] Step 200: Pay out and take in the cable according to the attitude compensation data to feedback control the current attitude and change towards the opposite attitude of the deviation attitude of the median data relative to the standard data.

[0049] In this step, the cable payout and take-in are controlled according to the deviation degree to adjust the current attitude of the ship, so that the ship starts to change towards the opposite attitude of the deviation attitude in advance, so as to pre-resist the predicted future attitude change through the opposite movement, so that the ship can maintain the standard attitude within the preset future time period. For example, if the ship's bow is higher than the standard head attitude and the deviation degree is 4 / 25, the process of changing towards the opposite attitude is: gradually feedback control the ship's head to descend by the height corresponding to the 4 / 25 deviation degree through the cable payout and take-in to resist the future attitude change caused by tides and winds.

[0050] When this embodiment is applied, by obtaining tidal, wind, and cable tension data, this method can comprehensively consider the impacts of various environmental factors on the mooring structure, improving the adaptability and accuracy of the control method. By monitoring the cable tension data, it is possible to determine in real time whether the cable is approaching the preset tension and take timely measures, such as cable releasing operations, to avoid cable breakage and ensure the safety of the mooring structure. By integrating tidal and wind data and combining with a ship attitude prediction model (such as a combined model of CNN and GRU, or CNN and LSTM, or LSTM), it is possible to predict the attitude changes of the ship within a preset time period in the future, providing a basis for subsequent attitude adjustments. By sampling continuous attitude data and calculating the difference ratio, and extracting the predicted data of the median difference as the median data, it is possible to avoid the influence of extreme values to a certain extent and improve the stability and reliability of the prediction. According to the deviation degree between the median data and the standard data, attitude compensation data is generated, and based on this, the cable winding and unwinding are adjusted to achieve feedback control of the ship's attitude, enabling it to resist environmental changes and maintain the standard attitude. In summary, this embodiment can maintain the stable attitude of the ship within a certain time period in the future, reduce the ship attitude fluctuations caused by environmental changes, and improve the stability and safety of the mooring structure when the ship is docked.

[0051] Figure 2 The following shows a schematic diagram of the method steps for predicting the attitude based on wave data. In one embodiment, as Figure 2 shown, step 150 includes: Step 1501, obtaining wave data based on tidal data and wind data.

[0052] In this step, ADCIRC (An Advanced Circulation Model For Oceanic, Coastal and Estuarine Waters) or MATLAB can be used for wave data modeling and wave simulation. The ADCIRC model is an ocean hydrodynamic calculation model, which can collect tidal data and wind data in combination with Python to obtain wave data based on tides and winds. ADCIRC is widely used in predicting wave data based on tides and winds. MATLAB can also be used for wave data simulation. For example, according to the linear wave theory, taking tidal data and wind data as code parameters to generate a wave simulation model to know the wave data caused by future tidal data and wind data.

[0053] Step 1502, obtaining the historical attitude at a historical preset moment and the current attitude at the current moment.

[0054] Step 1503, based on the wave data, historical attitude, and current attitude, performing ship attitude prediction using a combined model of CNN and GRU or CNN and LSTM to obtain attitude prediction data.

[0055] In this embodiment, when predicting the ship's attitude, continuous attitude change data can be combined with wave data for prediction. Considering the influence of waves on the ship's movement, a model that can reflect the actual marine environmental conditions is created through the process of obtaining wave data based on tidal data and wind data. The attitude data of the ship at past time points and the current attitude data are collected as part of the input to the attitude prediction model. A model combining CNN and GRU or CNN and LSTM is used, where CNN is used to extract features, and GRU or LSTM is used to process time series data, so as to more accurately predict the ship's attitude.

[0056] Figure 3 The figure shows a schematic diagram of the method steps for controlling the rope retraction and extension according to loading and unloading. In one embodiment, as Figure 3 shown, the mooring structure motion control method based on multi-source input further includes:

[0057] Step 210: Obtain loading and unloading data;

[0058] Step 220: Obtain the ship position lifting data according to the loading and unloading data;

[0059] Step 230: Convert the rope retraction and extension length according to the ship position lifting data and the rope retraction and extension coefficient;

[0060] Step 240: Simultaneously retract and extend each cable based on the rope retraction and extension length.

[0061] When this embodiment is applied, the loading and unloading data includes the weight of the goods. The lifting and lowering data of the ship's draft caused by the weight of the goods during loading and unloading is pre-calculated, and the corresponding ship position lifting data can be obtained according to the current loading and unloading data. When the ship position rises and falls, it will inevitably bring about a change in the distance between the winch on the ship and the cable fixing post on the shore. According to the hull size data of the ship, the corresponding relationship between the change in the ship's draft and the rope retraction and extension length can be calculated, that is, the corresponding relationship between the ship position lifting data and the rope retraction and extension length. The corresponding relationship is the rope retraction and extension coefficient. By simultaneously retracting and extending each cable according to the rope retraction and extension length, the ship's attitude will not change due to cable dragging when the ship position rises and falls.

[0062] Figure 4 The figure shows a schematic diagram of the calculation method of the corresponding relationship between the ship position lifting data and the rope extension length. Specifically, in combination with Figure 4 it explains the calculation method of the corresponding relationship between the ship position lifting data and the rope extension length. Figure 4The relative vertical height between the ship's deck and the shore ground is h, the length of the cable between the edge of the ship's deck and the shore cable fixing post is s, and the horizontal distance L between the edge of the ship's deck and the shore cable fixing post remains unchanged when the ship's loading and unloading position is lifted or lowered. During loading and unloading, the relative vertical height h changes. The change value of the relative vertical height h can be measured through visual measurement by an on-board camera. Since the horizontal distance L remains unchanged, the change value of the cable length s can be obtained from the change value of the relative vertical height h through trigonometric calculation. The trigonometric conversion formula is the cable winding and unwinding coefficient in step 230.

[0063] Figure 5 The figure shows a schematic diagram of the method steps for dividing a future preset time period into multiple time nodes and extracting corresponding prediction data. In one embodiment, as Figure 5 shown, step 160 includes:

[0064] Step 1601: Evenly divide the future preset time period according to a preset step size to obtain multiple time nodes;

[0065] Step 1602: Extract multiple prediction data corresponding to the multiple time nodes.

[0066] When this embodiment is applied, evenly dividing the future preset time period according to a preset step size can obtain a series of time nodes. It can ensure the continuity and uniformity of time series data during the prediction process, thereby improving the accuracy and reliability of the prediction. By extracting the prediction data corresponding to multiple time nodes, the continuous prediction data can be decomposed into discrete and easily processed multiple data points. And sampling multiple prediction data can reduce the subsequent data processing volume to a certain extent.

[0067] Figure 6 The figure shows a schematic diagram of the method steps for reducing the ship's heading according to the median data. In one embodiment, as Figure 6 shown, step 190 includes: Step 1901: If the median data is higher than the ship's heading standard attitude corresponding to the ship's predicted heading relative to the standard data, obtain the first heading deviation degree and generate the first compensation data.

[0068] Step 200 includes: Step 2001: According to the first compensation data, tighten the head cable and the head backstay, and release the tail cable and the tail backstay, and feedback control until the ship's heading decreases by the amplitude corresponding to the first heading deviation degree within the future preset time period.

[0069] When this embodiment is applied, by comparing the median data with the standard data, it can be determined whether the predicted heading of the ship is higher than the standard attitude, and accordingly, the amplitude corresponding to the first heading deviation degree of the excess can be calculated. When the head height of the predicted ship attitude is higher than the head height of the standard attitude, the ship's head is pre-lowered. The head rope, the head back rope, the tail rope, and the tail back rope are respectively connected to different cable machines, that is, the head rope and the head back rope are tightened and the tail rope and the tail back rope are payed out, and closed-loop feedback control is performed, that is, the head rope and the head back rope are gradually tightened and the tail rope and the tail back rope are payed out until the ship's head is lowered by the amplitude corresponding to the first heading deviation degree. For example, if the predicted heading of the ship is 3° higher than the standard attitude of the ship's heading, that is, the relative inclination angle between the predicted attitude of the ship and the standard attitude is 3°, then the opposite attitude of the deviation attitude of the median data relative to the standard data is that the ship's heading is 3° lower than the standard attitude of the ship's heading. That is, the ship's heading is lowered by the first heading deviation degree within a preset future time period, corresponding to the ship's heading being lowered by 3° within a preset future time period. Figure 7 The figure shows a schematic diagram of the ship's cable distribution. In combination with Figure 7 As shown in the figure, by tightening the head rope 701 and the head back rope 702 and paying out the tail rope 703 and the tail back rope 704, the ship's head is gradually lowered and the ship's tail is raised, so as to pre-adjust the ship's attitude to pre-resist the predicted future attitude change.

[0070] Figure 8 The figure shows a schematic diagram of the method steps for raising the ship's heading according to the median data. In one embodiment, as Figure 8 shown, step 190 includes: step 1902, if the median data corresponds to the ship's predicted heading being lower than the standard attitude of the ship's heading relative to the standard data, then obtain the second attitude deviation degree and generate the second compensation data.

[0071] Step 200 includes: step 2002, according to the second compensation data, pay out the head rope and the head back rope, tighten the tail rope and the tail back rope, and perform feedback control until the ship's heading is raised by the amplitude corresponding to the second attitude deviation degree within a preset future time period.

[0072] When this embodiment is applied, by comparing the median data with the standard data, it can be determined whether the predicted heading of the ship is lower than the standard attitude, and accordingly, the amplitude corresponding to the second attitude deviation of sinking is calculated. When the head height of the predicted ship attitude is lower than the head height of the standard attitude, the ship's tail is pulled down in advance. The head rope, the head back rope, the tail rope, and the tail back rope are respectively connected to different cable machines, that is, the tail rope and the tail back rope are tightened and the head rope and the head back rope are paid out, and closed-loop feedback control is executed, that is, the tail rope and the tail back rope are gradually tightened and the head rope and the head back rope are paid out until the ship's head is raised by the amplitude corresponding to the second attitude deviation. For example, if the predicted heading of the ship is 2° lower than the standard attitude of the ship's heading, that is, the relative tilt angle between the predicted attitude of the ship and the standard attitude is 2°, then the opposite attitude of the deviation attitude of the median data relative to the standard data is that the ship's heading is 2° higher than the standard attitude of the ship's heading. That is, the ship's heading is raised by the first heading deviation within a preset future time period, corresponding to the ship's heading being raised by 2° within a preset future time period. Combined with Figure 7 As shown, by paying out the head rope 701 and the head back rope 702 and tightening the tail rope 703 and the tail back rope 704, the ship's tail is gradually pulled down and the ship's head is raised, realizing pre-adjustment of the ship's attitude to resist the predicted future attitude change in advance.

[0073] Figure 9 The figure shows a schematic diagram of the method steps for synchronously controlling the cross cable when reducing the ship's heading. In one embodiment, as Figure 9 shown, during the execution of step 2001, the method further includes: step S101, synchronously tightening the head cross cable based on the first speed proportionality coefficient and synchronously paying out the tail cross cable based on the second speed proportionality coefficient.

[0074] In this step, combined with Figure 7 , the first speed proportionality coefficient is proportional to the ship-shore rope length ratio of the head cross cable 705 and the head rope, and the second speed proportionality coefficient is proportional to the ship-shore rope length ratio of the tail cross cable 706 and the tail rope. Since the head cross cable 705 is basically perpendicular to the head rope and the head back rope, and the tail cross cable 706 is basically perpendicular to the tail rope and the tail back rope. By synchronously tightening the head cross cable 705, the ship's attitude can be assisted in stabilizing during the process of tightening the head rope and the head back rope, and tightening according to the rope length ratio of the head cross cable 705 and the head rope can avoid excessive or insufficient rope winding. Synchronously paying out the tail cross cable 706 can assist in stabilizing the ship's attitude during the process of paying out the tail rope and the tail back rope, and paying out according to the rope length ratio of the tail cross cable 706 and the tail rope can avoid excessive or insufficient rope paying out.

[0075] Figure 10 The figure shows a schematic diagram of the method steps for synchronously controlling the cross cable when raising the ship's heading. In one embodiment, as Figure 10As shown, during the execution of step 2002, the method further includes: step S201, synchronously paying out the head cross cable based on the third speed ratio coefficient, and synchronously tightening the tail cross cable based on the fourth speed ratio coefficient.

[0076] In this step, in combination with Figure 7 , the third speed ratio coefficient is proportional to the ratio of the ship-shore rope length of the head cross cable 705 and the head cable, and the fourth speed ratio coefficient is proportional to the ratio of the ship-shore rope length of the tail cross cable 706 and the tail cable. Since the head cross cable 705 is substantially perpendicular to the head cable and the head backstay, and the tail cross cable 706 is substantially perpendicular to the tail cable and the tail backstay. By synchronously paying out the head cross cable 705, the ship's attitude can be assisted in stabilizing during the process of paying out the head cable and the head backstay, and paying out the cable according to the ratio of the rope lengths of the head cross cable 705 and the head cable can avoid overpaying or underpaying the cable. Synchronously tightening the tail cross cable 706 can assist in stabilizing the ship's attitude during the process of tightening the tail cable and the tail backstay, and taking in the cable according to the ratio of the rope lengths of the tail cross cable 706 and the tail cable can avoid over-taking in or under-taking in the cable.

[0077] Figure 11 The figure shows a schematic diagram of the method steps of step-by-step cable paying. In one embodiment, as Figure 11 shown, steps 130 and 140 include: step S401, setting the cable paying step length.

[0078] Step S402, intermittently paying out each cable with the cable paying step length.

[0079] In this embodiment, through step-by-step cable paying, after each cable is paid out, the self-structure of the cable has enough time to stabilize the tension, so as to more accurately detect the tension value of the cable.

[0080] Figure 12 The figure shows a schematic diagram of the method steps of using the average tension as the monitored tension value during cable paying. In one embodiment, as Figure 12 shown, step S401 includes:

[0081] Step S4011, when performing a single cable paying with the cable paying step length, continuously detecting the cable tension data for a preset detection duration;

[0082] Step S4012, calculating the average tension of the cable tension data within the preset detection duration;

[0083] Step S4013, sampling the average tension and collecting it into the dataset of the monitored tension value.

[0084] In this embodiment, after a single rope pay-out, the rope pay-out operation is stopped and the tension of the cable is detected for a preset detection duration, so as to obtain more accurate cable tension data. After a single rope pay-out, the cable will be in a state of unstable tension. The average tension is obtained by taking the average value from the continuously detected cable tension. In step S4013, the average tension is collected. Subsequently, the average tension can be directly used as the monitored tension value in steps 120 and 130, so as to judge the condition of the cable according to the average tension. In some embodiments, a minimum tension value range is set. When the rope is paid out to the point where the cable tension reaches the minimum set range value in step S402, the rope pay-out for the cable is stopped.

[0085] Figure 13 The following shows a schematic structural diagram of a cable tensioning system based on multi-source input. The present application also provides a cable tensioning system based on multi-source input. In one embodiment, as Figure 13 shown, the cable tensioning system based on multi-source input includes: a data acquisition module 1301, a tension regulation module 1302, and an attitude control module 1303.

[0086] The data acquisition module 1301 is configured to: acquire tidal data, wind force data, and cable tension data; and obtain the monitored tension value of each cable according to the cable tension data.

[0087] The tension regulation module 1302 is communicatively connected to the data acquisition module 1301. The tension regulation module 1302 is configured to: if it is determined that at least one monitored tension value is greater than a preset pulling force, start paying out each cable simultaneously.

[0088] The attitude control module 1303 is communicatively connected to the data acquisition module 1301. The attitude control module 1303 is configured to: if it is determined that each monitored tension value is less than the preset pulling force, perform the following steps: stop paying out each cable, import the tidal data and wind force data into an attitude simulation model, calculate the attitude prediction data within a preset future time period; sample multiple prediction data from the attitude prediction data; respectively compare the multiple difference ratios between the multiple prediction data and the standard data; extract the prediction data with the median difference ratio from the multiple difference ratios and mark it as the median data; compare the deviation degree between the median data and the standard data to generate attitude compensation data; and pay out and wind in the cable according to the attitude compensation data to feedback control the current attitude and change it towards the opposite attitude of the deviation attitude of the median data relative to the standard data.

[0089] The present application has the following technical effects when applied: By integrating various environmental and structural data such as tides, wind forces, and cable tensions, the present application improves the adaptability and accuracy of the motion control of the mooring structure. By monitoring the cable tension data, it is possible to determine in real time whether the cable is approaching the preset tension and take timely measures to release the cable to avoid cable breakage and ensure the safety of the mooring structure. A combined model of CNN and GRU or CNN and LSTM or CNN and LSTM is used for ship attitude prediction. By sampling continuous attitude data and calculating the differential ratio, the predicted data of the median differential is extracted as the median data, avoiding the influence of extreme values and improving the stability and reliability of the prediction. According to the deviation degree between the median data and the standard data, attitude compensation data is generated, and the cable winding and unwinding are adjusted accordingly, realizing the pre-adjustment of the feedback control of the ship attitude, enabling it to resist environmental changes and maintain the standard attitude. Combining the loading and unloading data, the ship position lift is predicted, and the cable release length is adjusted accordingly, avoiding the change of the ship attitude caused by the cable drag when the ship position changes. Through the present application, by integrating multi-source data, prediction models, and feedback control technologies, the stable pre-control of the ship attitude is realized, the stability and safety of the mooring structure are improved, and the influence of environmental changes on the ship attitude is reduced.

[0090] Next, reference is made to Figure 14 to describe the electronic device according to an embodiment of the present application. Figure 14 The following shows a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0091] As Figure 14 shown, the electronic device 1400 includes one or more processors 1401 and a memory 1402.

[0092] The processor 1401 may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 1400 to perform desired functions.

[0093] The memory 1402 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage media, and the processor 1401 may run the program instructions to implement the mooring structure motion control method based on multi-source input or other desired functions of the various embodiments of the present application described above. Various contents such as mooring structure motion control error parameters based on multi-source input may also be stored in the computer-readable storage media.

[0094] In one example, the electronic device 1400 may further include: an input device 1403 and an output device 1404, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0095] The input device 1403 may include, for example, a keyboard, a mouse, a joystick, a touch screen, and the like.

[0096] The output device 1404 may output various information to the outside, including the determined motion data, etc. The output device 1404 may include, for example, a display, a communication network, and remote output devices connected thereto, and the like.

[0097] Of course, for simplicity, Figure 14 only some of the components related to the present application in the electronic device 1400 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application scenarios, the electronic device 1400 may further include any other appropriate components.

[0098] In addition to the above methods and devices, the embodiments of the present application may also be a computer program product, which includes computer program instructions that, when run by a processor, cause the processor to execute the steps in the mooring structure motion control method based on multi-source input according to various embodiments of the present application described in this specification.

[0099] The computer program product may be written in any combination of one or more programming languages for programming code to perform the operations of the embodiments of the present application. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The programming code may be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0100] In addition, an embodiment of the present application may also be a computer-readable storage medium having computer program instructions stored thereon, and when the computer program instructions are run by a processor, the processor is caused to execute the steps in the mooring structure motion control method based on multi-source input according to various embodiments of the present specification.

[0101] The computer-readable storage medium may employ any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may, for example, include but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0102] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present application. In addition, the above-disclosed specific details are only for illustrative and facilitating understanding purposes, and not for limitation. The above details do not limit the present application to necessarily implement with the above specific details.

[0103] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any way. Words such as "including," "comprising," "having," etc. are open-ended terms that mean "including but not limited to" and can be used interchangeably with each other. The word "or" and "and" used herein refer to the phrase "and / or" and can be used interchangeably with it, unless the context clearly indicates otherwise. The phrase "such as" used herein refers to the phrase "such as but not limited to" and can be used interchangeably with it.

[0104] It should also be noted that in the devices, equipment, and methods of this application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of this application.

[0105] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0106] The above are only the preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent replacements, etc. made within the spirit and principles of this application shall be included within the protection scope of this application.

Claims

1. A method for controlling the motion of a moored structure based on multi-source input, characterized in that: include: Obtain tide data, wind data, and cable tension data; Obtaining a monitoring tension value of each cable according to the cable tension data; If it is determined that at least one of the monitored tension values ​​is greater than the preset tension, then the cables are simultaneously released; if it is determined that all of the monitored tension values ​​are less than the preset tension, the following steps are performed: stop releasing the cables, import the tidal data and the wind data into the attitude simulation model, and calculate the attitude prediction data within a preset time period in the future; sample multiple prediction data from the attitude prediction data; respectively compare multiple difference ratios of the multiple prediction data with the standard data; extract the prediction data with the median difference based on the multiple difference ratios and mark it as the median data; compare the deviation between the median data and the standard data to generate attitude compensation data; and reel in and release the cables according to the attitude compensation data to feedback control the current attitude, toward the desired direction. The median data is transformed to an opposite posture of the deviation posture of the standard data; the comparison of the deviation between the median data and the standard data to generate the posture compensation data includes: if the median data corresponds to a predicted bow of the ship higher than the standard bow posture of the ship relative to the standard data, a first bow deviation is obtained and a first compensation data is generated; at this time, the winding and releasing of the cable according to the posture compensation data to feedback control the current posture to transform to the opposite posture of the deviation posture of the median data relative to the standard data includes: tightening the head cable and the bow lay cable, releasing the stern cable and the stern lay cable according to the first compensation data, and feedback control until the bow of the ship is reduced by the amplitude corresponding to the first bow deviation within the future preset time period.

2. The method for controlling the motion of a moored structure based on multi-source input according to claim 1, characterized in that: The stopping of paying out each of the cables, importing the tidal data and the wind data into a posture simulation model, and calculating posture prediction data within a future preset time period include: obtaining wave data according to the tidal data and the wind data, or predicting future wave data based on artificial intelligence according to recorded historical wave data; obtaining historical postures at historical preset moments and current postures at the current moment; and predicting the ship posture based on a CNN and GRU or CNN and LSTM combination model according to the wave data, the historical postures and the current posture to obtain the posture prediction data.

3. The method for controlling the motion of a moored structure based on multi-source input according to claim 1, characterized in that: Also includes: Obtain loading and unloading data; Obtaining ship position lifting data according to the loading and unloading data; The length of the retractable rope is converted according to the ship position lifting data and the retractable rope coefficient; and the retractable ropes are simultaneously retracted and released for each of the cables based on the retractable rope length.

4. The method for controlling the motion of a moored structure based on multi-source input according to claim 1, characterized in that: The sampling of a plurality of prediction data from the posture prediction data includes: equally dividing the future preset time period according to a preset step length to obtain a plurality of time nodes; and extracting a plurality of the prediction data corresponding to the plurality of the time nodes.

5. The method for controlling the motion of a moored structure based on multi-source input according to claim 1, characterized in that: The comparing the deviation between the median data and the standard data to generate the attitude compensation data includes: if the median data is relative to the standard data, corresponding to the predicted bow of the ship being lower than the standard bow attitude of the ship, then a second attitude deviation is obtained and second compensation data is generated; at this time, the winding and releasing of the cable according to the attitude compensation data to feedback control the current attitude to transform to the attitude opposite to the deviation attitude of the median data relative to the standard data includes: according to the second compensation data, releasing the rope head cable and the bow cable, tightening the tail cable and the tail cable, and feedback control until the bow of the ship increases by an amplitude corresponding to the second attitude deviation within the future preset time period.

6. The method for controlling the motion of a moored structure based on multi-source input according to claim 1, characterized in that: The process of tightening the head cable and the bow lay cable, releasing the stern cable and the stern lay cable according to the first compensation data, and performing feedback control until the bow of the ship reduces the amplitude corresponding to the first bow deviation within the future preset time period, also includes: synchronously tightening the head transverse cable based on the first speed proportional coefficient, and synchronously releasing the stern transverse cable based on the second speed proportional coefficient; wherein the first speed proportional coefficient is proportional to the ship-to-shore rope length ratio of the head transverse cable and the head cable, and the second speed proportional coefficient is proportional to the ship-to-shore rope length ratio of the stern transverse cable and the stern cable.

7. The method for controlling the motion of a moored structure based on multi-source input according to claim 5, characterized in that: The process of releasing the head cable and the bow cable, tightening the stern cable and the stern cable according to the second compensation data, and performing feedback control until the bow of the ship increases by an amplitude corresponding to the second attitude deviation within the future preset time period, also includes: synchronously releasing the head transverse cable based on a third speed proportional coefficient, and synchronously tightening the stern transverse cable based on a fourth speed proportional coefficient; wherein the third speed proportional coefficient is proportional to the ratio of the ship-to-shore rope lengths of the head transverse cable and the head cable, and the fourth speed proportional coefficient is proportional to the ratio of the ship-to-shore rope lengths of the stern transverse cable and the stern cable.

8. The method for controlling the motion of a moored structure based on multi-source input according to claim 1, characterized in that: If it is determined that at least one of the monitored tension values ​​is greater than a preset tension, then simultaneously starting to release each cable includes: setting a release step length; and intermittently releasing each cable with the release step length.

9. The method for controlling the motion of a moored structure based on multi-source input according to claim 8, characterized in that: The intermittently releasing each cable at the releasing step length includes: continuously detecting the cable tension data for a preset detection time when performing a single release at the releasing step length; calculating the average tension of the cable tension data within the preset detection time length; and sampling the average tension and aggregating it into the data set of the monitored tension value.

10. A cable tensioning system based on multi-source input, characterized in that: include: A data acquisition module is configured to: acquire tide data, wind data, and cable tension data; Obtaining a monitoring tension value of each cable according to the cable tension data; A tension control module is connected in communication with the data acquisition module, and the tension control module is configured to: if it is determined that at least one of the monitored tension values ​​is greater than a preset tension, then the cables are simultaneously released; a posture control module is connected in communication with the data acquisition module, and the posture control module is configured to: if it is determined that each of the monitored tension values ​​is less than a preset tension, then the following steps are performed: stop releasing the cables, import the tidal data and the wind data into the posture simulation model, and calculate the posture prediction data within a preset time period in the future; sample a plurality of prediction data from the posture prediction data; respectively compare a plurality of difference ratios of the prediction data with the standard data; extract the prediction data with a median difference based on the plurality of difference ratios and mark it as median data; compare the deviation between the median data and the standard data, and generate a posture compensation compensation data; and winding and releasing the cable according to the attitude compensation data to feedback control the current attitude, and transforming to the opposite attitude of the deviation attitude of the median data relative to the standard data; the comparing the deviation between the median data and the standard data to generate the attitude compensation data includes: if the median data corresponds to a predicted bow of the ship higher than the standard bow attitude of the ship relative to the standard data, a first bow deviation is obtained and a first compensation data is generated; at this time, winding and releasing the cable according to the attitude compensation data to feedback control the current attitude, and transforming to the opposite attitude of the deviation attitude of the median data relative to the standard data includes: tightening the head cable and the bow lay cable, releasing the stern cable and the stern lay cable according to the first compensation data, and feedback controlling until the bow of the ship reduces the amplitude corresponding to the first bow deviation within the future preset time period.

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