Mooring rope tensioning system based on multi-source input and mooring structure motion control method

Abstract

The invention relates to the technical field of mooring control methods, in particular to a mooring rope tensioning system based on multi-source input and a mooring structure motion control method. According to the method, the adaptability and the accuracy of the prediction data are improved by integrating various environmental data. And measures are taken in time by monitoring tension data so as to ensure the safety of the mooring structure. Mooring motion control reference data are obtained by using a combined model of CNN and GRU or CNN and LSTM, continuous attitude data are sampled and difference proportion is calculated, and prediction data of median difference is extracted as median data, so that the influence of extreme values is avoided, and the stability and reliability of prediction are improved.

Description

Technical Field

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

[0002] In mooring structures, the stability control of mooring structures is a complex and critical issue, especially in the face of severe sea conditions and extreme environmental conditions. Marine environmental forces, including waves, currents, wind, and changes in ocean tides, have a significant impact on mooring structures. The action of these forces can cause moored vessels to produce complex motion responses, such as swaying, heaving, and drifting. In some sea conditions, these forces may cause mooring cables to break, thereby affecting the safety of ship operations. How to predict the ship's attitude based on environmental data and adjust the ship's attitude based on the predicted attitude data to improve the stability of the mooring structure is a technical problem that needs to be solved in this field. Summary of the invention

[0003] In view of this, the present application provides a cable tensioning system and a mooring structure motion control method based on multi-source input, which can predict the ship's attitude according to 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, the present application provides a method for motion control of a mooring structure based on multi-source input, comprising: acquiring tidal data, wind data, and cable tension data; obtaining a monitored tension value of each cable according to the cable tension data; starting to release each cable at the same time if at least one of the monitored tension values ​​is judged to be greater than a preset tension; executing the following steps if each of the monitored tension values ​​is judged to be less than the preset tension: stopping releasing each cable, importing the tidal data and the wind data into a posture simulation model, and calculating posture prediction data within a preset time period in the future; sampling a plurality of prediction data from the posture prediction data; respectively comparing a plurality of difference ratios between the plurality of prediction data and standard data; extracting the prediction data with a median difference based on the plurality of difference ratios and marking it as median data; comparing the deviation between the median data and the standard data to generate posture compensation data; and reeling in and out the cable according to the posture compensation data to feedback control the current posture, and transforming to the opposite posture of the deviation posture of the median data relative to the standard data.

[0005] In combination with the first aspect, in a possible implementation, the stopping of paying out each of the cables, importing the tidal data and the wind data into a posture simulation model, and calculating the posture prediction data for a preset time period in the future include: obtaining wave data based on the tidal data and the wind data; obtaining the historical posture at a preset historical moment and the current posture at a current moment; and predicting the ship's posture based on a CNN and GRU or CNN and LSTM combination model according to the wave data, the historical posture and the current posture to obtain the posture prediction data.

[0006] In combination with the first aspect, in a possible implementation method, it also includes: acquiring loading and unloading data; obtaining ship position lifting data based on the loading and unloading data; converting the length of the retractable rope according to the ship position lifting data and the retractable rope coefficient; and retracting and releasing the ropes of each cable at the same time based on the retractable rope length.

[0007] In combination with the first aspect, in a possible implementation method, sampling multiple prediction data from the posture prediction data includes: dividing the future preset time period equally according to a preset step size to obtain multiple time nodes; and extracting multiple prediction data corresponding to the multiple time nodes.

[0008] In combination with the first aspect, in a possible implementation, the comparison of the deviation between the median data and the standard data to generate attitude compensation data includes: if the median data relative to the standard data corresponds to a predicted bow of the ship being higher than the standard bow attitude of the ship, then a first bow deviation is obtained and first 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 opposite attitude of the deviation 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 reduces the first bow deviation within the future preset time period. The amplitude corresponding to the deviation; or; the comparison of 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 attitude of the bow 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 opposite attitude of 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 the amplitude corresponding to the second attitude deviation within the future preset time period.

[0009] In combination with the first aspect, in a possible implementation, during the execution 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 feedback controlling until the bow of the ship reduces the amplitude corresponding to the first bow deviation within the future preset time period, the method further 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 ratio of the ship-to-shore rope lengths of the head transverse cable and the head cable, and the second speed proportional coefficient is proportional to the ratio of the ship-to-shore rope lengths of the stern transverse cable and the stern cable.

[0010] In combination with the first aspect, in a possible implementation, during the execution of releasing the head cable and the bow cable, tightening the stern cable and the stern cable according to the second compensation data, and feedback controlling until the bow of the ship increases by an amplitude corresponding to the second attitude deviation within the future preset time period, the method further 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.

[0011] In combination with the first aspect, in a possible implementation, if it is determined that at least one of the monitored tension values ​​is greater than a preset tension, then starting to pay out each cable simultaneously includes: setting a pay-out step length; and intermittently paying out each cable with the pay-out step length.

[0012] In combination with the first aspect, in a possible implementation, the intermittently releasing each cable with the rope releasing step length includes: when performing a single rope releasing with the rope releasing step length, continuously detecting the cable tension data for a preset detection time; calculating the average tension of the cable tension data within the preset detection time; and sampling the average tension and aggregating it into the data set of the monitored tension value.

[0013] In a 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 data, and cable tension data; obtain a monitoring tension value of each cable according to the cable tension data; a tension regulation module, which is connected to the data acquisition module for communication, and the tension regulation module is configured to: start releasing each cable at the same time if it is determined that at least one of the monitoring tension values ​​is greater than a preset tension; a posture control module, which is connected to the data acquisition module for communication, and the posture control module is configured to: execute the following steps if it is determined that each of the monitoring tension values ​​is less than a preset tension: stop releasing each cable The cable is released, the tidal data and the wind data are imported into a posture simulation model to calculate the posture prediction data within a preset time period in the future; a plurality of prediction data are sampled from the posture prediction data; a plurality of difference ratios between the plurality of prediction data and the standard data are respectively compared; the prediction data with the median difference extracted based on the plurality of difference ratios is marked as the median data; the deviation between the median data and the standard data is compared to generate posture compensation data; and the cable is reeled in according to the posture compensation data to feedback control the current posture, and the posture is transformed to the opposite posture of the deviation of the median data relative to the standard data.

[0014] The present application has the following technical effects when applied: The present application improves the adaptability and accuracy of the motion control of the mooring structure by integrating various environmental and structural data such as tide, wind and cable tension. By monitoring the cable tension data, it is possible to judge in real time whether the cable is close to the preset tension, and take timely measures to release the cable to avoid cable breakage and ensure the safety of the mooring structure. The combined model of CNN and GRU or CNN and LSTM or CNN and LSTM is used to predict the ship's attitude. 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. According to the deviation between the median data and the standard data, the attitude compensation data is generated, and the winding and unwinding of the cable is adjusted accordingly, realizing the feedback control pre-adjustment of the ship's attitude, so that it can resist environmental changes and maintain the standard attitude. Combined with the loading and unloading data, the ship's position rise and fall is predicted, and the length of the rope is adjusted accordingly, avoiding the change of the ship's attitude caused by the dragging of the cable when the ship's position changes. Through this application, by integrating multi-source data, prediction models and feedback control technology, stable pre-control of the ship's attitude is achieved, the stability and safety of the mooring structure are improved, and the impact of environmental changes on the ship's attitude is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 FIG. 1 is a schematic diagram of method steps of a mooring structure motion control method based on multi-source input provided by an embodiment of the present application; Figure 2Shown is a schematic diagram of the steps of a method for predicting attitude based on ocean wave data; Figure 3 The figure shows a schematic diagram of the method steps for controlling the retracting and releasing of the rope according to loading and unloading; 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 length; Figure 5 The figure shows a schematic diagram of the method steps of dividing a future preset time period into multiple time nodes and extracting corresponding prediction data; Figure 6 Shown is a schematic diagram of the method steps for lowering the ship's heading according to the median data; Figure 7 Shown is a schematic diagram of the distribution of ship cables; Figure 8 Shown is a schematic diagram of the method steps for raising the ship's bow direction according to the median data; Fig. 9 The figure shows a schematic diagram of the method steps for synchronously controlling the transverse cable when lowering the bow of a ship; Fig.10 Shown is a schematic diagram of the method steps for synchronously controlling the transverse cable when raising the bow of the ship; Fig.11 The figure shows a schematic diagram of the steps of the step-by-step rope-releasing method; Fig.12 The figure shows a schematic diagram of the method steps of using the average tension as the monitoring tension value when releasing the rope; Fig.13 Shown is a schematic diagram of the system structure of a cable tensioning system based on multi-source input; Fig.14 Shown is a schematic structural diagram of an electronic device provided in one embodiment of the present application.

[0016] Figure 7 In the middle: 701, head cable; 702, head fall cable; 703, tail cable; 704, tail fall cable; 705, head transverse cable; 706, tail transverse cable. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] Figure 1FIG. 1 is a schematic diagram of a method for controlling the motion of a moored structure based on multi-source input according to an embodiment of the present application. The present application provides a method for controlling the motion of a moored structure based on multi-source input. In one embodiment, Figure 1 As shown, the mooring structure motion control method based on multi-source input includes: step 110, acquiring tide data, wind data, and cable tension data.

[0019] In this step, the weather system of the shore control center can monitor and obtain the tidal data and wind data for a period of time in the future.

[0020] Step 120: Obtain the monitoring tension value of each cable according to the cable tension data.

[0021] In step 110 and step 120, a capstan is provided at the bow and the berth of the vessel, and the cable is wound on the capstan, and the capstan can reel in the cable, and one end of the cable is extended and fixed to the shore. The capstan can monitor the tension value of each cable, or a tension detector can be independently set to monitor.

[0022] Step 130, determine whether at least one monitored tension value is greater than the preset tension. If the judgment result of step 130 is yes, then execute step 140, if not, start to execute step 150 and subsequent steps. The preset tension can be set to be less than the breaking tension of 200N~400N.

[0023] Step 140: Start to release each cable at the same time.

[0024] In step 140, when at least one cable is about to break, each cable is released at the same time to reduce the cable tension, and releasing each cable at the same time can avoid the ship's attitude change caused by the asynchronous release. For example, if the ship has 2 head cables, 2 bow fall cables, 2 head transverse cables, 2 tail cables, 2 tail fall cables, and 2 tail transverse cables, the above 12 cables are released at the same time. The minimum tension limit can be set, and the cable is released until the cable tension reaches the minimum set range value. For example, when the breaking tension is 1300N and the preset tension is set to 1100N, the minimum set range value can be set to 600N~900N.

[0025] Step 150: Stop releasing the cables, import the tide data and wind data into the attitude simulation model, and calculate the attitude prediction data within a preset time period in the future.

[0026] In this step, an existing ship attitude prediction model can be used, such as using ADCIRC (An Advanced Circulation Model For Oceanic, Coastal and Estuarine Waters) or MATLAB to model and simulate wave data, convert tide data and wind data into wave data, and then predict the ship attitude based on the combined model of CNN (convolutional neural network) and GRU (gated recurrent unit) to obtain attitude prediction data. Alternatively, a combined model of CNN and LSTM (long short-term memory network) can be used for attitude prediction, CNN convolution operation is used for feature extraction, tide data and wind data are both environmental parameters in the model, and the output of CNN is used as the input of LSTM for time feature learning, and finally the attitude prediction data is obtained. The future preset time period can be set to the next 3 minutes, 10 minutes, or 15 minutes, etc.

[0027] Step 160: Sample multiple prediction data from the posture prediction data.

[0028] Since the posture prediction data obtained in step 150 is continuous posture data within a preset time period in the future, the continuous posture data is sampled in step 160 to obtain a plurality of discrete postures as a plurality of prediction data.

[0029] Step 170: respectively compare the difference ratios between the plurality of predicted data and the plurality of standard data.

[0030] In this step, the standard data corresponding to the standard posture of the ship is pre-set, for example, the standard posture is set when the ship deck is kept in a horizontal state, and the posture difference between the posture corresponding to each sampled prediction data and the standard posture is compared respectively, and the posture difference is recorded as the difference ratio of this step. For example, 10 prediction data are sampled, and the height difference between the bow of the ship corresponding to the third prediction data and the standard head posture is calculated, and then the ratio of the height difference to the deck-bottom distance is calculated as 1 / 25, and the 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; the height difference between the bow of the ship corresponding to the fifth prediction data and the standard head posture is calculated, and then the ratio of the height difference to the deck-bottom distance is calculated as 1 / 28, and the ratio is recorded as the difference ratio.

[0031] Step 180: extract predicted data of median difference based on multiple difference ratios and mark them as median data.

[0032] In this step, considering that only the posture prediction data obtained by the algorithm in step 150 is used, this step takes the prediction data of the median value to avoid taking a value that is too large or too small, and the prediction data corresponding to the median value is relatively objective. Specifically, among all the sampled prediction data, the value of the difference ratio is 1 or 2 at the middle position as the median difference. For example, 10 prediction data are sampled and the prediction data are sorted from large to small according to the difference ratio: sequence number 1, sequence number 2, sequence number 3, sequence number 4, sequence number 5, sequence number 6, sequence number 7, sequence number 8, sequence number 9, sequence number 10, and sequence number 5 and sequence number 6 are the median differences. One of the prediction data of sequence number 5 and the prediction data of sequence number 6 is selected as the median data. Another example: Sort the predicted data from large to small according to the difference ratio: sequence number 1, sequence number 2, sequence number 3, sequence number 4, sequence number 5, sequence number 6, sequence number 7, sequence number 8, sequence number 9, sequence number 10, sequence number 11, sequence number 6 is the median difference, and the predicted data of sequence number 6 is taken as the median data.

[0033] Step 190: Compare the deviation between the median data and the standard data to generate posture compensation data.

[0034] In this step, the median data and standard data are used as data comparison objects to obtain the deviation of the corresponding postures of the two, and the posture compensation data is generated accordingly. For example, if the height difference between the ship's bow direction corresponding to the median data and the standard head posture is 4 / 25 in proportion to the distance between the deck and the bottom of the ship, then the deviation is 4 / 25, and the corresponding posture compensation data is generated, and the ship's posture needs to be corrected according to the deviation later.

[0035] Step 200: reel in and unwind the cable according to the attitude compensation data to feedback control the current attitude and transform it toward the attitude opposite to the deviation attitude of the median data relative to the standard data.

[0036] In this step, the cable is wound and unwound according to the deviation, and the current attitude of the ship is adjusted so that the ship begins to transform in advance to the opposite attitude of the deviation attitude, thereby resisting the predicted future attitude changes in advance through the opposite movement, so that the ship can maintain the standard attitude in the future preset time period. For example, if the bow of the ship is higher than the standard head attitude and the deviation is 4 / 25, the process of transforming to the opposite attitude is: gradually feedback and control the head of the ship to drop to the height corresponding to the deviation of 4 / 25 through the winding of the cable, so as to resist the future attitude changes caused by tides and wind.

[0037] When this embodiment is applied, by acquiring tide, wind and cable tension data, the method can comprehensively consider the influence of various environmental factors on the mooring structure, and improve 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 close to the preset tension, and take timely measures, such as rope release operation, to avoid cable breakage and ensure the safety of the mooring structure. Combining tide and wind data 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 change of the ship in the future preset time period, and provide a basis for subsequent attitude adjustment. By sampling continuous attitude data and calculating the difference ratio, the predicted data of the median difference is extracted as the median data, which can avoid the influence of extreme values ​​to a certain extent and improve the stability and reliability of the prediction. According to the deviation between the median data and the standard data, the attitude compensation data is generated, and the winding and unwinding of the cable is adjusted accordingly to realize feedback control of the ship attitude, so that it can resist environmental changes and maintain a standard attitude. In summary, this embodiment can maintain the stable posture of the ship for a certain period of time in the future, reduce the fluctuation of the ship's posture caused by environmental changes, and improve the stability and safety of the mooring structure when the ship is docked.

[0038] Figure 2 FIG. 1 is a schematic diagram of a method for predicting a posture based on ocean wave data. Figure 2 As shown, step 150 includes: step 1501, obtaining wave data according to tide data and wind data.

[0039] 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 that can be combined with Python to collect tidal data and wind data to obtain wave data based on tides and wind. ADCIRC is widely used to predict wave data based on tides and wind. MATLAB can also be used to simulate wave data. For example, according to linear wave theory, tidal data and wind data are used as code parameters to generate a wave simulation model to obtain wave data caused by future tidal data and wind data.

[0040] Step 1502: Obtain the historical posture at the historical preset time and the current posture at the current time.

[0041] Step 1503: According to the wave data, historical posture and current posture, the ship posture is predicted based on the CNN and GRU or CNN and LSTM combination model to obtain posture prediction data.

[0042] In this embodiment, when predicting the ship's attitude, the prediction can be made based on the continuous attitude change data combined with the wave data. Considering the impact of waves on the movement of the ship, a model that can reflect the actual marine environmental conditions is created by obtaining the wave data based on the tidal data and wind data. The attitude data of the ship at the past time point and the current attitude data are collected as part of the input of the attitude prediction model. A model combining CNN and GRU or CNN and LSTM is used, in which CNN is used to extract features and GRU or LSTM is used to process time series data, so as to more accurately predict the attitude of the ship.

[0043] Figure 3 The figure shows a schematic diagram of the method steps for controlling the retracting and releasing of the rope according to loading and unloading. Figure 3 As shown, the mooring structure motion control method based on multi-source input also includes: Step 210: Obtain loading and unloading data; Step 220, obtaining ship position lifting data according to loading and unloading data; Step 230, converting the length of the retractable rope according to the ship position lifting data and the retractable rope coefficient; Step 240: retract and release the cables simultaneously based on the length of the retracted and released cables.

[0044] When this embodiment is applied, the loading and unloading data includes the weight of the cargo, and the lifting and lowering data of the ship's draft caused by the weight of the cargo loaded and unloaded is calculated in advance. The corresponding ship position lifting and lowering data can be obtained according to the current loading and unloading data. When the ship position is raised and lowered, the distance between the winch on the ship and the shore cable fixing column will inevitably change. According to the ship's hull size data, the corresponding relationship between the change in the ship's draft and the length of the retracting and releasing rope can be calculated, that is, the corresponding relationship between the ship position lifting data and the length of the retracting and releasing rope is calculated, and the corresponding relationship is the retracting and releasing rope coefficient. If each cable is retracted and released at the same time according to the length of the retracting and releasing rope, the cable will not be dragged when the ship position is raised and lowered, causing the ship's posture to change.

[0045] Figure 4 The figure shows the calculation method of the corresponding relationship between the ship position lifting data and the rope length. Figure 4 Explain the calculation method of the corresponding relationship between the ship position lifting data and the rope length. Figure 4The relative vertical height between the ship deck and the shore ground is h, the cable length between the edge of the ship deck and the shore cable fixing column is s, and the horizontal distance L between the edge of the ship deck and the shore cable fixing column remains unchanged when the loading and unloading position is raised or lowered. During loading and unloading, the relative vertical height h changes, and the change value of the relative vertical height h can be measured by visual measurement of the ship-borne camera. The horizontal distance L remains unchanged. The change value of the cable length s can be calculated by trigonometric function calculation through the change value of the relative vertical height h. The trigonometric function conversion formula is the rope retracting coefficient in step 230.

[0046] Figure 5 FIG. 1 is a schematic diagram of a method for dividing a future preset time period into multiple time nodes and extracting corresponding prediction data. Figure 5 As shown, step 160 includes: Step 1601: divide the future preset time period equally according to the preset step length to obtain multiple time nodes; Step 1602: extract multiple prediction data corresponding to multiple time nodes.

[0047] When this embodiment is applied, the future preset time period is equally divided according to the preset step size to obtain a series of time nodes. The continuity and uniformity of the time series data can be ensured 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 multiple discrete and easy-to-process data points. And sampling multiple prediction data can reduce the subsequent data processing volume to a certain extent.

[0048] Figure 6 FIG. 1 is a schematic diagram of the method steps for reducing the heading of a ship according to the median data. In one embodiment, Figure 6 As shown, step 190 includes: step 1901, if the median data is relative to the standard data, corresponding to the predicted heading of the ship being higher than the standard heading attitude of the ship, then a first heading deviation is obtained and first compensation data is generated.

[0049] Step 200 includes: Step 2001, tightening the head cable and the bow lay cable, releasing the tail cable and the tail lay cable according to the first compensation data, and feedback control until the ship's bow direction reduces the amplitude corresponding to the first bow direction deviation within a preset time period in the future.

[0050] 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 the amplitude corresponding to the higher first heading deviation is calculated accordingly. When the head height of the predicted ship attitude is higher than the head height of the standard attitude, the head of the ship is lowered in advance, and the head cable, the bow cable, the stern cable and the stern cable are respectively connected to different cable machines, that is, the head cable and the bow cable are tightened and the stern cable and the stern cable are released, and closed-loop feedback control is performed, that is, the head cable and the bow cable are gradually tightened and the stern cable and the stern cable are released until the head of the ship reduces the amplitude corresponding to the first heading deviation. For example, the predicted ship's predicted heading 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 reduces the first heading deviation within a preset time period in the future, corresponding to the ship's heading reducing by 3° within a preset time period in the future. Figure 7 The diagram shows the distribution of ship cables. Figure 7 As shown, by tightening the head cable 701 and the bow lay cable 702, paying out the tail cable 703 and the tail lay cable 704, the bow of the ship is gradually lowered and the stern of the ship is raised, so as to pre-adjust the ship's attitude and resist the predicted future attitude changes in advance.

[0051] Figure 8 FIG. 1 is a schematic diagram of the method steps for raising the ship's bow direction according to the median data. Figure 8 As shown, step 190 includes: step 1902, if the median data is relative to the standard data, corresponding to the predicted heading of the ship being lower than the standard heading attitude of the ship, a second attitude deviation is obtained and second compensation data is generated.

[0052] Step 200 includes: Step 2002, according to the second compensation data, releasing the 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 a preset time period in the future.

[0053] When this embodiment is applied, by comparing the median data with the standard data, it can be determined whether the predicted bow of the ship is lower than the standard attitude, and the amplitude corresponding to the deviation of the sinking second attitude is calculated accordingly. When the head height of the predicted ship attitude is lower than the head height of the standard attitude, the stern of the ship starts to be lowered in advance, and the head cable, bow drop cable, stern cable and stern drop cable are respectively connected to different cable machines, that is, the stern cable and stern drop cable are tightened and the head cable and bow drop cable are released, and closed-loop feedback control is performed, that is, the stern cable and stern drop cable are gradually tightened and the head cable and bow drop cable are released until the bow of the ship is raised by the amplitude corresponding to the deviation of the second attitude. For example, the predicted bow of the ship is 2° lower than the standard attitude of the bow of the ship, that is, the relative inclination 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 bow of the ship is 2° higher than the standard attitude of the bow of the ship. That is, the bow of the ship is raised by the first bow deviation in the future preset time period, corresponding to the bow of the ship being raised by 2° in the future preset time period. Combined with Figure 7 As shown, by releasing the head cable 701 and the bow lay cable 702, and tightening the stern cable 703 and the stern lay cable 704, the stern of the ship is gradually lowered and the bow of the ship is raised, so as to pre-adjust the ship's attitude and resist the predicted future attitude changes in advance.

[0054] Fig. 9 FIG. 1 is a schematic diagram of the method steps for synchronously controlling the transverse cable when lowering the bow of a ship. Fig. 9 As shown, during the execution of step 2001, the method further includes: step S101, synchronously tightening the head transverse cable based on the first speed proportional coefficient, and synchronously releasing the tail transverse cable based on the second speed proportional coefficient.

[0055] In this step, combine Figure 7 , the first speed proportional coefficient is proportional to the ship-to-shore rope length ratio of the head transverse cable 705 and the head cable, and the second speed proportional coefficient is proportional to the ship-to-shore rope length ratio of the tail transverse cable 706 and the tail cable. Since the head transverse cable 705 is substantially perpendicular to the head cable and the bow fall cable, and the tail transverse cable 706 is substantially perpendicular to the tail cable and the tail fall cable. By synchronously tightening the head transverse cable 705, the ship's attitude can be assisted in stabilizing in the process of tightening the head cable and the bow fall cable, and tightening according to the rope length ratio of the head transverse cable 705 and the head cable can avoid too much or too little rope tightening. Synchronously releasing the tail transverse cable 706 can assist in stabilizing the ship's attitude in the process of releasing the tail cable and the tail fall cable, and releasing the rope according to the rope length ratio of the tail transverse cable 706 and the tail cable can avoid too much or too little rope release.

[0056] Fig.10 FIG. 1 is a schematic diagram of the steps of a method for synchronously controlling the transverse cable when raising the bow of a ship. Fig.10As shown, during the execution of step 2002, the method further includes: step S201, synchronously releasing the rope head transverse cable based on the third speed proportional coefficient, and synchronously tightening the tail transverse cable based on the fourth speed proportional coefficient.

[0057] In this step, combine Figure 7 , the third speed proportional coefficient is proportional to the ship-to-shore rope length ratio of the head transverse cable 705 and the head cable, and the fourth speed proportional coefficient is proportional to the ship-to-shore rope length ratio of the tail transverse cable 706 and the tail cable. Since the head transverse cable 705 is substantially perpendicular to the head cable and the bow fall cable, and the tail transverse cable 706 is substantially perpendicular to the tail cable and the tail fall cable. By synchronously releasing the head transverse cable 705, the ship's attitude can be assisted in stabilizing the process of releasing the head cable and the bow fall cable, and the rope can be released according to the rope length ratio of the head transverse cable 705 and the head cable, which can avoid releasing too much or too little rope. Synchronously tightening the tail transverse cable 706 can assist in stabilizing the ship's attitude in the process of tightening the tail cable and the tail fall cable, and the rope can be collected according to the rope length ratio of the tail transverse cable 706 and the tail cable, which can avoid collecting too much or too little rope.

[0058] Fig.11 FIG. 1 is a schematic diagram of the step-by-step method of releasing the rope. Fig.11 As shown, step 130 and step 140 include: step S401, setting the rope release step length.

[0059] Step S402: releasing each cable intermittently with a releasing step length.

[0060] In this embodiment, by releasing the cable in a step-by-step manner, the cable structure itself can have enough time to stabilize the tension after each release of the cable, so as to more accurately detect the tension value of the cable.

[0061] Fig.12 The figure shows a schematic diagram of the method steps for using the average tension as the monitoring tension value when releasing the rope. Fig.12 As shown, step S401 includes: Step S4011, when performing a single rope release with the rope release step length, continuously detecting the cable tension data with a preset detection time length; Step S4012, calculating the average tension of the cable tension data within a preset detection time; Step S4013: The sampled average tension is aggregated into a data set of monitored tension values.

[0062] In this embodiment, after a single release of the rope, the release action is stopped and the tension of the cable is detected for a preset detection time, so as to obtain more accurate cable tension data. After a single release of the rope, the cable will be in an unstable tension state. The average value is taken from the continuously detected cable tension to obtain the average tension. The average tension is aggregated in step S4013. The average tension can be directly used as the monitoring tension value in steps 120 and 130, so as to judge the cable condition according to the average tension. In some embodiments, a minimum tension value range is set, and when the cable tension reaches the minimum set range value during the release of the rope in step S402, the release of the rope is stopped.

[0063] Fig.13 FIG. 1 is a schematic diagram of the system structure 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, Fig.13 As shown, the cable tensioning system based on multi-source input includes: a data acquisition module 1301 , a tension regulation module 1302 and a posture control module 1303 .

[0064] The data acquisition module 1301 is configured to: acquire tidal data, wind data, and cable tension data; and obtain the monitoring tension value of each cable according to the cable tension data.

[0065] The tension control module 1302 is in communication connection with the data acquisition module 1301 , and the tension control module 1302 is configured to simultaneously start releasing the cables if it is determined that at least one monitored tension value is greater than a preset tension.

[0066] The attitude control module 1303 is communicatively connected with the data acquisition module 1301, and the attitude control module 1303 is configured to: if it is determined that each monitored tension value is less than a preset tension, perform the following steps: stop releasing each cable, import tide data and wind data into the attitude simulation model, and calculate 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 median data; compare the deviation between the median data and the standard data to generate attitude compensation data; and reel in the cable according to the attitude compensation data to feedback control the current attitude, and transform to the opposite attitude of the deviation of the median data relative to the standard data.

[0067] The present application has the following technical effects when applied: The present application improves the adaptability and accuracy of the motion control of the mooring structure by integrating various environmental and structural data such as tide, wind and cable tension. By monitoring the cable tension data, it is possible to judge in real time whether the cable is close to the preset tension, and take timely measures to release the cable to avoid cable breakage and ensure the safety of the mooring structure. The combined model of CNN and GRU or CNN and LSTM or CNN and LSTM is used to predict the ship's attitude. 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. According to the deviation between the median data and the standard data, the attitude compensation data is generated, and the winding and unwinding of the cable is adjusted accordingly, realizing the feedback control pre-adjustment of the ship's attitude, so that it can resist environmental changes and maintain the standard attitude. Combined with the loading and unloading data, the ship's position rise and fall is predicted, and the length of the rope is adjusted accordingly, avoiding the change of the ship's attitude caused by the dragging of the cable when the ship's position changes. Through this application, by integrating multi-source data, prediction models and feedback control technology, stable pre-control of the ship's attitude is achieved, the stability and safety of the mooring structure are improved, and the impact of environmental changes on the ship's attitude is reduced.

[0068] Below, reference Fig.14 To describe an electronic device according to an embodiment of the present application. Fig.14 Shown is a schematic structural diagram of an electronic device provided in one embodiment of the present application.

[0069] like Fig.14 As shown, the electronic device 1400 includes one or more processors 1401 and a memory 1402 .

[0070] The processor 1401 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 1400 to perform desired functions.

[0071] 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, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, 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 error parameters of mooring structure motion control based on multi-source input may also be stored in the computer-readable storage medium.

[0072] In one example, the electronic device 1400 may further include: an input device 1403 and an output device 1404 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0073] The input device 1403 may include, for example, a keyboard, a mouse, a joystick, a touch screen, and the like.

[0074] The output device 1404 can output various information to the outside, including the determined motion data, etc. The output device 1404 can include, for example, a display, a communication network and a remote output device connected thereto, and the like.

[0075] Of course, to simplify, Fig.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 conditions, the electronic device 1400 may also include any other appropriate components.

[0076] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the mooring structure motion control method based on multi-source input according to various embodiments of the present application described in this specification.

[0077] The computer program product may be written in any combination of one or more programming languages ​​to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages, such as Java, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0078] 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 executed by a processor, the processor executes the steps in the mooring structure motion control method based on multi-source input according to various embodiments of the present application.

[0079] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0080] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.

[0081] 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 diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0082] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0083] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features of the present invention.

[0084] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present 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 a plurality of prediction data from the attitude prediction data; respectively compare a plurality of difference ratios between the prediction data and the standard data; extract the prediction data with the 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 to generate attitude compensation data; and reel in the cables according to the attitude compensation data to feedback control the current attitude, and transform to the opposite attitude of the deviation of the median data relative to the standard data.

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 corresponds to a predicted heading of the ship higher than the standard heading attitude of the ship relative to the standard data, a first heading deviation is obtained and first 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 opposite attitude of the deviation 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 heading of the ship is reduced by the amplitude corresponding to the first heading deviation within the future preset time period; or The method comprises the following steps: comparing the deviation between the median data and the standard data to generate the attitude compensation data, including: if the median data corresponds to a predicted heading of the ship being lower than the standard heading of the ship relative to the standard data, then obtaining a second attitude deviation and generating second compensation data; at this time, reeling out the cable according to the attitude compensation data to feedback-control the current attitude to transform to the attitude opposite to the deviation of the median data relative to the standard data, including: releasing the head cable and the bow cable, tightening the tail cable and the tail cable according to the second compensation data, and performing feedback control until the heading 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 5, 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 communicatively connected 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 start to release the cables simultaneously; a posture control module is communicatively connected 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 execute the following steps: stop releasing the cables, import the tidal data and the wind data into a 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 between the plurality of prediction data and 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 to generate posture compensation data; and reel in and release the cables according to the posture compensation data to feedback control the current posture, and transform toward a posture opposite to the deviation posture of the median data relative to the standard data.

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