A method and system for predicting and handling a soft bend for a parallel berthing ship

Abstract

The application discloses a kind of ship and soft tube bend over prediction grading disposal method and system, it is related to deep sea mining and offshore wet transport safety control technical field, the method includes: obtaining minimum bending radius allowed to soft tube, current minimum curvature radius, predicted minimum curvature radius and associated working condition information;According to the relationship between minimum bending radius allowed and associated working condition information, dynamic safety threshold is constructed;According to the relationship between current minimum curvature radius, predicted minimum curvature radius and dynamic safety threshold, calculate predicted safety margin, predicted overrun time and sustained risk index;According to the risk discrimination quantity of bend over, five-level risk classification is carried out;The action of grading disposal corresponding grade is executed and the state of soft tube is continuously reviewed;According to the review result, upgrade disposal, maintenance disposal or degradation recovery is executed.The application realizes the active prevention and control, accurate grading and closed-loop management of the risk of ship and soft tube bend over, significantly improves the timeliness, adaptability and operability of disposal.

Description

Technical Field

[0001] This invention relates to the field of safety control technology for deep-sea mining and marine wet transport, and in particular to a method and system for predicting and classifying the handling of ships passing through bends using flexible hoses. Background Technology

[0002] Wet transport, where vessels berth side-by-side, is a critical operational link in deep-sea mining and marine fluid transshipment. Its operational safety directly impacts the stability of the high-end marine equipment, intelligent shipping, and marine engineering industry chain. During wet transport operations, the wet transport hose spans between two vessels and is subject to the combined effects of the relative six-degree-of-freedom motion of the two vessels, wave disturbances, fluid pulsation loads, and the hose's own weight and additional loads. This can easily lead to a small radius of curvature in localized areas. When the local radius of curvature of the hose continues to decrease and approaches or falls below its minimum allowable bending radius, it can easily cause localized buckling of the hose, structural damage, and reduced lifespan. In severe cases, it can even lead to leaks, transport shutdowns, and operational accidents.

[0003] Current technologies typically employ the following methods to monitor and manage the risks associated with hose bends: First, manual inspections or single sensors are used to monitor a few hotspot locations; second, fixed alarm thresholds are set for certain local measurements, and manual judgment is made to reduce load or stop transmission when the observed value exceeds the limit. The above methods have the following main shortcomings: First, the handling logic is mostly based on "whether the currently measured local value exceeds the limit", lacking a forward-looking judgment on the short-term bending trend of the hose in the future, and often only responding passively after the risk has already formed; Second, the use of fixed thresholds makes it difficult to adapt to and rely on differences in operating conditions such as changes in sea state, increased ship motion, and fluctuations in measurement uncertainty, which can easily lead to false alarms, missed alarms, or over-processing. Third, it usually only gives an "alarm" result, lacks executable actions corresponding to the risk level, and makes it difficult to form a closed-loop control process from risk identification, level classification, action execution to review and recovery; Fourth, existing methods rely heavily on on-site operators and lack standardization, which hinders rapid replication and widespread application in engineering projects.

[0004] Therefore, there is an urgent need for a predictive and tiered approach to handling vessels passing through bends using wet transport hoses, in order to improve the timeliness, adaptability, and feasibility of handling such situations. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for predicting and classifying the handling of risks when ships berth alongside each other via flexible hoses. This method and system address the problems of passive response, poor adaptability of fixed thresholds, lack of graded execution actions, reliance on human experience, and difficulty in forming a closed loop in current technologies for handling risks when ships berth alongside each other via wet transport hoses. The invention aims to achieve proactive prevention and control, precise classification, and closed-loop management of risks when ships berth alongside each other via flexible hoses, thereby improving the timeliness, adaptability, stability, and operability of the handling.

[0006] To achieve the above objectives, the present invention provides a method for predicting and classifying the handling of ships berthing through bends using flexible hoses, comprising the following steps: The system acquires the minimum allowable bending radius, current minimum curvature radius, predicted minimum curvature radius, and associated operating condition information for the ship and hose. The associated operating condition information includes: sea state information, ship motion information, hose delivery status information, and data quality information. Based on the minimum allowable bending radius and related working condition information, a dynamic safety judgment threshold is constructed. Based on the relationship between the current minimum radius of curvature, the predicted minimum radius of curvature, and the dynamic safety discrimination threshold, the cornering risk discrimination quantity is calculated; the cornering risk discrimination quantity includes: predicted safety margin, expected over-limit time, and continuous risk index; The risk level of a vessel when passing through a bend is classified according to the bend risk assessment metric, and the classification results are obtained. The classification results include: normal level, early warning level, control level, dangerous level and emergency level. Based on the classification results, perform the corresponding level of graded treatment actions, and continuously review the status of the hose to obtain the review results; Based on the review results, the appropriate action will be upgraded, maintained, or downgraded and restored.

[0007] Preferably, the specific content of constructing the dynamic safety judgment threshold based on the minimum allowable bending radius and associated working condition information includes: Based on the measurement uncertainty, sea state information, ship motion information, and hose delivery status information, calculate the uncertainty correction, sea state correction, and operating condition correction respectively; A dynamic safety threshold is constructed based on the minimum allowable bending radius, uncertainty correction, sea state correction, and operating condition correction.

[0008] Preferably, the formula for calculating the uncertainty correction is: ; in, This is the uncertainty correction amount. To allow the minimum bending radius, This is the uncertainty correction factor; The formula for calculating the sea state correction is: ; in, For sea state correction, This is a sea state correction factor; The formula for calculating the operating condition correction is as follows: ; in, This is the working condition correction amount. This is the working condition correction factor; The expression for the dynamic security discrimination threshold is: ; in, The threshold for dynamic security judgment.

[0009] Preferably, the specific content of calculating the cornering risk judgment quantity based on the relationship between the current minimum radius of curvature, the predicted minimum radius of curvature, and the dynamic safety judgment threshold includes: The predicted safety margin is calculated based on the difference between the predicted minimum radius of curvature and the dynamic safety discrimination threshold. The estimated time to exceed the limit is calculated based on the difference between the current minimum radius of curvature and the dynamic safety threshold, as well as the rate of change of the current minimum radius of curvature. The continuous risk index is calculated by determining the percentage of time within a set statistical time window during which the predicted safety margin is less than zero.

[0010] Preferably, the formula for calculating the predicted safety margin is: ; in, t For the current moment, This represents the predicted safety margin at the current moment. For a forward-looking time window, For the current moment t Based on the forward time window The predicted minimum radius of curvature is obtained. The current dynamic security threshold; The formula for calculating the expected over-limit time is as follows: ; ; in, The rate of change of the current minimum radius of curvature. The minimum radius of curvature at present. The dynamic security threshold at the current moment. To anticipate the time of exceeding the limit, The absolute value of the rate of change of the current minimum radius of curvature. 𝜀 For the minimum threshold, This represents the upper limit of the expected over-limit time. The formula for calculating the persistent risk indicator is as follows: ; in, As a continuous risk indicator at present, For statistical time windows, For indicator functions, To statistically analyze time variables within a time window, To count the time within the time window s The corresponding predicted safety margin.

[0011] Preferably, the risk level of a vessel's maneuvering around a flexible hose is classified according to the turning risk assessment metric, and the specific content of the classification result includes: The system includes preset thresholds for: early warning safety margin, hazard safety margin, expected early warning exceedance time, expected control exceedance time, expected hazard exceedance time, first persistent risk indicator threshold, second persistent risk indicator threshold, extreme handling threshold, hazard level duration threshold, and emergency trigger time threshold. The expected early warning exceedance time threshold is greater than the expected control exceedance time threshold, which is greater than the expected hazard exceedance time threshold. The second persistent risk indicator threshold is greater than the first persistent risk indicator threshold. The emergency trigger time threshold is greater than the hazard level duration threshold. The predicted safety margin is compared with the early warning safety margin threshold, 0, and the negative danger safety margin threshold to obtain the first judgment result; The expected time of exceeding the limit is compared with the expected time threshold for early warning, the expected time threshold for control, and the expected time threshold for danger to obtain the second judgment result. The persistent risk indicator is compared with the first persistent risk indicator threshold and the second persistent risk indicator threshold respectively, and it is determined whether the duration of the persistent risk indicator being greater than or equal to the second persistent risk indicator threshold exceeds the danger level duration threshold to obtain the third judgment result. The current minimum radius of curvature and the predicted minimum radius of curvature are compared with the limit treatment threshold to obtain the fourth judgment result; Based on the first, second, third, and fourth judgment results, and after determining the status as hazardous, it is determined whether the duration of the hazardous state exceeds the emergency trigger time threshold. The overall risk level of the current hose bending is then comprehensively determined as follows: When the predicted safety margin is greater than the early warning safety margin threshold, the expected over-limit time is greater than the early warning expected over-limit time threshold, and the persistent risk index is less than the first persistent risk index threshold, it is judged as normal level; When the predicted safety margin is greater than 0 and less than or equal to the early warning safety margin threshold, or the expected over-limit time is greater than the control expected over-limit time threshold and less than or equal to the early warning expected over-limit time threshold, or the persistent risk index is greater than or equal to the first persistent risk index threshold and less than the second persistent risk index threshold, it is determined to be at the early warning level. When the predicted safety margin is less than or equal to 0, or the expected over-limit time is greater than the hazard expected over-limit time threshold but less than or equal to the control expected over-limit time threshold, or the persistent risk index is greater than or equal to the second persistent risk index threshold, it is judged as control level; When the predicted safety margin is less than or equal to the negative hazard safety margin threshold, or the expected over-limit time is greater than 0 and less than or equal to the hazard expected over-limit time threshold, or the persistent risk index is greater than or equal to the second persistent risk index threshold and the duration exceeds the hazard level duration threshold, it is judged as a hazard level. An emergency level is determined when the current minimum radius of curvature is less than or equal to the extreme handling threshold, or the predicted minimum radius of curvature is less than or equal to the extreme handling threshold, or the duration of the hazardous state exceeds the emergency triggering time threshold.

[0012] Preferably, the expression for the early warning safety margin threshold is: ; in, To provide an early warning safety margin threshold, To provide an early warning safety margin coefficient, Minimum allowable bending radius; The expression for the hazard safety margin threshold is: ; in, This is the safety margin threshold for hazards. This refers to the safety margin factor for risks. The expression for the extreme handling threshold is: ; in, This is the safety margin threshold for hazards. This is the limit of the disposal coefficient; The predicted time threshold for exceeding the warning limit is 20s~60s; The control is expected to exceed the time threshold by 10s to 30s; The threshold for the estimated time limit for exceeding the danger limit is 3s to 10s; The threshold for the first persistent risk indicator is 0.2 to 0.4; The threshold for the second persistent risk indicator is 0.5 to 0.8; The threshold for the duration of the hazard level is 3s to 10s; The emergency trigger time threshold is 5s~15s.

[0013] Preferably, the corresponding graded treatment actions are performed according to the classification results, and the status of the hose is continuously checked. The specific content of the check results includes: When the condition is determined to be normal, maintain the current conveying and parallel operation status, and only perform routine monitoring; When the alert level is determined, enhanced monitoring is implemented, including shortening the refresh cycle, increasing the data sampling frequency, prompting operators to pay attention to the hose crossing area and recording the alert status; When the situation is determined to be at the control level, control measures will be implemented, including reducing the transport flow, limiting the sway and bow roll adjustment of both ships, limiting the rapid manipulation of the ship's propellers, and requiring the personnel to enter the control mode. When the situation is determined to be dangerous, dangerous measures shall be taken, including suspending delivery, maintaining the stability of the vessel position, prohibiting unnecessary relative movement adjustments, and, if necessary, releasing local additional loads or switching to a hose protection posture. When the emergency level is determined, emergency response measures shall be implemented, including emergency shutdown, activation of emergency broadcast, implementation of hose release or unloading plan, and notification of relevant personnel to enter the accident prevention and control process; After executing the corresponding graded handling actions for each level, the current minimum radius of curvature and the predicted minimum radius of curvature are continuously monitored, and the predicted safety margin, the expected over-limit time, and the continuous risk indicators are calculated on a rolling basis to obtain the review results.

[0014] Preferably, the specific details of implementing escalation, maintenance, or downgrade restoration based on the review results include: Based on the review results, determine whether the risk assessment of the curve continues to worsen, remains stable, or continues to improve; If the risk assessment of the curve continues to worsen, the response level will be upgraded to a higher level. If the risk assessment of the curve is stable but the exit conditions are not met, the current level of handling will be maintained; If the cornering risk assessment continuously meets the exit hysteresis condition and continues to reach the recovery observation time window, the risk level will be downgraded to the next lower level. The exit hysteresis condition includes: the recovery threshold is higher than the entry threshold, the recovery observation time is longer than the entry judgment time, and the switching between adjacent levels must meet the consistency of judgments for multiple consecutive frames or multiple consecutive cycles. The recovery observation time window increases with the risk level. If the warning conditions are triggered again after the system returns to normal, the system will re-enter the tiered response process.

[0015] This invention also provides a ship berthing hose bend prediction and classification handling system, used to implement the above-mentioned ship berthing hose bend prediction and classification handling method, including: The data acquisition module is used to acquire the minimum allowable bending radius, current minimum curvature radius, predicted minimum curvature radius, and related operating condition information of the ship alongside the hose; the related operating condition information includes: sea state information, ship motion information, hose delivery status information, and data quality information; The threshold construction module is used to construct dynamic safety judgment thresholds based on the minimum allowable bending radius and associated working condition information; The risk assessment module is used to calculate the cornering risk assessment quantity based on the relationship between the current minimum radius of curvature, the predicted minimum radius of curvature, and the dynamic safety assessment threshold. The cornering risk assessment quantity includes: predicted safety margin, expected over-limit time, and continuous risk index. The risk classification module is used to classify the risk of a vessel taking a bend alongside a flexible hose based on the bend risk assessment value, and obtain the classification results; the risk classification includes: normal level, early warning level, control level, dangerous level and emergency level; The handling review module is used to execute the corresponding level of handling actions based on the classification results, and continuously review the status of the hose to obtain the review results; The tiered handling module is used to perform escalation, maintenance, or downgrade recovery based on the review results.

[0016] In summary, the present invention provides a method and system for predicting and classifying the handling of ship berthing hoses during bends. Compared with traditional technologies, it offers the following advantages: It elevates the core criterion for handling hose bend risks from "whether the current limit has been exceeded" to "whether the predicted minimum curvature radius is close to the dynamic safety threshold," enabling proactive measures to be taken before the risk actually materializes, significantly enhancing the foresight of the handling process; it is not limited to specific measurement methods, as long as the current minimum curvature radius and the predicted minimum curvature radius can be provided, it can be integrated into the judgment and handling process, thus possessing good versatility and scalability; by constructing a dynamic safety judgment threshold, it integrates the minimum allowable bending radius of the hose, measurement uncertainty, sea state disturbance, and operational status into the judgment logic, avoiding the problem of poor adaptability of fixed thresholds under complex sea conditions; by combining the predicted safety margin, the expected time of exceeding the limit, and the degree of continuous risk for bend classification, it can more accurately reflect the severity and evolution trend of hose bend risks compared to a single threshold alarm; it establishes a one-to-one correspondence between risk levels and classified handling actions, and sets up escalation, maintenance, and recovery mechanisms, forming a complete closed-loop handling method that can be directly executed by on-site personnel, resulting in strong engineering replicability.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] Figure 1 This is a flowchart of a method for predicting and classifying the handling of ships passing through bends using a hose in this invention; Figure 2 This is a flowchart illustrating the process of obtaining the current minimum radius of curvature, the predicted minimum radius of curvature, and related operating condition information of a ship alongside a hose in this invention. Figure 3 This is a flowchart illustrating the construction of the dynamic security discrimination threshold in this invention; Figure 4 This is a flowchart illustrating the calculation and classification of the cornering risk assessment parameters in this invention. Figure 5 This is a flowchart of the graded processing and review process in this invention; Figure 6 This is a block diagram of a ship's bend prediction and graded handling system using a flexible hose, as described in this invention. Detailed Implementation

[0019] The technical method of the present invention will be further described below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application.

[0020] The following description of at least one exemplary embodiment is merely illustrative and is not intended to limit the scope of this application or its application or use.

[0021] Techniques, systems, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the instruction manual.

[0022] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0023] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0024] The present invention provides a method for predictive and graded handling of ship berthing hoses during bends based on the prediction of minimum curvature radius. The core idea of ​​this method is to first obtain the current minimum curvature radius of the ship berthing hose and its predicted minimum curvature radius in the near future, then combine the minimum allowable bending radius of the hose body and the on-site working conditions to construct a dynamic safety judgment threshold, and then perform risk judgment, grade classification and action handling. Finally, based on the review results, it is decided to upgrade, maintain or restore, thereby forming a complete closed loop for graded handling of bends.

[0025] In this invention, the current minimum radius of curvature and the predicted minimum radius of curvature of the ship's mooring hose can be provided by the upstream radius of curvature distribution acquisition module. The upstream module can be a 3D reconstruction system based on binocular vision and line laser, a centerline inversion system based on a ranging array and MRU six-degree-of-freedom fusion, or any other system capable of obtaining the hose's minimum radius of curvature and its short-term predicted value. This invention does not limit its specific implementation.

[0026] This invention provides a method for predicting and classifying the handling of ships berthing through bends using flexible hoses, such as... Figure 1 As shown, it includes the following steps: S1. Obtain the minimum allowable bending radius and current minimum curvature radius of the hose used for berthing of the vessel. (i.e., the current moment) t Minimum radius of curvature), predicted minimum radius of curvature (i.e., future forward-looking time window) The predicted minimum radius of curvature (within the specified range) and related operating conditions are available. The minimum permissible bending radius can be obtained by reading the hose product manual or engineering design documents.

[0027] Among them, the forward-looking time window The time window is 2s to 10s. The optimal time is 3s to 5s.

[0028] The associated operating condition information includes: sea state information, ship motion information, hose delivery status information, and data quality information. Specifically, this includes: delivery flow information: current pumping flow rate, flow rate change rate, pump start / stop status, pump speed, pipe pressure, pressure fluctuation, and valve opening; data quality information: time synchronization status, effective data ratio, sensor online status, point cloud or centerline fitting residuals, number of abnormal jump points, proportion of obstructed or weak echoes, and prediction confidence; current operating status: normal delivery, reduced flow delivery, suspended delivery, berthing adjustment, ship position holding, hose connection, hose disconnection preparation, emergency stop, and resumption of operation. If the relevant monitoring system detects that the timestamps of the above associated operating condition information are not synchronized, key data is missing, the fitting residual is too large, or the prediction confidence is below the threshold, it considers the input conditions to not meet the normal judgment requirements and directly enters a conservative handling mode, at least outputting a warning level or control level suggestion to avoid missed judgments due to data anomalies.

[0029] Specifically, such as Figure 2 As shown, step S1 specifically includes the following steps: S101, the minimum radius of curvature of the acquisition hose at the current moment.

[0030] S102. Based on the minimum radius of curvature change information at the current time and within the sliding time window, obtain the predicted minimum radius of curvature within the future look-ahead time window.

[0031] S103. Collect sea state, ship motion, hose delivery status and data quality information corresponding to the current moment.

[0032] S104. Determine whether the input data is complete and valid. If invalid, enter the conservative processing mode; otherwise, proceed to step S2.

[0033] S2. Based on the minimum allowable bending radius and related working condition information, construct a dynamic safety judgment threshold.

[0034] Furthermore, such as Figure 3 As shown, assuming the input data is complete and valid, and the minimum allowable bending radius has been read, step S2 specifically includes the following steps: S201. Based on the measurement uncertainty, sea state information, ship motion information, and hose delivery status information, calculate the uncertainty correction, sea state correction, and operating condition correction, respectively. The uncertainty correction is related to sensor accuracy, point cloud fitting residual, data integrity rate, and time synchronization error; the sea state correction is related to roll, pitch, heave, root mean square of combined acceleration, or sea state level; the operating condition correction is related to delivery flow rate, hose internal pressure, hose aging status, or connection attitude. The formula for calculating the uncertainty correction is: ; in, This is the uncertainty correction amount. To allow the minimum bending radius, This is the uncertainty correction factor.

[0035] The formula for calculating sea state correction is: ; in, For sea state correction, This is the sea state correction factor.

[0036] The formula for calculating the working condition correction is: ; in, This is the working condition correction amount. This is the working condition correction factor.

[0037] S202. Construct a dynamic safety threshold based on the minimum allowable bending radius, uncertainty correction, sea state correction, and operating condition correction. The expression for the dynamic safety threshold is: ; in, The threshold for dynamic security judgment.

[0038] All of the above corrections are positive values, used to increase the safety margin based on the minimum allowable bending radius of the hose.

[0039] In an exemplary embodiment of the present invention, the uncertainty correction coefficient The value ranges from 0.02 to 0.20. More specifically, when the sensor is stable, the time synchronization error is small, the point cloud or centerline fitting residual is low, and the proportion of effective data is not less than 90%, the uncertainty correction coefficient is... Take a value of 0.02 to 0.05; when there is slight occlusion, weak echo, increased fitting residual, or the proportion of valid data is 70% to 90%, the uncertainty correction coefficient is [value missing]. The value is taken as 0.05~0.12; when there is significant occlusion, many anomalous abrupt changes, and large fitting residuals, but the data can still be used for discrimination, the uncertainty correction coefficient is [value missing]. Use a value between 0.12 and 0.20. If the proportion of valid data is less than 70%, or if key sensors are offline, the system will no longer be judged according to the normal threshold and will directly enter the conservative handling mode.

[0040] Sea state correction factor The value ranges from 0.03 to 0.35. More specifically, when the roll, pitch, and heave of both ships are small, the root mean square value of the combined acceleration is low, and the operation is in a stable sea state, the sea state correction factor is used. Take a value of 0.03~0.08; when the relative motion between the two ships increases, and the amplitudes of roll, pitch, or heave increase periodically, the sea state correction factor is used. The value is taken as 0.08~0.18; when the sea state is significantly enhanced, the root mean square value of the combined acceleration is high, and the relative motion of the two ships has a significant impact on the bending morphology of the hose, the sea state correction factor is increased. Use a value between 0.18 and 0.35. If the sea state exceeds the permissible range for wet transport operations, the system will directly determine it as a hazardous or emergency response level, instead of simply increasing the sea state correction amount. Make corrections.

[0041] Operating condition correction factor The value ranges from 0.02 to 0.25. More specifically, when the flow rate is low, the pump speed is stable, the pressure fluctuation in the pipe is small, and the hose is in its normal lifespan, the operating condition correction factor is... Take a value of 0.02~0.06; when the flow rate is close to the rated flow rate, the pump speed changes rapidly, the pressure fluctuation in the pipe increases, or the valve opening is frequently adjusted, the operating condition correction factor is adjusted accordingly. Take a value of 0.06~0.15; when the flow rate is high, the internal pressure of the hose is large, the pressure pulsation is obvious, the service life of the hose is close to the maintenance cycle, or the connection posture is not conducive to the natural drooping of the hose, the operating condition correction factor is used. Take a value of 0.15 to 0.25.

[0042] Furthermore, to avoid false negatives due to excessively low dynamic security thresholds, the following settings are configured: ; in, The dynamic safety judgment threshold is dynamically adjusted according to changes in measurement uncertainty, sea state disturbance, and hose delivery conditions.

[0043] Under normal operating conditions: .

[0044] Under high sea states or high-load transport conditions: .

[0045] When calculated When the maximum conservative threshold allowed on site is exceeded, the threshold will not be raised further, and the process will directly proceed to the control level, danger level, or emergency level.

[0046] Through the above processing, the discrimination threshold is no longer a fixed constant, but a dynamic quantity that can be adjusted in real time according to the on-site conditions.

[0047] The calculation and classification process of the cornering risk assessment quantity after importing the dynamic safety threshold is as follows: Figure 4 As shown. Specifically, it includes steps S3 and S4.

[0048] S3. Based on the relationship between the current minimum radius of curvature, the predicted minimum radius of curvature, and the dynamic safety judgment threshold, calculate the cornering risk judgment quantity. This cornering risk judgment quantity includes: predicted safety margin, expected over-limit time, and persistent risk indicators.

[0049] Furthermore, step S3 can be replaced by the following steps: S301. Calculate the predicted safety margin based on the difference between the predicted minimum radius of curvature and the dynamic safety discrimination threshold. The formula for calculating the predicted safety margin is as follows: ; ; in, t For the current moment, This represents the predicted safety margin at the current moment. For a forward-looking time window, For the current moment t Based on the forward time window The predicted minimum radius of curvature is obtained. This is the dynamic security threshold for the current moment.

[0050] If the safety margin is predicted This indicates that the predicted minimum radius of curvature is still greater than the dynamic safety threshold, and the hose still has a safety margin; if the predicted safety margin is... This indicates that the predicted minimum radius of curvature is close to or below the dynamic safety threshold, and the hose is at risk of bending.

[0051] S302. Calculate the estimated time to exceed the limit based on the difference between the current minimum radius of curvature and the dynamic safety threshold, and the rate of change of the current minimum radius of curvature. To further assess the speed of risk development, calculate the estimated time to exceed the limit. Set a sliding time window. The rate of change of the current minimum radius of curvature is: ; in, The rate of change of the current minimum radius of curvature. This represents the minimum radius of curvature at the current time t. The rate of change of the current minimum radius of curvature is determined by a sliding time window of the most recent 2 to 5 seconds. The current minimum radius of curvature within The data is obtained through linear fitting. If the rate of change of the current minimum radius of curvature... This indicates that the minimum radius of curvature of the hose is decreasing, and the risk of bending is increasing. At this point, the expected over-limit time is defined as: The formula for calculating the expected over-limit time is as follows: ; in, The dynamic security threshold at the current moment. To anticipate the time of exceeding the limit, 𝜀 For the minimum threshold, This represents the upper limit of the expected over-limit time. The absolute value of the rate of change of the current minimum radius of curvature. This is the minimum threshold. When Less than the minimum threshold At this point, it is assumed that the minimum radius of curvature of the hose will not decrease significantly in a short period of time, and the estimated time of exceeding the limit can be determined. Set to infinity or a sufficiently large value. For example, 999s is used to indicate that there is no tendency to exceed the limit in the short term.

[0052] S303. Calculate the persistence risk index by determining the percentage of time within a set statistical time window when the predicted safety margin is less than zero. To determine whether a risk is persistent, a persistence risk index is defined. Within the most recent statistical time window... Within, statistical forecast safety margin Cumulative time percentage: ; in, As a continuous risk indicator at present, For statistical time windows, This is an indicator function (it takes the value 1 if the condition inside the parentheses is true, otherwise it takes the value 0). To statistically analyze time variables within a time window, To count the time within the time window s The corresponding predicted safety margin.

[0053] when When the conditions are met, I =1; when When the conditions are not met, I =0. Therefore, the persistent risk indicator... The value range is 0 to 1. If the persistent risk indicator... This indicates that the predicted safety margin has consistently been positive within the most recent statistical time window, and the risk has not persisted; if the risk indicator persists... A value of 0.5 indicates that the forecast exceeded the limit for half of the recent statistical time window; if the risk indicator continues... This indicates that the forecast has consistently exceeded the limit within the most recent statistical time window.

[0054] In the case of discrete sampling, the persistent risk index can be written as: ; in, This represents the number of data points within the most recent statistical time window. For the statistical time window, the first j Each sampling time. Among them, The sampling time is 5s to 30s, preferably 10s to 20s. When the sampling frequency is high, the statistics can be directly based on the number of sampling points; when the sampling frequency is uneven, the statistics are weighted according to the duration of each segment.

[0055] S4. Based on the turning risk assessment metric, the risk level of the vessel when passing through the flexible hose during a turn is classified into levels, resulting in the following classification: Normal, Warning, Control, Dangerous, and Emergency. The classification is based on risk indicators, jointly determined by the predicted safety margin, the expected overrun time, and the persistent risk indicators.

[0056] Furthermore, the specific steps of step S4 include: S401, Preset early warning safety margin threshold Hazard safety margin threshold Warning of expected time threshold exceeding the limit Control the expected time threshold for exceeding the limit Threshold for anticipated danger exceeding the time limit First persistent risk indicator threshold Second persistent risk indicator threshold Extreme handling threshold Hazard level duration threshold and emergency trigger time threshold Among them, the warning is expected to exceed the time limit threshold. Greater than the expected over-limit threshold Greater than the expected danger threshold time limit ,Right now Second persistent risk indicator threshold Greater than the first persistent risk indicator threshold ,Right now Emergency trigger time threshold Duration greater than the danger level threshold ,Right now .

[0057] The expression for the early warning safety margin threshold is: ; in, To provide an early warning safety margin threshold, To provide an early warning safety margin coefficient, Minimum allowable bending radius. Early warning safety margin factor. The value is 0.05~0.25, preferably 0.10. When sea conditions are stable, data quality is good, and transmission load is low, the early warning safety margin coefficient is... The safety margin factor is 0.05~0.10; when the sea state is normal or the transport flow rate is close to the rated operating condition, the early warning safety margin factor is... The margin is 0.10~0.18; when sea state is high, hose condition is aging, transmission load is large, or data quality is uncertain, the early warning safety margin coefficient is increased. The value is 0.18~0.25.

[0058] The expression for the hazard safety margin threshold is: ; in, This is the safety margin threshold for hazards. This refers to the safety margin factor for hazards. for Preferred .

[0059] The expression for the extreme handling threshold is: ; in, This is the safety margin threshold for hazards. This is the limit of the disposal coefficient.

[0060] The expected time threshold for early warning exceeding the limit is 20s~60s. The expected time threshold for control exceeding the limit is 10s~30s. The expected time threshold for danger exceeding the limit is 3s~10s. The threshold for the first persistent risk indicator is 0.2~0.4. The threshold for the second persistent risk indicator is 0.5~0.8. The threshold for the duration of danger level is 3s~10s. The threshold for emergency triggering time is 5s~15s.

[0061] Warning: Expected time threshold to exceed the warning limit Control the expected time threshold for exceeding the limit and the threshold for anticipated danger exceeding the time limit The on-site response time is determined based on the system identification and alarm time, operator confirmation time, time required to reduce the transport flow rate, time required to suspend transport, vessel position adjustment response time, and hose protection action execution time. Specifically, the early warning expected over-limit time threshold is defined. Control the expected over-limit time threshold Danger expected to exceed time threshold Preferably, the warning is set at the threshold for the expected time limit to be exceeded. Control the expected over-limit time threshold Danger expected to exceed time threshold When the on-site equipment responds slowly, a time threshold (early warning time limit exceeding the warning limit) is set. Control the expected time threshold for exceeding the limit and the threshold for anticipated danger exceeding the time limit The overall value increases; when the sampling frequency is high and the automatic control response is fast, the time threshold can be appropriately reduced.

[0062] First persistent risk indicator threshold The second persistent risk indicator threshold is used to determine whether a risk has begun to persist. Used to determine whether a risk has become clearly persistent. Specifically, the first persistent risk indicator threshold. The second persistent risk indicator threshold Preferably, the first persistent risk indicator threshold The second persistent risk indicator threshold When the statistical time window At that time, the first persistent risk indicator threshold This indicates that the second persistent risk indicator threshold has been in a state of exceeding the prediction limit for approximately 3 seconds within the last 10 seconds. This indicates that the system has been in a predicted out-of-limit state for approximately 6 seconds within the last 10 seconds. If a more conservative safety strategy is required on-site, then the first persistent risk indicator threshold... Second persistent risk indicator threshold The threshold can be appropriately lowered; however, if the on-site data fluctuates significantly, the threshold for the first persistent risk indicator should be lowered to avoid false alarms caused by short-term noise. Second persistent risk indicator threshold It can be appropriately increased.

[0063] Extreme handling threshold Preferred Alternatively, a more conservative approach can be taken. ; Threshold for duration of hazard level The preferred time is 5 seconds; emergency triggering time threshold. The preferred setting is 10 seconds.

[0064] S402. Compare the predicted safety margin with the early warning safety margin threshold, 0, and the negative danger safety margin threshold to obtain the first judgment result.

[0065] S403. The expected over-limit time is compared with the expected over-limit time threshold for early warning, the expected over-limit time threshold for control, and the expected over-limit time threshold for danger, respectively, to obtain the second judgment result.

[0066] S404. Compare the persistent risk indicator with the first persistent risk indicator threshold and the second persistent risk indicator threshold respectively, and determine whether the duration of the persistent risk indicator being greater than or equal to the second persistent risk indicator threshold exceeds the danger level duration threshold, and obtain the third judgment result.

[0067] S405. Compare the current minimum radius of curvature and the predicted minimum radius of curvature with the limit treatment threshold respectively to obtain the fourth judgment result.

[0068] S406. Based on the first, second, third, and fourth judgment results, and after determining the status as hazardous, determine whether the duration of the hazardous state exceeds the emergency trigger time threshold, and comprehensively determine the current hose bending risk level, specifically: When predicting safety margin Greater than the warning safety margin threshold Expected overdue time The time limit for exceeding the warning threshold is greater than the expected time limit. And persistent risk indicators Less than the first persistent risk indicator threshold At that time, that is , and If the hose is in a normal state, it is classified as such. A normal state indicates that the current and predicted state of the hose is relatively safe, the predicted safety margin is sufficient, the expected over-limit time is relatively long, and no obvious and persistent risk has appeared within the most recent statistical time window.

[0069] When predicting safety margin Greater than 0 and less than or equal to the warning safety margin threshold or the expected time exceeding the limit Greater than the expected over-limit threshold And less than or equal to the predicted time threshold for exceeding the warning limit or persistent risk indicators Greater than or equal to the first persistent risk indicator threshold And less than the second persistent risk indicator threshold At that time, that is ,or ,or When the hose has not exceeded its limits, it is classified as a warning level. A warning level indicates that although the hose has not exceeded its limits, the safety margin is decreasing, or the time of exceeding the limits is expected to enter the warning range, or the exceeding state is predicted to become somewhat persistent, requiring enhanced monitoring.

[0070] When predicting safety margin Less than or equal to 0, or expected over-limit time Greater than the expected danger threshold time limit And less than or equal to the control threshold for the expected over-limit time. or persistent risk indicators Greater than or equal to the second persistent risk indicator threshold At that time, that is ,or ,or At this point, the situation is classified as Control Level. Control Level indicates that a clear approach risk has been identified in the hose, and proactive intervention should be implemented by reducing the flow rate, limiting relative maneuvering between the two vessels, and controlling rapid corrections by the vessel's propellers.

[0071] When predicting safety margin Less than or equal to the negative hazard safety margin threshold or the expected time exceeding the limit Greater than 0 and less than or equal to the danger expected over-limit time threshold or persistent risk indicators Greater than or equal to the second persistent risk indicator threshold And the duration exceeds the danger level duration threshold. At that time, that is ,or ,or And the duration exceeds the set duration. At this point, the situation is classified as hazardous. A hazardous level indicates that the risk of the hose bending is high, and delivery should be suspended while maintaining the vessel's stable position.

[0072] When the current minimum radius of curvature Less than or equal to the extreme treatment threshold Or predict the minimum radius of curvature Less than or equal to the extreme treatment threshold Or the duration of the hazardous state exceeds the emergency trigger time threshold. At that time, that is ,or Or the duration of the hazardous state exceeds the emergency trigger time threshold. At this point, it is classified as an emergency. An emergency level indicates that the hose is approaching its critical danger level or the danger persists, and an emergency shutdown and disconnection plan should be implemented.

[0073] The process of implementing graded handling and review results after importing risk levels is as follows: Figure 5 As shown. Specifically, it includes steps S5 and S6.

[0074] S5. Based on the classification results, execute the corresponding level-based handling actions and continuously review the hose status to obtain the review results. Each risk level corresponds to a preset action list, action execution sequence, responsible position, and confirmation feedback items, thus forming a standardized work instruction process. Specifically, step S5 includes the following: When the condition is determined to be normal, maintain the current conveying and parallel operation status, and only perform routine monitoring.

[0075] When the alert level is determined, enhanced monitoring is implemented, including shortening the refresh cycle, increasing the data sampling frequency, prompting operators to pay attention to the hose crossing area, and recording the alert status.

[0076] When the situation is determined to be at the control level, control measures will be implemented, including reducing the transport flow rate, limiting the sway and bow roll adjustment range of both ships, restricting the rapid maneuvering of the ship's propellers, and requiring personnel to enter the control mode.

[0077] When the situation is deemed dangerous, dangerous measures should be taken, including suspending transport, maintaining the vessel's position, prohibiting unnecessary relative movement adjustments, and, if necessary, releasing local additional loads or switching to a hose protection posture.

[0078] When the emergency level is determined, emergency response measures shall be implemented, including emergency shutdown, activation of emergency broadcasting, implementation of hose disconnection or unloading plans, and notification of relevant personnel to enter the accident prevention and control process.

[0079] After executing the corresponding graded handling actions for each level, continuously monitor the current minimum radius of curvature and the predicted minimum radius of curvature, and continuously calculate the cornering risk judgment quantity (predicted safety margin, expected over-limit time and continuous risk indicators) to obtain the review results.

[0080] S6. Based on the review results, implement escalation measures, maintain measures, or downgrade and restore the status.

[0081] Specifically, step S6 includes the following: Based on the review results, determine whether the risk assessment of the curve continues to worsen, remains stable, or continues to ease.

[0082] If the risk assessment of cornering continues to worsen, the response level will be upgraded to a higher level.

[0083] If the risk assessment for cornering is stable but the exit conditions are not met, the current level of handling will be maintained.

[0084] If the cornering risk assessment continuously meets the exit hysteresis condition and continues to reach the recovery observation time window... If the risk assessment of cornering is significantly reduced, the level will be downgraded to the next lower level.

[0085] The exit hysteresis conditions include: the recovery threshold being higher than the entry threshold, the recovery observation time being longer than the entry judgment time, and the switching between adjacent levels requiring consistent judgments over multiple consecutive frames or cycles. This process employs a hysteresis strategy, meaning the threshold for entering a certain risk level differs from the threshold for exiting that risk level, and the exit threshold is set to a safer level than the entry threshold. For example, a predictive safety margin can be set when entering the control level. satisfy When exiting the control level, the predicted safety margin must meet the following requirements: ; in, To restore the safety margin threshold, and .and, ; in, To recover the hysteresis coefficient, a recovery safety margin is required to determine the exit from the control level, and is set to 0.03~0.15, preferably 0.05~0.10. Therefore, exiting the control level is only allowed when the predicted minimum radius of curvature is again above the dynamic safety discrimination threshold by a certain distance and remains there for a preset observation time window.

[0086] For the expected overdue time When entering the control level, settings can be configured. Exiting the control level requires: ; in, To restore the expected over-limit time threshold, it is used to determine whether the risk of hose bending has been mitigated by the stable control state; and Preferably, when controlling the expected over-limit time threshold. When it is 15 seconds, It lasts for 20 to 30 seconds.

[0087] Warning: Expected time threshold to exceed the warning limit Control the threshold for the expected time limit to exceed the limit. Danger expected to exceed time threshold First persistent risk indicator threshold Second persistent risk indicator threshold For persistent risk indicators When entering the control level, settings can be configured. Exiting the control level requires: ; in, To restore the threshold of the persistent risk indicator, used to determine whether the predicted out-of-limit states have been significantly reduced; and Preferably, when the second persistent risk indicator threshold... hour, The range is 0.20 to 0.40. The aforementioned hysteresis strategy can prevent the prediction of safety margins. Expected overdue time or persistent risk indicators When there are slight fluctuations around the critical threshold, the system frequently enters and exits the same treatment level.

[0088] Restoring the observation time window The value increases with the risk level and is used to determine the stability of risk mitigation. It only applies when the recovery conditions are within the recovery observation window. The risk level can only be lowered when the conditions are met continuously. Specifically, the observation window for exiting the warning level is... The time window is 10s to 30s, preferably 15s; the control stage exits the observation time window. The observation time window is 20s to 60s, preferably 30s; the danger level exits the observation window. The preset recovery observation time window is 30s to 120s, with 60s being preferred. The higher the risk level, the longer the preset recovery observation time window. If the sea conditions are poor, the hose is aging, or the transport load is high, the recovery observation time window will be adjusted accordingly. Take the larger value; if the sea state is stable, the data quality is good, and the automatic control responds quickly, then restore the observation time window. A smaller value can be taken.

[0089] When at the warning level, if , and Continuous satisfaction If so, it is permissible to restore to the normal level.

[0090] When the system is at the control level, if , and Continuous satisfaction If so, it is permissible to downgrade to the warning level or the normal level.

[0091] When the system is at a dangerous level, if Furthermore, the triggering condition for the danger level no longer applies, and the condition is continuously met to the specified level. If so, it is permissible to downgrade to the control level.

[0092] Once the emergency response level is reached, the system will not automatically restore the normal delivery status. Instead, manual confirmation is required that the hoses, connectors, valves, pump sets, and parallel connections all meet the restoration conditions before the monitoring and tiered response process can be restarted.

[0093] If the warning conditions are triggered again after the system returns to normal, the system will re-enter the tiered response process.

[0094] This invention, through the exit hysteresis and recovery observation mechanism, can effectively prevent the risk level from frequently changing in a critical state, thereby improving the stability and operability of the handling strategy.

[0095] Through the above-mentioned closed-loop review and recovery control method, the present invention can upgrade the handling in a timely manner when the risk worsens, maintain the handling when the risk is stable, and restore the handling step by step after the risk continues to ease. This avoids frequent switching caused by short-term fluctuations and improves the stability and on-site feasibility of graded handling of ships passing through bends by wet transport hoses.

[0096] This invention provides a ship berthing hose bend prediction and classification handling system, used to implement the aforementioned ship berthing hose bend prediction and classification handling method, such as... Figure 6 As shown, it includes: The data acquisition module is used to acquire the minimum allowable bending radius, current minimum curvature radius, predicted minimum curvature radius, and related operating condition information for the vessel alongside the hose. The related operating condition information includes: sea state information, vessel motion information, hose delivery status information, and data quality information.

[0097] The threshold construction module is used to construct dynamic safety judgment thresholds based on the minimum allowable bending radius and associated working condition information.

[0098] The risk assessment module is used to calculate the cornering risk assessment quantity based on the relationship between the current minimum radius of curvature, the predicted minimum radius of curvature, and the dynamic safety assessment threshold. The cornering risk assessment quantity includes: predicted safety margin, expected over-limit time, and persistent risk indicators.

[0099] The risk classification module is used to classify the risk of a vessel maneuvering around a bend using a flexible hose based on the bend risk assessment parameter, and obtain the classification results. The risk levels include: Normal, Warning, Control, Danger, and Emergency.

[0100] The handling review module is used to execute the corresponding level of handling actions based on the classification results, and continuously review the status of the hose to obtain the review results.

[0101] The tiered handling module is used to perform escalation, maintenance, or downgrade recovery based on the review results.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for predicting and classifying the handling of ships berthing through bends using flexible hoses, characterized in that, Includes the following steps: Obtain the minimum allowable bending radius, current minimum curvature radius, predicted minimum curvature radius, and related operating condition information for the ship and the hose; The associated operating condition information includes: sea state information, ship motion information, hose delivery status information, and data quality information; Based on the minimum allowable bending radius and related working condition information, a dynamic safety judgment threshold is constructed. Based on the relationship between the current minimum radius of curvature, the predicted minimum radius of curvature, and the dynamic safety discrimination threshold, the cornering risk discrimination quantity is calculated; the cornering risk discrimination quantity includes: predicted safety margin, expected over-limit time, and continuous risk index; The risk level of a vessel when passing through a bend is classified according to the bend risk assessment metric, and the classification results are obtained. The classification results include: normal level, early warning level, control level, dangerous level and emergency level. Based on the classification results, perform the corresponding level of graded treatment actions, and continuously review the status of the hose to obtain the review results; Based on the review results, the appropriate action will be upgraded, maintained, or downgraded and restored.

2. The method for predicting and classifying the handling of ships berthing through bends using flexible hoses according to claim 1, characterized in that, The specific details of constructing the dynamic safety judgment threshold based on the minimum allowable bending radius and related working condition information include: Based on the measurement uncertainty, sea state information, ship motion information, and hose delivery status information, calculate the uncertainty correction, sea state correction, and operating condition correction respectively; A dynamic safety threshold is constructed based on the minimum allowable bending radius, uncertainty correction, sea state correction, and operating condition correction.

3. The method for predicting and classifying the handling of ships berthing through bends using flexible hoses according to claim 2, characterized in that, The formula for calculating the uncertainty correction is: ； in, This is the uncertainty correction amount. To allow the minimum bending radius, This is the uncertainty correction factor; The formula for calculating the sea state correction is: ； in, For sea state correction, This is a sea state correction factor; The formula for calculating the operating condition correction is: ； in, This is the working condition correction amount. This is the working condition correction factor; The expression for the dynamic security discrimination threshold is: ； in, The threshold for dynamic security judgment.

4. The method for predicting and classifying the handling of ships berthing through bends using flexible hoses according to claim 3, characterized in that, Based on the relationship between the current minimum radius of curvature, the predicted minimum radius of curvature, and the dynamic safety judgment threshold, the specific content of calculating the cornering risk judgment quantity includes: The predicted safety margin is calculated based on the difference between the predicted minimum radius of curvature and the dynamic safety discrimination threshold. The estimated time to exceed the limit is calculated based on the difference between the current minimum radius of curvature and the dynamic safety threshold, as well as the rate of change of the current minimum radius of curvature. The continuous risk index is calculated by determining the percentage of time within a set statistical time window during which the predicted safety margin is less than zero.

5. The method for predicting and classifying the handling of ships berthing through bends using flexible hoses according to claim 4, characterized in that, The formula for calculating the predicted safety margin is as follows: ； in, t For the current moment, This represents the predicted safety margin at the current moment. For a forward-looking time window, For the current moment t Based on the forward time window The predicted minimum radius of curvature is obtained. The current dynamic security threshold; The formula for calculating the expected over-limit time is as follows: ； ； in, The rate of change of the current minimum radius of curvature. The current minimum radius of curvature, The dynamic security threshold at the current moment. To anticipate the time of exceeding the limit, 𝜀 For the minimum threshold, This represents the upper limit of the expected over-limit time. The formula for calculating the persistent risk indicator is as follows: ； in, As a continuous risk indicator at present, For statistical time windows, For indicator functions, To statistically analyze time variables within a time window, To count the time within the time window s The corresponding predicted safety margin.

6. The method for predicting and classifying the handling of ships berthing through bends using flexible hoses according to claim 5, characterized in that, Based on the turning risk assessment metric, the risk level of ships navigating alongside flexible hoses during turns is classified into different levels. The specific details of the classification results include: The system includes preset thresholds for: early warning safety margin, hazard safety margin, expected early warning exceedance time, expected control exceedance time, expected hazard exceedance time, first persistent risk indicator threshold, second persistent risk indicator threshold, extreme handling threshold, hazard level duration threshold, and emergency trigger time threshold. The expected early warning exceedance time threshold is greater than the expected control exceedance time threshold, which is greater than the expected hazard exceedance time threshold. The second persistent risk indicator threshold is greater than the first persistent risk indicator threshold. The emergency trigger time threshold is greater than the hazard level duration threshold. The predicted safety margin is compared with the early warning safety margin threshold, 0, and the negative danger safety margin threshold to obtain the first judgment result; The expected time of exceeding the limit is compared with the expected time threshold for early warning, the expected time threshold for control, and the expected time threshold for danger to obtain the second judgment result. The persistent risk indicator is compared with the first persistent risk indicator threshold and the second persistent risk indicator threshold respectively, and it is determined whether the duration of the persistent risk indicator being greater than or equal to the second persistent risk indicator threshold exceeds the danger level duration threshold to obtain the third judgment result. The current minimum radius of curvature and the predicted minimum radius of curvature are compared with the limit treatment threshold to obtain the fourth judgment result; Based on the first, second, third, and fourth judgment results, and after determining the status as hazardous, it is determined whether the duration of the hazardous state exceeds the emergency trigger time threshold. The overall risk level of the current hose bending is then comprehensively determined as follows: When the predicted safety margin is greater than the early warning safety margin threshold, the expected over-limit time is greater than the early warning expected over-limit time threshold, and the persistent risk index is less than the first persistent risk index threshold, it is judged as normal level; When the predicted safety margin is greater than 0 and less than or equal to the early warning safety margin threshold, or the expected over-limit time is greater than the control expected over-limit time threshold and less than or equal to the early warning expected over-limit time threshold, or the persistent risk index is greater than or equal to the first persistent risk index threshold and less than the second persistent risk index threshold, it is determined to be at the early warning level. When the predicted safety margin is less than or equal to 0, or the predicted over-limit time is greater than the hazard predicted over-limit time threshold but less than or equal to the control predicted over-limit time threshold, or the persistent risk index is greater than or equal to the second persistent risk index threshold, it is judged as control level; When the predicted safety margin is less than or equal to the negative hazard safety margin threshold, or the expected over-limit time is greater than 0 and less than or equal to the hazard expected over-limit time threshold, or the persistent risk index is greater than or equal to the second persistent risk index threshold and the duration exceeds the hazard level duration threshold, it is judged as a hazard level. An emergency level is determined when the current minimum radius of curvature is less than or equal to the extreme handling threshold, or the predicted minimum radius of curvature is less than or equal to the extreme handling threshold, or the duration of the hazardous state exceeds the emergency triggering time threshold.

7. The method for predicting and classifying the handling of ships berthing through bends using flexible hoses according to claim 6, characterized in that, The expression for the early warning safety margin threshold is: ； in, To provide an early warning safety margin threshold, To provide an early warning safety margin coefficient, Minimum allowable bending radius; The expression for the hazard safety margin threshold is: ； in, This is the safety margin threshold for hazards. This refers to the safety margin factor for risks. The expression for the extreme handling threshold is: ； in, This is the safety margin threshold for hazards. This is the limit of the disposal coefficient; The predicted time threshold for exceeding the warning limit is 20s~60s; The control is expected to exceed the time threshold of 10s to 30s; The threshold for the estimated time limit for exceeding the danger limit is 3s to 10s; The threshold for the first persistent risk indicator is 0.2 to 0.4; The threshold for the second persistent risk indicator is 0.5 to 0.8; The threshold for the duration of the hazard level is 3s to 10s; The emergency trigger time threshold is 5s to 15s.

8. The method for predicting and classifying the handling of ships berthing through bends using flexible hoses according to claim 1, characterized in that, Based on the classification results, the corresponding level of tiered treatment actions are executed, and the status of the hose is continuously reviewed. The specific content of the review results includes: When the condition is determined to be normal, maintain the current conveying and parallel operation status, and only perform routine monitoring. When the alert level is determined, enhanced monitoring is implemented, including shortening the refresh cycle, increasing the data sampling frequency, prompting operators to pay attention to the hose crossing area and recording the alert status; When the situation is determined to be at the control level, control measures will be implemented, including reducing the transport flow, limiting the sway and bow roll adjustment of both ships, limiting the rapid manipulation of the ship's propellers, and requiring the personnel to enter the control mode. When the situation is determined to be dangerous, dangerous measures shall be taken, including suspending delivery, maintaining the stability of the vessel position, prohibiting unnecessary relative movement adjustments, and, if necessary, releasing local additional loads or switching to a hose protection posture. When the emergency level is determined, emergency response measures shall be implemented, including emergency shutdown, activation of emergency broadcast, implementation of hose release or unloading plan, and notification of relevant personnel to enter the accident prevention and control process; After executing the corresponding graded handling actions for each level, the current minimum radius of curvature and the predicted minimum radius of curvature are continuously monitored, and the predicted safety margin, the expected over-limit time, and the continuous risk indicators are calculated on a rolling basis to obtain the review results.

9. The method for predicting and classifying the handling of ships berthing through bends using flexible hoses according to claim 1, characterized in that, The specific details of implementing upgraded, maintained, or downgraded / restored measures based on the review results include: Based on the review results, determine whether the risk assessment of the curve continues to worsen, remains stable, or continues to improve; If the risk assessment of the curve continues to worsen, the response level will be upgraded to a higher level. If the risk assessment of the curve is stable but the exit conditions are not met, the current level of handling will be maintained; If the cornering risk assessment continuously meets the exit hysteresis condition and continues to reach the recovery observation time window, the risk level will be downgraded to the next lower level. The exit hysteresis condition includes: the recovery threshold is higher than the entry threshold, the recovery observation time is longer than the entry judgment time, and the switching between adjacent levels must meet the consistency of judgments for multiple consecutive frames or multiple consecutive cycles. The recovery observation time window increases with the risk level. If the warning conditions are triggered again after the system returns to normal, the system will re-enter the tiered response process.

10. A ship berthing hose bend prediction and grading system, characterized in that, The method for predicting and classifying the handling of ships passing through bends by hoses as described in any one of claims 1-9 includes: The data acquisition module is used to acquire the minimum allowable bending radius, current minimum curvature radius, predicted minimum curvature radius, and related operating condition information of the ship alongside the hose; the related operating condition information includes: sea state information, ship motion information, hose delivery status information, and data quality information; The threshold construction module is used to construct dynamic safety judgment thresholds based on the minimum allowable bending radius and associated working condition information; The risk assessment module is used to calculate the cornering risk assessment quantity based on the relationship between the current minimum radius of curvature, the predicted minimum radius of curvature, and the dynamic safety assessment threshold. The cornering risk assessment quantity includes: predicted safety margin, expected over-limit time, and continuous risk index. The risk classification module is used to classify the risk of a vessel taking a bend alongside a flexible hose based on the bend risk assessment value, and obtain the classification results; the risk classification includes: normal level, early warning level, control level, dangerous level and emergency level; The handling review module is used to execute the corresponding level of handling actions based on the classification results, and continuously review the status of the hose to obtain the review results; The tiered handling module is used to perform escalation, maintenance, or downgrade recovery based on the review results.

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