A ship-shore integrated loading and unloading method and system applicable to mast cranes

Abstract

This application relates to the field of port machinery loading and unloading technology, and provides a ship-shore integrated loading and unloading method and system suitable for mast cranes. The method includes: acquiring real-time ship position, heading, and attitude data through ship navigation equipment, and acquiring real-time tidal height and tidal current data through tidal monitoring equipment; inputting the acquired ship position, heading, attitude, tidal height, and tidal current data into the mast crane's control system; the control system generating corresponding control commands based on calculated dynamic compensation parameters and sending the control commands to the mast crane's luffing control system; the luffing control system adjusting the mast crane's lifting path and lifting attitude in real-time according to the control commands to maintain the lifting point vertical and the force balanced during equipment lowering; and monitoring the entire lifting operation in real-time through monitoring equipment installed on the mast crane and the ship.

Description

Technical Field

[0001] This application relates to the field of port machinery loading and unloading technology, and in particular to a ship-shore integrated loading and unloading method and system suitable for mast cranes. Background Technology

[0002] In offshore docks, floating platforms, and other environments with significant vessel berthing dynamics, mast crane shore loading and unloading operations face substantial challenges. The roll, pitch, and displacement changes caused by waves and tides, combined with fluctuations in tidal velocity and height, can lead to equipment swaying, lifting point tilting, or uneven stress during lifting, potentially causing hook detachment, equipment collisions, or even accidents. Traditional mast crane loading and unloading methods rely on manual experience to predict vessel movement trends or use simple sensors for local parameter compensation, making it difficult to respond accurately and synchronously to the coupled effects of vessel dynamics and tidal changes in real time. Existing technologies typically use vessel navigation data and tidal monitoring data independently, lacking a systematic dynamic compensation model for the lifting process, thus failing to achieve intelligent adjustment of the lifting path and attitude throughout the entire process. For example, some technologies only use a single sensor to monitor vessel displacement for local compensation, without integrating the influence of tidal velocity on lifting forces; or, while mentioning environmental data access, they lack a dynamic compensation algorithm based on multi-source data, resulting in insufficient compensation accuracy. Therefore, how to deeply integrate the ship's motion state with tidal change information to form an intelligent control method that can calculate dynamic compensation parameters in real time, in order to solve the technical problems of vertical maintenance of the suspension point and force balance in dynamic environments, has become a difficult problem that urgently needs to be solved in this field.

[0003] Therefore, a method is urgently needed to solve at least one of the above problems. Summary of the Invention

[0004] This application provides a ship-shore integrated loading and unloading method and system applicable to mast cranes, aiming to solve the problem that the existing technology has not proposed a systematic solution to connect ship navigation data with tidal change information in real time and automatically adjust the lifting path by constructing a dynamic lifting curve compensation model.

[0005] In a first aspect, embodiments of this application provide a ship-shore integrated loading and unloading method applicable to mast cranes, the method comprising: The ship's position, heading, and attitude data are acquired in real time through ship navigation equipment, and the tidal height and tidal current data of the sea surface are acquired in real time through tidal monitoring equipment. The acquired ship position, heading, attitude, tidal height, and tidal current data are then input into the mast crane's control system. The control system calculates the dynamic compensation parameters required for the current lifting operation based on the preset dynamic lifting curve compensation model and the input ship navigation data and sea surface tidal change information. The dynamic lifting curve compensation model is obtained in advance by analyzing and training lifting data under different ship motion states and tidal change conditions. The control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the luffing control system of the mast crane. The luffing control system adjusts the lifting path and lifting posture of the mast crane in real time according to control commands to keep the lifting point vertical and the force balanced during the equipment lowering process. Throughout the lifting operation, the operation process is monitored in real time by monitoring equipment installed on the mast crane and the ship to obtain real-time parameters during the lifting process.

[0006] In some embodiments, the real-time acquisition of the ship's position data, heading data, and attitude data through the ship navigation equipment includes: real-time acquisition of the ship's latitude and longitude position data through a global positioning system installed on the ship, real-time acquisition of the ship's roll angle, pitch angle, and heading angle data through an inertial navigation system, packaging the above data according to a preset time interval, and transmitting the data in real time to the control system of the mast crane through the ship's local area network.

[0007] In some embodiments, the real-time acquisition of tidal height data and tidal velocity data of the sea surface through tidal monitoring equipment includes: real-time acquisition of sea surface height data through a water level sensor deployed in the operating sea area; real-time acquisition of surface seawater velocity and direction data through a current meter; calculation of the difference between the tidal height data and preset reference surface data to obtain the real-time tidal height; and conversion of the velocity and direction data into vector data relative to the dock coordinate system to form tidal change information containing height and velocity.

[0008] In some embodiments, the step of inputting the acquired ship position data, heading data, attitude data, tidal height data, and tidal current velocity data into the mast crane's control system includes: performing analog-to-digital conversion on the analog signals output by the ship navigation equipment and tidal monitoring equipment, encapsulating the multi-source data according to a unified data protocol, and transmitting the encapsulated data packets to the central processing unit of the control system in real time via industrial Ethernet or fieldbus; wherein, the unified data protocol includes data type, timestamp, and checksum.

[0009] In some embodiments, the control system calculates the dynamic compensation parameters required for the current lifting operation based on a preset dynamic lifting curve compensation model, combined with input ship navigation data and sea surface tidal change information. This includes: inputting real-time acquired ship roll angle, pitch angle, heading angle, and tidal current velocity vector data into the dynamic lifting curve compensation model; using the model's built-in kinematic algorithm to calculate the impact of the ship's dynamic displacement on the lifting path; and generating dynamic compensation parameters including amplitude compensation, height compensation, and angle compensation based on the target position of the equipment lowering.

[0010] In some embodiments, the dynamic lifting curve compensation model is obtained in advance by analyzing and training lifting data under different ship motion states and tidal changes. This includes: collecting lifting path data and equipment attitude data of the ship under different roll amplitudes, pitch amplitudes, heading change rates, and different tidal current speeds in historical operations; constructing a training dataset containing input parameters and output parameters; and using machine learning algorithms to iteratively train the initial model until the error between the compensated lifting path output by the model and the actual stable lifting path is less than a preset threshold. The input parameters include ship motion parameters and tidal parameters, and the output parameters include the compensated lifting path.

[0011] In some embodiments, the control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the luffing control system of the mast crane. This includes: converting the amplitude compensation amount in the dynamic compensation parameters into speed adjustment commands for the luffing mechanism motor, converting the height compensation amount into start / stop and speed control commands for the winch, converting the angle compensation amount into angle adjustment commands for the slewing mechanism, encoding the control commands according to their priority and execution sequence, and sending them in real time to the execution unit of the luffing control system via a dedicated control bus.

[0012] In some embodiments, the step of adjusting the lifting path and lifting posture of the mast crane in real time according to control commands by the luffing control system to maintain the verticality and balanced force of the lifting point during the equipment lowering process includes: the luffing control system synchronously adjusting the boom amplitude, hook height and slewing angle of the mast crane according to the received control commands; monitoring the vertical deviation of the lifting point in real time by an inclination sensor installed at the hook; monitoring the force value of each sling in real time by a tension sensor; and triggering closed-loop feedback control when the vertical deviation or force imbalance exceeds a preset threshold to correct the control commands in real time.

[0013] In some embodiments, during the entire lifting operation, the operation process is monitored in real time by monitoring equipment installed on the mast crane and the ship to obtain real-time parameters during the lifting process. This includes: real-time acquisition of equipment lowering images by a camera installed on the mast crane; real-time acquisition of boom amplitude and hook height data by displacement sensors installed on the boom and luffing mechanism; real-time transmission of the ship's roll and pitch angles by attitude sensors on the ship; and synchronous recording of the above image data and sensor data in a time sequence to form full-process monitoring data including equipment status, ship status, and operating environment.

[0014] Secondly, this application provides a ship-shore integrated loading and unloading system suitable for mast cranes, the system comprising: The data acquisition unit is used to acquire the ship's position data, heading data, and attitude data in real time through the ship navigation equipment, and to acquire the tidal height data and tidal current speed data of the sea surface in real time through the tidal monitoring equipment; and to input the acquired ship position data, heading data, attitude data, tidal height data, and tidal current speed data into the mast crane's control system; The model input unit is used by the control system to calculate the dynamic compensation parameters required for the current lifting operation based on the preset dynamic lifting curve compensation model and the input ship navigation data and sea surface tidal change information. The dynamic lifting curve compensation model is obtained in advance by analyzing and training lifting data under different ship motion states and tidal change conditions. The control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the luffing control system of the mast crane. The control completion unit is used to adjust the lifting path and lifting posture of the mast crane in real time according to the control command through the luffing control system, so as to keep the lifting point vertical and the force balanced during the equipment lowering process; throughout the entire lifting operation, the operation process is monitored in real time by the monitoring equipment set on the mast crane and the ship to obtain real-time parameters during the lifting process.

[0015] This application provides a ship-shore integrated loading and unloading method and system suitable for mast cranes. By real-time access to ship navigation data and tidal change information, combined with a pre-set dynamic lifting curve compensation model, the invention automatically generates and adjusts the lifting path and attitude. This effectively addresses the operational needs of large-scale ship dynamic scenarios such as offshore terminals and floating platforms, overcoming the limitations of traditional methods that rely on manual experience or simple compensation. Dynamic adjustments maintain the verticality and balanced force of the lifting points, preventing hook detachment or tilting due to swaying during equipment lowering, reducing the risk of lifting accidents and ensuring the safety of personnel and equipment. The fully automated compensation process requires no manual intervention, shortening lifting adjustment time. Combined with real-time monitoring and parameter playback of the operation process, it facilitates subsequent operation review and strategy optimization, improving the efficiency of ship-shore docking and loading / unloading. The pre-trained dynamic lifting curve compensation model enables data-driven intelligent control, providing core technical support for the intelligent upgrading of port machinery equipment and aligning with the modern port automation development trend.

[0016] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic flowchart illustrating the steps of a ship-shore integrated loading and unloading method applicable to mast cranes, provided in an embodiment of this application. Figure 2 This is a schematic diagram illustrating the principle of a ship-shore integrated loading and unloading method applicable to mast cranes, provided in an embodiment of this application. Figure 3 This is a schematic block diagram of a ship-shore integrated loading and unloading system applicable to mast cranes, provided in one embodiment of this application; Figure 4 This is a schematic block diagram of the structure of a computer device provided in an embodiment of this application.

[0019] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0022] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0023] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0024] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0025] In offshore docks, floating platforms, and other environments with significant vessel berthing dynamics, mast crane shore loading and unloading operations face substantial challenges. The roll, pitch, and displacement changes caused by waves and tides, combined with fluctuations in tidal velocity and height, can lead to equipment swaying, lifting point tilting, or uneven stress during lifting, potentially causing hook detachment, equipment collisions, or even accidents. Traditional mast crane loading and unloading methods rely on manual experience to predict vessel movement trends or use simple sensors for local parameter compensation, making it difficult to respond accurately and synchronously to the coupled effects of vessel dynamics and tidal changes in real time. Existing technologies typically use vessel navigation data and tidal monitoring data independently, lacking a systematic dynamic compensation model for the lifting process, thus failing to achieve intelligent adjustment of the lifting path and attitude throughout the entire process. For example, some technologies only use a single sensor to monitor vessel displacement for local compensation, without integrating the influence of tidal velocity on lifting forces; or, while mentioning environmental data access, they lack a dynamic compensation algorithm based on multi-source data, resulting in insufficient compensation accuracy. Therefore, how to deeply integrate the ship's motion state with tidal change information to form an intelligent control method that can calculate dynamic compensation parameters in real time, in order to solve the technical problems of vertical maintenance of the suspension point and force balance in dynamic environments, has become a difficult problem that urgently needs to be solved in this field.

[0026] Existing technologies have not yet proposed a systematic solution for connecting ship navigation data with tidal change information in real time and automatically adjusting the lifting path by constructing a dynamic lifting curve compensation model.

[0027] To solve the above problem, please refer to Figure 1 and Figure 2 This application provides a ship-shore integrated loading and unloading method applicable to mast cranes. The computer equipment can be deployed on a single server or a server cluster. It can also be deployed on handheld terminals, laptops, wearable devices, or robots, etc.

[0028] The provided ship-shore integrated loading and unloading method for mast cranes includes steps S101 to S103. Details are as follows: Step S101. Obtain the ship's position data, heading data, and attitude data in real time through the ship navigation equipment, and obtain the tidal height data and tidal current speed data of the sea surface in real time through the tidal monitoring equipment; input the obtained ship position data, heading data, attitude data, tidal height data, and tidal current speed data into the mast crane's control system.

[0029] Specifically, ship motion status and sea surface environment data are acquired through ship navigation equipment and tide monitoring equipment, processed, and then input into the mast crane control system to build basic data support for the dynamic operating environment.

[0030] Ship navigation data acquisition utilizes the Global Positioning System (GPS) to collect real-time latitude and longitude position data with sub-meter accuracy, ensuring precise real-time positioning of the ship. The Inertial Navigation System (INS) acquires real-time data on the ship's roll angle (the angle of inclination about the transverse axis), pitch angle (the angle of pitch about the longitudinal axis), and heading angle at a frequency of no less than 100Hz to capture the ship's high-frequency swaying attitude. Data processing involves packaging position, heading, and attitude data at preset time intervals (e.g., 0.1 seconds), adding timestamps to mark the data acquisition time, and transmitting the data in real-time to the mast crane control system via the ship's Local Area Network (LAN), avoiding data delays caused by manual intervention.

[0031] Tidal change information is collected by deploying water level sensors (such as pressure or radar sensors) in the operating area to collect sea surface height data in real time. The difference between the data and the preset dock reference level data (such as mean sea level) is calculated to obtain the real-time tidal height, which reflects the impact of water level rise and fall on the ship's draft and lifting height. The surface seawater velocity (m / s) and direction (°) data are collected by an acoustic Doppler current meter (ADCP) and converted into vector data (including x and y direction velocity components) relative to the dock coordinate system to form dynamic influence parameters of tidal flow velocity.

[0032] Data synchronization ensures temporal consistency of multi-source data by aligning tidal height and current velocity data with ship navigation data using the same timestamp.

[0033] The data access control system converts analog signals (such as voltage and current signals) output by ship navigation equipment and tide monitoring equipment into digital signals through analog-to-digital conversion (A / D conversion). After conversion, the digital signals are encapsulated according to a unified data protocol (including data type, timestamp, and checksum) and transmitted to the central processing unit (CPU) of the control system via industrial Ethernet (EtherNet / IP) or fieldbus (such as PROFIBUS). This enables real-time fusion access of multi-source data and solves the problems of independent data application and lack of systematic integration in existing technologies.

[0034] Step S102. The control system calculates the dynamic compensation parameters required for the current lifting operation based on the preset dynamic lifting curve compensation model and the input ship navigation data and sea surface tidal change information. The dynamic lifting curve compensation model is obtained in advance by analyzing and training lifting data under different ship motion states and tidal change conditions. The control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the luffing control system of the mast crane.

[0035] Specifically, based on a preset dynamic lifting curve compensation model, real-time collected ship and tidal data are integrated to calculate the dynamic compensation parameters of the lifting path and convert them into control commands for each mechanism of the mast crane.

[0036] The construction and application of the dynamic lifting curve compensation model includes: Model input: Real-time acquired ship roll angle, pitch angle, heading angle (reflecting ship attitude), and tidal current vector data (reflecting the impact force of water flow on the ship and lifting equipment) are input into the model. The model incorporates a kinematic algorithm based on the principle of rigid body motion to calculate the hook position offset caused by ship roll / pitch, the lifting force deviation caused by tidal current velocity, and the influence of ship displacement on the target position of equipment lowering. Model training: Lifting path data (such as boom amplitude and hook height) and equipment attitude data (such as lifting point tilt angle and sling tension) of the ship under different roll amplitudes (within ±15°), pitch amplitudes (within ±10°), heading change rates (0.1° / s~5° / s), and tidal current velocities (0~3m / s) are collected in advance from historical operations. A training dataset containing input parameters (ship motion parameters and tidal parameters) and output parameters (compensated lifting path) is constructed. Machine learning algorithms (such as neural networks and support vector machines) are used to iteratively train the initial model, using the actual path data during stable hoisting as labels, until the error between the compensated path output by the model and the actual path is less than a preset threshold (such as vertical deviation < 0.5°, positional deviation < 5cm), to ensure the model's adaptability to complex dynamic environments.

[0037] The model outputs three-dimensional compensation parameters, including amplitude compensation (ΔR, horizontal extension distance of the boom), height compensation (ΔH, lifting distance of the hook), and angle compensation (Δθ, rotation angle of the slewing mechanism), which correspond to the control requirements of the mast crane's luffing, hoisting, and slewing mechanisms, respectively. For example, when the ship's roll causes the hook to shift to the right, the model generates a negative amplitude compensation to drive the boom to move to the left to counteract the shift.

[0038] Control command encoding and transmission converts compensation parameters into control commands for each mechanism: amplitude compensation is converted into speed adjustment commands for the luffing mechanism motor (e.g., when ΔR>0, the motor rotates forward to accelerate; when ΔR<0, the motor rotates in reverse to decelerate); height compensation is converted into start / stop and speed control commands for the winch (e.g., when ΔH>0, the winch rotates forward to lift the hook); and angle compensation is converted into angle adjustment commands for the slewing mechanism (e.g., when Δθ>0, the slewing motor rotates clockwise).

[0039] According to the command priority (such as safety protection command > position adjustment command > speed optimization command) and execution timing code, the commands are sent in real time to the execution unit of the variable amplitude control system through a dedicated control bus (such as CAN bus) to ensure the synchronization and accuracy of multi-mechanism collaborative control and avoid the one-sidedness of single parameter compensation in traditional methods.

[0040] Step S103. The luffing control system adjusts the lifting path and lifting posture of the mast crane in real time according to the control command to keep the lifting point vertical and the force balanced during the equipment lowering process; throughout the lifting operation, the operation process is monitored in real time by the monitoring equipment set on the mast crane and the ship to obtain real-time parameters during the lifting process.

[0041] The luffing control system executes control commands to dynamically adjust the hoisting path and attitude, while multi-source sensors enable real-time monitoring and data recording of the operation process.

[0042] The lifting path and attitude are dynamically adjusted via the luffing control system. Upon receiving commands, the system synchronously adjusts the boom amplitude (driven by the luffing cylinder or motor), hook height (by the winch winding and unwinding of the wire rope), and slewing angle (by the slewing bearing and motor), achieving three-dimensional path compensation. For example, when increased tidal current speed causes a ship to drift downstream, the system synchronously increases the amplitude and angle compensation to ensure the hook remains aligned with the target position for lowering the equipment. A dual-axis tilt sensor is installed at the hook to monitor the vertical deviation between the lifting point and the plumb line in real time (accuracy ±0.1°), and tension sensors are installed on the slings to monitor the force on each sling in real time (accuracy ±1%FS). When the vertical deviation exceeds a preset threshold (e.g., 1°) or the force imbalance (difference between maximum and minimum tension / average tension) exceeds 5%, closed-loop feedback control is triggered. The control command is then corrected a second time by combining real-time monitoring data, forming a closed-loop control loop of "model calculation → execution adjustment → feedback correction" to ensure that the lifting point is vertical (deviation ≤ 0.5°) and the force is balanced (imbalance ≤ 3%), fundamentally solving the problems of equipment shaking and tilting.

[0043] The monitoring data acquisition is carried out by using a high-definition camera (resolution ≥1080P) on the mast crane to collect real-time images of the equipment being lowered, and to monitor the docking status between the hook and the equipment; the displacement sensor (such as a laser rangefinder) installed on the boom obtains real-time boom amplitude data, and the encoder of the luffing mechanism obtains hook height data, with accuracy down to the centimeter level; the attitude sensor on the ship transmits the ship's roll angle and pitch angle in real time, and cross-checks them with the inertial navigation data in step S101.

[0044] Data recording and synchronization involves recording screen data and sensor data in a time sequence (accurate to milliseconds) to form full-process monitoring data that includes equipment status (amplitude, height, angle), ship status (roll, pitch, heading), and environmental data (tidal height, current speed). This data is stored on the hard drive or cloud server of the control system, supporting subsequent operation parameter playback, accident tracing, and model optimization, thereby improving the efficiency and intelligence level of operation review.

[0045] In some embodiments, the real-time acquisition of the ship's position data, heading data, and attitude data through the ship navigation equipment includes: real-time acquisition of the ship's latitude and longitude position data through a global positioning system installed on the ship, real-time acquisition of the ship's roll angle, pitch angle, and heading angle data through an inertial navigation system, packaging the above data according to a preset time interval, and transmitting the data in real time to the control system of the mast crane through the ship's local area network.

[0046] The ship's position, heading, and attitude are collected in real time by specialized navigation equipment and transmitted to the mast crane control system in a standardized format, providing basic parameters for dynamic compensation.

[0047] The data acquisition equipment uses a Global Positioning System (GPS) receiver (such as an NMEA-0183 protocol device) to collect the ship's latitude and longitude position data in real time, with a positioning accuracy better than 1 meter and an update frequency of ≥1Hz, ensuring dynamic tracking of the ship's real-time position. An Inertial Navigation System (INS) (including a three-axis gyroscope and accelerometer) is deployed to acquire the ship's roll angle (tilt angle around the x-axis, ±45° range), pitch angle (pitch angle around the y-axis, ±30° range), and heading angle (azimuth angle around the z-axis, 0°~360°) in real time, with a sampling frequency of ≥100Hz to capture high-frequency swaying attitudes. Data processing and transmission: Position, heading, and attitude data are packaged at preset time intervals (e.g., 0.2 seconds), with a UTC timestamp (accurate to milliseconds) and a data identifier header (e.g., "SHIP_DATA_2025") appended. This data is then transmitted in real time to the mast crane control system's network port via the ship's local area network (LAN) using the TCP / IP protocol, avoiding data delays and packet loss.

[0048] In some embodiments, the real-time acquisition of tidal height data and tidal velocity data of the sea surface through tidal monitoring equipment includes: real-time acquisition of sea surface height data through a water level sensor deployed in the operating sea area; real-time acquisition of surface seawater velocity and direction data through a current meter; calculation of the difference between the tidal height data and preset reference surface data to obtain the real-time tidal height; and conversion of the velocity and direction data into vector data relative to the dock coordinate system to form tidal change information containing height and velocity.

[0049] Sensors deployed in the sea area acquire tidal height and current velocity data in real time. After coordinate transformation, standardized tidal change information is generated, providing dynamic environmental parameters for the compensation model.

[0050] The data acquisition equipment collects sea surface height in real time by deploying radar water level sensors (range 0~50 meters, accuracy ±1 cm) at the pier front or ship anchorage, and synchronously accesses the State Oceanic Administration's reference surface data (such as the local theoretical lowest tide level). The real-time tidal height (height value relative to the reference surface, unit m) is obtained by calculating the difference. An acoustic Doppler current meter (ADCP) (operating frequency 600 kHz, measurement range 0~5 m / s, accuracy ±1%) is used to collect the surface seawater current velocity (m / s) and direction (°, calculated clockwise with true north as 0°), covering the water flow field in the ship operation area.

[0051] Data processing involves establishing a local coordinate system with the fixed point of the wharf as the origin (x-axis parallel to the wharf's leading edge, y-axis perpendicular to the wharf and outwards), converting the velocity and direction data into vector components (vx, vy) in the coordinate system, forming a tidal change information packet containing height (H) and velocity vectors (vx, vy), which is aligned with the timestamp of the ship navigation data.

[0052] In some embodiments, the step of inputting the acquired ship position data, heading data, attitude data, tidal height data, and tidal current velocity data into the mast crane's control system includes: performing analog-to-digital conversion on the analog signals output by the ship navigation equipment and tidal monitoring equipment, encapsulating the multi-source data according to a unified data protocol, and transmitting the encapsulated data packets to the central processing unit of the control system in real time via industrial Ethernet or fieldbus; wherein, the unified data protocol includes data type, timestamp, and checksum.

[0053] By standardizing the signals output from multiple devices and transmitting them to the control system via an industrial-grade communication network, the problem of fusion and access of heterogeneous data is solved.

[0054] Signal conversion is performed on ship navigation equipment (such as INS outputting ±5V analog signals) and tide sensors (such as ADCP outputting 4~20mA current signals). The signals are converted into digital signals through an analog-to-digital converter (A / D module) (16-bit resolution, 1kHz sampling rate) to match the digital input interface of the control system.

[0055] Data encapsulation is achieved by defining a unified data protocol format: [Data type (1 byte)][Timestamp (8 bytes)][Data content (N bytes)][CRC checksum (2 bytes)]; where the data type distinguishes between ship data (0x01) and tide data (0x02); the timestamp uses Unix epoch time (millisecond level); the data content includes the original values ​​and units of each sensor (e.g., latitude and longitude are retained to 6 decimal places, and angles are retained to 2 decimal places).

[0056] The encapsulated data packets are transmitted to the central processing unit (CPU) of the control system via industrial Ethernet (EtherCAT) or fieldbus (such as Modbus TCP), with a network latency of ≤10ms, ensuring data real-time performance.

[0057] In some embodiments, the control system calculates the dynamic compensation parameters required for the current lifting operation based on a preset dynamic lifting curve compensation model, combined with input ship navigation data and sea surface tidal change information. This includes: inputting real-time acquired ship roll angle, pitch angle, heading angle, and tidal current velocity vector data into the dynamic lifting curve compensation model; using the model's built-in kinematic algorithm to calculate the impact of the ship's dynamic displacement on the lifting path; and generating dynamic compensation parameters including amplitude compensation, height compensation, and angle compensation based on the target position of the equipment lowering.

[0058] Based on real-time ship attitude and tidal current data, a kinematic algorithm is used to calculate the three-dimensional compensation parameters of the hoisting path, thus solving the position deviation problem in dynamic environments.

[0059] The model input parameters are obtained in real time by accessing the ship's roll angle (φ), pitch angle (θ), heading angle (ψ), and tidal current velocity vector (vx, vy). φ / θ reflects the effect of the ship's tilt on the hook position, and vx / vy reflects the lateral impact force of the water flow on the lifting equipment.

[0060] The kinematic algorithm establishes a ship-mast crane kinematic model, assuming the hook is a rigid point mass, and calculates the hook displacement caused by the ship's roll / pitch through coordinate system transformation: Δx = L × sinθ, Δy = L × sinφ (L is the horizontal distance from the ship's center of gravity to the hook); and incorporates the additional force on the hook from the tidal current (F=1 / 2ρv). 2 (where A and ρ are the density of seawater, and A is the windward area of ​​the equipment), calculate the amplitude, height, and angular offset that need to be compensated.

[0061] The output parameters are generated by the amplitude compensation amount ΔR (arm extension distance, in meters, positive / negative indicates extension / retraction), the height compensation amount ΔH (hook lifting distance, in meters, positive / negative indicates rising / falling), and the angle compensation amount Δψ (rotation angle of the slewing mechanism, in degrees, positive / negative indicates clockwise / counterclockwise). These three parameters constitute a three-dimensional compensation parameter vector [ΔR, ΔH, Δψ].

[0062] In some embodiments, the dynamic lifting curve compensation model is obtained in advance by analyzing and training lifting data under different ship motion states and tidal changes. This includes: collecting lifting path data and equipment attitude data of the ship under different roll amplitudes, pitch amplitudes, heading change rates, and different tidal current speeds in historical operations; constructing a training dataset containing input parameters and output parameters; and using machine learning algorithms to iteratively train the initial model until the error between the compensated lifting path output by the model and the actual stable lifting path is less than a preset threshold. The input parameters include ship motion parameters and tidal parameters, and the output parameters include the compensated lifting path.

[0063] By training a dynamic compensation model using historical hoisting data, the model's adaptability to complex working conditions is improved, solving the problem of insufficient accuracy in traditional experience-based compensation.

[0064] Training data collection involved collecting ship motion parameters (roll amplitude 0°~15°, pitch amplitude 0°~10°, heading change rate 0.5° / s~3° / s) and tidal parameters (current velocity 0~2.5m / s, current direction 0°~180°) under different operational scenarios, while simultaneously recording lifting path data (lifting boom amplitude R, hook height H, slewing angle ψ) and equipment attitude data (lifting point tilt angle α, sling tension F1~F4), forming a training dataset containing over 100,000 samples.

[0065] Model construction and training adopted a neural network model (such as an LSTM+CNN hybrid network) as the initial model. The input layer consists of ship motion parameters (3D) + tidal parameters (3D, including height, vx, vy), and the output layer consists of compensated path parameters (R', H', ψ'). The mean squared error (MSE) was used as the loss function, and the model was optimized by stochastic gradient descent (SGD). The model was iteratively trained until the deviation between the compensated path output by the model and the actual stable path was ≤ the threshold (α≤0.5°, ΔR≤10cm). The generalization ability was then verified on the test set.

[0066] In some embodiments, the control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the luffing control system of the mast crane. This includes: converting the amplitude compensation amount in the dynamic compensation parameters into speed adjustment commands for the luffing mechanism motor, converting the height compensation amount into start / stop and speed control commands for the winch, converting the angle compensation amount into angle adjustment commands for the slewing mechanism, encoding the control commands according to their priority and execution sequence, and sending them in real time to the execution unit of the luffing control system via a dedicated control bus.

[0067] By converting compensation parameters into execution commands for each mechanism of the mast crane, encoding them according to priority, and transmitting them in real time, multi-mechanism collaborative control is achieved.

[0068] The instruction conversion logic includes: Amplitude compensation ΔR: mapped to the speed command of the servo motor of the luffing mechanism (e.g., ΔR=+0.5m corresponds to a motor speed of +200rpm, and the reverse is similar), and the motor start, stop and direction are controlled through the PLC pulse output module; Height compensation ΔH: converted to the speed command of the winch inverter (e.g., ΔH=+1m corresponds to a frequency of +5Hz), and closed-loop position control is achieved by combining absolute encoder feedback; Angle compensation Δψ: generates the angle increment command of the slewing mechanism (e.g., Δψ=+5° corresponds to a servo motor rotation of 5°), and positioning is achieved using an absolute encoder with an accuracy of ±0.1°.

[0069] Command processing is achieved by defining command priorities: emergency stop command (highest) > safety limit command > compensation adjustment command > status monitoring command; commands are sent to each execution unit via a dedicated control bus (such as CANopen) in periodic messages (period 20ms) to ensure command synchronization and avoid mechanism action conflicts.

[0070] In some embodiments, the step of adjusting the lifting path and lifting posture of the mast crane in real time according to control commands by the luffing control system to maintain the verticality and balanced force of the lifting point during the equipment lowering process includes: the luffing control system synchronously adjusting the boom amplitude, hook height and slewing angle of the mast crane according to the received control commands; monitoring the vertical deviation of the lifting point in real time by an inclination sensor installed at the hook; monitoring the force value of each sling in real time by a tension sensor; and triggering closed-loop feedback control when the vertical deviation or force imbalance exceeds a preset threshold to correct the control commands in real time.

[0071] By monitoring the status of the lifting points in real time through multiple sensors and combining control commands, dynamic adjustments and closed-loop corrections are achieved to ensure the verticality and balanced force of the lifting points.

[0072] After receiving instructions through the luffing control system, the multi-mechanism collaborative control synchronously drives the boom luffing cylinder (adjusting the amplitude), the winch wire rope (adjusting the height), and the slewing bearing gear (adjusting the angle). The speed matching algorithm of the three mechanisms ensures smooth movement (e.g., amplitude adjustment speed ≤ 0.3m / s, angle adjustment speed ≤ 5° / s).

[0073] The closed-loop feedback correction uses a dual-axis tilt sensor (accuracy ±0.1°) installed at the hook to monitor the vertical deviation (α) of the lifting point in real time. When |α|>1°, the proportional-integral (PI) controller is triggered to dynamically correct the angle compensation amount Δψ'. A tension sensor (range 0~50 tons, accuracy ±0.5%) is installed at the root of the sling to calculate the force imbalance η=|Fmax-Fmin| / Favg. When η>5%, the height compensation amount ΔH' is automatically adjusted to balance the force, forming a "monitoring-correction-execution" closed loop (response time ≤200ms).

[0074] In some embodiments, during the entire lifting operation, the operation process is monitored in real time by monitoring equipment installed on the mast crane and the ship to obtain real-time parameters during the lifting process. This includes: real-time acquisition of equipment lowering images by a camera installed on the mast crane; real-time acquisition of boom amplitude and hook height data by displacement sensors installed on the boom and luffing mechanism; real-time transmission of the ship's roll and pitch angles by attitude sensors on the ship; and synchronous recording of the above image data and sensor data in a time sequence to form full-process monitoring data including equipment status, ship status, and operating environment.

[0075] By collecting operational data through multiple types of sensors and cameras and recording it synchronously in a time sequence, a full-process monitoring system is built to support safety traceability and model optimization.

[0076] The monitoring data acquisition includes: visual monitoring: a high-definition camera (1920×1080, 30fps) is installed at the head of the mast boom to collect the image from the device in real time, convert it into a digital signal through an HDMI encoder, and transmit it to the control system after adding a timestamp; displacement monitoring: a magnetostrictive displacement sensor (accuracy ±0.1mm) is installed on the boom luffing cylinder to obtain the amplitude R, and an incremental encoder (resolution 1024 pulses / revolution) is installed on the winch drum to calculate the hook height H; ship attitude: the roll angle φ and pitch angle θ of the inertial navigation system are reused and transmitted back in real time through the ship's local area network for cross-verification with the data in step S101.

[0077] Data recording involves synchronously storing image data and sensor data on solid-state drives (SSDs) in millisecond-level time series. The file format is a custom binary protocol and includes data type, timestamp, device ID, and parameter values. It supports the playback of the operation process through dedicated software, providing data support for accident analysis and model iteration.

[0078] This invention automatically generates and adjusts the lifting path and attitude by real-time access to ship navigation data and tidal change information, combined with a pre-set dynamic lifting curve compensation model. This effectively addresses the operational needs of highly dynamic ship scenarios such as offshore terminals and floating platforms, overcoming the limitations of traditional methods that rely on manual experience or simple compensation. Dynamic adjustments maintain the verticality and balanced force of the lifting points, preventing hook detachment or tilting due to swaying during equipment lowering, reducing the risk of lifting accidents and ensuring the safety of personnel and equipment. The fully automated compensation process requires no manual intervention, shortening lifting adjustment time. Combined with real-time monitoring and parameter playback of the operation process, it facilitates subsequent operation review and strategy optimization, improving the efficiency of ship-to-shore loading and unloading. The pre-trained dynamic lifting curve compensation model enables data-driven intelligent control, providing core technical support for the intelligent upgrading of port machinery equipment and aligning with the modern trend of port automation.

[0079] Please see Figure 3 As shown, Figure 3 This is a schematic diagram of a ship-shore integrated loading and unloading system 200 for mast cranes provided in this application embodiment. The ship-shore integrated loading and unloading system 200 for mast cranes is used to execute the steps of the ship-shore integrated loading and unloading methods for mast cranes shown in the above embodiments. The ship-shore integrated loading and unloading system 200 for mast cranes can be a single server or a server cluster, or it can be a terminal, such as a handheld terminal, laptop computer, wearable device, or robot.

[0080] like Figure 3 As shown, the ship-shore integrated loading and unloading system 200 suitable for mast cranes includes: The data acquisition unit 201 is used to acquire the ship's position data, heading data, and attitude data in real time through the ship navigation equipment, and to acquire the tidal height data and tidal current speed data of the sea surface in real time through the tidal monitoring equipment; and to input the acquired ship position data, heading data, attitude data, tidal height data, and tidal current speed data into the mast crane's control system; The model input unit 202 is used by the control system to calculate the dynamic compensation parameters required for the current lifting operation based on the preset dynamic lifting curve compensation model and the input ship navigation data and sea surface tidal change information. The dynamic lifting curve compensation model is obtained in advance by analyzing and training lifting data under different ship motion states and tidal change conditions. The control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the luffing control system of the mast crane. The control completion unit 203 is used to adjust the lifting path and lifting posture of the mast crane in real time according to the control command through the luffing control system, so as to keep the lifting point vertical and the force balanced during the equipment lowering process; during the entire lifting operation, the operation process is monitored in real time by the monitoring equipment set on the mast crane and the ship to obtain real-time parameters during the lifting process.

[0081] In some embodiments, the real-time acquisition of the ship's position data, heading data, and attitude data through the ship navigation equipment includes: real-time acquisition of the ship's latitude and longitude position data through a global positioning system installed on the ship, real-time acquisition of the ship's roll angle, pitch angle, and heading angle data through an inertial navigation system, packaging the above data according to a preset time interval, and transmitting the data in real time to the control system of the mast crane through the ship's local area network.

[0082] In some embodiments, the real-time acquisition of tidal height data and tidal velocity data of the sea surface through tidal monitoring equipment includes: real-time acquisition of sea surface height data through a water level sensor deployed in the operating sea area; real-time acquisition of surface seawater velocity and direction data through a current meter; calculation of the difference between the tidal height data and preset reference surface data to obtain the real-time tidal height; and conversion of the velocity and direction data into vector data relative to the dock coordinate system to form tidal change information containing height and velocity.

[0083] In some embodiments, the step of inputting the acquired ship position data, heading data, attitude data, tidal height data, and tidal current velocity data into the mast crane's control system includes: performing analog-to-digital conversion on the analog signals output by the ship navigation equipment and tidal monitoring equipment, encapsulating the multi-source data according to a unified data protocol, and transmitting the encapsulated data packets to the central processing unit of the control system in real time via industrial Ethernet or fieldbus; wherein, the unified data protocol includes data type, timestamp, and checksum.

[0084] In some embodiments, the control system calculates the dynamic compensation parameters required for the current lifting operation based on a preset dynamic lifting curve compensation model, combined with input ship navigation data and sea surface tidal change information. This includes: inputting real-time acquired ship roll angle, pitch angle, heading angle, and tidal current velocity vector data into the dynamic lifting curve compensation model; using the model's built-in kinematic algorithm to calculate the impact of the ship's dynamic displacement on the lifting path; and generating dynamic compensation parameters including amplitude compensation, height compensation, and angle compensation based on the target position of the equipment lowering.

[0085] In some embodiments, the dynamic lifting curve compensation model is obtained in advance by analyzing and training lifting data under different ship motion states and tidal changes. This includes: collecting lifting path data and equipment attitude data of the ship under different roll amplitudes, pitch amplitudes, heading change rates, and different tidal current speeds in historical operations; constructing a training dataset containing input parameters and output parameters; and using machine learning algorithms to iteratively train the initial model until the error between the compensated lifting path output by the model and the actual stable lifting path is less than a preset threshold. The input parameters include ship motion parameters and tidal parameters, and the output parameters include the compensated lifting path.

[0086] In some embodiments, the control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the luffing control system of the mast crane. This includes: converting the amplitude compensation amount in the dynamic compensation parameters into speed adjustment commands for the luffing mechanism motor, converting the height compensation amount into start / stop and speed control commands for the winch, converting the angle compensation amount into angle adjustment commands for the slewing mechanism, encoding the control commands according to their priority and execution sequence, and sending them in real time to the execution unit of the luffing control system via a dedicated control bus.

[0087] In some embodiments, the step of adjusting the lifting path and lifting posture of the mast crane in real time according to control commands by the luffing control system to maintain the verticality and balanced force of the lifting point during the equipment lowering process includes: the luffing control system synchronously adjusting the boom amplitude, hook height and slewing angle of the mast crane according to the received control commands; monitoring the vertical deviation of the lifting point in real time by an inclination sensor installed at the hook; monitoring the force value of each sling in real time by a tension sensor; and triggering closed-loop feedback control when the vertical deviation or force imbalance exceeds a preset threshold to correct the control commands in real time.

[0088] In some embodiments, during the entire lifting operation, the operation process is monitored in real time by monitoring equipment installed on the mast crane and the ship to obtain real-time parameters during the lifting process. This includes: real-time acquisition of equipment lowering images by a camera installed on the mast crane; real-time acquisition of boom amplitude and hook height data by displacement sensors installed on the boom and luffing mechanism; real-time transmission of the ship's roll and pitch angles by attitude sensors on the ship; and synchronous recording of the above image data and sensor data in a time sequence to form full-process monitoring data including equipment status, ship status, and operating environment.

[0089] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the ship-shore integrated loading and unloading system and its modules applicable to mast cranes described above can be found in the corresponding contents of the various embodiments of the ship-shore integrated loading and unloading method applicable to mast cranes, and will not be repeated here.

[0090] The aforementioned ship-shore integrated loading and unloading method applicable to mast cranes can be implemented as a computer program, which can be used in various ways, such as... Figure 3 It runs on the device shown.

[0091] Please see Figure 4 , Figure 4 This is a schematic block diagram of the structure of a computer device provided in an embodiment of this application. The computer device includes a processor, a memory, and a network interface connected via a device bus, wherein the memory may include a storage medium and internal memory.

[0092] The storage medium may store operating equipment and computer programs. The computer program includes program instructions that, when executed, cause the processor to perform any ship-to-shore integrated loading and unloading method applicable to mast cranes.

[0093] The processor provides computing and control capabilities, supporting the operation of the entire computer device.

[0094] Internal memory provides an environment for the execution of computer programs stored in non-volatile storage media. When executed by a processor, the computer program enables the processor to perform any ship-to-shore integrated loading and unloading method applicable to mast cranes.

[0095] This network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the terminal to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0096] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.

[0097] In one embodiment, the processor is configured to run a computer program stored in memory to perform the following steps: The ship's position, heading, and attitude data are acquired in real time through ship navigation equipment, and the tidal height and tidal current data of the sea surface are acquired in real time through tidal monitoring equipment. The acquired ship position, heading, attitude, tidal height, and tidal current data are then input into the mast crane's control system. The control system calculates the dynamic compensation parameters required for the current lifting operation based on the preset dynamic lifting curve compensation model and the input ship navigation data and sea surface tidal change information. The dynamic lifting curve compensation model is obtained in advance by analyzing and training lifting data under different ship motion states and tidal change conditions. The control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the luffing control system of the mast crane. The luffing control system adjusts the lifting path and lifting posture of the mast crane in real time according to control commands to keep the lifting point vertical and the force balanced during the equipment lowering process. Throughout the lifting operation, the operation process is monitored in real time by monitoring equipment installed on the mast crane and the ship to obtain real-time parameters during the lifting process.

[0098] In some embodiments, the real-time acquisition of the ship's position data, heading data, and attitude data through the ship navigation equipment includes: real-time acquisition of the ship's latitude and longitude position data through a global positioning system installed on the ship, real-time acquisition of the ship's roll angle, pitch angle, and heading angle data through an inertial navigation system, packaging the above data according to a preset time interval, and transmitting the data in real time to the control system of the mast crane through the ship's local area network.

[0099] In some embodiments, the real-time acquisition of tidal height data and tidal velocity data of the sea surface through tidal monitoring equipment includes: real-time acquisition of sea surface height data through a water level sensor deployed in the operating sea area; real-time acquisition of surface seawater velocity and direction data through a current meter; calculation of the difference between the tidal height data and preset reference surface data to obtain the real-time tidal height; and conversion of the velocity and direction data into vector data relative to the dock coordinate system to form tidal change information containing height and velocity.

[0100] In some embodiments, the step of inputting the acquired ship position data, heading data, attitude data, tidal height data, and tidal current velocity data into the mast crane's control system includes: performing analog-to-digital conversion on the analog signals output by the ship navigation equipment and tidal monitoring equipment, encapsulating the multi-source data according to a unified data protocol, and transmitting the encapsulated data packets to the central processing unit of the control system in real time via industrial Ethernet or fieldbus; wherein, the unified data protocol includes data type, timestamp, and checksum.

[0101] In some embodiments, the control system calculates the dynamic compensation parameters required for the current lifting operation based on a preset dynamic lifting curve compensation model, combined with input ship navigation data and sea surface tidal change information. This includes: inputting real-time acquired ship roll angle, pitch angle, heading angle, and tidal current velocity vector data into the dynamic lifting curve compensation model; using the model's built-in kinematic algorithm to calculate the impact of the ship's dynamic displacement on the lifting path; and generating dynamic compensation parameters including amplitude compensation, height compensation, and angle compensation based on the target position of the equipment lowering.

[0102] In some embodiments, the dynamic lifting curve compensation model is obtained in advance by analyzing and training lifting data under different ship motion states and tidal changes. This includes: collecting lifting path data and equipment attitude data of the ship under different roll amplitudes, pitch amplitudes, heading change rates, and different tidal current speeds in historical operations; constructing a training dataset containing input parameters and output parameters; and using machine learning algorithms to iteratively train the initial model until the error between the compensated lifting path output by the model and the actual stable lifting path is less than a preset threshold. The input parameters include ship motion parameters and tidal parameters, and the output parameters include the compensated lifting path.

[0103] In some embodiments, the control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the luffing control system of the mast crane. This includes: converting the amplitude compensation amount in the dynamic compensation parameters into speed adjustment commands for the luffing mechanism motor, converting the height compensation amount into start / stop and speed control commands for the winch, converting the angle compensation amount into angle adjustment commands for the slewing mechanism, encoding the control commands according to their priority and execution sequence, and sending them in real time to the execution unit of the luffing control system via a dedicated control bus.

[0104] In some embodiments, the step of adjusting the lifting path and lifting posture of the mast crane in real time according to control commands by the luffing control system to maintain the verticality and balanced force of the lifting point during the equipment lowering process includes: the luffing control system synchronously adjusting the boom amplitude, hook height and slewing angle of the mast crane according to the received control commands; monitoring the vertical deviation of the lifting point in real time by an inclination sensor installed at the hook; monitoring the force value of each sling in real time by a tension sensor; and triggering closed-loop feedback control when the vertical deviation or force imbalance exceeds a preset threshold to correct the control commands in real time.

[0105] In some embodiments, during the entire lifting operation, the operation process is monitored in real time by monitoring equipment installed on the mast crane and the ship to obtain real-time parameters during the lifting process. This includes: real-time acquisition of equipment lowering images by a camera installed on the mast crane; real-time acquisition of boom amplitude and hook height data by displacement sensors installed on the boom and luffing mechanism; real-time transmission of the ship's roll and pitch angles by attitude sensors on the ship; and synchronous recording of the above image data and sensor data in a time sequence to form full-process monitoring data including equipment status, ship status, and operating environment.

[0106] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to implement the steps of the ship-shore integrated loading and unloading method for mast cranes as provided in any embodiment of this application.

[0107] The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device.

[0108] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A ship-shore integrated loading and unloading method suitable for mast cranes, characterized in that, The method includes: The ship's position, heading, and attitude data are acquired in real time through ship navigation equipment, and the tidal height and tidal current data of the sea surface are acquired in real time through tidal monitoring equipment. The acquired ship position, heading, attitude, tidal height, and tidal current data are then input into the mast crane's control system. The control system calculates the dynamic compensation parameters required for the current lifting operation based on a preset dynamic lifting curve compensation model, combined with input ship navigation data and sea surface tidal change information. This includes: inputting real-time acquired ship roll angle, pitch angle, heading angle, and tidal current vector data into the dynamic lifting curve compensation model; using the model's built-in kinematic algorithm to calculate the impact of ship dynamic displacement on the lifting path; and generating dynamic compensation parameters including amplitude compensation, height compensation, and angle compensation based on the target position of the equipment. The dynamic lifting curve compensation model is obtained in advance through analysis and training of lifting data under different ship motion states and tidal change conditions. The control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the mast crane's luffing control system. This includes: converting the amplitude compensation in the dynamic compensation parameters into speed adjustment commands for the luffing mechanism motor; converting the height compensation into start / stop and speed control commands for the winch; and converting the angle compensation into angle adjustment commands for the slewing mechanism. The commands are encoded according to their priority and execution sequence and sent to the execution unit of the luffing control system in real time via a dedicated control bus. The luffing control system adjusts the lifting path and posture of the mast crane in real time according to control commands to maintain the verticality and balanced force of the lifting points during equipment lowering. This includes: the luffing control system synchronously adjusts the boom amplitude, hook height, and slewing angle of the mast crane according to received control commands; it monitors the vertical deviation of the lifting points in real time using tilt sensors installed at the hook; and it monitors the force values ​​of each sling in real time using tension sensors. When the vertical deviation or force imbalance exceeds a preset threshold, closed-loop feedback control is triggered to correct the control commands in real time. Throughout the lifting operation, monitoring equipment installed on the mast crane and the ship monitors the operation in real time to obtain real-time parameters during the lifting process. The construction and application of the dynamic lifting curve compensation model includes: Input to the dynamic lifting curve compensation model: Real-time acquired data on the ship's roll angle, pitch angle, heading angle, and tidal current velocity vector are input into the model. The dynamic lifting curve compensation model incorporates a kinematic algorithm based on the principle of rigid body motion to calculate the hook position offset caused by the ship's roll or pitch, the lifting force deviation caused by the tidal current velocity, and the influence of the ship's displacement on the target position of the equipment. Training of the dynamic lifting curve compensation model: Pre-collecting lifting path data and equipment attitude data of the ship under different roll amplitudes, pitch amplitudes, heading change rates, and tidal current velocities in historical operations, and constructing a model containing input parameters. The training dataset for the output parameters is used; the initial model is iteratively trained using machine learning algorithms, with the actual stable lifting path data as labels, until the error between the compensated path output by the model and the actual path is less than a preset threshold, ensuring the model's adaptability to complex dynamic environments; the preset thresholds are: vertical deviation < 0.5°, position deviation < 5cm; roll amplitude within ±15°; pitch amplitude within ±10°; heading change rate of 0.1° / s~5° / s; tidal current speed of 0~3m / s; lifting path data includes boom amplitude and hook height; equipment attitude data includes lifting point tilt angle and sling tension; input parameters include ship motion parameters and tidal parameters; output parameters include the compensated lifting path.

2. The method according to claim 1, characterized in that, The method of acquiring real-time ship position data, heading data, and attitude data through ship navigation equipment includes: The ship's latitude and longitude position data are collected in real time by a global positioning system installed on the ship, and the ship's roll angle, pitch angle and heading angle data are obtained in real time by an inertial navigation system. The above data are packaged according to a preset time interval and transmitted to the control system of the mast crane in real time through the ship's local area network.

3. The method according to claim 1, characterized in that, The method of acquiring real-time tidal height and tidal current data of the sea surface through tidal monitoring equipment includes: Sea level sensors deployed in the operating area collect sea surface height data in real time, and current meters collect surface seawater velocity and direction data in real time. The tidal height data is calculated by subtracting from the preset reference surface data to obtain the real-time tidal height. The velocity and direction data are converted into vector data relative to the dock coordinate system to form tidal change information containing height and velocity.

4. The method according to claim 1, characterized in that, The process of inputting the acquired ship position data, heading data, attitude data, tidal height data, and tidal current speed data into the mast crane control system includes: The analog signals output by ship navigation equipment and tide monitoring equipment are converted from analog to digital, and the multi-source data is encapsulated according to a unified data protocol. The encapsulated data packets are then transmitted in real time to the central processing unit of the control system via industrial Ethernet or fieldbus. The unified data protocol includes data type, timestamp, and checksum.

5. The method according to claim 1, characterized in that, The dynamic lifting curve compensation model is obtained in advance through analysis and training of lifting data under different ship motion states and tidal changes, including: Data on the lifting path and equipment attitude of the vessel under different roll amplitudes, pitch amplitudes, rates of change of course, and tidal current speeds during historical operations are collected to construct a training dataset containing input and output parameters. Machine learning algorithms are used to iteratively train the initial model until the error between the compensated lifting path output by the model and the actual stable lifting path is less than a preset threshold. The input parameters include vessel motion parameters and tidal parameters, and the output parameters include the compensated lifting path.

6. The method according to claim 1, characterized in that, Throughout the entire lifting operation, monitoring equipment installed on the mast crane and the vessel is used to monitor the operation in real time and obtain real-time parameters during the lifting process, including: The system uses cameras mounted on the mast crane to capture real-time images of the equipment being lowered, displacement sensors installed on the boom and luffing mechanism to acquire real-time data on boom amplitude and hook height, and attitude sensors on the ship to transmit real-time roll and pitch angles. The system records the above video and sensor data synchronously in a time sequence to form a full-process monitoring system that includes equipment status, ship status, and operating environment.

7. A ship-shore integrated loading and unloading system suitable for mast cranes, characterized in that, The system includes: The data acquisition unit is used to acquire the ship's position data, heading data, and attitude data in real time through the ship navigation equipment, and to acquire the tidal height data and tidal current speed data of the sea surface in real time through the tidal monitoring equipment; and to input the acquired ship position data, heading data, attitude data, tidal height data, and tidal current speed data into the mast crane's control system; The model input unit is used to calculate the dynamic compensation parameters required for the current lifting operation based on a preset dynamic lifting curve compensation model, combined with input ship navigation data and sea surface tidal change information. This includes: inputting real-time acquired ship roll angle, pitch angle, heading angle, and tidal current vector data into the dynamic lifting curve compensation model; using the model's built-in kinematic algorithm to calculate the impact of ship dynamic displacement on the lifting path; and generating dynamic compensation parameters including amplitude compensation, height compensation, and angle compensation based on the target position of the equipment. The dynamic lifting curve compensation model is obtained in advance through analysis and training of lifting data under different ship motion states and tidal change conditions. The control system generates corresponding control commands based on the calculated dynamic compensation parameters and sends the control commands to the mast crane's luffing control system. This includes: converting the amplitude compensation in the dynamic compensation parameters into speed adjustment commands for the luffing mechanism motor; converting the height compensation into start / stop and speed control commands for the winch; and converting the angle compensation into angle adjustment commands for the slewing mechanism. The commands are encoded according to their priority and execution sequence and sent to the execution unit of the luffing control system in real time via a dedicated control bus. The control completion unit is used to adjust the lifting path and lifting posture of the mast crane in real time according to the control command through the luffing control system, so as to keep the lifting point vertical and the force balanced during the equipment lowering process. This includes: the luffing control system synchronously adjusting the boom amplitude, hook height, and slewing angle of the mast crane according to the received control command; monitoring the vertical deviation of the lifting point in real time through an inclination sensor installed at the hook; monitoring the force value of each sling in real time through a tension sensor; and triggering closed-loop feedback control when the vertical deviation or force imbalance exceeds a preset threshold to correct the control command in real time. Throughout the lifting operation, the monitoring process is monitored in real time through monitoring equipment installed on the mast crane and the ship to obtain real-time parameters during the lifting process. The construction and application of the dynamic lifting curve compensation model includes: Input to the dynamic lifting curve compensation model: Real-time acquired data on the ship's roll angle, pitch angle, heading angle, and tidal current velocity vector are input into the model. The dynamic lifting curve compensation model incorporates a kinematic algorithm based on the principle of rigid body motion to calculate the hook position offset caused by the ship's roll or pitch, the lifting force deviation caused by the tidal current velocity, and the influence of the ship's displacement on the target position of the equipment. Training of the dynamic lifting curve compensation model: Pre-collecting lifting path data and equipment attitude data of the ship under different roll amplitudes, pitch amplitudes, heading change rates, and tidal current velocities in historical operations, and constructing a model containing input parameters. The training dataset for the output parameters is used; the initial model is iteratively trained using machine learning algorithms, with the actual stable lifting path data as labels, until the error between the compensated path output by the model and the actual path is less than a preset threshold, ensuring the model's adaptability to complex dynamic environments; the preset thresholds are: vertical deviation < 0.5°, position deviation < 5cm; roll amplitude within ±15°; pitch amplitude within ±10°; heading change rate of 0.1° / s~5° / s; tidal current speed of 0~3m / s; lifting path data includes boom amplitude and hook height; equipment attitude data includes lifting point tilt angle and sling tension; input parameters include ship motion parameters and tidal parameters; output parameters include the compensated lifting path.

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