Automatic hull balance correction method based on collaborative operation of multiple ship unloaders

Abstract

The invention discloses a ship body balance automatic correction method based on cooperative operation of multiple ship unloaders, and particularly relates to the technical field of ship body balance automatic correction. When it is recognized that a ship enters a to-be-unloaded area, the volume and weight distribution of goods in a cabin is monitored in real time; based on the ship structure parameters and the real-time weight data, calculating barycentric coordinates and moment distribution of the ship body; the unbalance risk level is judged by monitoring the transverse and longitudinal torque difference in real time; according to the ship unloader, the cabin is divided into a plurality of areas according to the working range of the ship unloader; at the moment, the area weight coefficient of the area where the cargo coordinates belong, the moving cost coefficient of the current position of each ship unloader and the historical operation load index of the ship unloader need to be comprehensively evaluated to determine the number of the ship unloader for grabbing the cargo; after grabbing is completed, an updating coefficient is calculated according to the unbalance risk level and the grabbing weight; when the updating coefficient is larger than a system preset threshold value, the barycentric coordinates and torque distribution of the ship body need to be updated.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic correction of hull balance, and more specifically, to an automatic correction method for hull balance based on collaborative operation of multiple ship unloaders. Background Art

[0002] The collaborative operation of multiple ship unloaders refers to integrating the operations of multiple ship unloaders through intelligent technologies, enabling them to dynamically coordinate actions, share data, and adjust strategies in real time during the unloading process to maintain hull balance and improve overall efficiency. The core lies in using high-precision sensors to monitor the weight distribution of goods in real time, dynamically calculate the offset of the ship's center of gravity, and generate multi-machine collaborative unloading instructions, thereby avoiding the risk of hull tilt caused by traditional single-machine independent operation.

[0003] In the prior art, it is necessary to recalculate the center of gravity and moment of the ship after grasping the goods, which wastes computing power and is also likely to cause the ship unloader to become sluggish in response.

[0004] To solve the above defects, a technical solution is provided now. Summary of the Invention

[0005] To overcome the above defects of the prior art, an embodiment of the present invention provides an automatic correction method for hull balance based on collaborative operation of multiple ship unloaders to solve the problems raised in the above background art.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The automatic correction method for hull balance based on collaborative operation of multiple ship unloaders includes the following steps:

[0008] When it is recognized that the ship enters the area to be unloaded, the volume and weight distribution of the goods in the cargo hold are monitored in real time; based on the ship structure parameters and real-time weight data, the center of gravity coordinates and moment distribution of the ship are calculated; the imbalance risk level is judged by monitoring the transverse and longitudinal moment differences in real time;

[0009] The cargo hold is divided into multiple areas according to the working range of the ship unloader, and each ship unloader is responsible for the unloading task of each area; if the goods to be grasped are at the junction of two areas, it is necessary to comprehensively evaluate the area weight coefficient of the area where the goods coordinates belong, the movement cost coefficient of the current position of each ship unloader, and its historical operation load index to determine the ship unloader number for grasping the goods;

[0010] After grasping, the update coefficient is calculated according to the imbalance risk level and the grasped weight; when the update coefficient is greater than the system preset threshold, it is necessary to update the center of gravity coordinates and moment distribution of the hull.

[0011] In a preferred embodiment, the steps of calculating the ship's center of gravity coordinates and moment distribution based on ship structure parameters and real-time weight data are as follows: Establish a three-dimensional coordinate system for the ship, with the origin at the intersection of the baseline and the midship section, the longitudinal X-axis pointing forward, the transverse Y-axis pointing to the starboard side, and the vertical Z-axis pointing vertically upward; for each weight unit, obtain its real-time weight W i and the centroid coordinates (x i , y i , z i ), and calculate the overall ship center of gravity coordinates through weighted averaging: where the center of gravity coordinates (X g , Y g , Z g ) represent the weighted average position of the overall ship weight distribution, where W i is the real-time weight of each compartment or load unit, and x i , y i , z i are the centroid coordinates of the corresponding unit;

[0012] For the moment distribution, the static moments of each unit about the three axes need to be calculated separately. Among them, the transverse tilting moment: M x = ∑W i (y i - Y g ); the longitudinal trimming moment: M y = ∑W i (x i - X g ); the vertical torque

[0013] In a preferred embodiment, the W i is obtained through real-time monitoring by sensors or from a preset database; x i , y i , z i are determined based on the ship structure drawings or digital models, and the compartment layout parameters need to be input into the system in advance.

[0014] In a preferred embodiment, the stability threshold is set according to the ship stability manual, including the initial metacentric height GM ≥ 0.15 m, the maximum transverse inclination angle θmax ≤ 12°, and the trimming limit. It is verified through the transverse stability formula . If the calculation result exceeds the stability threshold, it is necessary to optimize the load distribution or adjust the ballast water, and at the same time check the influence of the free surface effect and compartment flooding on the center of gravity to ensure that the moment distribution satisfies ∑M x ≤ Δ·GM·sinθ max and the longitudinal strength requirements, and finally generate the imbalance risk level.

[0015] In a preferred embodiment, when it is detected that the ship unloader grab operation causes the ship moment to shift, the system first obtains the grab load weight in real time through the built-in dynamic weighing module; verifies the deviation amount e(t) = θ of the actual ship tilt angle θ from the theoretical value through the attitude sensor real -θ ref ; The system inputs the deviation e(t) and its change rate into the fuzzy PID controller. In the fuzzification stage, the continuous quantity is converted into a fuzzy linguistic variable through the triangular membership function. According to the set fuzzy rules, the PID parameter adjustment amounts ΔK p 、ΔK i 、ΔK d are obtained by defuzzification using the centroid method, realizing the adaptive update of the control parameters; in the compensation strategy generation link, the controller outputs the compensation torque; the scheduling algorithm preferentially selects the ship unloader group that is diagonally distributed with the disturbance source according to the spatial topological relationship. By solving the constrained optimization problem, the ship unloaders in the diagonal area are finally adjusted for trimming operation.

[0016] In a preferred embodiment, in the fuzzy PID process, the Kalman filter is continuously used to fuse multi-source sensor data to update the control quantity.

[0017] In a preferred embodiment, when the goods are at the area junction, the decision-making system comprehensively evaluates the area weight coefficient of the area where the goods coordinates belong, the moving cost coefficient of the current position of each ship unloader, and its historical operation load index, and calculates the working coefficient of the ship unloaders near the area junction through weighted summation; determines which specific ship unloader to dispatch for grabbing work according to the working coefficient value of the ship unloaders near the area junction; the one with a large value is used as the working ship unloader.

[0018] In a preferred embodiment, the area weight coefficient of the area where the goods coordinates belong is calculated by mapping the GIS coordinates, and the proportion of the projected area of the goods i in the junction area j is calculated; specifically, the area weight coefficient of the area where the goods coordinates belong is equal to the covered area of the goods i in the area j divided by the total projected area of the goods;

[0019] The moving cost coefficient of the current position of each ship unloader is equal to the moving distance of the ship unloader k from the current position to the area j;

[0020] The historical operation load index is calculated using the sliding window statistical method, and the formula is as follows: L k =1 - e -λt *Q k / Q max ; where Q k represents the equivalent cargo unloading amount completed by the ship unloader k in the past 2 hours; Q maxrepresents the rated capacity of the ship unloader; λ is the attenuation factor, which represents the attenuation rate of the impact of historical workload on the current load; it can be verified by Monte Carlo simulation.

[0021] In a preferred embodiment, after each grab is completed, the update coefficient is calculated by weighted summation according to the imbalance risk level and the weight of the grab.

[0022] In a preferred embodiment, when the update coefficient is greater than a preset threshold of the system, it is necessary to update the center of gravity coordinates and moment distribution of the hull; then, the next cargo grabbing position is determined based on the updated center of gravity coordinates, moment distribution and generated compensation strategy of the hull; and at the same time, the imbalance risk level of the ship is updated.

[0023] Technical effects and advantages of the present invention:

[0024] The present invention first identifies the ship entering the unloading area, and uses high-precision pressure sensors, laser scanners or 3D imaging technology to monitor the volume and weight distribution of cargo in the cabin in real time. Based on the ship structure parameters and real-time weight data, the center of gravity coordinates and moment distribution of the ship are calculated.

[0025] According to the ship stability manual, the safety threshold is set, and the imbalance risk level is determined by real-time monitoring of the lateral and longitudinal moment differences, and then the location of the grabbed cargo is determined, and then the ship unloader is controlled to grab it; avoid the tilt of the hull. When the grab operation of a ship unloader causes a torque offset, the system generates a compensation strategy based on the fuzzy PID control algorithm, and preferentially dispatches the diagonal area ship unloader for balancing operations. In terms of spatial scheduling, the Delaunay triangulation algorithm is used to divide the cargo hold into dynamic operation units, and the Delaunay triangulation network is dynamically constructed based on the coordinate set of the ship unloader operation base point. The algorithm imposes dual constraints: the maximum side length of the triangle does not exceed twice the length of the ship unloader arm to avoid the risk of cross-region interference of the mechanical arm; the minimum internal angle is limited to 25° to prevent the generation of narrow and long units and cause joint over-limit. The operating displacement of each ship unloader is calculated by the convex hull algorithm. For the cargo in the boundary area, the decision system comprehensively evaluates the area weight coefficient of the area to which the cargo coordinates belong, the movement cost coefficient of the current position of each ship unloader and its historical operation load index to achieve the optimal task allocation, and then achieve accurate allocation of the grabbing task.

[0026] After the grab is completed, the imbalance risk level and the weight of the grab are used to determine whether the center of gravity coordinates and moment distribution of the hull need to be updated, thereby avoiding the waste of computing power caused by frequent calculations of the center of gravity coordinates of the hull. The next grab position is then determined based on the center of gravity coordinates of the hull, moment distribution, and the generated compensation strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0028] Figure 1 This is a schematic flow chart of the automatic correction method for hull balance based on the collaborative operation of multiple ship unloaders in the present invention;

[0029] Figure 2 This is a schematic flow chart of the trimming operation in the present invention. Specific embodiments

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

[0031] Embodiment 1

[0032] The present invention first identifies that the ship enters the waiting unloading area, and uses high-precision pressure sensors, laser scanners or 3D imaging technology to monitor the volume and weight distribution of the goods in the cargo hold in real time. Based on the ship structure parameters and real-time weight data, the ship's center of gravity coordinates (lateral, longitudinal, vertical) and moment distribution are calculated.

[0033] According to the ship stability manual, a safety threshold is set. By monitoring the lateral and longitudinal moment differences in real time, the imbalance risk level is judged, and then the position of the grabbed goods is judged, and then the ship unloader is controlled to grab; to avoid hull tilt. When it is monitored that the grab operation of a certain ship unloader causes moment offset, the system generates a compensation strategy based on the fuzzy PID control algorithm, and preferentially schedules the ship unloaders in the diagonal area for trimming operations. In terms of spatial scheduling, the Delaunay triangulation algorithm is used to divide the cargo hold into dynamic operation units, and a Delaunay triangular network is dynamically constructed based on the set of operation base point coordinates of the ship unloaders. The algorithm forcibly imposes two constraints: the maximum side length of the triangle does not exceed 2 times the length of the ship unloader's boom, to avoid the risk of mechanical arm cross-region interference; the minimum interior angle is limited to 25°, to prevent the generation of long and narrow units that cause joint overrun. The operation displacements of each ship unloader are calculated through the convex hull algorithm. For the goods in the boundary area, the decision-making system comprehensively evaluates the area weight coefficient of the area where the goods coordinates belong, the movement cost coefficient of the current position of each ship unloader, and its historical operation load index to achieve optimal task allocation.

[0034] After the grabbing is completed, it is judged whether it is necessary to update the ship's center of gravity coordinates and moment distribution according to the imbalance risk level and the grabbed weight; to avoid frequently calculating the ship's center of gravity coordinates. Then, according to the ship's center of gravity coordinates, moment distribution and the generated compensation strategy, the position of the next grabbed goods is judged.

[0035] The automatic correction method for hull balance based on the collaborative operation of multiple ship unloaders in the present invention, asFigure 1 As shown, it includes the following steps:

[0036] When it is recognized that the ship enters the area to be unloaded, the volume and weight distribution of the goods in the cargo hold are monitored in real time; based on the ship structure parameters and real-time weight data, the ship's center of gravity coordinates and moment distribution are calculated; the imbalance risk level is judged by monitoring the lateral and longitudinal moment differences in real time;

[0037] The cargo hold is divided into multiple areas according to the working range of the ship unloader, and each ship unloader is responsible for the unloading task of each area; if the goods to be grabbed are at the junction of two areas, it is necessary to comprehensively evaluate the area weight coefficient of the area where the goods coordinates belong, the movement cost coefficient of the current position of each ship unloader, and its historical operation load index to determine the ship unloader number for grabbing the goods.

[0038] After the grabbing is completed, the update coefficient is calculated according to the imbalance risk level and the grabbed weight; when the update coefficient is greater than the system preset threshold, it is necessary to update the ship's center of gravity coordinates and moment distribution.

[0039] Specifically;

[0040] First, when it is recognized that the ship enters the area to be unloaded, high-precision pressure sensors, laser scanners or 3D imaging technology are used to monitor the volume and weight distribution of the goods in the cargo hold in real time. Specifically, at the bottom frame and load-bearing beams of the cargo hold, a high-precision strain-type pressure sensor array is deployed at a density of 4-6 measuring points per square meter, and a digital compensation circuit is used to eliminate temperature drift and mechanical vibration noise. At the same time, a multi-view scanning array is composed of a ceiling-mounted Velodyne VLP-32C lidar and a structured light 3D camera, and the ship's sway error is compensated in real time through an inertial measurement unit (IMU) to form millimeter-level three-dimensional point cloud data.

[0041] The improved D-S evidence theory is used to fuse the data, the weight distribution is associated with the volume characteristics, combined with the pre-built cargo density-morphology knowledge graph, and the load change trend is predicted through the LSTM network. The three-dimensional reconstruction engine based on the improved Poisson surface algorithm real-time segments the cargo units and dynamically displays the weight distribution in the form of a heat map in the WebGL visualization interface, and at the same time combines the ship's hydrodynamic model to calculate the real-time stability parameters.

[0042] The steps for calculating the center of gravity coordinates and stability threshold based on the ship structure parameters and real-time weight data are as follows: Establish a three-dimensional coordinate system for the ship, with the origin at the intersection of the baseline (bottom of the ship) and the midship section, the longitudinal X-axis pointing to the bow, the lateral Y-axis pointing to the starboard side, and the vertical Z-axis pointing vertically upward. For each weight unit (such as goods, fuel, ballast water), obtain its real-time weight W i and the centroid coordinates (x i , y i , z i) Calculate the center of gravity coordinates of the whole ship by weighted average: Among them, the center of gravity coordinates (X g , Y g , Z g ) represent the weighted average position of the weight distribution of the whole ship, where W i is the real-time weight of each compartment or load unit (such as cargo, ballast water), and x i , y i , z i are the centroid coordinates of the corresponding unit. The center of gravity position in the transverse direction (Y-axis) affects the ship's roll, the longitudinal direction (X-axis) determines the trim, and the vertical direction (Z-axis) is related to the metacentric height.

[0043] Further, W i is obtained through real-time monitoring by sensors or a preset database (such as a cargo loading list, fuel consumption); x i , y i , z i are determined based on the ship's structural drawings or digital models, and the compartment layout parameters (such as the geometric center of the cargo hold, the position of the oil tank) need to be input into the system in advance.

[0044] The moment distribution needs to calculate the static moments of each unit about the three axes respectively. Among them, the transverse tilt moment: M x = ∑W i (y i - Y g ); The longitudinal trim moment: M y = ∑W i (x i - X g ); The vertical torque

[0045] The stability safety threshold is set according to the ship's stability manual, including the initial metacentric height GM≥0.15m, the maximum roll angle θmax≤12°, and the trim limit (such as the draft difference does not exceed 1% of the ship's length). Through the transverse stability formula Check. If the calculation result exceeds the threshold, it is necessary to optimize the load distribution or adjust the ballast water. At the same time, check the influence of the free surface effect and the flooding of the compartment on the center of gravity to ensure that the moment distribution satisfies ∑M x ≤ Δ·GM·sinθ max and the longitudinal strength requirements, and finally generate the imbalance risk level.

[0046] The system first constructs a high-precision three-dimensional model of the cargo hold through multi-source perception data; the laser SLAM system is at 0.5cm / m 3Precision scanning generates point cloud data. The coordinates of the ship unloader base are obtained by integrating Beidou / GNSS and UWB fusion positioning technology. Meanwhile, the position of the hull structural members is marked by calling the preset obstacle database. Through quaternion rotation transformation, the original coordinate system is normalized into a standardized rectangular coordinate system with the ship's keel line as the X-axis and the ship width direction as the Y-axis, eliminating the spatial distortion caused by ship longitudinal / transverse inclination.

[0047] When it is monitored that the operation of a ship unloader grab (equipped with a dynamic weighing module) causes a moment offset of the ship, the system generates a compensation strategy based on the fuzzy PID control algorithm and preferentially schedules the ship unloaders in the diagonal area for trimming operations.

[0048] Specifically, when it is monitored that the operation of the ship unloader grab causes a moment offset of the ship, as Figure 2 shown, the system first obtains the load weight of the grab in real time through the built-in dynamic weighing module; the deviation amount e(t)=θ of the actual inclination angle θ of the ship verified by the attitude sensor from the theoretical value is obtained. real -θ ref . The system inputs the deviation e(t) and its change rate into the fuzzy PID controller. In the fuzzification stage, the continuous quantity is transformed into 7 linguistic variables such as "negative large", "zero", "positive large" through the triangular membership function. According to 49 fuzzy rules set in the expert experience library (such as "if the deviation is positive large and the change rate is negative small, then the output proportional coefficient increment ΔK p is negative medium"), the PID parameter adjustment amounts ΔK p , ΔK i , ΔK d are obtained by defuzzification using the centroid method, realizing the adaptive update of the control parameters; in the compensation strategy generation link, the controller outputs the compensation torque; the scheduling algorithm preferentially selects the ship unloader group distributed diagonally to the disturbance source according to the spatial topological relationship. By solving the constrained optimization problem, finally, the ship unloaders in the diagonal area are adjusted for trimming operations. During the process, the Kalman filter is continuously used to fuse multi-source sensor data to update the control quantity.

[0049] The cabin is divided into regions according to the operation radius of the ship unloader; specifically, based on the Bowyer-Watson incremental triangulation algorithm, with the set of operation base point coordinates P={p1, p2,..., pn} (n is the number of ship unloaders) of the ship unloader, a Delaunay triangulation network is dynamically constructed. The algorithm imposes two constraints: the maximum side length of the triangle does not exceed 2 times the length of the ship unloader arm to avoid the risk of mechanical arm cross-region interference; the minimum interior angle is limited to 25° to prevent the generation of long and narrow elements from causing joint overrun. When the volume change rate of the cargo exceeds 5% / min or the position offset of the ship unloader is greater than 0.5m, the local triangulation network reconstruction mechanism is triggered, and only the affected topological region is incrementally updated to reduce the computational load.

[0050] Furthermore, the Delaunay triangulation is mapped to a Voronoi diagram through a dual transformation, and each ship unloader corresponds to a dynamic Voronoi polygon operation unit. The historical operation efficiency weighting factor ω i = Q i / ∑Q is introduced. According to the operation volume Q of each ship unloader per unit time i the Voronoi cell boundary is adjusted in real time to achieve load balancing. For example, when the operation efficiency of a certain ship unloader is significantly higher than that of other equipment, its responsible area will expand towards the low-efficiency area, forming an adaptive spatial redistribution.

[0051] At the same time, the reachable domain modeling and safety boundary optimization are carried out; based on the D-H parameter model of the ship unloader, the forward kinematic equation is solved, and the reachable coordinate set S = {s1, s2,..., sm} of the grab is generated by traversing each joint rotation angle combination. The Gilbert-Johnson-Keerthi (GJK) distance algorithm is used for collision detection, and the points that interfere with the cargo hold wall and fixed equipment are removed to form a safe reachable domain. The convex polygon vertex sequence C = {c1, c2,..., ck} is extracted from the reachable point set SS through the Andrew's monotone chain algorithm, and its time complexity is controlled at the O(n log n) level, meeting the real-time requirement.

[0052] The initial convex hull boundary is double-optimized: the Bézier curve fitting technology is used to smooth the curvature of the convex hull edge, and the distance between control points is strictly limited within 10% of the theoretical maximum arm span R to ensure the smooth transition of the manipulator motion trajectory; a 3σ safety buffer zone (σ is the standard deviation of the positioning system) is superimposed, and the nominal operation radius is corrected to R eff = R max - 3σ to effectively avoid the risk of positioning drift.

[0053] Furthermore, when the stack height of the goods exceeds the preset threshold, the height constraint mode is activated, and the operation radius is dynamically adjusted where H current is the real-time grasping height, and H base is the height of the reference plane. Furthermore, a wind speed sensor is installed on the top of the ship unloader; if the detected wind speed > 10m / s, the anti-sway mode is started, and the operation radius of the ship unloader is automatically reduced to 85% of the nominal value.

[0054] When the goods are located at the area junction, the decision-making system comprehensively evaluates the area weight coefficient of the area where the goods coordinates belong, the moving cost coefficient of the current position of each ship unloader, and its historical operation load index, and calculates the working coefficient of the ship unloader near the area junction through weighted summation. Determine which specific ship unloader to perform the grasping work according to the working coefficient value of the ship unloader near the area junction; the one with a large value is used as the working ship unloader.

[0055] Furthermore, the specific formula for calculating the working coefficient of the ship unloader near the regional boundary through weighted summation is as follows: G = a * W ij - b * C jk - c * L k ; where G represents the working coefficient of the ship unloader near the regional boundary; a, b, and c are respectively the area weight coefficient of the area where the cargo coordinates belong, the movement cost coefficient of the current position of each ship unloader, and the weight coefficient of its historical operation load index.

[0056] After determining the working coefficient of the ship unloader near the regional boundary, determine which specific ship unloader to deploy for grasping work according to the value of the working coefficient of the ship unloader near the regional boundary; the larger the value of the working coefficient of the ship unloader near the regional boundary, the higher the grasping priority of the ship unloader.

[0057] Among them, the area weight coefficient W of the area where the cargo coordinates belong ij ; through GIS coordinate mapping, calculate the proportion of the projected area of cargo i in the boundary area j; specifically, the area weight coefficient of the area where the cargo coordinates belong is equal to the covered area of cargo i in area j divided by the total projected area of the cargo.

[0058] Among them, the movement cost coefficient C of the current position of each ship unloader jk ; dynamically calculate the path cost of ship unloader k from the current position to area j. Specifically, the path cost of ship unloader k from the current position to area j is jointly affected by the distance that ship unloader k needs to move from the current position to area j and the obstacles that need to be avoided. The higher the path cost, the smaller the working coefficient value of the ship unloader k.

[0059] Among them, the historical operation load index L k ; calculated using the sliding window statistical method: L k = 1 - e -λt * Q k / Q max ; where Q k represents the equivalent cargo unloading volume completed by ship unloader k in the past 2 hours; Q max represents the rated production capacity of the ship unloader; λ is the attenuation factor, representing the attenuation rate of the influence of historical operation volume on the current load; it can be verified through Monte Carlo simulation. For example, when λ = 0.05, the weight of the operation volume 2 hours ago drops to 12%.

[0060] After each grasping is completed, judge whether it is necessary to update the center of gravity coordinates and moment distribution of the hull according to the imbalance risk level and the grasped weight; specifically, calculate the update coefficient through the following formula: F = d * dj + e * zl; where F represents the update coefficient; dj represents the imbalance risk level; zl represents the grasped weight; d and e respectively represent the imbalance risk level and the weight coefficient of the grasped weight.

[0061] Avoid frequently calculating the center of gravity coordinates of the hull to save computing power and response time. When the update coefficient is greater than the system preset threshold, it is necessary to update the center of gravity coordinates and moment distribution of the hull; then, based on the updated center of gravity coordinates, moment distribution of the hull, and the generated compensation strategy, determine the next cargo grabbing position; meanwhile, update the imbalance risk level of the ship.

[0062] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0063] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling, direct coupling, or communication connection can be through some interfaces. The indirect coupling or communication connection of devices or units can be in an electrical, mechanical, or other form.

[0064] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0065] In addition, the functional units in each embodiment of this application can be integrated in one processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0066] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. An automatic correction method for hull balance based on collaborative operation of multiple ship unloaders, characterized in that It includes the following steps: When it is recognized that the ship enters the area to be unloaded, the volume and weight distribution of the goods in the cabin are monitored in real time; based on the ship structure parameters and real-time weight data, the ship's center of gravity coordinates and moment distribution are calculated; the imbalance risk level is judged by monitoring the lateral and longitudinal moment differences in real time; The cabin is divided into multiple areas according to the working range of the ship unloader, and each ship unloader is responsible for the unloading task of each area; if the goods to be grabbed are at the junction of two areas, at this time, it is necessary to comprehensively evaluate the area weight coefficient of the area where the goods coordinates belong, the movement cost coefficient of the current position of each ship unloader and its historical operation load index to determine the ship unloader number for grabbing the goods; After the grabbing is completed, the update coefficient is calculated according to the imbalance risk level and the grabbed weight; when the update coefficient is greater than the system preset threshold, it is necessary to update the ship's center of gravity coordinates and moment distribution.

2. The automatic correction method for hull balance based on the collaborative operation of multiple ship unloaders according to claim 1, characterized in that: The steps for calculating the center of gravity coordinates and moment distribution of the ship's hull based on the ship's structural parameters and real-time weight data are as follows: Establish a three-dimensional coordinate system for the ship, with the origin at the intersection of the baseline and the midship section, the longitudinal X-axis pointing forward, the transverse Y-axis pointing to the starboard side, and the vertical Z-axis pointing vertically upward; for each weight unit, obtain its real-time weight W i and the center of mass coordinates (x i , y i , z i ), and calculate the center of gravity coordinates of the whole ship by weighted average: where the center of gravity coordinates (X g , Y g , Z g ) represent the weighted average position of the weight distribution of the whole ship, where W i is the real-time weight of each compartment or load unit, and x i , y i , z i are the center of mass coordinates of the corresponding unit; The moment distribution needs to calculate the static moments of each element about the three axes separately. Among them, the transverse inclination moment: M x = ∑W i (y i - Y g ); The longitudinal trim moment: M y = ∑W i (x i - X g ); The vertical torque 3. The automatic correction method for hull balance based on collaborative operation of multiple ship unloaders according to claim 2, wherein: The said W i is obtained by real-time monitoring with sensors or from a preset database; x i , y i , z i is determined based on the ship structure drawings or digital models, and the cabin layout parameters need to be input into the system in advance.

4. The automatic correction method for hull balance based on collaborative operation of multiple ship unloaders according to claim 2, wherein: The stability threshold is set according to the ship stability manual, including the initial metacentric height GM ≥ 0.15 m, the maximum transverse heel angle θmax ≤ 12°, and the trim limit. Through the transverse stability formula check. If the calculation result exceeds the stability threshold, it is necessary to optimize the load distribution or adjust the ballast water. At the same time, check the effect of the free surface effect and compartment flooding on the center of gravity to ensure that the moment distribution satisfies ∑M x ≤ Δ·GM·sinθ max and longitudinal strength requirements, and finally generate the imbalance risk level.

5. The automatic correction method for hull balance based on collaborative operation of multiple ship unloaders according to claim 2, characterized in that: When it is detected that the ship moment offset is caused by the operation of the grab of the ship unloader, the system first obtains the grab load weight in real time through the built-in dynamic weighing module; the deviation amount e(t)=θ of the actual tilt angle θ of the ship from the theoretical value is verified through the attitude sensor real -θ ref ; The system inputs the deviation e(t) and its change rate into the fuzzy PID controller. In the fuzzification stage, the continuous quantity is converted into a fuzzy language variable through the triangular membership function. According to the set fuzzy rules, the PID parameter adjustment amounts ΔK p 、ΔK i 、ΔK d are obtained through defuzzification by the centroid method, realizing the adaptive update of the control parameters; in the compensation strategy generation link, the controller outputs the compensation torque; the scheduling algorithm preferentially selects the ship unloader group distributed diagonally with the disturbance source according to the spatial topological relationship, and finally carries out the trimming operation by adjusting the ship unloaders in the diagonal area 6. The automatic correction method for hull balance based on collaborative operation of multiple ship unloaders according to claim 5, wherein: In the fuzzy PID process, the Kalman filter is continuously used to fuse multi-source sensor data to update the control quantity.

7. The automatic correction method for hull balance based on collaborative operation of multiple ship unloaders according to claim 1, characterized in that: When the goods are at the area junction, the decision-making system comprehensively evaluates the area weight coefficient of the area where the goods coordinates belong, the movement cost coefficient of the current position of each ship unloader and its historical operation load index, and calculates the working coefficient of the ship unloader near the area junction by weighted summation; determines which specific ship unloader to deploy for grabbing work according to the value of the working coefficient of the ship unloader near the area junction; the one with a larger value is used as the working ship unloader.

8. The automatic correction method for hull balance based on collaborative operation of multiple ship unloaders according to claim 7, characterized in that: The area weight coefficient of the area where the goods coordinates belong is calculated by GIS coordinate mapping, and the proportion of the projected area of goods i in the junction area j is calculated; specifically, the area weight coefficient of the area where the goods coordinates belong is equal to the covered area of goods i in area j divided by the total projected area of the goods; The movement cost coefficient of the current position of each ship unloader is equal to the moving distance of ship unloader k from the current position to area j; The historical operation load index is calculated using the sliding window statistical method, and the formula is as follows: L k = 1 - e -λt *Q k / Q max ; where Q k represents the equivalent cargo unloading volume completed by the ship unloader k within the past 2 hours; Q max represents the rated production capacity of the ship unloader; λ is the attenuation factor, representing the attenuation rate of the influence of the historical operation volume on the current load; it can be verified through Monte Carlo simulation.

9. The automatic correction method for hull balance based on the collaborative operation of multiple ship unloaders according to claim 1, characterized in that: After each grabbing is completed, the update coefficient is calculated by weighted summation according to the imbalance risk level and the grabbed weight.

10. The automatic correction method for hull balance based on collaborative operation of multiple ship unloaders according to claim 9, characterized in that: When the update coefficient is greater than the system preset threshold, it is necessary to update the ship's center of gravity coordinates and moment distribution; then judge the next goods grabbing position according to the updated ship's center of gravity coordinates, moment distribution and the generated compensation strategy; at the same time, update the ship's imbalance risk level.

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