Dynamic sensing and intelligent calculating system for cargo weight and gravity center of sand self-discharging ship

Abstract

The invention relates to the field of self-discharging sand ships, and discloses a self-discharging sand ship cargo weight gravity center dynamic sensing and intelligent calculation system, which comprises the following steps: firstly, before cargo loading, recording the volume of a void cabin of a self-discharging sand ship and geometric parameters of a cargo cabin; acquiring real geographic coordinate point cloud data of a void of the sand self-discharging ship; establishing a void three-dimensional model; in the cargo loading process, cargo coordinate point cloud data is obtained, and a cargo three-dimensional model is obtained; importing the real geographic coordinate point cloud data of the void cabin and the cargo carrying coordinate point cloud data into point cloud data processing software to carry out point cloud denoising and cutting optimization processing, retaining cargo pile point cloud data, and carrying out analysis and calculation to obtain three-dimensional volume data of a cargo pile body; the weight and the gravity center of the cargo pile body are calculated through a three-partition integral algorithm; the problems that in the prior art, due to the fact that the weight and the gravity center of a cargo pile are calculated inaccurately, potential safety hazards are likely to occur, and the ship data visualization scanning effect is poor are solved.

Description

Technical Field

[0001] The present invention relates to the field of self-unloading sand ships, and in particular to a dynamic sensing and intelligent calculation system for the center of gravity of cargo weight of self-unloading sand ships. Background Art

[0002] The cargo hold of a self-unloading sand ship has a complex shape. When loading bulk cargo (such as sand and gravel), it is difficult to accurately calculate the cargo weight and center of gravity using traditional methods. The traditional method of calculating the center of gravity of cargo is to simply equate the cargo hold cross-section to an isosceles trapezoid. The height of the centroid of the trapezoid is the center of gravity height of the cargo. Judging from the actual shape of the cargo hold, it is unscientific to simply regard the cargo hold as a trapezoid. This will seriously underestimate the center of gravity height of the cargo, posing a serious hidden danger to the stability of the ship.

[0003] Based on the actual loading conditions of such ships, the cargo hold is divided into three parts: a pseudo-cylindrical portion at the bottom, a trapezoidal portion, and a naturally stacked portion. Using integral calculations, the accurate center of gravity height of the cargo can be determined. Verification shows that this algorithm accurately calculates the center of gravity height of the cargo, reflecting the center of gravity height under various loading conditions. Comparisons with traditional algorithms show that this algorithm provides more accurate results, significantly improving ship safety. Summary of the Invention

[0004] The present invention aims to provide a dynamic perception and intelligent calculation system for the weight and center of gravity of cargo on self-unloading sand ships, which solves the problems in the prior art of inaccurate calculation of cargo pile weight and center of gravity, which easily lead to safety hazards and poor data visualization scanning effect of ships.

[0005] In order to achieve the above object, the present invention provides the following method:

[0006] The present invention provides a self-unloading sand ship cargo weight center of gravity dynamic perception and intelligent calculation system is:

[0007] S1: Before the self-unloading sand ship is loaded with cargo, laser ranging is performed by a three-dimensional laser scanner to record the volume of the empty hold and the geometric parameters of the cargo hold of the self-unloading sand ship;

[0008] S2: obtaining the real geographic coordinate point cloud data of the empty hold of the self-unloading sand ship through the volume of the empty hold and the geometric parameters of the cargo hold;

[0009] S3: Establishing a three-dimensional model of the empty compartment according to the real geographic coordinate point cloud data of the empty compartment of the self-unloading sand ship;

[0010] S4: During the cargo loading process, the hull in the loading state is scanned by the three-dimensional laser scanner to obtain cargo coordinate point cloud data and obtain a three-dimensional cargo model;

[0011] S5: Importing the empty cabin real geographic coordinate point cloud data and the cargo coordinate point cloud data into point cloud data processing software to perform point cloud denoising and cropping optimization processing, and retaining the cargo pile point cloud data;

[0012] S6: Analyze and calculate the empty cabin 3D model, the loaded cargo 3D model, and the cargo pile point cloud data to obtain 3D volume data of the cargo pile;

[0013] S7: Calculate the weight and center of gravity of the cargo pile based on the three-dimensional volume data of the cargo pile using a three-partition integration algorithm.

[0014] Preferably, the step of performing laser ranging by a three-dimensional laser scanner on the self-unloading sand ship to record the volume of the empty hold and the cargo hold geometric parameters of the self-unloading sand ship includes: circling the self-unloading sand ship with the three-dimensional laser scanner or fixing the three-dimensional laser scanner to high places at both ends of the self-unloading sand ship to collect the volume and cargo hold geometric parameters of the self-unloading sand ship, including the length of the upper opening of the cargo hold, the width of the upper opening of the cargo hold, the length and width of the hopper door, and the shape, size and number of the transverse partitions.

[0015] Preferably, the step of establishing a three-dimensional model of the empty compartment according to the real geographic coordinate point cloud data of the empty compartment of the self-unloading sand ship includes: establishing a three-dimensional rectangular coordinate system of the empty compartment with the bottom center of the self-unloading sand ship as the origin according to the real geographic coordinate point cloud data of the empty compartment of the self-unloading sand ship; marking the three-dimensional rectangular coordinate system of the empty compartment submerged below the water surface as the empty compartment underwater coordinate system; marking the three-dimensional rectangular coordinate system of the empty compartment floating above the water surface as the empty compartment above-water coordinate system; marking the actual submerged depth of the empty compartment corresponding to the coordinates of the empty compartment underwater coordinate system and the empty compartment above-water coordinate system, and calculating the empty compartment inclination and the empty compartment submerged depth in combination with the actual submerged depth of the empty compartment; integrating the data of the empty compartment underwater coordinate system, the empty compartment above-water coordinate system, the empty compartment inclination and the empty compartment submerged depth to obtain the three-dimensional model of the empty compartment.

[0016] Preferably, during the cargo loading process, the hull in the loading state at each moment is scanned by the three-dimensional laser scanner to obtain cargo coordinate point cloud data, and the step of obtaining a three-dimensional cargo model includes: establishing a three-dimensional rectangular coordinate system for cargo based on the cargo coordinate point cloud data of the self-unloading sand ship with the bottom center of the self-unloading sand ship as the origin; marking the three-dimensional rectangular coordinate system for cargo submerged below the water surface as the underwater coordinate system for cargo; marking the three-dimensional rectangular coordinate system for cargo floating above the water surface as the surface coordinate system for cargo; marking the actual sinking depth of cargo corresponding to the coordinates of the underwater coordinate system for cargo and the surface coordinate system for cargo, and calculating the cargo inclination and the cargo sinking depth in combination with the actual sinking depth of cargo; integrating the data of the underwater coordinate system for cargo, the surface coordinate system for cargo, the cargo inclination and the cargo sinking depth to obtain a three-dimensional cargo model.

[0017] Preferably, the step of importing the empty cabin real geographic coordinate point cloud data and the cargo coordinate point cloud data into point cloud data processing software for point cloud denoising and cropping optimization processing, and retaining the cargo pile point cloud data, includes: overlapping point cloud contours according to the empty cabin real geographic coordinate point cloud data and the cargo coordinate point cloud data, identifying the spatial shape of the cargo pile point cloud according to the empty cabin three-dimensional model and the cargo three-dimensional model; determining the cargo pile point cloud cutting interval according to the spatial shape of the cargo pile point cloud; dividing the point cloud cutting interval according to the spatial shape of the cargo pile point cloud; obtaining the coordinate value and preset cutting parameters of the cargo pile point cloud according to the point cloud cutting interval, the preset cutting parameters including the interval width parameter and the edge expansion parameter; cutting the cargo pile point cloud according to the coordinate value of the cargo pile point cloud and the preset cutting parameters, and screening redundant point clouds to obtain cargo pile point cloud data.

[0018] Preferably, the step of dividing the point cloud cutting interval according to the spatial shape of the point cloud of the cargo pile includes: if the point cloud set of the cargo pile is a protrusion, the point cloud cutting interval is set to 0.2 times to 1 times the number of point cloud sets of the cargo pile; if the point cloud set of the cargo pile is a depression, the point cloud cutting interval is set to 1 times to 1.5 times the number of point cloud sets of the cargo pile.

[0019] Preferably, point cloud denoising and cropping optimization processing are performed on the real geographic coordinate point cloud data of the empty cabin and the cargo coordinate point cloud data when they are imported into the point cloud data processing software, and point cloud position alignment is performed before retaining the cargo pile point cloud data; the empty cabin submergence depth and the cargo submergence depth are linearly translated so that the origin of the empty cabin three-dimensional rectangular coordinate system and the origin of the cargo three-dimensional rectangular coordinate system coincide with each other; and the first center of gravity of the cargo pile is determined based on the angle between the empty cabin inclination and the cargo inclination.

[0020] Preferably, the step of analyzing and calculating the empty hold three-dimensional model, the loaded cargo three-dimensional model and the cargo pile point cloud data to obtain the three-dimensional volume data of the cargo pile includes: triangulating the cargo pile point cloud data and integrally calculating the volume of the cargo pile; segmenting the point cloud in different directions of the cargo pile according to the empty hold three-dimensional model and the loaded cargo three-dimensional model to obtain a plurality of segmented blocks; calculating the filling status of each segmented block according to the three-dimensional coordinate value of the point cloud data; processing the edges of each inner surface of the internal space of the cargo pile to eliminate the filling error of the segmented block; and calculating the three-dimensional volume data of the cargo pile based on the filling status of the segmented block.

[0021] Preferably, the formula for calculating the weight and center of gravity of the cargo pile by a three-partition integration algorithm based on the three-dimensional volume data of the cargo pile includes:

[0022] Decomposing the cargo pile into pseudo-cylindrical, trapezoidal and naturally stacked parts;

[0023] The formula for calculating the volume of a pseudo-cylindrical body is:

[0024] ;

[0025] Where a is the width of the wedge, n is the number of concave blocks between the wedges, b is the length of the wedge, h is the height of the wedge, and a1 is the top width of the wedge;

[0026] The formula for calculating the volume of a trapezoid is:

[0027] ;

[0028] Where A2 is the bottom area of ​​the trapezoid, d is the height, Z is the top area, and L is the bottom area of ​​the trapezoid. 下口 is the length of the bottom opening of the cargo box, is the inclination angle of the front end plate of the cargo box, is the inclination angle of the rear end plate of the cargo box, h2 is the height from the surface of the cargo box door, and α is the inclination angle of the cargo box;

[0029] The formula for calculating the volume of the naturally accumulated part is:

[0030] ;

[0031] A3 is the bottom area of ​​the trapezoid, d is the height, Z is the top area, L is the length at the starting point of natural stacking, h3 is the height from the surface of the cargo bucket door, and B is the width at the starting point of natural stacking.

[0032] Preferably, the steps of calculating the weight and center of gravity of the cargo pile according to the three-dimensional volume data of the cargo pile by a three-partition integration algorithm include: scanning the empty compartment by a three-dimensional laser scanner, constructing an empty compartment model, obtaining the cargo compartment geometric parameters and outputting them; calculating the weight and center of gravity of the cargo by a three-partition method; scanning the loading process, obtaining the loading volume and centroid position in real time, and obtaining the length and width of the cargo stacking starting point and the stacking height, and comparing and analyzing them with the stacking starting point width and height calculated in the three-partition calculation method to obtain the weight and center of gravity of the cargo pile.

[0033] The beneficial effects of this invention are as follows: Based on a real-world cargo hold geometry decomposition and integration algorithm, the system divides the cargo distribution into three parts: a wedge-shaped deduction zone, an intermediate trapezoidal zone, and a natural accumulation zone. This system then constructs a layered integral model to accurately calculate the cargo center of gravity. This system also constructs a dynamic cargo loading and unloading model, simulating the loading and unloading process through digital twin technology to dynamically and real-timely obtain cargo weight and center of gravity information. On this basis, a dynamic perception system is developed. By installing pressure sensors, lidars, perception cameras and other equipment on the actual ship, relevant data on cargo distribution are collected in real time, and these data are transmitted to the system for analysis and processing, so as to achieve dynamic and real-time acquisition of cargo weight and center of gravity, providing more comprehensive and accurate data support for ship stability management; breaking the limitations of the traditional equivalent trapezoidal method, and innovatively proposing a partition integral model based on pseudo-cylinders, trapezoids, and natural stacking, which effectively reduces the errors caused by the defects of traditional calculation methods, thereby improving the safety of ship operations; organically integrating high-precision information collection of cargo loading and unloading status with algorithm models, successfully realizing dynamic tracking of the center of gravity position of cargo, filling the gap in domestic real-time stability management technology for self-unloading sand ships; focusing on the core of "precise calculation-dynamic monitoring-active optimization", through the deep integration of algorithm innovation and intelligent hardware, promoting the transformation of self-unloading sand ship stability management from empirical estimation mode to data-driven mode, and improving the level of intelligent cargo loading and unloading. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly describes the drawings required for the specific embodiments or the description of the prior art. Similar elements or parts are generally identified by similar reference numerals throughout the drawings. Elements or parts in the drawings are not necessarily drawn to scale.

[0035] Figure 1 A schematic diagram of the process flow of a dynamic perception and intelligent calculation system for the weight and center of gravity of a self-unloading sand ship cargo provided by an embodiment of the present invention;

[0036] Figure 2 A cargo stacking diagram of a dynamic perception and intelligent calculation system for the weight center of gravity of a self-unloading sand ship provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to help those skilled in the art better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0038] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different items, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or end comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed therein, or may optionally include other steps or elements inherent to such process, method, product, or end.

[0039] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0040] Based on the actual loading conditions of such ships, the cargo hold is divided into three parts: a pseudo-cylindrical portion at the bottom, a trapezoidal portion, and a naturally stacked portion. Using integral calculations, the accurate center of gravity height of the cargo can be determined. Verification shows that this algorithm accurately calculates the center of gravity height of the cargo, reflecting the center of gravity height under various loading conditions. Comparisons with traditional algorithms show that this algorithm provides more accurate results, significantly improving ship safety.

[0041] The present invention aims to provide a dynamic perception and intelligent calculation system for the weight and center of gravity of cargo on self-unloading sand ships, which solves the problems in the prior art of inaccurate calculation of cargo pile weight and center of gravity, which easily lead to safety hazards and poor data visualization scanning effect of ships.

[0042] like Figure 1 and Figure 2 As shown, a specific embodiment of the present invention provides a dynamic perception and intelligent calculation system for the weight center of gravity of a self-unloading sand ship cargo, including the following steps:

[0043] S1: Before the self-unloading sand ship is loaded with cargo, laser ranging is performed using a 3D laser scanner to record the volume of the empty hold and the geometric parameters of the cargo hold.

[0044] In an embodiment of the present invention, a three-dimensional laser scanner is placed around the self-unloading sand ship or fixed to high positions at both ends of the self-unloading sand ship to collect the volume and cargo hold geometric parameters of the self-unloading sand ship, including the length and width of the cargo hold upper opening, the length and width of the hopper door, and the shape, size and number of the transverse partitions.

[0045] S2: Obtain the real geographic coordinate point cloud data of the empty hold of the self-unloading sand ship through the volume of the empty hold and the geometric parameters of the cargo hold.

[0046] S3: Establish a three-dimensional model of the empty tank based on the real geographic coordinate point cloud data of the empty tank of the self-unloading sand ship.

[0047] In an embodiment of the present invention, a three-dimensional rectangular coordinate system of the empty compartment is established with the bottom center of the self-unloading sand ship as the origin based on the real geographic coordinate point cloud data of the empty compartment of the self-unloading sand ship; the three-dimensional rectangular coordinate system of the empty compartment submerged below the water surface is marked as the empty compartment underwater coordinate system; the three-dimensional rectangular coordinate system of the empty compartment floating above the water surface is marked as the empty compartment surface coordinate system; the actual sinking depth of the empty compartment is marked corresponding to the coordinates of the empty compartment underwater coordinate system and the empty compartment surface coordinate system, and the empty compartment inclination and the empty compartment sinking depth are calculated in combination with the actual sinking depth of the empty compartment; the data of the empty compartment underwater coordinate system, the empty compartment surface coordinate system, the empty compartment inclination and the empty compartment sinking depth are integrated to obtain a three-dimensional model of the empty compartment.

[0048] S4: During the cargo loading process, a 3D laser scanner is used to scan the hull at each moment of loading to obtain the cargo coordinate point cloud data and obtain a 3D cargo model.

[0049] In an embodiment of the present invention, a three-dimensional rectangular coordinate system for cargo is established with the bottom center of the self-unloading sand ship as the origin based on the cargo coordinate point cloud data of the self-unloading sand ship; the three-dimensional rectangular coordinate system for cargo submerged below the water surface is marked as the underwater coordinate system for cargo; the three-dimensional rectangular coordinate system for cargo floating above the water surface is marked as the surface coordinate system for cargo; the actual sinking depth of the cargo is marked corresponding to the coordinates of the underwater coordinate system for cargo and the surface coordinate system for cargo, and the cargo inclination and the cargo sinking depth are calculated in combination with the actual sinking depth of the cargo; the data of the underwater coordinate system for cargo, the surface coordinate system for cargo, the cargo inclination and the cargo sinking depth are integrated to obtain a three-dimensional model of cargo.

[0050] S5: Import the empty cabin real geographic coordinate point cloud data and cargo coordinate point cloud data into the point cloud data processing software to perform point cloud denoising and cropping optimization processing, and retain the cargo pile point cloud data.

[0051] In an embodiment of the present invention, point cloud contours are overlapped based on the real geographic coordinate point cloud data of the empty compartment and the cargo coordinate point cloud data, and the spatial shape of the point cloud of the cargo pile is identified based on the empty compartment three-dimensional model and the cargo three-dimensional model; the cargo pile point cloud cutting interval is determined based on the spatial shape of the cargo pile point cloud; the step of dividing the point cloud cutting interval according to the spatial shape of the cargo pile point cloud comprises: if the point cloud set of the cargo pile is a protrusion, the point cloud cutting interval is set to 0.2 to 1 times the number of point cloud sets of the cargo pile; if the point cloud set of the cargo pile is a depression, the point cloud cutting interval is set to 1 to 1.5 times the number of point cloud sets of the cargo pile; the point cloud cutting interval is divided according to the spatial shape of the point cloud of the cargo pile; the point cloud cutting interval is divided according to the spatial shape of the point cloud of the cargo pile; the point cloud cutting interval is divided according to the point cloud cutting interval. The coordinate values ​​and preset cutting parameters of the cargo pile point cloud are obtained in the interval, and the preset cutting parameters include the interval width parameter and the edge expansion parameter; the cargo pile point cloud is cut according to the coordinate values ​​and the preset cutting parameters, and the redundant point clouds are screened to obtain the cargo pile point cloud data; the real geographic coordinate point cloud data of the empty cabin and the cargo coordinate point cloud data are imported into the point cloud data processing software for point cloud denoising and cropping optimization processing, and the point cloud position alignment is performed before retaining the cargo pile point cloud data; the empty cabin submergence depth and the cargo submergence depth are linearly translated to make the origin of the empty cabin three-dimensional rectangular coordinate system and the origin of the cargo three-dimensional rectangular coordinate system coincide; the first center of gravity of the cargo pile is determined according to the angle between the empty cabin inclination and the cargo inclination.

[0052] S6: Analyze and calculate the empty cabin 3D model, the loaded cargo 3D model, and the cargo pile point cloud data to obtain the 3D volume data of the cargo pile.

[0053] In an embodiment of the present invention, triangulation is performed based on the point cloud data of the cargo pile, and the volume of the cargo pile is calculated by integration; the point cloud is segmented in different directions of the cargo pile based on the empty compartment three-dimensional model and the loaded cargo three-dimensional model to obtain a plurality of segmented blocks; the filling status of each segmented block is calculated based on the three-dimensional coordinate values ​​of the point cloud data; the edges of each inner surface of the internal space of the cargo pile are processed to eliminate the filling error of the segmented blocks; and the three-dimensional volume data of the cargo pile is calculated based on the filling status of the segmented blocks.

[0054] S7: Based on the three-dimensional volume data of the cargo pile, the weight and center of gravity of the cargo pile are calculated using a three-partition integration algorithm.

[0055] In an embodiment of the present invention, the weight and center of gravity of the cargo pile are calculated based on the three-dimensional volume data of the cargo pile using a three-partition integration algorithm, including:

[0056] Decompose the cargo pile into pseudo-cylinders, trapezoids and natural stacking parts;

[0057] The formula for calculating the volume of a pseudo-cylindrical body is:

[0058] ;

[0059] Where a is the width of the wedge, n is the number of concave blocks between the wedges, b is the length of the wedge, h is the height of the wedge, and a1 is the top width of the wedge;

[0060] The formula for calculating the volume of a trapezoid is:

[0061] ;

[0062] Where A2 is the bottom area of ​​the trapezoid, d is the height, Z is the top area, and L is the bottom area of ​​the trapezoid. 下口 is the length of the bottom opening of the cargo box, is the inclination angle of the front end plate of the cargo box, is the inclination angle of the rear end plate of the cargo box, h2 is the height from the surface of the cargo box door, and α is the inclination angle of the cargo box;

[0063] The formula for calculating the volume of the naturally accumulated part is:

[0064] ;

[0065] A3 is the bottom area of ​​the trapezoid, d is the height, Z is the top area, L is the length at the starting point of natural stacking, h3 is the height from the surface of the cargo bucket door, and B is the width at the starting point of natural stacking. The empty compartment is scanned using a 3D laser scanner to construct an empty compartment model, obtain the cargo compartment geometric parameters, and output them. The weight and center of gravity of the cargo are calculated using a three-partition method. The loading process is scanned to obtain the loading volume and centroid position in real time, as well as the length, width, and height of the cargo stacking starting point. These are then compared and analyzed with the width and height of the stacking starting point calculated using the three-partition calculation method to determine the weight and center of gravity of the cargo pile.

[0066] The beneficial effects of this invention are as follows: Based on a real-world cargo hold geometry decomposition and integration algorithm, the system divides the cargo distribution into three parts: a wedge-shaped deduction zone, an intermediate trapezoidal zone, and a natural accumulation zone. This system then constructs a layered integral model to accurately calculate the cargo center of gravity. This system also constructs a dynamic cargo loading and unloading model, simulating the loading and unloading process through digital twin technology to dynamically and real-timely obtain cargo weight and center of gravity information. On this basis, a dynamic perception system is developed. By installing pressure sensors, lidars, perception cameras and other equipment on the actual ship, relevant data on cargo distribution are collected in real time, and these data are transmitted to the system for analysis and processing, so as to achieve dynamic and real-time acquisition of cargo weight and center of gravity, providing more comprehensive and accurate data support for ship stability management; breaking the limitations of the traditional equivalent trapezoidal method, and innovatively proposing a partition integral model based on pseudo-cylinders, trapezoids, and natural stacking, which effectively reduces the errors caused by the defects of traditional calculation methods, thereby improving the safety of ship operations; organically integrating high-precision information collection of cargo loading and unloading status with algorithm models, successfully realizing dynamic tracking of the center of gravity position of cargo, filling the gap in domestic real-time stability management technology for self-unloading sand ships; focusing on the core of "precise calculation-dynamic monitoring-active optimization", through the deep integration of algorithm innovation and intelligent hardware, promoting the transformation of self-unloading sand ship stability management from empirical estimation mode to data-driven mode, and improving the level of intelligent cargo loading and unloading.

[0067] The above description is merely an embodiment of the present invention. Common knowledge such as the specific technical solutions or features of the solutions is not described in detail here. It should be noted that those skilled in the art may make several modifications and improvements without departing from the solution of the present invention, and these modifications and improvements should also be considered as the scope of protection of the present invention. These modifications and improvements will not affect the effects of the present invention and the practicality of the patent. The scope of protection claimed in this application shall be based on the content of the claims, and the specific embodiments and other descriptions in the specification may be used to interpret the content of the claims.

Claims

1. A dynamic perception and intelligent calculation system for the weight center of gravity of a self-unloading sand ship cargo, characterized in that: The system comprises: S1: Before the self-unloading sand ship is loaded with cargo, laser ranging is performed by a three-dimensional laser scanner to record the volume of the empty hold and the geometric parameters of the cargo hold of the self-unloading sand ship; S2: obtaining the real geographic coordinate point cloud data of the empty hold of the self-unloading sand ship through the volume of the empty hold and the geometric parameters of the cargo hold; S3: Establishing a three-dimensional model of the empty compartment according to the real geographic coordinate point cloud data of the empty compartment of the self-unloading sand ship; S4: During the cargo loading process, the hull in the loading state is scanned by the three-dimensional laser scanner to obtain cargo coordinate point cloud data and obtain a three-dimensional cargo model; S5: Importing the empty cabin real geographic coordinate point cloud data and the cargo coordinate point cloud data into point cloud data processing software to perform point cloud denoising and cropping optimization processing, and retaining the cargo pile point cloud data; S6: Analyze and calculate the empty cabin 3D model, the loaded cargo 3D model, and the cargo pile point cloud data to obtain 3D volume data of the cargo pile; S7: Calculate the weight and center of gravity of the cargo pile based on the three-dimensional volume data of the cargo pile using a three-partition integration algorithm.

2. The self-unloading sand ship cargo weight center dynamic perception and intelligent calculation system according to claim 1 is characterized in that: The step of performing laser ranging by using a three-dimensional laser scanner on the self-unloading sand ship to record the volume of the empty hold and the geometric parameters of the cargo hold of the self-unloading sand ship includes: The three-dimensional laser scanner is placed around the self-unloading sand ship or fixed to high places at both ends of the self-unloading sand ship to collect the volume and cargo hold geometric parameters of the self-unloading sand ship, including the length and width of the cargo hold upper opening, the length and width of the hopper door, and the shape, size and number of the transverse partitions.

3. The self-unloading sand ship cargo weight center dynamic perception and intelligent calculation system according to claim 1 is characterized in that: The step of establishing a three-dimensional model of the empty compartment according to the real geographic coordinate point cloud data of the empty compartment of the self-unloading sand ship comprises: According to the real geographic coordinate point cloud data of the empty cabin of the self-unloading sand ship, a three-dimensional rectangular coordinate system of the empty cabin is established with the bottom center of the self-unloading sand ship as the origin; The three-dimensional rectangular coordinate system of the empty tank sunk below the water surface is marked as the empty tank underwater coordinate system; the three-dimensional rectangular coordinate system of the empty tank floating above the water surface is marked as the empty tank above the water coordinate system; Marking the actual submerged depth of the empty tank corresponding to the coordinates of the empty tank underwater coordinate system and the empty tank above water coordinate system, and calculating the inclination of the empty tank and the submerged depth of the empty tank in combination with the actual submerged depth of the empty tank; The data of the underwater coordinate system of the empty tank, the above-water coordinate system of the empty tank, the inclination of the empty tank and the submerged depth of the empty tank are integrated to obtain a three-dimensional model of the empty tank.

4. A self-unloading sand ship cargo weight center dynamic perception and intelligent calculation system according to claim 3, characterized in that: During the cargo loading process, the step of scanning the hull in the loading state at each moment by the three-dimensional laser scanner to obtain cargo coordinate point cloud data and obtain a cargo three-dimensional model includes: According to the cargo coordinate point cloud data of the self-unloading sand ship, a cargo three-dimensional rectangular coordinate system is established with the bottom center of the self-unloading sand ship as the origin; The three-dimensional rectangular coordinate system of cargo sunk below the water surface is marked as the underwater coordinate system of cargo; the three-dimensional rectangular coordinate system of cargo floating above the water surface is marked as the above-water coordinate system of cargo; Marking the actual submerged depth of the cargo in the coordinates of the cargo underwater coordinate system and the cargo surface coordinate system, and calculating the cargo inclination and the cargo submerged depth based on the actual submerged depth of the cargo; The cargo underwater coordinate system, the cargo above water coordinate system, the cargo inclination and the cargo submerged depth are integrated to obtain a three-dimensional cargo model.

5. The self-unloading sand ship cargo weight center dynamic perception and intelligent calculation system according to claim 1 is characterized in that: The step of importing the empty cabin real geographic coordinate point cloud data and the cargo coordinate point cloud data into point cloud data processing software to perform point cloud denoising and cropping optimization processing, and retaining the cargo pile point cloud data, comprises: Overlapping point cloud contours based on the empty hold real geographic coordinate point cloud data and the cargo coordinate point cloud data, and identifying the spatial shape of the cargo pile point cloud based on the empty hold three-dimensional model and the cargo three-dimensional model; determining a cutting interval of the cargo pile point cloud according to the spatial shape of the cargo pile point cloud; Dividing the point cloud cutting intervals according to the spatial shape of the point cloud of the cargo pile; Obtaining coordinate values ​​and preset cutting parameters of the cargo pile point cloud according to the point cloud cutting interval, wherein the preset cutting parameters include an interval width parameter and an edge expansion parameter; The cargo pile point cloud is cut according to the coordinate values ​​of the cargo pile point cloud and the preset cutting parameters, and redundant point clouds are screened to obtain cargo pile point cloud data.

6. The self-unloading sand ship cargo weight center dynamic perception and intelligent calculation system according to claim 5 is characterized in that: The step of dividing the point cloud cutting intervals according to the spatial shape of the point cloud of the cargo pile includes: If the point cloud of the cargo pile is a protrusion, the point cloud cutting interval is set to 0.2 to 1 times the number of point clouds of the cargo pile; If the point cloud set of the cargo pile is a recessed portion, the point cloud cutting interval is set to 1 to 1.5 times the number of point cloud sets of the cargo pile.

7. The system for dynamic sensing and intelligent calculation of the weight center of gravity of a self-unloading sand ship according to claim 4 is characterized in that: Importing the empty cabin real geographic coordinate point cloud data and the cargo coordinate point cloud data into point cloud data processing software to perform point cloud denoising and cropping optimization processing, and performing point cloud position alignment before retaining the cargo pile point cloud data; Performing a linear translation of the empty compartment submergence depth and the loaded cargo submergence depth so that the origin of the empty compartment three-dimensional rectangular coordinate system coincides with the origin of the loaded cargo three-dimensional rectangular coordinate system; The first center of gravity of the cargo pile is determined based on the included angle between the empty compartment inclination and the loaded compartment inclination.

8. The self-unloading sand ship cargo weight center dynamic perception and intelligent calculation system according to claim 7 is characterized in that: The step of analyzing and calculating the empty cabin three-dimensional model, the loaded cargo three-dimensional model, and the cargo pile point cloud data to obtain the three-dimensional volume data of the cargo pile includes: Perform triangulation based on the cargo pile point cloud data and calculate the cargo pile volume by integration; Segmenting the point cloud in different directions of the cargo pile according to the empty cabin three-dimensional model and the cargo three-dimensional model to obtain a plurality of segmented blocks; Calculating the filling state of each segmented block according to the three-dimensional coordinate values ​​of the point cloud data; Processing the edges of each inner surface of the interior space of the cargo pile to eliminate filling errors of the segmented blocks; The three-dimensional volume data of the cargo pile is calculated based on the filling conditions of the divided blocks.

9. The self-unloading sand ship cargo weight center dynamic perception and intelligent calculation system according to claim 8 is characterized in that: The formula for calculating the weight and center of gravity of the cargo pile using a three-partition integration algorithm based on the three-dimensional volume data of the cargo pile includes: Decomposing the cargo pile into pseudo-cylindrical, trapezoidal and naturally stacked parts; The formula for calculating the volume of a pseudo-cylindrical body is: ； Where a is the width of the wedge, n is the number of concave blocks between the wedges, b is the length of the wedge, h is the height of the wedge, and a1 is the top width of the wedge; The formula for calculating the volume of a trapezoid is: ； Where A2 is the bottom area of ​​the trapezoid, d is the height, Z is the top area, and L is the bottom area of ​​the trapezoid. 下口 is the length of the bottom opening of the cargo box, The tilt angle of the front end plate of the cargo box. is the inclination angle of the rear end plate of the cargo box, h2 is the height from the surface of the cargo box door, and α is the inclination angle of the cargo box; The formula for calculating the volume of the naturally accumulated part is: ； A3 is the bottom area of ​​the trapezoid, d is the height, Z is the top area, L is the length at the starting point of natural stacking, h3 is the height from the surface of the cargo bucket door, and B is the width at the starting point of natural stacking.

10. The self-unloading sand ship cargo weight center dynamic perception and intelligent calculation system according to claim 9 is characterized in that: The step of calculating the weight and center of gravity of the cargo pile using a three-partition integration algorithm based on the three-dimensional volume data of the cargo pile includes: Scan the empty cabin with a 3D laser scanner, build an empty cabin model, obtain and output the cargo cabin geometric parameters; Use the three-partition method to calculate the weight and center of gravity of the cargo; Scan the loading process to obtain the loading volume and centroid position in real time, as well as the length, width and height of the cargo stacking starting point. Compare and analyze the width and height of the stacking starting point calculated in the three-partition calculation method to obtain the weight and center of gravity of the cargo stack.

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