CN113255022B

CN113255022B - Corrugated paper structure design method and system based on demand import model

Info

Publication number: CN113255022B
Application number: CN202110647419.6A
Authority: CN
Inventors: 杨德龙; 郑生长; 胡红平; 舒奎明; 王召霞; 詹凯
Original assignee: Zhejiang Great Shengda Packing Co Ltd
Current assignee: Zhejiang Great Shengda Packing Co Ltd
Priority date: 2021-06-10
Filing date: 2021-06-10
Publication date: 2021-10-19
Anticipated expiration: 2041-06-10
Also published as: CN113255022A

Abstract

The application discloses corrugated paper structure design method and system based on demand import model, at first acquire the point cloud data of the commodity to be packaged, and establish the voxel model of the commodity based on the point cloud data, then discern the commodity type information of voxel model, acquire the structural feature of model based on this information, later right structural feature analyzes and determines the posture of putting and the reinforcement element of this voxel model, again based on the size of posture of putting and this voxel model select from the inside lining model storehouse with the inside lining model of reinforcement element looks adaptation, at last from the outer container model storehouse select with the voxel model with the packing box model of inside packing body looks adaptation that the inside lining model combines the back and obtains. The method is carried out in a full-automatic manner in the whole process, manual participation is not needed, and packaging design can be carried out on commodities of different types and forms, so that the packaging design is intelligent and convenient.

Description

Corrugated paper structure design method and system based on demand import model

Technical Field

The application relates to the technical field of structural design of paper products, in particular to a corrugated paper structural design method and system based on a demand import model.

Background

The paper product processing industry is one of the important industries in China, both corrugated boards for packing boxes and paper towels serving as sanitary articles are indispensable daily articles in daily life, and most of packages of products, commodities and other commodities are wrapped and contained by packing boxes formed by paper products.

Due to the rise of internet e-commerce, most users purchase commodities at a commodity production side, but the commodities on the commodity production side are various, and due to structural specificity or material specificity, when the commodities are packaged, the whole packaging needs to be carried out by using a carton, and some lining pieces are required to be arranged inside the carton to serve as buffering between the commodities and the carton, so that the damage to the commodities caused by vibration and the like of the carton in the transportation process is avoided.

At present, the corrugated paper packaging structure is designed for different types of commodities manually through experience in the aspect of commodity packaging, a packaging structure is designed at one time, the packaging structure can only aim at single type commodities, the mode is difficult to meet the packaging requirements of various commodity types, and the automation degree and the convenience are low.

Disclosure of Invention

Based on this, in order to can the automatic design out the corrugated paper packaging structure of adaptation in multiple different grade type commodity, save the manual work and carry out manual design to commodity, satisfy the packing design demand to multiple commodity kind, this application discloses following technical scheme.

On one hand, the corrugated paper structure design method based on the demand import model is provided, and comprises the following steps:

acquiring point cloud data of a commodity to be packaged, and constructing a voxel model of the commodity based on the point cloud data;

identifying commodity type information of the voxel model, and acquiring structural characteristics of the model based on the information;

analyzing the structural characteristics and determining the placing posture and the reinforcing elements of the voxel model;

selecting a lining model matched with the reinforcing elements from a lining model library based on the placing posture and the size of the voxel model;

and selecting a packaging box model which is matched with the inner packaging body obtained after the voxel model and the lining model are combined from an outer box model library.

In a possible embodiment, the constructing a voxel model of the commodity based on the point cloud data includes:

acquiring the maximum coordinate and the minimum coordinate of the point cloud data in the horizontal direction, the longitudinal direction and the vertical direction to obtain the spatial range of a voxel model;

determining the size of a voxel unit according to the space range and the granularity requirement of the voxel model;

and judging a voxel unit where each point is located in the point cloud data, and generating a voxel model through the voxel unit containing the points.

In one possible embodiment, the method further comprises:

before the point cloud data is constructed to form the voxel model of the commodity, the point cloud data is segmented, the projection of each point cloud area obtained after segmentation on a three-axis reference plane is obtained, the points obtained by projection are fitted to obtain a projection graph, and the minimum length of the outer contour of the projection graph in the axial direction is used as the upper limit setting basis of the granularity requirement.

In a possible embodiment, the identifying the commodity type information of the voxel model includes:

calculating first similarity between the voxel model and each voxel template in a voxel model library, and sequencing the first similarity from large to small to obtain a difference value between adjacent first similarities;

and when the head difference value is not lower than the difference threshold, taking the commodity type to which the voxel template corresponding to the first similarity belongs as the commodity type of the voxel model, otherwise, obtaining a candidate voxel template with the first similarity not lower than the similarity threshold under the current resolution, improving the resolution of the voxel model, calculating a second similarity between the voxel model and the candidate voxel template under the corresponding resolution after the resolution is improved, calculating the overall similarity between the voxel model and the candidate voxel template by combining the first similarity and the second similarity, and taking the commodity type to which the candidate voxel template with the highest overall similarity belongs as the commodity type of the voxel model.

In a possible implementation manner, the calculation manner of the first similarity and the second similarity includes:

respectively obtaining an appearance voxel unit of the voxel model and the voxel template, and obtaining the position of the appearance voxel unit;

comparing the positions of each appearance voxel unit of the voxel model and the voxel template, and counting homotopic voxel units and ectopic voxel units;

and calculating the corresponding similarity based on the sum of the number of the co-located voxel units and the number of the ectopic voxel units.

In a possible implementation, the obtaining of the structural feature of the model based on the information includes:

acquiring the structural composition and structural relationship of the commodity based on the commodity type information;

segmenting the voxel model based on the structure composition to obtain a corresponding voxel structure and a function type thereof;

and generating a structural dependency relationship of each voxel structure based on the structural relationship and the function type.

In a possible embodiment, the analyzing the structural feature and determining the pose of the voxel model includes:

and when the voxel structure contains a voxel structure with a bottom balance function type, taking the voxel model posture of the lowest position of the voxel structure as the placing posture, otherwise, determining the gravity center of the voxel model according to the voxel structure and the function type of the voxel model, and taking the voxel model posture with the lowest gravity center as the placing posture.

In a possible embodiment, the analyzing the structural feature and determining the reinforcement element of the voxel model includes:

determining a target voxel structure to be reinforced according to the structure dependency relationship and the gravity center of the voxel model;

and determining a reinforcement element of each target voxel structure according to the commodity type information.

In a possible embodiment, the selecting a lining model adapted to the reinforcement element from a lining model library based on the pose and the size of the voxel model includes:

obtaining the distance between the target voxel structure and the voxel model space range in each axial direction according to the size of the target voxel structure and the placing posture;

distributing reinforcement elements to the target voxel structure according to the distance, the center of gravity of the voxel model and the commodity type information;

and acquiring the surface geometric characteristics of the target voxel structure, and determining a lining model of which the spatial position constraint generated on the target voxel structure conforms to the correspondingly distributed reinforcement elements from a lining model library according to the surface geometric characteristics.

On the other hand, the corrugated paper structure design system based on the demand import model is further provided, and comprises the following components:

the voxel model establishing module is used for acquiring point cloud data of the commodity to be packaged and establishing a voxel model of the commodity based on the point cloud data;

the structural feature acquisition module is used for identifying the commodity type information of the voxel model and acquiring the structural feature of the model based on the information;

the reinforcement element determining module is used for analyzing the structural characteristics and determining the placing posture and the reinforcement elements of the voxel model;

the lining model selecting module is used for selecting a lining model matched with the reinforcing element from a lining model library based on the placing posture and the size of the voxel model;

and the box body model selecting module is used for selecting a packaging box model which is matched with the inner packaging body obtained after the voxel model and the lining model are combined from an outer box model library.

In one possible embodiment, the voxel model building module comprises:

the spatial range acquisition unit is used for acquiring the maximum coordinates and the minimum coordinates of the point cloud data in the horizontal direction, the longitudinal direction and the vertical direction to obtain the spatial range of the voxel model;

the voxel size determining unit is used for determining the size of a voxel unit according to the space range and the granularity requirement of the voxel model;

and the voxel model generating unit is used for judging the voxel unit where each point is located in the point cloud data and generating a voxel model through the voxel unit containing the points.

In a possible implementation, the voxel model building module further includes:

and the particle size upper limit determining unit is used for segmenting the point cloud data before the point cloud data is used for constructing the voxel model of the commodity, acquiring the projection of each point cloud area obtained after segmentation on a three-axis reference plane, fitting the points obtained by projection to obtain a projection graph, and taking the minimum length of the outer contour of the projection graph in the axial direction as the upper limit setting basis of the particle size requirement.

In one possible implementation, the structural feature obtaining module includes:

the difference value calculating unit is used for calculating first similarity between the voxel model and each voxel template in the voxel model library, and sequencing the first similarity from large to small to obtain a difference value between the adjacent first similarity;

and the commodity type determining unit is used for taking the commodity type to which the voxel template corresponding to the first similarity belongs as the commodity type of the voxel model when the head difference value is not lower than the difference threshold, otherwise, obtaining a candidate voxel template of which the first similarity is not lower than the similarity threshold under the current resolution, improving the resolution of the voxel model, calculating a second similarity between the voxel model and the candidate voxel template under the corresponding resolution after the resolution is improved, calculating the overall similarity between the voxel model and the candidate voxel template by integrating the first similarity and the second similarity, and taking the commodity type to which the candidate voxel template with the highest overall similarity belongs as the commodity type of the voxel model.

In a possible implementation, the manner in which the structural feature acquisition module calculates the first similarity and the second similarity includes:

the structure composition acquisition unit is used for acquiring the structure composition and the structure relationship of the commodity based on the commodity type information;

the voxel structure acquisition unit is used for segmenting the voxel model based on the structure composition to obtain a corresponding voxel structure and a function type thereof;

and the dependency relationship generation unit is used for generating the structural dependency relationship of each voxel structure based on the structural relationship and the function type.

In one possible embodiment, the reinforcing element determining module includes:

and the placing posture determining unit is used for taking the posture of the voxel model with the voxel structure positioned at the lowest position as the placing posture when the voxel structure contains the voxel structure with the bottom balance as the functional type, otherwise, determining the gravity center of the voxel model according to the voxel structure of the voxel model and the functional type thereof, and taking the posture of the voxel model with the lowest gravity center as the placing posture.

the target structure determining unit is used for determining a target voxel structure to be reinforced according to the structure dependency relationship and the gravity center of the voxel model;

and the reinforced element determining unit is used for determining reinforced elements of the target voxel structures according to the commodity type information.

In one possible embodiment, the liner model selecting module includes:

an axial distance obtaining unit, configured to obtain, according to the size of the target voxel structure and the placement posture, a distance between the target voxel structure and a voxel model spatial range in each axial direction;

a reinforcement element allocation unit for allocating reinforcement elements to the target voxel structure according to the distance, the center of gravity of the voxel model, and the commodity type information;

and the lining model determining unit is used for acquiring the surface geometric characteristics of the target voxel structure and determining a lining model of which the spatial position constraint generated on the target voxel structure conforms to the corresponding distributed reinforcement elements from a lining model library according to the surface geometric characteristics.

The utility model discloses a corrugated paper structure design method and system based on demand import model utilizes the voxel model to express the commodity form to judge the structural form characteristic of voxel model, obtain from this what kind of mode reinforcement need be carried out to commodity when the packing, then select corresponding inside lining buffering model and packing box model from the model storehouse automatically, generate the packing scheme of commodity, whole process full automatization goes on, need not artifical the participation, and can carry out the packing design to the commodity of various different grade types and form, make packing design intelligent, convenient.

Drawings

The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining and illustrating the present application and should not be construed as limiting the scope of the present application.

Fig. 1 is a schematic flow chart of an embodiment of a corrugated paper structure design method based on a demand import model disclosed in the present application.

Fig. 2 is a schematic diagram of voxel model M1 of a desktop display.

Fig. 3 is a schematic diagram of a minimum length cut-out of a projection plan.

FIG. 4 is a diagram illustrating similarity comparison between models.

Fig. 5 is a schematic structural diagram of a lining model adopted by the voxel model M1.

Fig. 6 is a schematic structural diagram of another liner model adopted by the voxel model M1.

Fig. 7 is a block diagram of an embodiment of a corrugated paper structure design system based on a demand import model disclosed in the present application.

Detailed Description

In order to make the implementation objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the drawings in the embodiments of the present application.

An embodiment of a corrugated paper structure design method based on a demand-induced model disclosed in the present application is described in detail below with reference to fig. 1 to 6. As shown in fig. 1, the method disclosed in this embodiment includes the following steps 100 to 500.

Step 100, a voxel model building module obtains point cloud data of a commodity to be packaged, and builds a voxel model of the commodity based on the point cloud data.

When a commodity producer or a commodity agent purchases commodities sold by oneself and packs the required corrugated paper, the corrugated paper producer needs to obtain point cloud data of the commodities firstly, the point cloud data can be obtained by scanning the commodities through a laser scanner and other devices, and the point cloud data is high in obtaining cost, so that the method is particularly suitable for companies integrating the commodity producer, a logistics center and a corrugated paper production line. It can be understood that the voxel model is a demand import model, and the voxel model generates reinforcement demands to further complete the selection of the lining parts, and finally complete the adaptation of the packing box.

And after point cloud data sent by a commodity producer or a merchant or point cloud data obtained after home scanning is obtained, constructing a prime model. A voxel is an abbreviation of Volume element (Volume Pixel), and a voxel model is a model composed of a plurality of voxels and capable of expressing a three-dimensional form of a commodity. It can be understood that the voxel model is established for determining the corrugated paper lining structure which is needed and adapted by the commodity, and the corrugated paper structure is mainly a flat plate piece and does not contain a curved surface structure, so that the voxel model is adopted, the voxel model is not very sensitive to precision, but the precision requirement on the commodity form representation can be met, meanwhile, the required calculation resource during calculation can be saved, and the outer surface of the voxel model is a plane and does not contain a curved surface, thereby being beneficial to calculation during the lining structure adaptation judgment. Specifically, fig. 2 is a schematic diagram of a voxel model M1 constructed from point cloud data of a desktop display.

Step 200, the structural feature acquisition module identifies the commodity type information of the voxel model and acquires the structural features of the model based on the information.

After the voxel model is analyzed, commodity type information of the voxel model can be determined, wherein the commodity type information comprises commodity types, such as a desktop computer display screen with a D1 model, and information of all structural components, structural connection relations and the like in the desktop computer display screen with the model. The structural characteristics refer to the basis for determining what kind of reinforcement is needed for the commodity, for example, the structural characteristics may be structural dependence, and it can be known from the structural dependence which structural components in each structural component are subjected to a larger force so as to be easily damaged by the influence of vibration.

And 300, analyzing the structural characteristics by a reinforcement element determining module and determining the placing posture and the reinforcement elements of the voxel model.

Put the gesture and be a problem that needs the consideration when commodity packing, put the different fragile nature that can make commodity in the transportation of gesture different, the inside lining paper structure and the packing box structure that adopt during the packing also can be different. The reinforcing element refers to movement constraints on a target voxel structure, and mainly comprises a transverse movement constraint, a longitudinal movement constraint and a vertical movement constraint. The placing posture and the reinforcing elements required to be applied are analyzed through the structural characteristics, and the protection of which form is required to be carried out on the commodity is determined.

And 400, selecting a lining model matched with the reinforcement elements from a lining model library by a lining model selecting module based on the placing posture and the size of the voxel model.

The lining model library is stored with various types of lining models, such as a buffer type model, a shock absorption type model, a support type model and the like, and the same type of model comprises various models which adapt to different commodity shapes, such as a cuboid, a cuboid with flaps on two sides, a 'mountain' shaped plate, a butt-inserting type grid plate and the like. The different postures of the voxel models affect the installation positions of the lining models, for example, the top buffer of the display screen of the display model M1 in fig. 2 is fixed on the inner side of the upper cover of the carton in the current posture that the screen faces forwards, but the top buffer of the display screen is fixed on the side wall of the carton in the posture that the screen faces upwards. And because the base loses the supporting function under the posture that the screen faces upwards, still need increase the support at the screen bottom, consequently the display screen top bolster that adopts also can change, and the inside lining model that also chooses can change.

The size of the voxel model refers to a space region occupied by the voxel model in a space range, and includes data such as three-dimensional size of each structural component of the voxel model. The different sizes of the voxel models also affect the selection of the lining model, because the lining model with the same shape also exists as two different lining models due to the different sizes.

And 500, selecting a packing case model matched with the inner packing body obtained after the voxel model and the lining model are combined from an outer case model library by a case model selection module.

The outer box model library stores outer box models in various styles, including folding type, bonding type, nailing type and the like, the packing box models in different styles also have various sizes which can be selected, and the packing box models in different sizes are regarded as two different models.

The inner package body is obtained after the lining model is assembled on the voxel model, the space range of the inner package body is larger than that of the voxel model due to the lining model, and the space range of the inner package body is used as the inner space of the packing carton so that the space in the packing carton is more compact and the lining model is more convenient to install, and therefore the packing carton model is designed. For example, the spatial extent of the voxel model M9 is 500 × 400, and the lining model includes the left and right buffer models and the top buffer model, so the spatial extent of the inner package is 540 × 500 × 420, and therefore the carton fitted with the inner package also needs to have an internal space of 540 × 500 × 420.

The embodiment utilizes the voxel model to express the commodity form, and judges the structural form characteristics of the voxel model, thereby obtaining what kind of mode reinforcement needs to be carried out when the commodity is packed, then automatically selecting corresponding lining buffer model and packing box model from the model base, generating the packing scheme of the commodity, the whole process is carried out automatically, does not need manual participation, and can carry out packing design aiming at commodities of various different types and forms, so that the packing design is intelligent and convenient.

In an embodiment, the way of constructing the voxel model of the commodity by the voxel model establishing module based on the point cloud data specifically includes the following steps 110 to 130.

And 110, acquiring the maximum coordinate and the minimum coordinate of the point cloud data in the horizontal direction, the longitudinal direction and the vertical direction by a spatial range acquisition unit to obtain the spatial range of the voxel model.

Assuming that the point cloud data has 500 points, determining the maximum value and the minimum value of the 500 points on X, Y, Z three axes to obtain Xmax, Xmin, Ymax, Ymin, Zmax and Zmin, wherein the minimum value defines the limit position of one side where the voxel model may exist, and the maximum value defines the limit position of the other side where the voxel model may exist, thereby obtaining a cuboid or cube three-dimensional matrix as the spatial range of the voxel model. In the built desktop display voxel model shown in fig. 2, the X, Y, Z three-axis directions are shown, corresponding to landscape, portrait, and portrait, respectively.

And step 120, determining the size of the voxel unit by the voxel size determining unit according to the space range and the granularity requirement of the voxel model.

The granularity requirement defines the true degree of the voxel model capable of reaching the actual shape of the commodity, and the higher the granularity requirement is, the lower the true degree of the actual shape of the commodity is reflected, and otherwise, the higher the granularity requirement is. Assuming that the spatial range of the voxel model M is (0,0, 0) to (500,200,400), if the granularity requirement is 10, the size of each voxel unit (the smallest square unit of the voxel model) is 10 × 10, and there are 50 × 20 × 40 voxel cells in the spatial range, and a voxel cell is a space that can contain only one voxel cell; if the granularity requirement is 2, the size of each voxel unit is 2 × 2, the spatial range has 250 × 100 × 200 voxel units, and the resolution when the granularity requirement is 2 is obviously higher than that when the granularity requirement is 10, so that more detailed contents of commodity shapes can be embodied, and the reflected trueness degree is higher.

Step 130, the voxel model generating unit judges the voxel unit where each point is located in the point cloud data, and generates a voxel model through the voxel unit containing the points.

Taking the particle size requirement =10 as an example, the voxel model M at this time includes 50 × 20 × 40 voxel units, each point in the point cloud data is located in one of the voxel units, some of the voxel units include a plurality of points, and some of the voxel units do not include any point, each voxel unit including one or more points is counted, and a voxel model corresponding to the shape of the product is formed from the counted voxel units.

In one embodiment, the corrugated paper structure designing method further comprises the step 101: before the point cloud data is constructed into the voxel model of the commodity, the particle size upper limit determining unit of the voxel model construction module firstly segments the point cloud data, obtains the projection of each point cloud area obtained after segmentation on a three-axis reference plane, fits the points obtained by projection to obtain a projection graph, and takes the minimum length of the outer contour of the projection graph in the three-axis direction as the upper limit setting basis of the particle size requirement.

The point cloud data is divided, for example, by means of ransac (random Sample consensus) or clustering algorithm, and the point cloud data is divided into different point cloud areas, which respectively include different components of the commodity, and the components have different sizes, thicknesses, lengths, and lengths, so that for each point cloud area, the projection of each point cloud area on the reference plane of the XY, YZ, and XZ axes is obtained, and three projections of the point cloud area are obtained, each projection includes a plurality of points, and the plurality of points are connected and fitted to obtain a projection graph, wherein the projection graph includes a closed outer contour line and a plurality of connected connecting lines in the contour. As shown in fig. 3, the outer contour lines of the projected graph are extracted, each outer contour line is used as a plan view, the outer contour lines are respectively swept by a single step length by using the X axis and the Y axis, the dotted arrows in fig. 3 are the process that the axes sweep the outer contour lines step by step, and the process intersects with the outer contour lines to obtain a plurality of line segments, and the line segments are shown in the form of dotted lines in fig. 3.

Assuming that 10 point cloud areas are segmented from the point cloud data, 30 projection graphs are obtained, 30 outer contour lines are obtained, each outer contour line is subjected to bidirectional sweep through X, Y to obtain a minimum length line segment, the minimum length line segments of all 30 outer contour lines are compared to determine the minimum length line segment of the whole point cloud data, the minimum length line segment is the position with the thinnest or thinnest' in the outer contour lines, particularly, the positions may need to be reinforced by configuring a lining structure, and if the requirement on granularity is too high, the thinnest or thinnest part in the voxel model cannot be really expressed, the finally determined lining model may not be properly assembled with actual commodities,

therefore, in order to make the voxel model truly reflect the shape of the commodity at the positions, the upper limit of the granularity requirement is set to be the shape capable of just expressing the positions, for example, the thinnest position is 5, and the granularity requirement is set to be that the voxel unit size determined according to the granularity requirement is not larger than 5, so that the thinnest degree at the corresponding position of the commodity can be truly reflected.

It can be understood that the final result of step 101 is an upper limit value of the granularity requirement, and when the granularity requirement is selected in reality, a lower granularity requirement may be selected, so that the voxel model is more realistic as long as the voxel unit does not exceed the thinnest or thinnest position, and for the remaining thicker or thicker positions, the voxel unit can be inevitably characterized without distortion under the constraint of the upper limit of the granularity requirement.

In one embodiment, the identifying the commodity type information of the voxel model by the structural feature acquisition module includes the following steps 210 to 220.

Step 210, the structural feature obtaining module calculates a first similarity between the voxel model and each voxel template in the voxel model library, and orders the first similarities from large to small to obtain a difference value between adjacent first similarities.

The voxel model library is a template library which is pre-established for various commodities, a first similarity sequence is obtained by carrying out first similarity calculation on the voxel model M and all n individual voxel templates in the model library, similarity values in the sequence are sorted from large to small, and adjacent similarity difference values are calculated to obtain n-1 difference values.

And step 220, when the first difference value is not lower than the difference threshold value, the structural feature acquisition module takes the commodity type to which the voxel template corresponding to the first similarity belongs as the commodity type of the voxel model.

The difference threshold is used to determine how large the difference between the calculated similarities is, if the first similarity of the leading position is 0.95 (1 is completely the same, 0 is completely different), and the first similarity of the second position is 0.85, the leading position difference is 0.1, and exceeds the difference threshold 0.05, which indicates that the similarity of the voxel template most similar to the voxel model M is far higher than that of the other voxel templates, and at this time, it can be determined that the commodity type of the voxel model M is the same as that of the most similar voxel template.

If the leading difference is lower than the difference threshold, for example, the similarity of the second, third and fourth bits is 0.92, 0.91 and 0.91 in turn, the leading difference is 0.03 and lower than the difference threshold of 0.05, which indicates that the previous voxel templates are all very similar to the voxel model M, so that the voxel template that should be most similar in reality is not the leading voxel template due to the deviation generated during the construction of the voxel model, that is, the voxel model is most similar to other voxel templates due to the deviation, and at this time, if the most similar voxel template is directly used as the voxel model, the product type recognition may be wrong, and at this time, the granularity needs to be further refined to determine the true product type of the voxel model.

The method comprises the following steps that a structural feature obtaining module obtains a candidate voxel template with a first similarity not lower than a similarity threshold value under the current resolution, the resolution of the voxel model is improved, a second similarity between the voxel model with the improved resolution and the candidate voxel template under the corresponding resolution is calculated, the overall similarity between the voxel model and the candidate voxel template is calculated by combining the first similarity and the second similarity, and the commodity type of the candidate voxel template with the highest overall similarity is used as the commodity type of the voxel model.

The similarity threshold is used for screening out voxel templates with similarity reaching a certain degree, and because the first four voxel templates under the current resolution are all very similar to the voxel model M, the similarity exceeds 0.9 of the similarity threshold, and the similarity of the fifth bit is 0.87, only the first four voxel templates participate in the similarity calculation of a new round. Then, the resolution of the voxel model is increased, that is, the requirement for granularity is reduced, the size of the voxel unit is reduced, and because the model library includes the forms of the voxel templates under different resolutions, the second similarity between the model M after the resolution is increased and the four voxel templates is calculated, at this time, both the first similarity between the model M and the four templates under the original resolution and the second similarity between the model M and the four templates under the higher resolution are obtained, a weight higher than the first similarity is assigned to the second similarity, the similarity is multiplied by the corresponding weight to obtain the comprehensive score of the four voxel templates, the voxel template with the highest score is used as the template most similar to the model M, and the commodity type of the most similar template is used as the commodity type of the voxel model M, for example, the commodity type is a desktop computer display model D1.

In one embodiment, the structural feature acquisition module calculates the first similarity and the second similarity through the following steps a1 through A3.

Step a1, respectively obtaining exterior voxel units of the voxel model and the voxel template, and obtaining the positions of the exterior voxel units.

The appearance voxel unit refers to a voxel unit that can be observed from the outside of the voxel model, and as shown in fig. 2, all the observable voxel units are appearance voxel units, for example, all the voxel units on the front side of the display screen are appearance voxel units. Since the first similarity and the second similarity are both calculated at the same resolution (the granularity requirement is the same), the spatial extent of the voxel model and the voxel template involved in the similarity calculation is the same.

Step A2, comparing the voxel model with each appearance voxel unit position of the voxel template, and counting the homotopic voxel unit and the ectopic voxel unit.

Assuming that the voxel model M and the voxel template T1 are compared currently, all voxel cells in the whole spatial range are traversed, and whether a voxel unit exists in a voxel cell, whether the voxel unit is an exterior voxel unit, and the position of the exterior voxel unit are determined, so as to count the number of co-located voxel units and the number of ex-located voxel units. The in-situ voxel unit refers to an internal voxel unit in which one part has an appearance voxel unit and the other part has an upper, lower, left, right, front and rear adjacent voxel units, and the ex-situ voxel unit refers to a voxel unit in which one part has an appearance voxel unit and the other part is empty.

It can be understood that, since there may be a case where the exterior voxel units of one of the two parties completely include the exterior voxel units of the other party in terms of position and number and voxel characteristics thereof, and a part of the exterior voxel units are further added than the exterior voxel units of the other party, for example, in fig. 4, the model M3 at the middle position is one exterior voxel unit U4 more than the model M2 at the left side, so that U4 is only one ectopic voxel unit between M2 and M3; the model M4 on the right side has more units U5, U6, and U7 than M3, but less units U4, assuming that M3 is a voxel model and M4 is a voxel template, the ectopic voxel units between M3 and M4 include four units U4 to U7 in total.

Step a3, calculating the corresponding similarity based on the sum of the number of the co-located voxel units and the number of the ectopic voxel units.

Continuing with the example of fig. 4, there are 9 homotopic voxel units and 1 ectopic voxel unit in the models M2 and M3, so the similarity Si (M2, M3) =9/(1+9) =0.9 between M2 and M3. The models M3 and M4 have 9 co-located voxel units and 4 ectopic voxel units, so the similarity Si of M3 and M4 (M3, M4) =9/(4+9) = 0.69. The models M2 and M4 have 9 co-located voxel units and 3 ectopic voxel units, so the similarity Si of M2 and M4 (M2, M4) =9/(3+9) = 0.75.

For the case where the shapes are almost the same but the size of one model is slightly enlarged in size in an equal proportion to the other model, the similarity calculated through steps a1 through A3 may be less than 0.5, in practice, the two are different in size, so the algorithm is not good at calculating the similarity with different size ratios but the same shape, but the algorithm is fast, and because the compared model and template are all under the same resolution, the spatial range and the number of voxel cells are the same, the situation that the voxel model constructed for the same commodity has different size proportions is difficult to occur, since the thickness, length, etc. of the partial positions of the voxel model are greatly distorted if the size ratio is different, in fact, the distortion degree cannot reach the degree, so that the algorithm can not only quickly calculate the similarity, but also avoid the distortion influence by comparison under the same resolution.

In one embodiment, the acquiring the structural feature of the model by the structural feature acquiring module based on the information includes the following steps 230 to 250.

In step 230, the structural composition obtaining unit obtains the structural composition and the structural relationship of the product based on the product type information.

Assuming that the commodity type information indicates that the voxel model is a D1 desktop display, the structural feature acquisition module automatically extracts product structural data of the display of the model from the system, as shown in fig. 2, the voxel model in fig. 2 is M1, and includes a square display screen S1, a support column S2 with one end hinged to S1, and a disk-shaped base S3 fixedly connected to S2, where S1 to S3 are structural components, and the hinged and fixed connections are structural relationships.

And 240, the voxel structure acquisition unit divides the voxel model based on the structure composition to obtain a corresponding voxel structure and a function type thereof.

After the structure composition and the structure relationship thereof are known, the voxel units of the voxel model M1 can be correspondingly divided according to the structure composition to obtain the voxel structures of the square display screen S1, the support columns S2 and the disk-shaped base S3. The functional type of each structural component can be obtained after the structural components are obtained, and the functional type can be paired with the corresponding voxel structure after the model segmentation. The function type refers to the type of the function of each voxel structure (i.e., structural composition), and the function type may be various, for example, the function type of S1 is a main desired function, the function type of S2 is an upright support, and the function type of S3 is a bottom balance, where the main desired function refers to being able to realize the most important function that the commercial product is expected to realize, that is, realizing a display function.

In step 250, the dependency relationship generation unit generates a structural dependency relationship of each voxel structure based on the structural relationship and the function type.

The structural dependency relationship refers to a structural building sequence relationship according to which the voxel model is required to be established on the structure, and for a mechanical structure, the structural building sequence relationship mainly includes a force transmission relationship, for example, a model M1 in fig. 2, establishment of S1 in M1 depends on a support of S2, and establishment of S2 depends on a support of S3, so the structural dependency relationship is S1- > S2- > S3, a- > B indicates that a depends on B, and the structural dependency relationship is the structural feature acquired by the structural feature acquisition module.

In one embodiment, the analyzing the structural features and determining the pose of the voxel model by the reinforcement element determination module includes the following step 310.

In step 310, when the voxel structure includes a voxel structure with a bottom balance function type, the pose determination module determines the pose of the voxel model with the lowest voxel structure as the pose, otherwise determines the center of gravity of the voxel model according to the voxel structure and the function type of the voxel model, and determines the pose of the voxel model with the lowest center of gravity as the pose.

Pose determination requires consideration of whether the item has pose constraints or references specifically set for use in unique or limited situations. Taking the display model M1 of fig. 2 as an example, the plate-shaped base S3 with the function type of bottom balance is S3, which is the posture constraint of the display, so the posture of the display when packed should be the posture of the display in the use state, i.e. the front side is facing forward.

Some commodities are structural components without a bottom balance function type or structural components similar to the bottom balance function type, such as porcelain bowls, the placing postures of the porcelain bowls are not constrained, the placing postures at the moment can be selected according to needs, the gravity center of the commodities, namely the gravity center of the voxel model, is mainly considered in the selection mode, the commodities are less susceptible to vibration due to the fact that the gravity center is lower, the transportation process of the commodities is more stable, therefore, the estimated weight of each structural component or the weight ratio among each structural component can be known according to the function type of the voxel structure, the approximate gravity center position of the whole voxel model can be estimated through the size of the voxel structure, and the posture when the gravity center is lowest is used as the placing posture of the model.

In one embodiment, the step of analyzing the structural features and determining the reinforcement elements of the voxel model by the reinforcement element determination module includes the following steps 320 to 330.

And 320, determining a target voxel structure to be reinforced by the target structure determining unit according to the structure dependency relationship and the gravity center of the voxel model.

Taking the model M1 in fig. 2 as an example, the structure dependence is S1- > S2- > S3, and the position of the center of gravity is determined to be located above the center of the model M1 in the calculation of the pose. From the structural dependency, since the finally depended structure is S3, the disk-shaped base S3 is the target voxel structure to be reinforced; from the barycentric position, the barycentric is located in S1 at the top of the model, and thus the square display screen S1 is also the target voxel structure to be reinforced.

It can be understood that since the commercial product such as the porcelain bowl may be integrally formed and has no other structural features except the bowl body, the commercial product has no structural dependency relationship, and the reinforcing element is determined only by the center of gravity of the voxel model, and the structural dependency relationship is not used as the basis for the reinforcing element.

In step 330, the reinforcement element determining unit determines reinforcement elements of each target voxel structure according to the commodity type information.

From the shape of the target voxel structure, S1 is a flat rectangular parallelepiped, and S3 is a flat square plate. According to the commodity type, one side of the S1 is provided with the screen, so that the movement constraint is required in the axial direction perpendicular to the screen, and if the model posture in the figure 2 is taken as the placing posture, the longitudinal (Y-axis) movement constraint is required, and besides the front surface of the screen is easy to damage, the damage is also caused by the collision around the screen, so that the transverse (X-axis) movement constraint and the vertical (Z-axis) movement constraint are required.

In one embodiment, the liner model selecting module selects a liner model matching the reinforcement element from a liner model library based on the pose and the size of the voxel model, including the following steps 410 to 430.

And step 410, the axial distance obtaining unit obtains the distance between the target voxel structure and the voxel model space range in each axial direction according to the size of the target voxel structure and the placing posture.

Taking the model M1 of fig. 2 as an example, the shortest vertical distances of S1 of M1 from the boundary surface of the spatial range in six directions, i.e., top, bottom, left, right, front, and rear, and the distances of S3 from the boundary surface of the spatial range in the six directions are determined by the size and the above-mentioned posture.

In step 420, the reinforcement element assigning unit assigns reinforcement elements to the target voxel structure according to the distance, the center of gravity of the voxel model, and the commodity type information.

The specific target voxel structure to which each reinforcing element is applied can be determined by the above-mentioned distance, center of gravity and commodity type, for example, since S1 is closest to the center of gravity, and the center of gravity is within S1, so that the distance between the center of gravity and the center of gravity is 0, the determination of the reinforcing element is preferentially performed for the target voxel structure S1 closest to the center of gravity, and for S1 which is flat and is placed front, since it is closest to the top and the left and right sides, the reinforcing of the inner liner is facilitated, and therefore, the lateral and vertical movement restriction in the reinforcing element is applied to S1; then, the target voxel structure S3 with the second closest distance from the center of gravity is identified as S3, which is flat and is placed front-front, and is closest to the front and rear sides, so that the remaining longitudinal movement constraint of the reinforcing elements is applied to S3, thereby completing the assignment of the reinforcing elements.

It will be appreciated that the centre of gravity has an effect not only on the order of assignment of the target voxel structure, but also on the assignment of the stiffening elements, and in particular, since the centre of gravity is within S1 and S1 is the largest proportion by weight of the three voxel structures, the longitudinal movement constraint may also be applied to S1, i.e. all the stiffening elements are applied to S1.

Step 430, the lining model determining unit obtains the surface geometric characteristics of the target voxel structure, and determines a lining model, in which the spatial position constraint generated on the target voxel structure conforms to the corresponding allocated reinforcement elements, from a lining model library according to the surface geometric characteristics.

Since the reinforcement using the inner-lining paper structure is performed for the faces, the reinforcement is performed by the face contact, not by the line contact and the point contact, and thus the face geometric features of S1 and S3 need to be obtained. The surface geometry is the shape, position and size of the whole surface obtained after the visible surfaces (exposed surfaces) of the exterior voxel units of S1 and S3 are merged in the same plane. Wherein the form includes a general plane, a concave bottom surface (the inner bottom surface of the groove), a concave side surface (the inner side surface of the groove), a convex top surface (the convex outer top surface), and a convex side surface (the convex outer side surface). For example, in fig. 2, the front surface (i.e., front surface) of S1 is a general plane, the side surface of S2 is a convex side surface, the top surface, left and right side surfaces, and rear surface of S3 are general planes, and the front surface of S3 includes a concave side surface, a concave bottom surface, and a general plane.

The lining model library is a pre-established model library containing multiple types of lining models, each lining model is screened from the lining model library based on the surface geometric characteristics of S1 and S3, and a corresponding lining model structurally matched with the target voxel structure is selected for each reinforcing element. As shown in fig. 5 (not shown in the drawing), S1 needs to be restrained by lateral movement, so that a lining structure resisting movement of S1, for example, a rectangular parallelepiped buffer block R1 is provided as a lining model, needs to be provided on both left and right sides of S1; s1 needs to be constrained by vertical movement, so a lining structure resisting movement of S1 needs to be provided on top of S1, for example, a rectangular parallelepiped buffer block R2 is provided as a lining model; s3 needs to be restrained by longitudinal movement, so that it is necessary to provide a lining structure resisting movement of S3, for example, a rectangular parallelepiped cushion R3 as a lining model, on both front and rear sides of S3. The cuboid buffer block is mainly used for buffering a common plane and can be fixed at an adaptive position in the carton box in an adhering mode, R1, R2 and R3 are the same in shape and size and are different in installation position, and if the cuboid buffer block is used for surfaces of other shapes, other more appropriate lining pieces can be selected from the lining model base.

It will be appreciated that if all the reinforcement elements are applied to S1 as described above, S1 needs to be constrained against lateral, longitudinal and vertical movement as shown in fig. 6 (drawing of the carton in the figure), and therefore the longitudinal movement constraint is achieved by using the rectangular parallelepiped blocks R4 and R5 with flaps as lining forms, with the flap portions replacing R3.

An embodiment of the corrugated paper structure design system based on the demand import model disclosed in the present application is described in detail below with reference to fig. 7. The embodiment is a system for implementing the embodiment of the corrugated paper structure design method based on the demand import model.

As shown in fig. 7, the system disclosed in this embodiment mainly includes:

In one embodiment, the voxel model building module comprises:

In one embodiment, the voxel model building module further comprises:

In one embodiment, the structural feature acquisition module comprises:

In one embodiment, the manner in which the structural feature acquisition module calculates the first similarity and the second similarity includes:

In one embodiment, the structural feature acquisition module comprises:

In one embodiment, the reinforcing element determining module includes:

In one embodiment, the liner model selection module comprises:

In this document, "first", "second", and the like are used only for distinguishing one from another, and do not indicate their degree of importance, order, and the like.

The division of modules, units or components herein is merely a logical division, and other divisions may be possible in an actual implementation, for example, a plurality of modules and/or units may be combined or integrated in another system. Modules, units, or components described as separate parts may or may not be physically separate. The components displayed as cells may or may not be physical cells, and may be located in a specific place or distributed in grid cells. Therefore, some or all of the units can be selected according to actual needs to implement the scheme of the embodiment.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A corrugated paper structure design method based on a demand import model is characterized by comprising the following steps:

selecting a lining model matched with the reinforcing element from a lining model library based on the placing posture and the size of the voxel model, wherein the lining model library is stored with a plurality of types of lining models, and the types of the lining models comprise a buffer type model, a shock absorption type model and a support type model and are used for buffering and fixing between commodities and cartons;

selecting a packaging box model which is matched with the inner packaging body obtained after the voxel model and the lining model are combined from an outer box model library; wherein,

the building of the voxel model of the commodity based on the point cloud data comprises the following steps:

judging a voxel unit where each point is located in the point cloud data, and generating a voxel model through the voxel unit containing the points; in addition, the first and second substrates are,

the identifying of the commodity type information of the voxel model comprises:

when the leading difference value is not lower than the difference threshold value, taking the commodity type to which the voxel template corresponding to the leading first similarity belongs as the commodity type of the voxel model, otherwise, obtaining a candidate voxel template of which the first similarity is not lower than the similarity threshold value under the current resolution, improving the resolution of the voxel model, calculating a second similarity between the voxel model and the candidate voxel template under the corresponding resolution after the resolution is improved, calculating the overall similarity between the voxel model and the candidate voxel template by combining the first similarity and the second similarity, and taking the commodity type to which the candidate voxel template with the highest overall similarity belongs as the commodity type of the voxel model, wherein the leading difference value is the difference value between the first similarity of the leading position and the first similarity of the second position; and the number of the first and second groups,

the calculation method of the first similarity and the second similarity includes:

comparing the positions of each apparent voxel unit of the voxel model and the voxel template, and counting an in-situ voxel unit and an ex-situ voxel unit, wherein the in-situ voxel unit is in the same voxel unit cell, the model and the template both have the apparent voxel unit, or one side has the apparent voxel unit and the other side has the internal voxel unit of the adjacent voxel units, the other side has the upper, lower, left, right, front and back sides, the ex-situ voxel unit is in the same voxel unit cell, one side of the model and the template has the apparent voxel unit and the other side is an empty voxel unit cell;

calculating corresponding similarity based on the number of the co-located voxel units and the sum of the number of the co-located voxel units and the number of the ectopic voxel units; and the number of the first and second groups,

the overall similarity calculation mode is as follows: distributing a weight higher than the first similarity to the second similarity, and multiplying the first similarity and the second similarity by the respective weights respectively to obtain a comprehensive score of the voxel template as the overall similarity between the candidate voxel template and the voxel model; in addition, the first and second substrates are,

the selecting of the lining model matched with the reinforcing element from the lining model library based on the placing posture and the size of the voxel model comprises the following steps:

2. The corrugated paper structure design method of claim 1, wherein the obtaining of the structural characteristics of the model based on the information comprises:

3. A method of designing a corrugated paper structure as set forth in claim 2 wherein analyzing the structural features and determining the pose of the voxel model comprises:

4. A corrugated paper structure design system based on a demand import model, comprising:

the lining model selecting module is used for selecting a lining model matched with the reinforcing element from a lining model library based on the placing posture and the size of the voxel model, wherein multiple types of lining models are stored in the lining model library, and the types of the lining models comprise a buffer model, a shock absorption model and a support model and are used for buffering and fixing between commodities and cartons;

the box body model selecting module is used for selecting a packaging box model which is matched with the inner packaging body obtained after the voxel model and the lining model are combined from an outer box model library; wherein,

the voxel model building module comprises:

the voxel model generating unit is used for judging the voxel unit where each point is located in the point cloud data and generating a voxel model through the voxel unit containing the points; in addition, the first and second substrates are,

the structural feature acquisition module includes:

a commodity type determining unit, configured to, when a head difference value is not lower than a difference threshold, take a commodity type to which a voxel template corresponding to a head first similarity belongs as a commodity type of the voxel model, otherwise, obtain a candidate voxel template of which a first similarity is not lower than a similarity threshold at a current resolution, improve the resolution of the voxel model, calculate a second similarity between the voxel model and the candidate voxel template at a corresponding resolution after the resolution is improved, calculate an overall similarity between the voxel model and the candidate voxel template by integrating the first similarity and the second similarity, and take a commodity type to which the candidate voxel template with the highest overall similarity belongs as a commodity type of the voxel model, where the head difference value is a difference value between the first similarity of the head and the first similarity of the second head; and the number of the first and second groups,

the manner of calculating the first similarity and the second similarity by the structural feature acquisition module includes:

the lining model selecting module comprises:

5. The corrugated paper structural design system of claim 4, wherein the structural feature acquisition module comprises:

6. The corrugated paper structural design system of claim 5, wherein the reinforcing element determining module comprises: