Method and system for drawing construction drawings of belt conveyors based on secondary development

Abstract

The present invention discloses a method and system for realizing the drawing of belt conveyor construction drawings based on secondary development, which belongs to the technical field of conveyor drawing drawing, including: generating multiple construction planning schemes based on construction area data, extracting an optimal planning scheme, and obtaining planning information of the optimal planning scheme; extracting construction component elements of the conveyor in a first database based on planning information, generating multiple groups of CAD element information based on construction component elements and planning information; generating suggested drawings based on CAD element information, generating a first mean value corresponding to feature information based on suggested drawings, topological optimization values ​​and associated attributes, and generating CAD drawings based on the first mean value; predicting and outputting the best shape in all CAD drawings based on an optimization algorithm, generating construction drawings based on CAD data contained in the best shape, and completing the construction work of the conveyor. The present invention can accurately draw the construction drawings of belt conveyors and improve the integrity of construction drawing drawing.

Description

Technical Field

[0001] The invention belongs to the technical field of conveyor drawing drawing, and specifically relates to a method and system for realizing belt conveyor construction drawing drawing based on secondary development. Background Art

[0002] Belt conveyor is the main equipment for modern bulk material transportation. It has been widely used in metallurgy, chemical industry, mining, power station, port and other industrial fields due to its safe and efficient continuous transportation advantages. However, the calculation theory of belt conveyor design software is outdated, and the software technology architecture limits the application of big data and artificial intelligence technology in the field of belt conveyor design, which cannot meet the design requirements of industry development. Therefore, secondary development is needed to realize the belt conveyor construction drawing system, so that it has artificial intelligence assisted design, precise resistance calculation, dynamic analysis function and fine drawing function, which can meet the design, processing and manufacturing needs of belt conveyors in various industries.

[0003] For example, Chinese patent CN115481457B discloses a long-distance belt conveyor line planning method, electronic equipment and storage medium, which relates to the technical field of belt conveyor lines. According to the topographic map, conveyor longitudinal section line data and conveyor longitudinal section line CAD drawing are generated in the Weidi software; the conveyor longitudinal section line CAD drawing is processed by the CAD software to obtain the conveyor longitudinal section line CAD drawing with equally divided point marks; the conveyor longitudinal section line CAD drawing with equally divided point marks is processed by the Weidi software and the conveyor longitudinal section line data to obtain the conveyor longitudinal section line CAD drawing after secondary discretization and process it to obtain the final plan view of the conveyor line and the final elevation view of the conveyor line; the coordinates of the final plan view and elevation view are automatically set to correspond to each other to obtain the leg height and truss length. The invention can determine the leg height and truss length of the long-distance belt conveyor with high efficiency and high accuracy. Another example is Chinese patent application CN117786816A, which discloses a method for drawing and calculating the quantity of building intelligent design based on AutoCAD secondary development technology, including: organizing the building base map, writing codes, extracting data from the drawings through CAD secondary development, cleaning and organizing the data, and automatically designing each intelligent subsystem, etc., and performing secondary development on AutoCAD by writing programs, importing the marked CAD drawings, reading the architectural feature information of the project and the coordinate information of the intelligent terminal points, and automatically implementing the design of the background equipment according to the read information. After checking the design defects, the intelligent system design description, intelligent system diagram, large sample diagram, equipment material table and design budget are automatically generated. It overcomes the defects of the existing secondary development automatic design plug-in technology, which is relatively limited, comprehensive and not practical, and has the technical characteristics of high intelligence, automation, comprehensive functions, and simple operation, which greatly improves the design efficiency and accuracy, and can be widely used in the field of building intelligent design in the construction industry.

[0004] However, the above-mentioned prior art does not combine the utilization efficiency of the belt conveyor when drawing the construction drawing, and cannot realize the automatic drawing function of the belt conveyor. In actual situations, it is necessary to build an intelligent decision-making algorithm to analyze various working conditions of the belt conveyor and quickly and accurately select the main components to realize the function of drawing the construction drawing. Summary of the invention

[0005] In order to solve the above problems, the present invention provides a method and system for realizing the drawing of construction drawings of belt conveyors based on secondary development, so as to solve the problems in the prior art.

[0006] In order to achieve the above-mentioned purpose of the invention, the present invention proposes a method for drawing a belt conveyor construction drawing based on secondary development, comprising:

[0007] S1: Acquire construction area data, generate multiple construction planning schemes based on the construction area data, extract an optimal planning scheme from the construction planning schemes, and acquire planning information of the optimal planning scheme;

[0008] S2: setting label information, establishing a first database based on the label information, extracting construction component elements of the conveyor from the first database based on the planning information, generating multiple groups of CAD element information based on the construction component elements and the planning information, and checking whether all CAD element information is missing, and if so, supplementing the CAD element information;

[0009] S3: sequentially connecting the component elements included in each group of CAD element information, generating a suggested drawing, establishing a structural optimization model, respectively acquiring feature information and topology optimization values ​​corresponding to the suggested drawing based on the structural optimization model, acquiring associated attributes of the component elements based on the feature information, generating a first mean value corresponding to the feature information based on the topology optimization value and the associated attributes, and generating a CAD drawing based on the first mean value;

[0010] S4: Establish an optimization algorithm, predict and output the best shape in all CAD drawings based on the optimization algorithm, generate construction drawings based on the CAD data contained in the best shape, and complete the construction work of the conveyor based on the construction drawings.

[0011] Furthermore, extracting the best planning scheme from the construction planning schemes includes the following steps:

[0012] The construction area data includes site data, equipment data and a transportation rule set, a connection relationship is obtained based on the equipment data, a three-dimensional space is constructed based on the site data, a connection area of ​​the three-dimensional space is obtained based on the connection relationship, an inflection point distribution is set in the connection area, a plurality of connection routes are generated in the connection area based on the connection relationship and the inflection point distribution, and the connection routes are combined and set as the construction planning scheme;

[0013] An evaluation function is set based on the transport rule set, all evaluation functions are combined into a multi-objective algorithm, the evaluation value of the construction planning scheme is output based on the multi-objective algorithm, and the construction planning scheme corresponding to the minimum evaluation value is set as the optimal planning scheme.

[0014] Furthermore, the outputting of the evaluation value of the construction planning scheme based on the multi-objective algorithm includes:

[0015] The evaluation value F of the construction planning scheme is calculated based on the first formula, and the first formula is: , where i is a positive integer from 1 to I, and I is the total number of all the evaluation functions. is the preset coefficient, is the critical value of the i-th evaluation function, is the preset threshold of the i-th evaluation function, is the value of the construction planning scheme in the i-th evaluation function, and The values ​​and meanings of are the same, x is the variable corresponding to the i-th evaluation function, X is the set of variables x, and min is the operator symbol for finding the minimum value.

[0016] Furthermore, the optimization conditions of the structural optimization model are set, the density values ​​corresponding to the suggested drawings under the optimization conditions are calculated based on the finite element algorithm and the density method, and the set of the density values ​​is set as the topology optimization value.

[0017] Further, generating a CAD drawing based on the first mean value comprises the following steps:

[0018] Combining the suggested drawings with the corresponding topology optimization values ​​to generate a second database, setting clustering conditions, clustering and dividing the second database in sequence based on the self-organizing map and the clustering conditions to generate multiple clustering results, obtaining a variable mean of each clustering result, and setting the variable mean as the first mean;

[0019] A learning model is established, the second database, the clustering condition and the clustering result are input into the learning model, and a new drawing corresponding to the first mean is generated based on the topology optimization value and the clustering result, and the parameters of the learning model are repeatedly adjusted until the new drawing has the same topology optimization value as the recommended drawing, and the new drawing is set as the CAD drawing.

[0020] Further, the predicting and outputting the best shape in all CAD drawings based on the optimization algorithm comprises the following steps:

[0021] The number of subsets contained in the clustering result is obtained, and a weight coefficient of the clustering result is set based on the number of subsets. The suggested drawings corresponding to the center points of the clustering results are extracted and set as standard subsets. The optimization algorithm generates a fixed shape based on the standard subset and the corresponding weight coefficients, and sets the fixed shape as the optimal shape.

[0022] Furthermore, the step of checking whether all CAD element information is missing includes the following steps:

[0023] Collect historical construction components of the conveyor, obtain performance labels of the historical construction components, build a construction sample set based on the performance labels and the historical construction components, obtain performance characteristics corresponding to the component elements in the CAD element information, and if the performance characteristics belong to the performance labels and the number of the performance characteristics is equal to the number of the performance labels, then determine that the CAD element information is not missing; otherwise, determine that the CAD element information is missing, and supplement the component elements of the CAD element information based on the missing performance labels.

[0024] The present invention also provides a system for realizing the drawing of belt conveyor construction drawings based on secondary development, the system is used to realize the method for realizing the drawing of belt conveyor construction drawings based on secondary development as described above, and the system mainly comprises:

[0025] A scheme planning module is used to obtain construction area data, generate multiple construction planning schemes based on the construction area data, extract an optimal planning scheme from the construction planning schemes, and obtain planning information of the optimal planning scheme;

[0026] A component generation module, used for setting label information, establishing a first database based on the label information, extracting construction component elements of the conveyor from the first database based on the planning information, generating multiple groups of CAD element information based on the construction component elements and the planning information, and checking whether all CAD element information is missing, and if so, supplementing the CAD element information;

[0027] A drawing analysis module, used to sequentially connect the component elements included in each group of CAD element information, generate a suggested drawing, establish a structural optimization model, respectively obtain characteristic information and topology optimization values ​​corresponding to the suggested drawing based on the structural optimization model, obtain associated attributes of the component elements based on the characteristic information, generate a first mean value corresponding to the characteristic information based on the topology optimization value and the associated attributes, and generate a CAD drawing based on the first mean value;

[0028] The drawing drawing module is used to establish an optimization algorithm, predict and output the best shape in all CAD drawings based on the optimization algorithm, generate construction drawings based on the CAD data contained in the best shape, and complete the construction work of the conveyor based on the construction drawings.

[0029] The present invention also provides a computer storage medium storing program instructions, wherein when the program instructions are executed, the device where the computer storage medium is located is controlled to execute the above-mentioned method for drawing construction drawings of belt conveyors based on secondary development.

[0030] Compared with the prior art, the beneficial effects of the present invention are at least as follows:

[0031] The present invention firstly generates the best planning scheme through the construction area data and extracts the construction component elements of the conveyor, so as to quickly and comprehensively describe the construction area and construction method of the conveyor. Then, it checks whether the CAD element information is missing through the construction sample set, so as to improve the integrity of the CAD element information. Finally, the suggested drawings are generated through the component elements, and the CAD drawings are generated based on the structural optimization model combined with the suggested drawings. The conveyor construction drawings corresponding to different feature information can be automatically drawn, so as to improve the construction efficiency.

[0032] The present invention also predicts the best shape of the output construction drawing in all CAD drawings by establishing an optimization algorithm, and generates a construction drawing from the CAD data corresponding to the best shape, thereby improving the accuracy of the construction operation of the conveyor. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a flow chart of the steps of the method for drawing the construction drawing of a belt conveyor based on secondary development of the present invention;

[0034] Figure 2 This is a system structure diagram for drawing construction drawings of belt conveyors based on secondary development of the present invention. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0036] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0037] like Figure 1 As shown, the method for drawing the construction drawing of the belt conveyor based on secondary development includes:

[0038] S1: Acquire construction area data, generate multiple construction planning schemes based on the construction area data, extract an optimal planning scheme from the construction planning schemes, and obtain planning information of the optimal planning scheme.

[0039] Specifically, the present invention uses computer-aided design (CAD) software as a basic platform for secondary development and application to achieve specific functions. In this embodiment, the construction area data refers to the data information contained in the area where the belt conveyor needs to be installed, including but not limited to site data, equipment data and a conveying rule set, wherein the site data refers to the three-dimensional scene data of the construction area, the equipment data refers to the spatial position data of each device that needs to be connected to the belt conveyor and the conveying point coordinate data of each device, and the conveying rule set refers to a data set composed of the transmission direction data, transportation mode data, style data, and transportation material demand data of the belt conveyor. The transportation mode data includes but is not limited to parallel transportation, top-to-bottom transportation, bottom-to-top transportation, etc. The style data includes but is not limited to horizontal belt conveyors, inclined belt conveyors, curved belt conveyors, and tubular belt conveyors, etc. The transportation material demand data includes but is not limited to material particle size and particle size ratio, etc. By obtaining the construction area data, the area range and construction method where the belt conveyor can be constructed can be planned in detail to form a variety of feasible plans, that is, construction planning plans. In order to reduce the diversity of construction planning schemes, it is necessary to extract an optimal planning scheme, where the optimal planning scheme refers to a scheme that reduces the construction area and performs construction within a set spatial range. The specific generation method will be described later. Planning information refers to the planning data corresponding to the optimal planning scheme, including but not limited to the planning route, planning area, and planning method.

[0040] S2: Set label information, establish a first database based on the label information, extract construction component elements of the conveyor from the first database based on the planning information, generate multiple groups of CAD element information based on the construction component elements and the planning information, check whether all CAD element information is missing, and if so, supplement the CAD element information.

[0041] Specifically, in this embodiment, the label information refers to the label name used to set the first database, including but not limited to the component name, component function, component performance and component CAD parameters, etc. The first database refers to the component database, and various data information of the components corresponding to the label information can be accurately obtained through the first database. For example, the component name is a conveyor belt, and its corresponding component function is conveying, the component performance is strength and durability parameters, etc., and the component CAD parameters are data information such as width, length, thickness and material. Conveyor refers to belt conveyor, and construction component elements refer to the types of components required for belt conveyor construction obtained according to planning information. Since the same component function or the same component performance may have different component names, there may be a combination of multiple component elements in the construction component elements, and there may also be multiple combinations of corresponding CAD element information, wherein CAD element information refers to the CAD parameter data generated by combining the component CAD parameters of each component name with the planning information. For example, if the length of the conveyor belt used in the planned route in the planning information is 10 meters, then the CAD element information is the component CAD parameters corresponding to the conveyor belt with a straight-line distance of 10 meters between the starting point and the end point drawn using a scale, wherein it may be a horizontal straight line method, a curved method with a curved angle, or an inclined method with an inclined angle. The specific setting method will be described later. Since CAD element information is generated according to planning information, there may be incomplete CAD element information for connection and combination, resulting in missing drawings of the conveyor. Therefore, it is necessary to verify the integrity of all CAD element information and supplement the missing CAD element information.

[0042] S3: Connect the component elements contained in each group of CAD element information in sequence, generate a suggested drawing, establish a structural optimization model, obtain the feature information and topology optimization values ​​corresponding to the suggested drawing based on the structural optimization model, obtain the associated attributes of the component elements based on the feature information, generate a first mean value corresponding to the feature information based on the topology optimization value and the associated attributes, and generate a CAD drawing based on the first mean value.

[0043] Specifically, in this embodiment, the data contained in the CAD element information can control the size and position of the corresponding component CAD parameters by defining parameters. Therefore, by sequentially connecting all the construction component elements in each group of CAD element information based on the position, a suggested drawing can be generated. The component element is the construction component element. Since the CAD element information is a variety of combinations, the generated suggested drawings are also a variety of styles. The structural optimization model is an optimization model composed of topological optimization calculations. The characteristic information refers to characteristics such as manufacturing cost, efficiency, and component performance. The topological optimization value is a numerical value calculated and generated by the structural optimization model. The associated attribute refers to associating the characteristic information with the component element. The first mean refers to the average value of various variables contained in the characteristic information. The CAD drawing refers to a drawing that can be used for conveyor construction.

[0044] S4: Establish an optimization algorithm, predict and output the best shape in all CAD drawings based on the optimization algorithm, generate construction drawings based on the CAD data contained in the best shape, and complete the construction work of the conveyor based on the construction drawings.

[0045] Specifically, in this embodiment, the optimization algorithm is a numerical analysis algorithm based on density distribution. The optimization algorithm can predict the specific shape of the CAD drawing after construction, that is, the optimal shape. The CAD data has the same meaning as the component CAD parameters. Therefore, the CAD data contained in the optimal shape can be connected in sequence to generate a construction drawing, and the construction of the conveyor is completed by the construction drawing. The optimal shape can be used to display the construction shape of the conveyor after construction before construction, which is conducive to improving construction efficiency and improving construction accuracy.

[0046] As a preferred technical solution of the present invention, extracting the best planning scheme from the construction planning scheme includes the following steps:

[0047] The construction area data includes site data, equipment data and a transportation rule set. The connection relationship is obtained based on the equipment data, and a three-dimensional space is constructed based on the site data. The connection area of ​​the three-dimensional space is obtained based on the connection relationship, and the inflection point distribution is set in the connection area. Based on the connection relationship and the inflection point distribution, multiple connection routes are generated in the connection area, and the connection routes are combined and set as a construction planning scheme.

[0048] An evaluation function is set based on the transport rule set, all evaluation functions are combined into a multi-objective algorithm, the evaluation value of the construction planning scheme is output based on the multi-objective algorithm, and the construction planning scheme corresponding to the minimum evaluation value is set as the optimal planning scheme.

[0049] Specifically, in this embodiment, the three-dimensional space constructed by the site data can accurately describe the position and size of the component CAD parameters contained in each subsequent drawing. The connection relationship refers to the direction sequence of the corresponding conveying of each equipment data. The connection relationship is set by the production mode. The connection area refers to the spatial area planned in the three-dimensional space that can be used for the construction of the algebraic conveyor. The inflection point distribution refers to the distribution of points set in the three-dimensional space when the conveyor type is a curved belt conveyor that cannot be used. For example, when there is a long-distance straight-line conveyance in the equipment data, the equipment positions corresponding to the starting point and the end point can be set as the points contained in the inflection point distribution. The connection route refers to the route generated by connecting the inflection point distribution in sequence based on the connection relationship, wherein the range of the connection route is less than or equal to the range of the connection area in the three-dimensional space, and multiple construction planning schemes are generated by combining the connection routes based on the three-dimensional space.

[0050] The evaluation function is used to analyze and evaluate the feasibility of each construction planning scheme. The calculation method can be set in each data set corresponding to the transportation rule set according to the construction planning scheme, including but not limited to the space utilization function, cost function, and transportation efficiency function. The multi-objective algorithm is composed of a set of evaluation functions. The evaluation value can measure the feasibility of the construction plan. The smaller the evaluation value, the higher the feasibility. Therefore, the construction planning scheme corresponding to the minimum evaluation value is set as the optimal planning scheme.

[0051] As a preferred technical solution of the present invention, the evaluation value of the construction planning scheme output based on the multi-objective algorithm includes:

[0052] The evaluation value F of the construction planning scheme is calculated based on the first formula, which is: , where i is a positive integer from 1 to I, and I is the total number of all evaluation functions. is the preset coefficient, is the critical value of the i-th evaluation function, is the preset threshold of the i-th evaluation function, is the value of the construction planning scheme in the i-th evaluation function, and The values ​​and meanings of are the same, x is the variable corresponding to the i-th evaluation function, X is the set of variables x, and min is the operator symbol for finding the minimum value.

[0053] Specifically, in this embodiment, the first formula can be used to accumulate the values ​​corresponding to the various evaluation functions of the construction planning scheme to generate an evaluation value, wherein the preset coefficient can be set according to the preset result value range, the critical value of the evaluation function refers to the optimal value of the evaluation function, therefore, it is less than or equal to the minimum value of the evaluation function, and the preset threshold refers to the threshold set by the evaluation function. For example, when the evaluation function is a space utilization function, it can be calculated by space proportion, the critical value is 0.1, the preset threshold is 0.5, if The value of the evaluation function for the construction planning scheme is 0.4, which is less than the threshold value of 0.5, indicating that the space utilization rate of the construction planning scheme is high.

[0054] As a preferred technical solution of the present invention, the optimization conditions of the structural optimization model are set, the density values ​​corresponding to the recommended drawings under the optimization conditions are calculated based on the finite element algorithm and the density method, and the set of density values ​​is set as the topology optimization value.

[0055] Specifically, in this embodiment, the optimization condition refers to the conditions required for the topology optimization calculation, including but not limited to volume constraint conditions and material conditions, etc. The finite element algorithm is a numerical technique that can be used to solve various problems in engineering and physics, especially structural analysis problems with complex geometric shapes, constraints and loading conditions. The grid-like area of ​​the finite element algorithm can be used to set the calculation domain to form an analysis model of the optimization condition. The density method refers to a density algorithm for topology optimization. The material density can be used as an optimization method for design variables. Combined with the finite element algorithm, the density of each finite element is regarded as a design variable, generating highly innovative and efficient designs, and ensuring the stability and reliability of the optimization condition process. The density value refers to the value generated by the density method and the finite element algorithm, which is used to represent the material distribution or filling degree of each unit in the finite element algorithm. It is a scalar value between 0 and 1, which continuously represents the relative amount of the material in the optimization process, that is, the presence or absence of the material in the material drawing. Therefore, the distribution corresponding to all density values ​​is set as the distribution of the topology optimization value.

[0056] As a preferred technical solution of the present invention, generating a CAD drawing based on the first mean value includes the following steps:

[0057] The suggested drawings are combined with the corresponding topology optimization values ​​to generate a second database, clustering conditions are set, the second database is clustered and divided in turn based on the self-organizing map and the clustering conditions, a plurality of clustering results are generated, the variable mean of each clustering result is obtained, and the variable mean is set as the first mean.

[0058] A learning model is established, and the second database, clustering conditions and clustering results are input into the learning model. A new drawing corresponding to the first mean is generated based on the topology optimization value and the clustering result. The parameters of the learning model are repeatedly adjusted until the new drawing has the same topology optimization value as the recommended drawing, and the new drawing is set as the CAD drawing.

[0059] Specifically, in this embodiment, the second database is a drawing information database, which contains data information corresponding to the recommended drawings and topology optimization values. The clustering condition refers to a condition vector with different emphasis conditions. For example, the condition vectors corresponding to the feature information are selected and set as clustering conditions, including but not limited to manufacturing cost, efficiency and component performance. The self-organizing map is an unsupervised neural network algorithm that can extract drawing features from the second database, including size, shape, material properties, stress distribution, displacement and objective function value, etc., and divide the data into highly similar clusters, i.e., clustering results, through weight vectors. The variable mean refers to the average value corresponding to each variable in the clustering result, where the variable refers to the condition vector contained in the clustering condition, and the variable mean is set to the first mean.

[0060] The learning model refers to a machine learning model, which is constructed by the CycleGAN cyclic generative adversarial network algorithm and can realize various application scenarios of CAD drawings. In this embodiment, the learning model is used for image generation, and a cluster contained in a clustering result is extracted. After the topological optimization value and the clustering condition belonging to the cluster are input into the learning model, a new drawing can be generated, and then it is determined whether the new drawing is the same as the suggested drawing related to the input topological optimization value. If different, the parameters of the learning model are adjusted, and this step is repeated until the new drawing has the same topological optimization value as the suggested drawing to generate a CAD drawing.

[0061] As a preferred technical solution of the present invention, predicting and outputting the best shape in all CAD drawings based on the optimization algorithm includes the following steps:

[0062] The number of subsets contained in the clustering result is obtained, and the weight coefficient of the clustering result is set based on the number of subsets. The recommended drawings corresponding to the center points of the clustering results are extracted and set as the standard subsets. The optimization algorithm generates a fixed shape based on the standard subsets and the corresponding weight coefficients, and sets it as the optimal shape.

[0063] Specifically, in this embodiment, the number of subsets refers to the total number of suggested drawings contained in the cluster corresponding to the clustering result. The weight coefficient can be set according to the size of the number of subsets. The larger the number of subsets, the larger the weight coefficient, and the standard subset has the best reference. Therefore, the weight coefficient is used to standardize and set the optimal size of all standard subsets to form a fixed shape, that is, the optimal shape. For example, the cluster corresponding to the clustering result contains suggested drawings with high similarity. Each clustering result is generated by different clustering conditions. The weight coefficient of the standard subset is set by the number of subsets, and the fixed shape can be automatically generated by combining the topology optimization values ​​corresponding to all standard subsets, which is the optimal shape.

[0064] As a preferred technical solution of the present invention, checking whether all CAD element information is missing includes the following steps:

[0065] Collect historical construction components of the conveyor, obtain performance labels of the historical construction components, build a construction sample set based on the performance labels and historical construction components, obtain performance characteristics corresponding to component elements in the CAD element information, and if the performance characteristics belong to performance labels and the number of performance characteristics is equal to the number of performance labels, then it is determined that the CAD element information is not missing; otherwise, it is determined that the CAD element information is missing, and the component elements of the CAD element information are supplemented based on the missing performance labels.

[0066] Specifically, in this embodiment, the historical construction component refers to the set of components required for the construction and installation of the conveyor in the historical records, the performance label refers to the label information corresponding to the function of each historical construction component, and the construction sample set refers to a sample data set in which the historical construction components and the performance labels in various historical records correspond one to one. If the performance characteristics of each component element in the CAD element information belong to the performance label, and the number of performance characteristics is equal to the number of performance labels, it means that the component elements in the CAD element information correspond one to one with the performance labels contained in the construction sample set, and therefore, it is determined that the CAD element information is not missing. The supplementary component element can extract the largest number of historical construction components in the construction sample set according to the missing performance labels as a way to supplement the CAD element information.

[0067] like Figure 2 As shown, the present invention also provides a system for drawing a belt conveyor construction drawing based on secondary development, which is used to implement the above-mentioned method for drawing a belt conveyor construction drawing based on secondary development. The system mainly includes:

[0068] The scheme planning module is used to obtain construction area data, generate multiple construction planning schemes based on the construction area data, extract an optimal planning scheme from the construction planning schemes, and obtain planning information of the optimal planning scheme.

[0069] The component generation module is used to set label information, establish a first database based on the label information, extract the construction component elements of the conveyor from the first database based on the planning information, generate multiple sets of CAD element information based on the construction component elements and the planning information, and check whether all CAD element information is missing. If so, the CAD element information is supplemented.

[0070] The drawing analysis module is used to sequentially connect the component elements contained in each group of CAD element information, generate suggested drawings, establish a structural optimization model, obtain the feature information and topology optimization values ​​corresponding to the suggested drawings based on the structural optimization model, obtain the associated attributes of the component elements based on the feature information, generate a first mean value corresponding to the feature information based on the topology optimization value and the associated attributes, and generate a CAD drawing based on the first mean value.

[0071] The drawing drawing module is used to establish an optimization algorithm, predict and output the best shape in all CAD drawings based on the optimization algorithm, generate construction drawings based on the CAD data contained in the best shape, and complete the construction work of the conveyor based on the construction drawings.

[0072] The present invention also provides a computer storage medium storing program instructions, wherein when the program instructions are executed, the device where the computer storage medium is located is controlled to execute the above-mentioned method for drawing construction drawings of belt conveyors based on secondary development.

[0073] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0074] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the above-mentioned program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0075] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0076] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for those of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0077] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for drawing construction drawings of belt conveyors based on secondary development, characterized in that: The method comprises the following steps: S1: Acquire construction area data, generate multiple construction planning schemes based on the construction area data, extract an optimal planning scheme from the construction planning schemes, and acquire planning information of the optimal planning scheme; S2: setting label information, establishing a first database based on the label information, extracting construction component elements of the conveyor from the first database based on the planning information, generating multiple groups of CAD element information based on the construction component elements and the planning information, and checking whether all CAD element information is missing, and if so, supplementing the CAD element information; S3: sequentially connecting the component elements included in each group of CAD element information, generating a suggested drawing, establishing a structural optimization model, respectively acquiring feature information and topology optimization values ​​corresponding to the suggested drawing based on the structural optimization model, acquiring associated attributes of the component elements based on the feature information, generating a first mean value corresponding to the feature information based on the topology optimization value and the associated attributes, and generating a CAD drawing based on the first mean value; wherein, the optimization conditions of the structural optimization model are set, the density values ​​corresponding to the suggested drawings under the optimization conditions are calculated based on the finite element algorithm and the density method, and the set of the density values ​​is set as the topology optimization value; Generating a CAD drawing based on the first mean value comprises the following steps: Combining the suggested drawings with the corresponding topology optimization values ​​to generate a second database, setting clustering conditions, clustering and dividing the second database in sequence based on the self-organizing map and the clustering conditions to generate multiple clustering results, obtaining a variable mean of each clustering result, and setting the variable mean as the first mean; Establishing a learning model, inputting the second database, the clustering condition and the clustering result into the learning model, generating a new drawing corresponding to the first mean value based on the topology optimization value and the clustering result, repeatedly adjusting the parameters of the learning model until the new drawing has the same topology optimization value as the suggested drawing, and setting the new drawing as the CAD drawing; S4: establishing an optimization algorithm, predicting and outputting an optimal shape in all CAD drawings based on the optimization algorithm, generating a construction drawing based on the CAD data included in the optimal shape, and completing the construction work of the conveyor based on the construction drawing; Wherein, the predicting and outputting the best shape in all CAD drawings based on the optimization algorithm comprises the following steps: The number of subsets contained in the clustering result is obtained, and a weight coefficient of the clustering result is set based on the number of subsets. The suggested drawings corresponding to the center points of the clustering results are extracted and set as standard subsets. The optimization algorithm generates a fixed shape based on the standard subset and the corresponding weight coefficients, and sets the fixed shape as the optimal shape.

2. The method according to claim 1, characterized in that Extracting the best planning scheme from the construction planning schemes includes the following steps: The construction area data includes site data, equipment data and a transportation rule set, a connection relationship is obtained based on the equipment data, a three-dimensional space is constructed based on the site data, a connection area of ​​the three-dimensional space is obtained based on the connection relationship, an inflection point distribution is set in the connection area, a plurality of connection routes are generated in the connection area based on the connection relationship and the inflection point distribution, and the connection routes are combined and set as the construction planning scheme; An evaluation function is set based on the transport rule set, all evaluation functions are combined into a multi-objective algorithm, the evaluation value of the construction planning scheme is output based on the multi-objective algorithm, and the construction planning scheme corresponding to the minimum evaluation value is set as the optimal planning scheme.

3. The method according to claim 2, characterized in that The evaluation value of the construction planning scheme outputted based on the multi-objective algorithm includes: The evaluation value F of the construction planning scheme is calculated based on the first formula, and the first formula is: , where i is a positive integer from 1 to I, and I is the total number of all the evaluation functions. is the preset coefficient, is the critical value of the i-th evaluation function, is the preset threshold of the i-th evaluation function, is the value of the construction planning scheme in the i-th evaluation function, and The values ​​and meanings of are the same, x is the variable corresponding to the i-th evaluation function, X is the set of variables x, and min is the operator symbol for finding the minimum value.

4. The method according to claim 1, characterized in that The checking whether all CAD element information is missing includes the following steps: Collect historical construction components of the conveyor, obtain performance labels of the historical construction components, build a construction sample set based on the performance labels and the historical construction components, obtain performance characteristics corresponding to the component elements in the CAD element information, and if the performance characteristics belong to the performance labels and the number of the performance characteristics is equal to the number of the performance labels, then determine that the CAD element information is not missing; otherwise, determine that the CAD element information is missing, and supplement the component elements of the CAD element information based on the missing performance labels.

5. A system for drawing construction drawings of belt conveyors based on secondary development, used to implement the method according to any one of claims 1 to 4, characterized in that: The system includes the following modules: A scheme planning module is used to obtain construction area data, generate multiple construction planning schemes based on the construction area data, extract an optimal planning scheme from the construction planning schemes, and obtain planning information of the optimal planning scheme; A component generation module, used for setting label information, establishing a first database based on the label information, extracting construction component elements of the conveyor from the first database based on the planning information, generating multiple groups of CAD element information based on the construction component elements and the planning information, and checking whether all CAD element information is missing, and if so, supplementing the CAD element information; A drawing analysis module is used to sequentially connect the component elements included in each group of CAD element information, generate a suggested drawing, establish a structural optimization model, obtain the characteristic information and topology optimization value corresponding to the suggested drawing based on the structural optimization model, obtain the associated attributes of the component elements based on the characteristic information, generate a first mean value corresponding to the characteristic information based on the topology optimization value and the associated attributes, and generate a CAD drawing based on the first mean value; wherein, the optimization conditions of the structural optimization model are set, the density value corresponding to the suggested drawing under the optimization conditions is calculated based on the finite element algorithm and the density method, and the set of the density values ​​is set as the topology optimization value; the suggested The drawings and the corresponding topology optimization values ​​are combined to generate a second database, clustering conditions are set, the second database is clustered and divided in turn based on the self-organizing map and the clustering conditions, a plurality of clustering results are generated, the variable mean of each clustering result is obtained, and the variable mean is set as the first mean; a learning model is established, the second database, the clustering conditions and the clustering results are input into the learning model, and a new drawing corresponding to the first mean is generated based on the topology optimization value and the clustering result, the parameters of the learning model are repeatedly adjusted until the new drawing has the same topology optimization value as the recommended drawing, and the new drawing is set as the CAD drawing; A drawing drawing module is used to establish an optimization algorithm, predict and output the best shape in all CAD drawings based on the optimization algorithm, generate construction drawings based on the CAD data contained in the best shape, and complete the construction work of the conveyor based on the construction drawings, wherein the number of subsets contained in the clustering results is obtained, the weight coefficient of the clustering results is set based on the number of subsets, the recommended drawings corresponding to the center points of the clustering results are extracted and set as standard subsets, and the optimization algorithm generates a fixed shape based on the standard subset and the corresponding weight coefficient, and sets it as the best shape.

6. A computer storage medium, characterized in that: The computer storage medium stores program instructions, wherein when the program instructions are executed, the device where the computer storage medium is located is controlled to execute the method according to any one of claims 1 to 4.

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