A BIM-based intelligent woodworking method and system

Abstract

This invention provides a BIM-based intelligent woodworking processing method and system. The method includes: using BIM technology to model and calculate construction drawings to obtain several three-dimensional models of the required wooden formwork; based on the second dimension data of the raw material wood planks, the first dimension data of the wooden formwork, and their quantity, using a formwork matching analysis model to calculate and determine the optimal formwork matching scheme and generate a formwork matching diagram; inputting the formwork matching diagram into an intelligent cutting table saw, which generates a processing plan based on the diagram to cut the raw material wood planks; numbering the processed semi-finished wooden formwork according to the formwork matching diagram and stacking them according to different specifications; using a packing machine to pack the sorted and stacked semi-finished wooden formwork and using a transport robot to transport them to the construction site for on-site assembly by construction workers. This invention achieves precise centralized and automated processing of wooden formwork, reducing formwork waste.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing technology, and more specifically, to a BIM-based intelligent woodworking method and system. Background Technology

[0002] Currently, intelligent equipment is being used in more and more construction scenarios, and intelligent semi-finished product processing workshops are also common, such as for steel bars and steel structures. However, the processing of wooden formwork, the largest turnover material used in concrete structures, is still at a relatively primitive stage. There are a large number of carpenters using hand-held electric saws and simple table saws on construction sites, and the sawdust is difficult to clean up and can easily cause mechanical injuries. Summary of the Invention

[0003] To address the technical problems existing in the background art, the present invention provides a BIM-based intelligent woodworking processing method, system, electronic device, computer storage medium, and computer program product.

[0004] This invention provides a BIM-based intelligent woodworking method, comprising the following steps:

[0005] Using BIM technology, the construction drawings are modeled and calculated to obtain several three-dimensional models of the required wooden formwork. The three-dimensional models include the first dimension data and quantity of the wooden formwork.

[0006] Based on the second dimension data of the raw wood board, the first dimension data and quantity of the wood template, the template matching analysis model is used to perform calculations to determine the optimal template matching scheme and generate a template matching diagram.

[0007] The mold drawing is input into the intelligent cutting table saw, which generates a processing plan based on the mold drawing to cut the raw wood board.

[0008] The semi-finished wooden templates obtained after processing are numbered according to the template matching diagram and stacked according to different specifications;

[0009] The categorized and stacked semi-finished wooden formwork is packaged using a packing machine and then transported to the construction site using a transport robot for on-site assembly by construction workers.

[0010] Optionally, the intelligent cutting table saw cuts the raw wood board according to the processing plan, including:

[0011] A robotic arm with suction cups adsorbs the raw wood board and feeds it into the intelligent cutting table saw, which then cuts the raw wood board according to the processing plan.

[0012] Optionally, a powerful suction device is also provided on the intelligent cutting table. The powerful suction device is used to be turned on during the cutting operation of the intelligent cutting table to absorb and collect the sawdust generated during the cutting operation.

[0013] Optionally, the step of using a mold matching analysis model to calculate and determine the optimal mold matching scheme based on the second dimension data of the raw material wood board, the first dimension data and quantity of the wood template, includes:

[0014] The second dimension data of the raw material wood board, the first dimension data of the wood template, and the quantity are input into the mold matching analysis model. The mold matching analysis model outputs several mold matching schemes and the corresponding expected processing time and mold matching loss rate.

[0015] Obtain assessment data on the use of wooden formwork at the construction site, and calculate the urgency level of the use of wooden formwork at the construction site based on the assessment data.

[0016] The optimal formwork matching scheme is obtained by screening each formwork matching scheme according to the urgency level of the use of the wooden formwork.

[0017] Optionally, the step of obtaining the assessment data on the use of wooden formwork at the construction site, and calculating the urgency level of the use of wooden formwork at the construction site based on the assessment data, includes:

[0018] u=k(α1q1+α2q2+α3q3+p) k-1

[0019] In the formula, u is the urgency parameter for the use of timber formwork, k is the difficulty value of transporting the timber formwork to the construction site; q1 is the normalized value of the consumption rate of timber formwork at the construction site, q2 is the normalized value of the expected remaining demand for timber formwork at the construction site, q3 is the normalized value of the assembly loss rate of timber formwork at the construction site, α1, α2, and α3 are the corresponding weighting coefficients; and p is the normalized transformation value of the artificially added urgency description data.

[0020] The urgency level of the wooden formwork is obtained by comparing it with the urgency parameter u according to the specified control relationship.

[0021] Optionally, the model matching analysis model is constructed and trained based on a deep learning algorithm; the objective function used during training is as follows:

[0022]

[0023] In the formula, Q is the objective function, which represents the sum of the attractive and repulsive forces of the mold arrangement to be determined, k is the number of wooden templates, and d is the average distance between the centroids of each wooden template in the mold arrangement to be determined. It is a unit direction vector.

[0024] This invention also provides a BIM-based intelligent woodworking processing system, characterized by comprising a processing module, an intelligent cutting table saw, a robotic arm with suction cups, a packing machine, a transport robot, and a powerful suction device; wherein,

[0025] The processing module is used to model and calculate the construction drawings using BIM technology to obtain several three-dimensional models of the required wooden formwork. The three-dimensional models include the first dimension data and quantity of the wooden formwork. Based on the second dimension data of the raw wood planks, the first dimension data and quantity of the wooden formwork, the module uses a formwork matching analysis model to perform calculations and determine the optimal formwork matching scheme and generate a formwork matching diagram.

[0026] The intelligent cutting table saw is used to generate a processing plan based on the mold drawing obtained by the processing module, so as to cut the raw wood board.

[0027] The robotic arm with suction cups is used to feed the raw wood planks into the intelligent cutting table saw, and to number the semi-finished wood templates obtained after processing according to the template drawing and stack them according to different specifications.

[0028] The packing machine is used to pack the sorted and stacked semi-finished wooden templates.

[0029] The transport robot is used to transport the packaged semi-finished wooden templates to the construction site for construction workers to assemble on-site.

[0030] The powerful suction device is activated during the cutting operation of the intelligent table saw to absorb and collect sawdust generated during the cutting operation.

[0031] The present invention also provides an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calling the executable program code stored in the memory to perform the method as described in any of the preceding claims.

[0032] The present invention also provides a computer storage medium storing a computer program that, when executed by a processor, performs the method described in any of the preceding claims.

[0033] The present invention also provides a computer program product comprising a computer program stored on a non-transitory computer-readable medium, the computer program being executed by a processor as described in any of the preceding claims.

[0034] The beneficial effects of this invention are as follows:

[0035] 1. This invention enables precise centralized processing of wooden formwork, reduces formwork waste, eliminates the need for carpenters to carry electric saws on site, and reduces potential hazards such as temporary power use, mechanical injury, and dust pollution.

[0036] 2. Centralized processing in the woodworking workshop can greatly improve the image of civilized construction and on-site processing.

[0037] 3. Mechanical processing is far more efficient and precise than manual processing, which can improve work efficiency and reduce labor costs. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a flowchart illustrating a BIM-based intelligent woodworking processing method disclosed in an embodiment of the present invention.

[0040] Figure 2 This is a schematic diagram of the structure of a BIM-based intelligent woodworking system disclosed in an embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram of a BIM-based intelligent woodworking system disclosed in an embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0043] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0044] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0045] In the description of this invention, it should be noted that if terms such as "upper," "lower," "inner," or "outer" are used to indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of this invention is usually placed, they are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0046] Furthermore, the terms "first" and "second" are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0047] It should be noted that, where there is no conflict, the features in the embodiments of the present invention can be combined with each other.

[0048] like Figure 1 As shown in the figure, this invention discloses a BIM-based intelligent woodworking method, which includes the following steps:

[0049] Using BIM technology, the construction drawings are modeled and calculated to obtain several three-dimensional models of the required wooden formwork. The three-dimensional models include the first dimension data and quantity of the wooden formwork.

[0050] Based on the second dimension data of the raw wood board, the first dimension data and quantity of the wood template, the template matching analysis model is used to perform calculations to determine the optimal template matching scheme and generate a template matching diagram.

[0051] The mold drawing is input into the intelligent cutting table saw, which generates a processing plan based on the mold drawing to cut the raw wood board.

[0052] The semi-finished wooden templates obtained after processing are numbered according to the template matching diagram and stacked according to different specifications;

[0053] The categorized and stacked semi-finished wooden formwork is packaged using a packing machine and then transported to the construction site using a transport robot for on-site assembly by construction workers.

[0054] In this invention, BIM modeling technology is first used to convert construction drawings into three-dimensional models of wooden formwork. Each three-dimensional model contains the size data and quantity of the corresponding type of wooden formwork. Then, a formwork matching analysis model is used for optimization to obtain the best formwork matching scheme and generate a formwork matching diagram. The intelligent cutting table saw determines the processing scheme for the actual cutting operation based on the formwork matching diagram and completes the cutting and processing of the whole raw material wood board. The semi-finished wooden formwork obtained by processing is numbered, classified, stacked and packaged according to the formwork matching diagram, and finally transported to the construction site for assembly.

[0055] Therefore, the solution of this invention realizes the full automation of the wooden formwork processing process, mainly demonstrating the following benefits:

[0056] 1) Social benefits: The formwork engineering has transformed from traditional manual formwork processing to intelligent formwork processing, realizing the application of Building Information Modeling (BIM) technology in the field of formwork engineering, improving production efficiency, and contributing to the improvement of the intelligent level of the construction industry.

[0057] 2) Environmental benefits: Precise calculation of formwork turning reduces formwork wear, and 100% sawdust collection effectively reduces the amount of construction waste, achieving a green and low-carbon formwork processing method.

[0058] 3) Construction period benefits. Based on the formwork layout drawings and numbered semi-finished formwork, the formwork is laid in a "building block" manner, enabling rapid on-site assembly of the formwork and saving laying time.

[0059] 4) Economic benefits: According to statistics from a branch company regarding traditional mold-making methods, the on-site mold-making loss rate is 10%, meaning that for every 1000m³ of mold-making material prepared... 2 The template used actually covers an area of ​​1100m². 2 By using the template configuration method of this invention, arbitrary on-site cutting and rework can be eliminated, and the template loss rate can be controlled within 3%, that is, for every 1000m³ of templates prepared... 2 The template used actually covers an area of ​​1030m². 2 The average price of formwork purchased from 300 Yunzhu suppliers was selected. The unit price of ordinary formwork (1830*915*15) was 27.25 yuan / m. 2 For every 1000m³ prepared 2 The material cost saved by the template is (1100-1030)*27.25=1907.5 yuan, with a saving rate of 6.99%.

[0060] Optionally, the intelligent cutting table saw cuts the raw wood board according to the processing plan, including:

[0061] A robotic arm with suction cups adsorbs the raw wood board and feeds it into the intelligent cutting table saw, which then cuts the raw wood board according to the processing plan.

[0062] In this embodiment of the invention, a robotic arm equipped with suction cups is also incorporated. This robotic arm can grip the raw wood planks using vacuum suction and feed them into the inlet of an intelligent cutting table saw, allowing the saw to cut the raw template. Thus, this invention further enhances the automation level of wood template cutting, thereby increasing the efficiency of wood template configuration.

[0063] In addition, the robotic arms with suction cups are also used to stack semi-finished wooden templates of different specifications, and to assist the packing machine in packaging the sorted and stacked semi-finished wooden templates. Of course, multiple sets of robotic arms with suction cups can be configured, which will not be elaborated further.

[0064] Optionally, a powerful suction device is also provided on the intelligent cutting table. The powerful suction device is used to be turned on during the cutting operation of the intelligent cutting table to absorb and collect the sawdust generated during the cutting operation.

[0065] In this embodiment of the invention, the wood cutting process generates a significant amount of sawdust, which pollutes the processing environment and poses health risks to workers due to dust inhalation. Therefore, this invention also includes a powerful suction device on the intelligent cutting table, which activates promptly whenever the intelligent cutting table performs a cutting operation, thereby minimizing the concentration of sawdust at the processing site.

[0066] Optionally, the step of using a mold matching analysis model to calculate and determine the optimal mold matching scheme based on the second dimension data of the raw material wood board, the first dimension data and quantity of the wood template, includes:

[0067] The second dimension data of the raw material wood board, the first dimension data of the wood template, and the quantity are input into the mold matching analysis model. The mold matching analysis model outputs several mold matching schemes and the corresponding expected processing time and mold matching loss rate.

[0068] Obtain assessment data on the use of wooden formwork at the construction site, and calculate the urgency level of the use of wooden formwork at the construction site based on the assessment data.

[0069] The optimal formwork matching scheme is obtained by screening each formwork matching scheme according to the urgency level of the use of the wooden formwork.

[0070] In this embodiment of the invention, different batches of raw material templates may have different sizes, while the required size and quantity of wooden templates are relatively fixed. In this case, it is difficult to achieve the most reasonable template matching manually. To address this, the invention constructs the aforementioned template matching analysis model, which can transform manual template turning into intelligent template turning, thereby greatly improving template turning efficiency and minimizing raw material template loss. Furthermore, if only considering reducing the raw material template loss rate to determine the optimal template matching scheme, it may lead to excessively long cutting times for the intelligent cutting table saw. Therefore, this invention requires a relatively optimal template matching scheme that can balance the raw material template loss rate and the cutting time of the intelligent cutting table saw.

[0071] Specifically, the formwork matching analysis model can output multiple formwork matching schemes and their corresponding expected processing time and formwork loss rate. This invention further acquires on-site assessment data on the use of wooden formwork, mainly including the consumption rate of wooden formwork, expected remaining demand, assembly loss rate, and urgency description data added by manual labor. Based on this, the urgency level of wooden formwork use at the construction site can be calculated, such as relaxed, normal, slightly urgent, and urgent. Therefore, based on different urgency levels, the multiple formwork matching schemes determined above are screened, and the optimal formwork matching scheme with suitable loss rate and processing time is selected.

[0072] Optionally, the step of obtaining the assessment data on the use of wooden formwork at the construction site, and calculating the urgency level of the use of wooden formwork at the construction site based on the assessment data, includes:

[0073] u=k(α1q1+α2q2+α3q3+p) k-1

[0074] In the formula, u is the urgency parameter for the use of timber formwork, k is the difficulty value of transporting the timber formwork to the construction site; q1 is the normalized value of the consumption rate of timber formwork at the construction site, q2 is the normalized value of the expected remaining demand for timber formwork at the construction site, q3 is the normalized value of the assembly loss rate of timber formwork at the construction site, α1, α2, and α3 are the corresponding weighting coefficients; and p is the normalized transformation value of the artificially added urgency description data.

[0075] The urgency level of the wooden formwork is obtained by comparing it with the urgency parameter u according to the specified control relationship.

[0076] In this embodiment of the invention, the urgency level of the use of wooden formwork at the construction site is mainly related to parameters such as the real-time consumption rate of wooden formwork at the construction site, the expected remaining demand, the assembly loss rate, and the urgency description data added by humans. After normalizing these parameters and then performing weighted calculations, the corresponding urgency parameter of the use of wooden formwork can be obtained. By comparing the area range in which the urgency parameter of the use of wooden formwork falls, the urgency level of the use of wooden formwork at the construction site can be determined.

[0077] In order to more accurately calculate the urgency level of the use of wooden formwork at the construction site, this invention also considers the difficulty value of transporting the wooden formwork to the construction site, that is, the time spent on the transportation route, which is mainly based on the transportation efficiency of the transportation vehicle and the real-time road conditions on the transportation route, and will not be elaborated further.

[0078] Furthermore, semantic analysis of the manually added urgency description data can extract the assessment values ​​regarding the urgency of the wooden formwork input by on-site construction personnel. Normalizing these values ​​yields a normalized transformation value. Of course, if no manually added urgency description data is detected, p = 0 is set directly.

[0079] Optionally, the model matching analysis model is constructed and trained based on a deep learning algorithm;

[0080] The objective function used during training is as follows:

[0081]

[0082] In the formula, Q is the objective function, which represents the sum of the attractive and repulsive forces of the mold arrangement to be determined, k is the number of wooden templates, and d is the average distance between the centroids of each wooden template in the mold arrangement to be determined. It is a unit direction vector.

[0083] In this embodiment of the invention, the model matching analysis model is constructed based on a deep learning algorithm. The deep learning algorithm preferably uses a neural network algorithm, but it is more preferably an improved neural network algorithm, such as TensorFlow, PointNet++ neural network model, etc.

[0084] Furthermore, this invention uses the aforementioned objective function when performing deep training on the model matching analysis model. This objective function draws on the artificial potential field method in collision budgeting. This represents the gravitational value of the mold matching scheme to be determined. The sum of the repulsive forces of the matching scheme represents the sum of the forces. Since both are vectors, when the sum of the two, i.e. the objective function, exceeds the threshold, it means that the current matching scheme to be determined is the optimal prediction value. Therefore, the training of the matching analysis model can be terminated depending on the situation (e.g., exceeding the threshold n times in a row).

[0085] like Figure 2 As shown, this embodiment of the invention also discloses a BIM-based intelligent woodworking processing system, including a processing module, an intelligent cutting table saw, a robotic arm with suction cups, a packing machine, a transport robot, and a powerful suction device; wherein,

[0086] The processing module is used to model and calculate the construction drawings using BIM technology to obtain several three-dimensional models of the required wooden formwork. The three-dimensional models include the first dimension data and quantity of the wooden formwork. Based on the second dimension data of the raw wood planks, the first dimension data and quantity of the wooden formwork, the module uses a formwork matching analysis model to perform calculations and determine the optimal formwork matching scheme and generate a formwork matching diagram.

[0087] The intelligent cutting table saw is used to generate a processing plan based on the mold drawing obtained by the processing module, so as to cut the raw wood board.

[0088] The robotic arm with suction cups is used to feed the raw wood planks into the intelligent cutting table saw, and to number the semi-finished wood templates obtained after processing according to the template drawing and stack them according to different specifications.

[0089] The packing machine is used to pack the sorted and stacked semi-finished wooden templates.

[0090] The transport robot is used to transport the packaged semi-finished wooden templates to the construction site for construction workers to assemble on-site.

[0091] The powerful suction device is activated during the cutting operation of the intelligent table saw to absorb and collect sawdust generated during the cutting operation.

[0092] Based on the BIM-based intelligent woodworking system of this invention, a corresponding "low-loss, zero-dust" intelligent woodworking workshop can be constructed, as detailed below. Figure 3 As shown.

[0093] This invention also discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calling the executable program code stored in the memory to execute the method described in the foregoing embodiments.

[0094] This invention also discloses a computer storage medium storing a computer program, which is executed by a processor to perform the methods described in the foregoing embodiments.

[0095] This invention also discloses a computer program product, including a computer program stored on a non-transitory computer-readable medium, the computer program being executed by a processor as described in any of the preceding claims.

[0096] It should be noted that the storage module (102) in Embodiment 2, the memory in Embodiment 3, and the computer storage medium in Embodiment 4 can all be, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital multifunction optical disc (DVD) or other optical storage, magnetic tape, etc.

[0097] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0098] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0099] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0100] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A BIM-based intelligent woodworking processing method, characterized in that, Includes the following steps: Using BIM technology, the construction drawings are modeled and calculated to obtain several three-dimensional models of the required wooden formwork. The three-dimensional models include the first dimension data and quantity of the wooden formwork. Based on the second dimension data of the raw wood board, the first dimension data and quantity of the wood template, the template matching analysis model is used to perform calculations to determine the optimal template matching scheme and generate a template matching diagram. The mold drawing is input into the intelligent cutting table saw, which generates a processing plan based on the mold drawing to cut the raw wood board. The semi-finished wooden templates obtained after processing are numbered according to the template matching diagram and stacked according to different specifications; The categorized and stacked semi-finished wooden formwork is packaged using a packing machine and transported to the construction site using a transport robot for on-site assembly by construction workers. Based on the second dimension data of the raw material wood planks, the first dimension data and quantity of the wood templates, a template matching analysis model is used to calculate and determine the optimal template matching scheme, including: The second dimension data of the raw material wood board, the first dimension data of the wood template, and the quantity are input into the mold matching analysis model. The mold matching analysis model outputs several mold matching schemes and the corresponding expected processing time and mold matching loss rate. Obtain assessment data on the use of wooden formwork at the construction site, and calculate the urgency level of the use of wooden formwork at the construction site based on the assessment data. The optimal formwork arrangement is obtained by screening each formwork arrangement scheme according to the urgency level of the use of the wooden formwork. The process involves obtaining assessment data on the use of timber formwork at the construction site, and calculating the urgency level of timber formwork use at the construction site based on this assessment data, including: ； In the formula, Use the urgency parameter for the wooden formwork. This represents the difficulty level of transporting the wooden formwork to the construction site. This is the normalized value of the consumption rate of wooden formwork at the construction site. This is the normalized value of the expected remaining demand for wooden formwork at the construction site. This is the normalized value of the assembly loss rate of the wooden formwork at the construction site. , , These are the corresponding weighting coefficients; Normalized transformation values ​​for manually added urgency description data; Use the urgency parameter on the wooden template. The urgency level of the use of the wooden formwork at the construction site was obtained by performing a comparative process according to the specified control relationship. The model matching analysis model is constructed and trained based on a deep learning algorithm; the objective function used during training is as follows: ； In the formula, Let be the objective function, which represents the sum of the attractive and repulsive forces of the model matching scheme to be determined. For the quantity of wooden templates, This represents the average distance between the centroids of each wooden template in the template configuration scheme to be determined. It is a unit direction vector.

2. The BIM-based intelligent woodworking method according to claim 1, characterized in that: The intelligent cutting table saw cuts the raw wood board according to the processing plan, including: A robotic arm with suction cups adsorbs the raw wood board and feeds it into the intelligent cutting table saw, which then cuts the raw wood board according to the processing plan.

3. The BIM-based intelligent woodworking method according to claim 2, characterized in that: A powerful suction device is also installed above the intelligent cutting table saw. The powerful suction device is used to be turned on during the cutting operation of the intelligent cutting table to absorb and collect the sawdust generated during the cutting operation.

4. A BIM-based intelligent woodworking system, wherein the system is based on the method described in any one of claims 1-3, characterized in that: This includes a processing module, an intelligent cutting table saw, a robotic arm with suction cups, a packing machine, a transport robot, and a powerful suction device; among which, The processing module is used to model and calculate the construction drawings using BIM technology to obtain several three-dimensional models of the required wooden formwork. The three-dimensional models include the first dimension data and quantity of the wooden formwork. Based on the second dimension data of the raw wood planks, the first dimension data and quantity of the wooden formwork, the module uses a formwork matching analysis model to perform calculations and determine the optimal formwork matching scheme and generate a formwork matching diagram. The intelligent cutting table saw is used to generate a processing plan based on the mold drawing obtained by the processing module, so as to cut the raw wood board. The robotic arm with suction cups is used to feed the raw wood planks into the intelligent cutting table saw, and to number the semi-finished wood templates obtained after processing according to the template drawing and stack them according to different specifications. The packing machine is used to pack the sorted and stacked semi-finished wooden templates. The transport robot is used to transport the packaged semi-finished wooden templates to the construction site for construction workers to assemble on-site. The powerful suction device is activated during the cutting operation of the intelligent table saw to absorb and collect sawdust generated during the cutting operation.

5. An electronic device, comprising: Memory containing executable program code; A processor coupled to the memory; characterized in that: the processor calls the executable program code stored in the memory to perform the method as described in any one of claims 1-3.

6. A computer storage medium storing a computer program, characterized in that: The computer program is executed by the processor to perform the method as described in any one of claims 1-3.

7. A computer program product comprising a computer program stored on a non-transitory computer-readable medium, characterized in that: When the computer program is executed by a processor, it implements the method as described in any one of claims 1-3.

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