Automatic furniture unloading and punching control method and system

Abstract

The application discloses a furniture automatic blanking and punching control method and system, and relates to the field of industrial automation control. The furniture automatic blanking and punching control method comprises the following steps: an order analysis module analyzes order data, a three-dimensional modeling module communicates with the order analysis module, a corresponding three-dimensional furniture model is automatically generated or called based on the order data, and all plate information needing to be blanked and punched is disassembled; the plate information is input into a plate optimization layout module, a layout scheme with the highest material utilization rate is automatically generated according to the specifications of the stock plates; a central control unit controls a material transmission module to transport the plates to a blanking device; and a blanking control module loads an NC program to control the blanking device to complete the accurate cutting of all plates. The application automatically analyzes order data through the order analysis module, realizes parameterized modeling in combination with the three-dimensional modeling module, reduces manual intervention, avoids information extraction errors, and improves the accuracy and efficiency of plate information generation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial automation control, in particular to a furniture automatic blanking and punching control method and system. BACKGROUND

[0002] In the furniture manufacturing process, blanking and punching are key links that affect product quality and production efficiency. In traditional furniture production, order analysis relies on manual identification of drawing information, which is prone to errors in plate parameter extraction due to human error; three-dimensional modeling requires manual drawing, which is inefficient and difficult to ensure model consistency; plate layout relies on experience, resulting in low material utilization and waste of raw materials; positioning in the blanking and punching process relies on mechanical references, which is affected by plate deformation, clamping errors, etc., and is prone to hole deviation, making subsequent assembly difficult; there is a lack of coordinated control between the links, the production process is not coherent, and the overall production efficiency is not high.

[0003] With the growth of furniture customization demand, traditional production methods have been difficult to meet the production requirements of high precision, high efficiency and high material utilization, and an automatic and intelligent blanking and punching control method and system are urgently needed. SUMMARY

[0004] To solve the above technical problems, the present application provides a furniture automatic blanking and punching control method and system. The following technical solutions are adopted:

[0005] The furniture automatic blanking and punching control method comprises the following steps:

[0006] Step 1, the order analysis module analyzes the order data, the three-dimensional modeling module communicates with the order analysis module, and automatically generates or calls the corresponding three-dimensional furniture model based on the order data, and disassembles all the plate information that needs to be blanked and punched;

[0007] Step 2, input the plate information into the plate optimization layout module, automatically generate the layout scheme with the highest material utilization rate according to the inventory plate specifications;

[0008] Step 3, the central control unit controls the material transfer module to transport the plate to the blanking equipment;

[0009] Step 4, the blanking control module loads the NC program to control the blanking equipment to complete the accurate cutting of all plates;

[0010] Step 5, the central control unit controls the material transfer module to transport the cut plate to the punching station and complete the clamping positioning;

[0011] Step 6, the machine vision positioning detection module takes a picture of the plate, the image processing algorithm identifies the key reference points or contours of the plate, calculates the translation and rotation deviation of the plate relative to the theoretical position, and sends the deviation value to the punching control module;

[0012] Step 7, the hole control module fuses the received theoretical hole coordinate of the layout scheme with the visual compensation data to generate corrected actual processing coordinates;

[0013] Step 8, the hole control module controls the hole processing equipment to complete the processing of all hole positions according to the corrected path.

[0014] Optionally, in step 1, the order data includes furniture model, board quantity, size parameter, material type and processing drawing data, the order analysis module analyzes the order data by combining OCR tool and JSON format analysis tool to generate structured board list data and corresponding to-be-processed hole distribution data.

[0015] Optionally, in step 1, the three-dimensional modeling module generates a three-dimensional furniture model based on a parameterized modeling technique, including the following specific steps:

[0016] Step 11, calling a pre-stored board feature library, automatically matching the board connection relationship according to the order analysis result;

[0017] Step 12, generating three-dimensional features of hole positions and slot positions through Boolean operation;

[0018] Step 13, the finally output board information includes: board ID, material parameter, three-dimensional size, hole theoretical coordinate set and hole diameter.

[0019] Optionally, in step 2, the layout scheme generation of the board optimization layout module includes the following constraint conditions:

[0020] Stock board specification limit: length ≤ L_max, width ≤ W_max;

[0021] Board direction constraint: the texture direction is parallel to the long side;

[0022] Cutting allowance constraint: the distance between adjacent boards is greater than or equal to 2mm;

[0023] When generating the layout scheme, output: cutting path length S, board coordinate offset on the board and board utilization rate η.

[0024] Optionally, the improved genetic algorithm is used for board optimization layout, the objective function is to maximize the material utilization rate, and the formula of the objective function is:

[0025] ;

[0026] Wherein, is the area of the jth board, , and Lj and Wj are the length and width of the jth sheet respectively; M is the total number of sheets, and K is the total number of sheets in stock, is the area of a single sheet in stock.

[0027] Optionally, in step 4, the NC program loaded by the blanking control module is automatically generated through the nesting scheme, and contains core G code instructions: G01 linear cutting instructions and tool radius compensation instructions.

[0028] Optionally, in step 6, the image processing algorithm of the machine vision positioning detection module includes the following steps:

[0029] Step 61, Gaussian filtering is used to remove noise;

[0030] Step 62, the edge of the sheet is extracted by the Canny operator;

[0031] Step 63, match the preset corner feature to obtain the actual reference point coordinate set;

[0032] The method for calculating the translation and rotation deviation relative to the theoretical position is:

[0033] Let the coordinates of the theoretical reference point in the image coordinate system be , the pixel coordinates of the actual reference point be , and the parameters be transformed by the following formula:

[0034] ;

[0035] ;

[0036] ;

[0037] Wherein, m is the number of reference points, is the rotation deviation in radians, and are the translation deviations.

[0038] Optionally, in step 7, the corrected actual machining coordinates ;

[0039] ;

[0040] ;

[0041] Wherein, is the coordinate of the theoretical hole position in the local coordinate system of the sheet; is the rotation deviation in radians calculated in step 6; k is the pixel physical size conversion coefficient; is the coordinate system origin offset of the sheet at the punching station.

[0042] The furniture automatic blanking and punching control system is used for realizing the method, and the system comprises a central control unit, an order analysis module, a three-dimensional modeling module, a plate optimization layout module, a blanking control module, a machine vision positioning detection module, a material conveying module, a punching control module, a blanking device and a punching device.

[0043] The central control unit is in communication connection with each module respectively, and is used for sending control instructions and receiving state feedback data of each module.

[0044] The order analysis module is in communication connection with the three-dimensional modeling module, and transmits the analyzed structured order data to the three-dimensional modeling module.

[0045] The three-dimensional modeling module is in communication connection with the plate optimization layout module, and transmits the generated plate three-dimensional information to the plate optimization layout module.

[0046] The plate optimization layout module is in communication connection with the blanking control module, and transmits the layout scheme to the blanking control module.

[0047] The blanking control module is in communication connection with the blanking device, and sends the cutting control instructions to the blanking device according to the generated NC program.

[0048] The material conveying module is in communication connection with the blanking device respectively, the material conveying module receives the scheduling instructions of the central control unit, and completes the transfer of the plate from the raw material area to the blanking device and from the blanking device to the punching station.

[0049] The machine vision positioning detection module is in communication connection with the punching control module, and transmits the calculated plate translation deviation and rotation deviation to the punching control module.

[0050] The punching control module is in communication connection with the punching device, and sends the multi-axis motion instructions to the punching device according to the corrected actual machining coordinates.

[0051] Optionally, the order analysis module, the three-dimensional modeling module and the plate optimization layout module are realized based on a computer.

[0052] In summary, the present application comprises at least one of the following beneficial technical effects:

[0053] The present application can provide a furniture automatic blanking and punching control method and system, through the order analysis module, the order data is automatically analyzed, the three-dimensional modeling module is combined to realize parameterized modeling, manual intervention is reduced, information extraction errors are avoided, and the accuracy and efficiency of plate information generation are improved.

[0054] The improved genetic algorithm is used for plate optimization layout, the material utilization rate is maximized as the target, raw material waste is reduced, and production cost is reduced.

[0055] The machine vision positioning detection module identifies the plate reference feature through an image processing algorithm, calculates the position deviation and is used for punching coordinate correction, effectively compensates for clamping error and plate deformation influence, improves hole position machining precision, and guarantees subsequent assembly quality.

[0056] The central control unit coordinates the collaborative work of each module and device, realizes the automatic flow of order analysis, modeling, layout to blanking and punching, reduces the process connection time, and improves the overall production efficiency and stability of the production process. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 is the schematic diagram of the architecture principle of the furniture automatic blanking and punching control system of the present application;

[0058] Figure 2 is the flowchart of the furniture automatic blanking and punching control method of the present application. DETAILED DESCRIPTION

[0059] The present application will be further described in detail below in combination with the drawings.

[0060] The embodiment of the present application discloses a furniture automatic blanking and punching control method and system.

[0061] Referring to Figure 1 and Figure 2 , embodiment 1, the furniture automatic blanking and punching control method comprises the following steps:

[0062] Step 1, the order analysis module 2 analyzes order data, the three-dimensional modeling module 3 communicates with the order analysis module 2, automatically generates or calls the corresponding three-dimensional furniture model based on the order data, and disassembles all plate information that needs to be blanked and punched;

[0063] Step 2, input the plate information into the plate optimization layout module 4, automatically generate the layout scheme with the highest material utilization rate according to the inventory plate specifications;

[0064] Step 3, the central control unit 1 controls the material conveying module 7 to transport the plate to the blanking equipment 100;

[0065] Step 4, the blanking control module 5 loads the NC program, controls the blanking equipment 100 to complete the accurate cutting of all plates;

[0066] Step 5, the central control unit 1 controls the material conveying module 7 to transport the cut plate to the punching station and completes the clamping and positioning;

[0067] Step 6, the machine vision positioning detection module 6 takes a picture of the plate, the image processing algorithm identifies the key reference point or contour of the plate, calculates the translation and rotation deviation of the plate relative to the theoretical position, and sends the deviation value to the punching control module 8;

[0068] Step 7, the punching control module 8 fuses the received theoretical hole coordinate of the layout scheme with the visual compensation data to generate corrected actual processing coordinates;

[0069] Step 8, the punching control module 8 controls the punching device 101 to complete the processing of all hole positions according to the corrected path.

[0070] In Example 2, Step 1, the order data includes furniture model, board quantity, size parameter, material type, and processing drawing data. The order analysis module 2 analyzes the order data by combining OCR tools and JSON format analysis tools to generate structured board list data and corresponding to-be-processed hole distribution data.

[0071] By adopting the above technical solutions, full-process automation is realized through modular collaborative work. The central control unit 1 serves as the core scheduling center and coordinates the operation of various modules and devices. Starting from order data, board processing information is obtained through analysis and three-dimensional modeling, and material utilization efficiency is improved through optimized layout. The program generated according to the layout scheme is used to realize accurate cutting in the cutting link. After the cut board is transported to the punching station, machine vision technology calculates the position deviation by recognizing the reference features to provide compensation basis for the punching coordinates. Finally, the punching device completes the processing according to the corrected coordinates to form a closed-loop control from order to finished product, reducing manual intervention and improving processing precision and efficiency.

[0072] In Step 1, order analysis processes diversified order data through multiple tools. Order data contains furniture model, size, and other information in various forms, including structured data and non-structured information such as processing drawings. OCR tools are used to identify graphic and text information in processing drawings and extract key parameters such as size and hole position. JSON format analysis tools are used to process structured data and extract board quantity, material, and other standard information. The combination of the two can comprehensively and accurately convert raw order data into standardized structured board list and hole distribution data, providing uniform and reliable basic information for subsequent three-dimensional modeling and processing, avoiding errors and low efficiency of manual analysis.

[0073] In Example 3, Step 1, the three-dimensional modeling module 3 generates a three-dimensional furniture model based on parametric modeling technology, including the following specific steps:

[0074] Step 11, call the pre-stored board feature library and automatically match the board connection relationship according to the order analysis result;

[0075] Step 12, generate three-dimensional features of holes and slots through Boolean operation;

[0076] Step 13, the finally output board information includes: board ID, material parameter, three-dimensional size, hole theoretical coordinate set, and hole diameter.

[0077] By adopting the above technical solution, the principle of the three-dimensional modeling module 3 generating a three-dimensional furniture model based on the parameterized modeling technology is to realize rapid construction and accurate output of the model through a standardized process. In step 11, the pre-stored plate feature library contains the standard parameters and feature information of various basic plates, and calling the library can avoid repeated modeling, and combining the plate type and connection requirements in the order analysis result, the connection relationship between the plates can be automatically matched to ensure that the model structure conforms to the assembly logic. In step 12, Boolean operations are used to accurately generate three-dimensional features such as holes and grooves on the basic plate model through set difference, intersection and other operations, so that the model details are consistent with the actual processing requirements. The plate information output in step 13 covers the key parameters required in the whole processing process, providing a unified and accurate data basis for subsequent nesting, cutting, punching and other links, realizing accurate connection from three-dimensional model to actual processing, and improving modeling efficiency and model reliability.

[0078] In step 2 of embodiment 4, the nesting scheme generated by the plate optimization nesting module 4 includes the following constraint conditions:

[0079] Stock plate size restrictions: length ≤ L_max, width ≤ W_max;

[0080] Plate direction constraints: the grain direction is parallel to the long side;

[0081] Cutting allowance constraints: the distance between adjacent plates ≥ 2mm;

[0082] When generating the nesting scheme, output the cutting path length S, the coordinate offset of the plate on the plate, and the plate utilization rate η.

[0083] In embodiment 5, the plate optimization nesting adopts an improved genetic algorithm, and the objective function is to maximize the material utilization rate, and the formula of the objective function is:

[0084] ;

[0085] Wherein, is the area of the jth plate, , and are the length and width of the jth plate, respectively; M is the total number of plates, and K is the number of all stock plates, is the area of a single stock plate.

[0086] By adopting the above technical solution, the core of the plate optimization nesting module 4 generating the nesting scheme is to ensure the feasibility and practicality of the scheme through multi-dimensional constraint conditions, and output key parameters to support subsequent processing links.

[0087] The inventory board specification limit defines the layout boundary from the basis, ensures that all board layouts are within the length and width range of a single inventory board, and avoids exceeding the actual material size to cause the scheme to be unable to be executed. The board direction constraint is set according to the physical characteristics and use requirements of the furniture board. The texture direction is parallel to the long side to ensure the structural strength of the finished board, and at the same time meets the conventional requirements of furniture appearance design. The cutting allowance constraint reserves the necessary space for actual cutting operation, avoids damage to adjacent boards due to overlapping of tool paths or too small spacing during cutting, and ensures cutting accuracy and board integrity. The cutting path length, board coordinate offset and board utilization rate output when generating the layout scheme provide direct data support for planning the cutting trajectory of the cutting equipment, positioning the board position and evaluating the economic efficiency of the scheme, and realize the accurate connection of the layout scheme and subsequent cutting processing.

[0088] The improved genetic algorithm is used for board optimization layout. The core is to maximize the material utilization rate under the premise of meeting the constraint conditions through intelligent optimization algorithm. The improved genetic algorithm is based on the selection, crossover and mutation mechanism of biological evolution. For the combination optimization problem of board layout, the optimal layout is obtained through iteration: first, generate an initial layout scheme population in a random way, then calculate the fitness of each scheme with the material utilization rate as the core evaluation index (i.e. objective function); through selection operation, keep the schemes with high fitness, through crossover operation, integrate the advantages of different schemes, through mutation operation, avoid falling into local optimum, and gradually iterate to obtain the layout scheme with the highest utilization rate.

[0089] The objective function quantifies the material utilization efficiency by calculating the ratio of the total area of all boards to be processed to the total area of the inventory boards used. Its formula logic clearly reflects the relationship between "total board demand" and "total material consumption", ensuring that the algorithm optimization direction is consistent with the production goals of reducing material waste and controlling production cost. At the same time, the improved algorithm can improve the convergence speed and optimization accuracy, and balance the layout efficiency and scheme quality.

[0090] In Example 6, Step 4, the NC program loaded by the cutting control module 5 is automatically generated by the layout scheme, which includes core G code instructions: G01 straight cutting instruction and tool radius compensation instruction.

[0091] By adopting the above technical scheme, the core principle of the cutting control module 5 is to realize the precise docking of the layout scheme and the cutting equipment through the automatically generated NC program, and to ensure the cutting accuracy. The layout scheme contains key information such as board coordinates on the board and cutting path. The cutting control module automatically generates the NC program based on this information, without the need for manual programming, reducing human error and improving efficiency.

[0092] G01 straight line cutting instruction is used to control the cutter of the blanking equipment to move along a straight line trajectory. By setting the coordinate parameters and the feed speed, the cutter can be ensured to cut accurately along the path planned in the layout scheme, ensuring the straightness and size accuracy of the plate edge.

[0093] Cutter radius compensation instruction is used to correct the influence of the cutter's own radius on the cutting size. Since the cutter has an inherent radius, if not compensated, the actual cutting size of the plate will deviate from the theoretical size. This instruction automatically offsets the cutter trajectory by a corresponding distance by pre-setting the compensation value, ensuring that the final cutting size of the plate meets the theoretical requirements of the layout scheme.

[0094] The combination of the three achieves the automatic conversion from the layout scheme to the actual cutting, ensuring the accuracy and efficiency of the blanking process.

[0095] In step 6 of embodiment 7, the image processing algorithm of the machine vision positioning detection module 6 includes the following steps:

[0096] Step 61: Gaussian filtering is used to remove noise;

[0097] Step 62: The plate edge is extracted by Canny operator;

[0098] Step 63: The actual reference point coordinate set is obtained by matching the pre-set corner features;

[0099] The method for calculating the translation and rotation deviation relative to the theoretical position is:

[0100] Let the coordinates of the theoretical reference point in the image coordinate system be , the actual reference point pixel coordinates be , and the transformation parameters be:

[0101] ;

[0102] ;

[0103] ;

[0104] Where m is the number of reference points, is the rotation deviation in radians, and are the translation deviations.

[0105] In step 7 of embodiment 8, the corrected actual machining coordinates are ;

[0106] ;

[0107] ;

[0108] wherein, is the coordinate of the theoretical hole position in the local coordinate system of the plate member; is the rotation deviation radian calculated in step 6; k is the conversion coefficient of the physical size of pixels; is the coordinate system origin offset of the plate member at the punching station.

[0109] By adopting the above technical scheme, the machine vision positioning and detection module 6 realizes accurate acquisition of the deviation of the actual position of the plate member from the theoretical position through step-by-step image processing and mathematical calculation, and provides data support for punching compensation.

[0110] Step 61 adopts Gaussian filtering, uses the smoothing property of the Gaussian function to process the photographed plate member image, weakens random noise interference in the image, avoids errors in subsequent feature recognition caused by noise, and ensures the clarity of the plate member contour and reference point information in the image.

[0111] Step 62 extracts the edge of the plate member through the Canny operator, which can accurately identify the edge pixels of the plate member contour through gradient calculation and double-threshold judgment, and clearly define the approximate range and shape of the plate member in the image, laying a foundation for subsequent reference point positioning.

[0112] Step 63 matches the preset corner point features. The corner point is a key position with obvious recognition degree in the plate member contour. By comparing with the pre-stored corner point feature template, the pixel coordinate set of the actual reference point of the plate member can be determined.

[0113] The deviation calculation link is based on the coordinate difference between the theoretical and actual reference points, and a coordinate transformation relationship is constructed through a mathematical formula: the rotation deviation formula uses the intersection operation of the theoretical and actual reference point coordinates to solve the angle of rotation of the plate member around the origin; the translation deviation formula eliminates the influence of individual reference point errors through averaging calculation, and obtains the overall offset of the plate member in the horizontal and vertical directions in the image coordinate system. The participation of multiple reference points can improve the stability and accuracy of the deviation calculation, ensuring that the rotation and translation deviations obtained finally can truly reflect the actual position offset of the plate member.

[0114] The correction of the machining coordinates in step 7 is the core of converting the position deviation obtained by machine vision detection into coordinate adjustment of actual machining dimensions, ensuring that the punching position matches the actual position of the plate. First, the theoretical hole position coordinates are set based on the ideal position of the plate. When the plate has a rotational deviation, the theoretical coordinates need to be rotated by trigonometric functions (cosθ, sinθ) to correct the angle deviation of the hole position caused by the rotation of the plate, so that the hole position direction is consistent with the actual placement direction of the plate. Second, the translation deviation obtained by machine vision detection is pixel dimension data, which needs to be converted into actual physical size deviation by the pixel physical size conversion coefficient k, to realize the unification of image coordinates and machining physical coordinates. Finally, the plate has a fixed coordinate system origin at the punching station, which needs to add the origin offset x0, y0 to map the corrected hole position coordinates to the actual working coordinate system of the punching equipment, to ensure that the punching equipment can accurately position the target hole position on the plate. The three work together to convert the theoretical coordinates into machining coordinates that match the actual position of the plate, completely compensate for the positioning deviation caused by clamping errors, plate deformation and other factors, and ensure punching accuracy.

[0115] Example 9, an automatic unloading and punching control system for furniture, for implementing the method, the system includes a central control unit 1, an order analysis module 2, a three-dimensional modeling module 3, a plate optimization layout module 4, a unloading control module 5, a machine vision positioning detection module 6, a material transfer module 7, a punching control module 8, a unloading device 100 and a punching device 101;

[0116] The central control unit 1 is in communication with each module respectively, for sending control instructions and receiving state feedback data of each module;

[0117] The order analysis module 2 is in communication with the three-dimensional modeling module 3, and transmits the analyzed structured order data to the three-dimensional modeling module 3;

[0118] The three-dimensional modeling module 3 is in communication with the plate optimization layout module 4, and transmits the generated plate three-dimensional information to the plate optimization layout module 4;

[0119] The plate optimization layout module 4 is in communication with the unloading control module 5, and transmits the layout scheme to the unloading control module 5;

[0120] The unloading control module 5 is in communication with the unloading device 100, and sends cutting control instructions to the unloading device 100 according to the generated NC program;

[0121] The material transfer module 7 is in communication with the unloading device 100 respectively, and the material transfer module 7 receives the scheduling instructions of the central control unit 1, and completes the transfer of the plate from the raw material area to the unloading device 100, and then from the unloading device 100 to the punching station;

[0122] The machine vision positioning detection module 6 is in communication connection with the punching control module 8, and transmits the calculated plate translation deviation and rotation deviation to the punching control module 8;

[0123] The punching control module 8 is in communication connection with the punching device 101, and sends multi-axis motion instructions to the punching device 101 according to the corrected actual machining coordinates.

[0124] In the embodiment 10, the order analysis module 2, the three-dimensional modeling module 3 and the plate optimization layout module 4 are realized based on computers.

[0125] By adopting the above technical solutions, the furniture automatic blanking and punching control system realizes automatic and precise control of the whole process through the modular architecture and clear communication connection. The central control unit 1 as the core of the system, through the communication connection with each module, sends control instructions and receives state feedback, ensures that each link runs synchronously according to the preset process, and avoids process disconnection or conflict.

[0126] The communication connection between the order analysis module 2 and the three-dimensional modeling module 3 realizes the direct transmission of the analyzed standardized order data to the modeling link, provides accurate basic information for three-dimensional model generation; the communication between the three-dimensional modeling module and the plate optimization layout module converts the three-dimensional information of the plate into the parameters required by the layout, ensures that the layout scheme is consistent with the actual plate requirement; the connection between the plate optimization layout module 4 and the blanking control module 5 makes the optimal layout scheme directly converted into the basis for blanking control, avoiding data processing error.

[0127] The communication between the blanking control module 5 and the blanking device converts the generated NC program into executable cutting instructions of the device, realizes the landing of the layout scheme to actual cutting; the material transportation module 7 cooperates with the blanking device 100 under the scheduling of the central control unit 1, completes the plate transportation according to the process rhythm, and ensures that the raw material supply matches the processing progress; the communication between the machine vision positioning detection module 6 and the punching control module 8 realizes real-time transmission of the plate position deviation data, and provides the basis for punching coordinate correction; the connection between the punching control module 8 and the punching device 101 converts the corrected machining coordinates into multi-axis motion instructions, and finally realizes precise punching.

[0128] The whole system forms a closed-loop control from order to machining through the orderly communication between each module and device, and guarantees the efficiency and precision of automatic production.

[0129] The order analysis module 2, the three-dimensional modeling module 3 and the plate optimization layout module 4 are realized based on computers, and the core is to utilize the computing and storage capacity of computers and software running environment to support the efficient implementation of each module function.

[0130] The computer's data processing capabilities enable it to quickly run OCR tools and JSON parsing tools, accurately analyze structured and unstructured data in orders, and generate standardized panel lists. Its graphics processing and parametric modeling software capabilities can call pre-stored panel feature libraries and quickly build 3D furniture models through algorithms such as Boolean operations, while ensuring the accuracy of model details.

[0131] Furthermore, the computer's computing power supports complex iterative calculations using improved genetic algorithms, enabling the rapid completion of optimized sheet metal layout under multiple constraints and the output of the optimal solution. The computer's storage capacity can save crucial information such as order data model parameters and layout schemes, facilitating subsequent retrieval and data traceability. Using the computer as a carrier, the three modules can achieve rapid data transmission and processing, avoiding the inefficiency and errors of manual operation. Simultaneously, it provides a stable operating environment for collaborative work between modules, ensuring the efficiency and reliability of the entire system's front-end data processing, laying a solid foundation for subsequent material cutting and drilling processes.

[0132] The following specific embodiments illustrate the implementation principle of the present invention:

[0133] Taking a custom furniture factory's order for "modern minimalist desks" as an example, the order requires the production of 10 desks, each containing 8 pieces of board, including the desktop, side panels, and drawer fronts, using "E1 grade particleboard" material. This technical solution enables automatic material cutting and drilling.

[0134] System implementation configuration:

[0135] The components of the automatic furniture feeding and drilling control system are connected as follows: The central control unit 1 (PLCS7-1200) establishes bidirectional communication with the order parsing module 2 and the board optimization and layout module 4 via Profinet industrial Ethernet;

[0136] Order parsing module 2 and 3D modeling module 3 transmit structured data via TCP / IP protocol;

[0137] 3D modeling module 3 and sheet metal optimization layout module 4 interact by sharing a database to exchange 3D information of the sheet metal parts;

[0138] The board optimization layout module 4 and the material cutting control module 5 transmit the layout plan through the OPCUA protocol;

[0139] The material feeding control module 5 and the material feeding device 100 send cutting commands via RS485 serial port;

[0140] The material transfer module 7 receives the scheduling instructions from the central control unit 1;

[0141] The machine vision positioning and detection module 6 and the drilling control module 8 transmit deviation data;

[0142] The punching control module 8 sends motion instructions to the punching device 101 through the EtherCAT protocol.

[0143] The order analysis module 2, the three-dimensional modeling module 3, and the plate optimization layout module 4 are implemented based on an industrial computer (configured with an Inteli7-12700K processor, 16 GB DDR4 memory, and a 1 TB SSD hard disk) and run a Windows 10 IoT Enterprise system.

[0144] The three-dimensional modeling module 3 is equipped with AutoCAD Plant 3D software to call the plate feature library, and the plate optimization layout module 4 runs MATLAB R2023a to implement improved genetic algorithm calculation, ensuring that the layout optimization time is less than 3 minutes.

[0145] The specific process is as follows:

[0146] Order analysis and three-dimensional modeling:

[0147] The order data includes a modern minimalist desk (model SY-2025), 80 plate pieces (10 sets x 8 pieces / set), a desktop size of 1200 mm x 600 mm x 18 mm, a side plate size of 750 mm x 600 mm x 18 mm, and E1 grade particle board as the material, as well as a CAD format processing drawing.

[0148] The order analysis module 2 is equipped with Tesseract OCR tools and FastJSON analysis libraries. First, it identifies the drawer panel hole size (diameter 5 mm) and side plate mounting hole coordinates in the CAD drawing through OCR, and then extracts the plate quantity and material parameters in the order using the JSON analysis tool to generate a structured plate list. The list includes information such as the desktop plate ID B001, hole theoretical coordinate set (200, 300, 9), (800, 300, 9), etc.

[0149] The three-dimensional modeling module 3 calls the pre-stored 18 mm thick particle board feature library (including edge sealing parameters), automatically matches the mortise and tenon connection relationship of the desktop and side plate according to the list, generates a three-dimensional feature of a diameter of 5 mm and a depth of 10 mm mounting hole on the side plate model through Boolean operation (set difference operation), and finally outputs plate information including B001 desktop plate, E1 grade particle board, 1200 x 600 x 18 mm, hole coordinate (200, 300, 9), and diameter 5 mm.

[0150] Plate optimization layout:

[0151] The stock board specifications are length ≤2440mm, width ≤1220mm (standard 4x8 feet board), the board optimization layout module 4 uses the improved genetic algorithm (population size 50, crossover probability 0.8, mutation probability 0.05) to layout the board according to the constraint condition that the board texture direction is parallel to the long side and the spacing between adjacent boards is greater than or equal to 2mm.

[0152] The target function calculates that the total area of 80 boards is about 36㎡, 4 stock boards are used (the area of each board is about 2.98㎡, and the total area of 4 boards is about 11.92㎡), the material utilization rate η is about 92%, and the output layout scheme includes a cutting path length S=150m and a coordinate offset of the desktop board on the stock board (50mm, 50mm).

[0153] Material transportation and preparation:

[0154] The central control unit 1 sends a scheduling instruction to the material transportation module 7, and the AGV transports the stock board from the raw material area shelf (No. A03) to the cutting equipment 100. After cutting is completed, the AGV transports the B001 desktop board and other cut parts to the punching station (No. D02), and the pneumatic clamping device completes clamping and positioning.

[0155] Cutting and preparation:

[0156] The cutting control module 5 automatically generates an NC program according to the layout scheme, including the core G code instructions "G01X50Y50F2000 (straight line cutting to coordinates (50, 50), feed speed 2000mm / min)" and "G41D3 (tool radius compensation, compensation value 3mm, tool is a 6mm diameter alloy saw blade)". After the cutting equipment 100 loads the program, it cuts out a "1200x600mm desktop board" according to the path.

[0157] Machine vision positioning detection:

[0158] The machine vision positioning detection module 6 (including a 20 million pixel industrial camera (model Basler acA2500-14uc) and a ring LED light source) takes a photo of the clamped desktop board. The image processing algorithm first performs Gaussian filtering (σ=8 pixels) to remove image noise, then extracts the board edge through the Canny operator (threshold T1=50, T2=150), and finally matches the preset desktop board four right-angled vertex corner features to obtain the actual reference point coordinate set "(102, 98), (1198, 99), (101, 597), (1199, 598)" (pixel coordinates). Compared with the theoretical reference point coordinates, the rotation deviation θ is calculated to be 0.3°, and the translation deviation Δx and Δy are calculated to be 2 pixels and 1 pixel, respectively.

[0159] Punching coordinate correction and processing:

[0160] After the deviation data is acquired by the punching control module 8, the corrected actual machining coordinates are generated according to the formula: the known pixel physical size conversion coefficient k = 0.05 mm / pixel, the punching station coordinate system origin offset amount (x0 = 100 mm, y0 = 100 mm), and the theoretical hole position (200, 300) is corrected to be “x´´≈300.2 mm, y´´=≈400.1 mm”. The punching control module 8 sends multi-axis motion instructions to the punching equipment 101 (“four-axis numerical control drilling machine (model Z3050)”), and the drilling machine completes the hole position machining in turn according to the corrected coordinates with a “feed speed of 1500 mm / min and a punching depth of 10 mm”.

[0161] Through the embodiment, the unloading and punching process of 10 sets of desks is shortened from 8 hours of traditional manual operation to 2.5 hours, the material utilization rate is improved from 75% to 92%, and the hole position machining qualified rate is improved from 92% to 99.5%, verifying the high efficiency and precision of the technical scheme.

[0162] The above are preferred embodiments of the present application, but do not limit the protection scope of the present application, therefore: any equivalent changes made according to the structure, shape, principle of the present application should be covered within the protection scope of the present application.

Claims

1. A furniture automatic unloading and punching control method, characterized in that, The method comprises the following steps: Step 1, the order analysis module (2) analyzes the order data, and the three-dimensional modeling module (3) automatically generates or calls corresponding three-dimensional furniture models based on the order data to disassemble all the plate information required for cutting and punching; Step 2, input the plate information into the plate optimization layout module (4), and automatically generate a layout scheme with the highest material utilization rate according to the inventory plate specifications; Step 3, the central control unit (1) controls the material transfer module (7) to transport the plate to the cutting equipment (100); Step 4, the cutting control module (5) loads the NC program to control the cutting equipment (100) to complete the accurate cutting of all plates; Step 5, the central control unit (1) controls the material transfer module (7) to transport the cut plates to the punching station and complete the clamping positioning; Step 6, the machine vision positioning detection module (6) takes a picture of the plate, the image processing algorithm identifies the key reference points or contours of the plate, calculates the translation and rotation deviation of the plate relative to the theoretical position, and sends the deviation value to the punching control module (8); Step 7, the punching control module (8) fuses the theoretical hole coordinates of the layout scheme with the visual compensation data to generate corrected actual processing coordinates; Step 8, the punching control module (8) controls the punching equipment (101) to complete the processing of all hole positions according to the corrected path; In step 1, the order data includes furniture model, plate quantity, size parameter, material type and processing drawing data, the order analysis module (2) analyzes the order data by combining OCR tool and JSON format analysis tool to generate structured plate list data and corresponding to-be-processed hole distribution data; In step 1, the three-dimensional modeling module (3) generates a three-dimensional furniture model based on parameterized modeling technology, which comprises the following specific steps: Step 11, call the pre-stored plate feature library to automatically match the plate connection relationship according to the order analysis result; Step 12, generate three-dimensional features of holes and grooves through Boolean operation; Step 13, the finally output plate information includes plate ID, material parameter, three-dimensional size, hole theoretical coordinate set and hole diameter.

2. The furniture automatic cutting and punching control method according to claim 1, wherein: In step 2, the layout scheme generated by the plate optimization layout module (4) comprises the following constraint conditions: Inventory plate specification limit: length ≤ L_max, width ≤ W_max; Plate direction constraint: the texture direction is parallel to the long side; Cutting allowance constraint: the distance between adjacent plates is ≥2mm; When generating the layout scheme, output: cutting path length S, plate coordinate offset on the plate and plate utilization rate η.

3. The furniture automatic unloading and punching control method according to claim 2, characterized in that: The plate optimization layout adopts an improved genetic algorithm, and the objective function is to maximize the material utilization rate, and the formula of the objective function is: ； wherein, is the area of the jth sheet, , and are the length and width of the jth sheet, respectively; M is the total number of sheets, and K is the total number of sheets in stock, is the area of a single sheet in stock.

4. The furniture automatic unloading and punching control method according to claim 3, characterized in that: In step 4, the NC program loaded by the cutting control module (5) is automatically generated through the layout scheme, and contains core G code instructions: straight line cutting instruction and tool radius compensation instruction.

5. The furniture automatic unloading and punching control method according to claim 4, characterized in that: In step 6, the image processing algorithm of the machine vision positioning detection module (6) comprises the following steps: Step 61, Gaussian filtering is used to remove noise; Step 62, extracting the edge of the plate by Canny operator; Step 63, matching the preset corner feature to obtain the actual reference point coordinate set; The method for calculating the translation and rotation deviation relative to the theoretical position is: Let the coordinates of the theoretical reference point in the image coordinate system be , and the actual reference point pixel coordinates be , the transformation parameters are transformed by the following formula: ； ； ； wherein m is the number of reference points, is the rotational deviation in radians, and is the translational deviation.

6. The furniture automatic unloading and punching control method according to claim 5, characterized in that: In step 7, the revised actual machining coordinates ; ； ； wherein, is the coordinate of the theoretical hole in the local coordinate system of the plate member; is the rotation deviation in radians calculated in step 6; k is the conversion coefficient of the physical size of the pixel; is the coordinate system origin offset of the plate member at the punching station.

7. An automatic furniture unloading and punching control system, characterized in that: The system for implementing the method of claim 6 comprises a central control unit (1), an order analysis module (2), a three-dimensional modeling module (3), a plate optimization layout module (4), a cutting control module (5), a machine vision positioning detection module (6), a material transfer module (7), a punching control module (8), a cutting equipment (100) and a punching equipment (101); The central control unit (1) is in communication connection with each module respectively, for sending control instructions and receiving state feedback data of each module; The order analysis module (2) is in communication connection with the three-dimensional modeling module (3), and transmits the parsed structured order data to the three-dimensional modeling module (3); The three-dimensional modeling module (3) is in communication connection with the plate optimization layout module (4), and transmits the generated plate three-dimensional information to the plate optimization layout module (4); The plate optimization layout module (4) is in communication connection with the cutting control module (5), and transmits the layout scheme to the cutting control module (5); The cutting control module (5) is in communication connection with the cutting equipment (100), and sends the cutting control instructions to the cutting equipment (100) according to the generated NC program; The material transfer module (7) is in communication connection with the cutting equipment (100) respectively, and the material transfer module (7) receives the scheduling instructions of the central control unit (1), and completes the transfer of the plate from the raw material area to the cutting equipment (100), and then from the cutting equipment (100) to the punching station; The machine vision positioning detection module (6) is in communication connection with the punching control module (8), and transmits the calculated plate translation deviation and rotation deviation to the punching control module (8); The punching control module (8) is in communication connection with the punching equipment (101), and sends the multi-axis motion instructions to the punching equipment (101) according to the corrected actual machining coordinates.

8. The automatic unloading and punching control system of furniture according to claim 7, characterized in that: The order analysis module (2), the three-dimensional modeling module (3) and the plate optimization layout module (4) are realized based on computer.

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