Dynamic correction system based on big data

Abstract

The present invention discloses a dynamic correction system based on big data, including a preprocessing module, an operation processing module and a dynamic correction module. The preprocessing module is used to scan and record the wood before processing, and the dynamic correction module is used to correct the processing according to the scanning situation and the situation of the furniture. The preprocessing module and the dynamic correction module are electrically connected. The preprocessing mechanism is used before the wood raw material is processed, so that small defects of the wood can be avoided during processing to ensure the quality of the finished product. The dynamic correction module is used to check the produced furniture to ensure the stability of the connection of the furniture. If there is a problem, it is corrected. Compared with the manual processing method, the use of coding technology can effectively prevent the problem of confusion in matching the wood board with the graphics in the database, and ensure that the processing of each piece of raw material is optimally processed to reflect intelligence. The present invention has the characteristics of accurate design detection and reasonable operation adjustment.

Description

Technical Field

[0001] The present invention relates to the technical field of furniture intelligent factory production, and in particular to a dynamic correction system based on big data. Background Art

[0002] As the economy develops faster and faster, labor costs continue to rise, so the concept of smart factories has emerged. At present, my country's factory production is gradually shifting from pure manual production to smart production. Although the concept of smart production is popular and used, it is still not completely perfect. For example, the current working method of the wood furniture industry is inseparable from manual production, so a dynamic correction system is designed to help factories carry out more rational production operations.

[0003] In my country's wood production sector, most production is still in a semi-mechanical or even primitive manual production state. Since there are many types of surface defects in boards, and the same type of defects vary in size and appearance, manual inspection methods are inevitably interfered by human factors, and it is impossible to avoid missed inspections, wrong inspections, etc., and the high quality of products cannot be guaranteed. The individual conditions of wooden boards are also an important influencing factor in furniture assembly. Different wood materials require different screw assembly methods, and whether the screws are assembled properly has a great impact on the quality of furniture. Therefore, it is necessary to design a dynamic correction system based on big data with accurate detection and reasonable operation adjustment. Summary of the invention

[0004] The purpose of the present invention is to provide a dynamic correction system based on big data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a dynamic correction system based on big data, including a preprocessing module, an operation processing module and a dynamic correction module, the preprocessing module is used to scan and record the wood before processing, and the dynamic correction module is used to make certain corrections to the processing according to the scanning situation and the situation of the furniture, and the preprocessing module and the dynamic correction module are electrically connected.

[0006] According to the above technical solution, the pre-processing module includes an integrated processing module and a coding mark database module. The integrated processing module is used to scan and record the initial raw materials to prepare for material processing. The coding mark database module is used to store and process the scanned wood conditions and mark the corresponding wood raw materials to ensure one-to-one correspondence.

[0007] The dynamic correction module includes an initial production module, a product monitoring module, a correction processing module and a robot arm adjustment module. The initial production module is used for the initial use of screws to connect furniture. The product detection module is used to scan the installation status of the initially processed products to ensure that the structure is firm. If it is not firm enough, it will be corrected again. The robot arm adjustment module is used to adjust the speed and angle of furniture screw installation. The initial production module is electrically connected to the product detection module, the product detection module is electrically connected to the correction processing module, the initial production module is electrically connected to the robot arm adjustment module, and the correction processing module is electrically connected to the robot arm adjustment module.

[0008] According to the above technical solution, the integrated processing module includes a CT scanning module 1 and an image analysis module, wherein the CT scanning module 1 is used to scan the raw material so as to facilitate the selection of a reasonable processing method during processing, and the image analysis module is used to save the image of the scanned raw material, and the CT scanning module 1 is electrically connected to the image analysis module;

[0009] The primary production module includes a product conveying module, a processing control module and a detection and transmission module. The product conveying module is used to transmit raw materials and transmit them to the processing control module. The processing control module is used to perform different screw connections on the raw materials according to the characteristics of each piece of material. The monitoring and transmission module is used to transmit the assembled furniture to the product detection module. The product conveying module is electrically connected to the processing control module, the processing control module is electrically connected to the detection and transmission module, and the detection and transmission module is electrically connected to the product detection module.

[0010] The product inspection module includes a CT scanning module 2 and a correction transmission module. The CT scanning module 2 is used to detect the connection of the product and whether the screws are firmly installed. The correction transmission module is used to transmit the products with unqualified connection after quality inspection to the correction processing module. The CT scanning module 2 is electrically connected to the correction transmission module.

[0011] The correction processing module includes a component correction module and a detection link module. The component correction module is used to correct unqualified screws, and the detection link module is used to transmit the corrected product to the product detection module. The component correction module is electrically connected to the detection link module, and the detection link module is electrically connected to the product detection module.

[0012] According to the above technical solution, the operation method of the dynamic correction system based on big data mainly includes the following steps:

[0013] Step S1: The dynamic correction system is turned on, and the pre-processing module works, and the CT scanning module is used to continuously scan the wood entering the system, and then the wood is numbered and marked, and the scanned image is stored in the coding and marking database module;

[0014] Step S2: The primary production module receives the transmitted raw materials, reads the coding information, and transmits it to the product inspection module after screw connection in the safe area;

[0015] Step S3: The product inspection module performs a CT scan on the side of the screw connection and analyzes whether the screw is firmly installed based on the imaging information;

[0016] Step S4: Output the image analysis results and judge the degree of installation firmness. If it is not firm, it will be sent to the correction processing module. After correction by the robotic arm, it will be tested again. If it is qualified, the product is completed, otherwise continue to correct it.

[0017] According to the above technical solution, step S1 further includes the following steps:

[0018] Step S11: The conveyor belt transports the wood to a CT scanning module, where the emission intensity is Q n of absorbable beams;

[0019] Step S12: After emitting the light beam, monitor its light intensity W n , and the residual light intensity E is obtained n , ;

[0020] Step S13: Refine the absorption amount of each beam of light, calculate the area where the absorption exceeds the threshold R, and fit the above node area into a closed graph;

[0021] Step S14: Remove the light in the area where the absorption exceeds the threshold R in the wood image, calculate the average intensity E0 of the remaining light, and thus obtain the density T of the wood board. ;

[0022] Step S15: The density information of each wooden board and the wood nodes are coded accordingly and stored in the database.

[0023] According to the above technical solution, step S2 further includes the following steps:

[0024] Step S21: The primary production module receives the wood raw material, reads the wood code, and obtains the data information of the wood in the database;

[0025] Step S22: According to the density of the wood, the robot arm selects different rotation speeds Y. ;

[0026] Step S23: reading the node area distribution of the wood, and selecting the screw connection position avoiding the node area;

[0027] Step S24: The robotic arm drills the screws vertically according to the rotation speed Y to connect the furniture together.

[0028] According to the above technical solution, step S3 further includes the following steps:

[0029] Step S31: The CT scanning module 2 takes a side view of the screw connection;

[0030] Step S32: The module analyzes the side view and analyzes the concave deformation angle U on both sides of the wood and the screw;

[0031] Step S33: If the deformation angles U are the same, the screw is in a vertical state, otherwise it is in a non-optimal state;

[0032] Step S34: transmitting the furniture connection in a non-optimal state to the component correction module.

[0033] According to the above technical solution, step S4 further includes the following steps:

[0034] Step S41: the component correction module reads the connection side scan image;

[0035] Step S42: Calculate the direction I of the force applied by the robot arm according to the deformation angle U of the wooden board on both sides of the screw. , I is the direction of adjusting U toward one end of the deformation protrusion;

[0036] Step S43: The robotic arm unscrews the screw, then finds a new connection point based on angle I, screws in the screw, and then sends the corrected furniture to the product inspection module again via the conveyor belt.

[0037] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention uses a pretreatment mechanism before processing the wood raw materials, which is convenient for avoiding small defects in the wood during processing and ensuring the quality of the finished product. The dynamic correction module is used to check the produced furniture to ensure the stability of the connection of the furniture. If there is a problem, it is corrected. Compared with the manual processing method, it embodies intelligence and the quality of the product can be better guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0039] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] See also Figure 1 The present invention provides a technical solution: a dynamic correction system based on big data, including a preprocessing module, an operation processing module and a dynamic correction module. The preprocessing module is used to scan and record the wood before processing, and the dynamic correction module is used to make certain corrections to the processing according to the scanning situation and the situation of the furniture. The preprocessing module and the dynamic correction module are electrically connected. The preprocessing mechanism is used before the wood raw material is processed, which is convenient for avoiding small defects in the wood during processing and ensuring the quality of the finished product. The dynamic correction module is used to check the produced furniture to ensure the stability of the connection of the furniture. If there is a problem, it will be corrected. Compared with the manual processing method, it embodies intelligence and the quality of the product can be better guaranteed.

[0042] The pre-processing module includes an integrated processing module and a coding mark database module. The integrated processing module is used to scan and record the initial raw materials to prepare for material processing. The coding mark database module is used to store and process the scanned wood conditions and mark the corresponding wood raw materials to ensure one-to-one correspondence. The use of coding technology can effectively prevent the problem of mismatch between the wood board and the graphics in the database, ensuring that the processing of each piece of raw material is optimal;

[0043] The dynamic correction module includes an initial production module, a product monitoring module, a correction processing module and a robot arm adjustment module. The initial production module is used for the initial use of screws to connect furniture. The product detection module is used to scan the installation status of the initially processed products to ensure that the structure is firm. If it is not firm enough, it will be corrected again. The robot arm adjustment module is used to adjust the speed and angle of furniture screw installation. The initial production module is electrically connected to the product detection module, the product detection module is electrically connected to the correction processing module, the initial production module is electrically connected to the robot arm adjustment module, and the correction processing module is electrically connected to the robot arm adjustment module. Different screwing methods are used for the wood according to the density of the wood to make the connection firm.

[0044] The integrated processing module includes a CT scanning module 1 and an image analysis module. The CT scanning module 1 is used to scan the raw material to facilitate the selection of a reasonable processing method during processing. The image analysis module is used to save the image of the scanned raw material. The CT scanning module 1 is electrically connected to the image analysis module. The raw material is scanned by a CT scanning instrument. The scanner emits a light beam to irradiate the surface of the raw material. The raw material has different absorption effects due to its own density and node conditions. The condition of the wood is analyzed based on these effects.

[0045] The primary production module includes a product conveying module, a processing control module and a detection and transmission module. The product conveying module is used to transmit raw materials and transmit them to the processing control module. The processing control module is used to perform different screw connections on the raw materials according to the characteristics of each piece of material. The monitoring and transmission module is used to transmit the assembled furniture to the product detection module. The product conveying module is electrically connected to the processing control module, the processing control module is electrically connected to the detection and transmission module, and the detection and transmission module is electrically connected to the product detection module.

[0046] The product inspection module includes a CT scanning module 2 and a correction transmission module. The CT scanning module 2 is used to detect the connection of the product and whether the screws are firmly installed. The correction transmission module is used to transmit the products with unqualified connection after quality inspection to the correction processing module. The CT scanning module 2 is electrically connected to the correction transmission module.

[0047] The correction processing module includes a component correction module and a detection link module. The component correction module is used to correct unqualified screws, and the detection link module is used to transmit the corrected product to the product detection module. The component correction module is electrically connected to the detection link module, and the detection link module is electrically connected to the product detection module.

[0048] The operation method of the dynamic correction system based on big data mainly includes the following steps:

[0049] Step S1: The dynamic correction system is turned on, and the pre-processing module works, and the CT scanning module is used to continuously scan the wood entering the system, and then the wood is numbered and marked, and the scanned image is stored in the coding and marking database module;

[0050] Step S2: The primary production module receives the transmitted raw materials, reads the coding information, and transmits it to the product inspection module after screwing in a safe area;

[0051] Step S3: The product inspection module performs a CT scan on the side of the screw connection and analyzes whether the screw is firmly installed based on the imaging information;

[0052] Step S4: Output the image analysis results and judge the degree of installation firmness. If it is not firm, it will be sent to the correction processing module. After correction by the robotic arm, it will be tested again. If it is qualified, the product is completed, otherwise continue to correct it.

[0053] Step S1 further comprises the following steps:

[0054] Step S11: The conveyor belt transports the wood to a CT scanning module, where the emission intensity is Q n The scanning instrument measures the condition of the wood by emitting a beam and observing the degree of absorption of the beam.

[0055] Step S12: After emitting the light beam, monitor its light intensity W n , and the residual light intensity E is obtained n , ;

[0056] Step S13: Refine the absorption amount of each beam of light, calculate the area where the absorption exceeds the threshold R, and fit the above node area into a closed figure. The nodes of wood are generally darker in color and have a stronger ability to absorb light beams, so the beam node range is calculated based on the method of light beam absorption exceeding the threshold;

[0057] Step S14: Remove the light in the area where the absorption exceeds the threshold R in the wood image, calculate the average intensity E0 of the remaining light, and thus obtain the density T of the wood board. , the density of wood is generally different. The situation of wood nodes is eliminated and the residual light intensity of the remaining area is calculated to make the calculation more accurate. The higher the density of wood, the less light absorption, but the density of wood has an upper limit and will not exceed a certain value;

[0058] Step S15: The density information of each wooden board and the wood nodes are coded accordingly and stored in the database.

[0059] Step S2 further comprises the following steps:

[0060] Step S21: The primary production module receives the wood raw material, reads the wood code, and obtains the data information of the wood in the database;

[0061] Step S22: According to the density of the wood, the robot arm selects different rotation speeds Y. , the higher the density of the wood, the slower the screw will be turned, so the work done is higher and the screw will be more firmly screwed into the wood;

[0062] Step S23: reading the node area distribution of the wood, and selecting the screw connection position avoiding the node area. Screwing the screw into the wood node is likely to cause the screw to fall off, and the wood of the wood node is not enough to support the connection;

[0063] Step S24: The robot arm drills the screws vertically according to the rotation speed Y to connect the furniture together. Drilling the screws vertically can avoid the occurrence of insufficient connection.

[0064] Step S3 further comprises the following steps:

[0065] Step S31: The CT scanning module 2 takes a side view of the screw connection;

[0066] Step S32: The module analyzes the side view and analyzes the concave deformation angle U on both sides of the wood and the screw. According to the degree of concave of the wood on both sides of the screw, it can be checked whether the screw is vertical. When it is vertical, the screw connection is more secure.

[0067] Step S33: If the deformation angles U are the same, the screw is in a vertical state, otherwise it is in a non-optimal state;

[0068] Step S34: transmitting the furniture connection in a non-optimal state to the component correction module.

[0069] Step S4 further comprises the following steps:

[0070] Step S41: the component correction module reads the connection side scan image;

[0071] Step S42: Calculate the direction I of the force applied by the robot arm according to the deformation angle U of the wooden board on both sides of the screw. , I is to adjust the direction of U toward one end of the deformed protrusion. After re-screwing the unqualified screws according to the correction angle, the screws can be guaranteed to be connected vertically, thus improving product quality;

[0072] Step S43: The robotic arm unscrews the screw, then finds a new connection point based on angle I, screws in the screw, and then sends the corrected furniture to the product inspection module again via the conveyor belt.

[0073] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0074] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A dynamic correction system based on big data, including a preprocessing module, a job processing module and a dynamic correction module, characterized in that: The pre-processing module is used to scan and record the wood before processing, and the dynamic correction module is used to make certain corrections to the processing according to the scanning situation and the situation of the furniture. The pre-processing module is electrically connected to the dynamic correction module; The pre-processing module includes an integrated processing module and a coding mark database module. The integrated processing module is used to scan and record the initial raw materials to prepare for material processing. The coding mark database module is used to store and process the scanned wood conditions and mark the corresponding wood raw materials to ensure one-to-one correspondence. The dynamic correction module includes an initial production module, a product detection module, a correction processing module and a robot arm adjustment module. The initial production module is used to connect the furniture with screws for the first time. The product detection module is used to scan the installation status of the initially processed product to ensure that the structure is firm. If it is not firm enough, it will be corrected again. The robot arm adjustment module is used to adjust the speed and angle of furniture screw installation. The initial production module is electrically connected to the product detection module, the product detection module is electrically connected to the correction processing module, the initial production module is electrically connected to the robot arm adjustment module, and the correction processing module is electrically connected to the robot arm adjustment module. The integrated processing module includes a CT scanning module 1 and an image analysis module. The CT scanning module 1 is used to scan the raw material to facilitate the selection of a reasonable processing method during processing. The image analysis module is used to save the image of the scanned raw material. The CT scanning module 1 is electrically connected to the image analysis module. The primary production module includes a product conveying module, a processing control module and a detection and transmission module. The product conveying module is used to transmit raw materials and transmit them to the processing control module. The processing control module is used to perform different screw connections on the raw materials according to the characteristics of each piece of material. The detection and transmission module is used to transmit the assembled furniture to the product detection module. The product conveying module is electrically connected to the processing control module, the processing control module is electrically connected to the detection and transmission module, and the detection and transmission module is electrically connected to the product detection module. The product inspection module includes a CT scanning module 2 and a correction transmission module. The CT scanning module 2 is used to detect the connection of the product and whether the screws are firmly installed. The correction transmission module is used to transmit the products with unqualified connection after quality inspection to the correction processing module. The CT scanning module 2 is electrically connected to the correction transmission module. The correction processing module includes a component correction module and a detection link module, wherein the component correction module is used to correct unqualified screws, and the detection link module is used to transmit the corrected product to the product detection module, and the component correction module is electrically connected to the detection link module, and the detection link module is electrically connected to the product detection module; The operation method of the dynamic correction system based on big data includes the following steps: Step S1: The dynamic correction system is turned on, and the pre-processing module works, and the CT scanning module is used to continuously scan and process the wood entering the system, and then the wood is numbered and marked, and the scanned image is stored in the coding and marking database module; Step S2: The primary production module receives the transmitted raw materials, reads the coding information, performs screw connection in a safe area, and then transmits it to the product inspection module; Step S3: The product inspection module performs a CT scan on the side of the screw connection and analyzes whether the screw is firmly installed based on the imaging information; Step S4: Output the image analysis results to judge the installation firmness. If it is not firm, send it to the correction processing module, use the robot arm to correct it, and then test it again. If it is qualified, the product is completed, otherwise continue to correct it; The step S1 further comprises the following steps: Step S11: The conveyor belt transports the wood to a CT scanning module, where the emission intensity is Q n of absorbable beams; Step S12: After emitting the light beam, monitor its light intensity W n , and the residual light intensity E is obtained n , ; Step S13: Refine the absorption amount of each beam of light, calculate the area where the absorption exceeds the threshold R, and fit the area where the absorption exceeds the threshold R into a closed figure; Step S14: Remove the light in the area where the absorption exceeds the threshold R in the wood image, calculate the average intensity E0 of the remaining light, and thus obtain the density T of the wood board. ; Step S15: The density information of each wooden board and the wood nodes are coded accordingly and stored in the database.

2. The big data-based dynamic correction system according to claim 1, characterized in that: The step S2 further comprises the following steps: Step S21: The primary production module receives the wood raw material, reads the wood code, and obtains the data information of the wood in the database; Step S22: According to the density of the wood, the robot arm selects different rotation speeds Y. ; Step S23: reading the node area distribution of the wood, and selecting the screw connection position avoiding the node area; Step S24: The robotic arm drills the screws vertically according to the rotation speed Y to connect the furniture together.

3. The big data-based dynamic correction system according to claim 2, characterized in that: The step S3 further comprises the following steps: Step S31: The CT scanning module 2 takes a side view of the screw connection; Step S32: Analyze the side view and the deformation angle U on both sides of the wood and the screw; Step S33: If the deformation angles U are the same, the screw is in a vertical state, otherwise it is in a non-optimal state; Step S34: transmitting the furniture connection in a non-optimal state to the component correction module.

4. The big data-based dynamic correction system according to claim 3, characterized in that: The step S4 further comprises the following steps: Step S41: the component correction module reads the side view of the connection; Step S42: Calculate the direction I of the force applied by the robot arm according to the deformation angle U of the wooden board on both sides of the screw. , I is the direction of adjusting U toward one end of the deformation protrusion; Step S43: The robotic arm unscrews the screw, then finds a new connection point based on angle I, screws in the screw, and then sends the corrected furniture to the product inspection module again via the conveyor belt.

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