Machine vision based lumber feeding system and method

Abstract

The application discloses a kind of wood feeding system and method based on machine vision, system includes vision system, numerical control positioning mechanism, automatic feeding system, man-machine interface, adaptive and learning module, method realizes the automatic feeding of wood, automatic scanning, automatic alignment and automatic sawing.The application realizes the automatic wood feeding by a kind of wood feeding system and method based on machine vision, improves processing precision by visual system data processing, and improves work efficiency by feeding into preferred saw for sawing after automatic alignment of board.

Description

Technical Field

[0001] This invention relates to the fields of intelligent manufacturing and machine vision, and in particular to a wood feeding system and method based on machine vision. Background Technology

[0002] In modern manufacturing, wood processing is a crucial link. With the development of technology, more and more wood processing equipment is adopting automation to improve production efficiency and processing accuracy. Among these, visual inspection technology and CNC positioning technology are two important technical fields, applied to various stages of wood processing, such as wood debarking and optimized sawing of boards.

[0003] In existing technologies, wood debarking and optimized board sawing are mainly achieved using longitudinal optimization saws. Regarding feeding, there are two main methods:

[0004] 1. Workers manually load the wood, then manually adjust the laser marking, manually align the wood position, and then feed it into the preferred saw for cutting;

[0005] 2. The wood is fed to the designated position by an automatic feeder, and then the position of the wood is manually adjusted by laser marking and then fed into the preferred saw for sawing.

[0006] Both of these feeding methods require manual intervention, which not only increases the workload but is also susceptible to human factors, resulting in low processing accuracy and low efficiency. The alignment of the timber relies on visual inspection, which incurs labor costs and is prone to misjudgment, affecting the processing quality. When dealing with large-scale production, it often fails to meet the needs of rapid response and efficient operation of the production line. Summary of the Invention

[0007] The purpose of this invention is to design a wood feeding system and method based on machine vision in order to solve the above-mentioned technical problems.

[0008] A machine vision-based wood feeding system includes a vision system, a CNC positioning mechanism, and an automatic feeding system;

[0009] The vision system scans the wood entering the system to obtain the location of the wood bark and defect information, and then processes the information into data.

[0010] The CNC positioning mechanism automatically aligns the boards based on the wood data acquired by the vision system;

[0011] The automatic feeding system integrates a vision system and a CNC positioning mechanism to achieve automatic feeding, scanning, alignment and sawing of wood.

[0012] Furthermore, a machine vision-based wood feeding system is provided, wherein the vision system employs an industrial camera and image processing algorithms to perform high-precision imaging and identification of wood.

[0013] The CNC positioning mechanism uses a servo motor and precision mechanical structure to achieve precise positioning and adjustment of the sheet metal.

[0014] Furthermore, a machine vision-based wood feeding system is provided, wherein the automatic feeding system further includes a human-machine interface and an adaptive and learning module;

[0015] The human-computer interaction interface satisfies the operator's needs for inputting parameters, viewing status, and performing control.

[0016] The adaptive and learning modules automatically adjust parameters and strategies based on actual production conditions and environmental changes.

[0017] A CNC positioning mechanism device includes a loading table frame, a conveyor chain assembly, a chain motor assembly, a reference positioning assembly, a baffle plate assembly, a conveyor roller assembly, a servo positioning assembly, and an upper pressure roller assembly;

[0018] The chain motor assembly drives the parallel conveyor chain assemblies to move the timber laterally.

[0019] The baffle assembly is located at the front end of the loading platform frame. The baffle assembly controls the feeding cycle by extending and retracting the cylinder according to the signal.

[0020] The reference positioning component is located at the rear end of the conveyor chain assembly, and is situated behind the limit switch;

[0021] The conveyor roller assembly is located above the loading platform frame, and the timber is conveyed through the conveyor roller assembly;

[0022] The servo positioning component corresponds to the reference positioning component, and the upper pressure roller component compacts the wood.

[0023] A machine vision-based wood feeding method includes the following sub-steps:

[0024] S1: When the wood enters the scanning range of the vision system, a positioning reference point is selected according to the different lengths;

[0025] S2: The vision system scans the wood to obtain the location of the veneer and defect information, and then processes the information into data.

[0026] S3: The CNC positioning mechanism activates the corresponding servo positioning component based on the reference positioning component used during vision system positioning, and moves the servo according to the results of vision inspection planning to straighten the board;

[0027] S4: After the CNC positioning mechanism is aligned, the conveyor chain assembly is lowered, and the sheet material is sent to the subsequent process through the conveyor roller assembly.

[0028] Furthermore, in a machine vision-based wood feeding method, step S2 includes the following sub-steps:

[0029] S21: The vision system performs image sampling, stitches together images taken by multiple cameras, and then compares the stitched images with the models.

[0030] S22: The acquired image is converted to grayscale and filtered. Edge detection and morphological processing algorithms are used to extract the location and defect information of the wood bark.

[0031] S23: The vision system obtains the positioning dimensions through calculation, plans according to customer needs, converts the planning results into digital signals, and transmits them to the CNC positioning mechanism.

[0032] Beneficial effects of this invention:

[0033] 1. High degree of automation: By combining a vision system and a CNC positioning and conveying system, the peeling, positioning and selective sawing of wood are automated, reducing manual intervention and improving production efficiency;

[0034] 2. High processing precision: It adopts visual inspection technology to accurately identify the position and defects of the wood veneer, and automatically aligns the boards according to the data, which improves processing precision and reduces misjudgment;

[0035] 3. High adaptability: It automatically adjusts the feeding parameters according to different types and specifications of wood, which is highly adaptable, meets the needs of large-scale production, and improves the rapid response and efficient operation of the production line;

[0036] 4. Reduced labor intensity: It eliminates the need for manual loading, manual adjustment of laser marking, and manual alignment of wood, thus reducing labor intensity and improving the working environment. Attached Figure Description

[0037] Figure 1 This is a system architecture diagram.

[0038] Figure 2 Figure a shows the structure of the device.

[0039] Figure 3 Figure b shows the structure of the device.

[0040] Figure 4 This is a flowchart of the method.

[0041] In the figure, 1-loading platform frame, 2-conveyor chain assembly, 3-chain motor assembly, 4-reference positioning assembly, 5-baffle plate assembly, 6-conveyor roller assembly, 7-servo positioning assembly, and 8-upper pressure roller assembly. Detailed Implementation

[0042] The present invention will be further described below, but the scope of protection of the present invention is not limited to the following description.

[0043] As attached Figure 1 As shown, a machine vision-based wood feeding system includes a vision system, a CNC positioning mechanism, and an automatic feeding system.

[0044] The vision system scans the wood entering the system to obtain the location of the wood bark and defect information, and then processes the information into data.

[0045] The CNC positioning mechanism automatically aligns the boards based on the wood data acquired by the vision system;

[0046] The automatic feeding system integrates a vision system and a CNC positioning mechanism to achieve automatic feeding, scanning, alignment and sawing of wood.

[0047] Furthermore, a machine vision-based wood feeding system is provided, wherein the vision system employs an industrial camera and image processing algorithms to perform high-precision imaging and identification of wood.

[0048] The CNC positioning mechanism uses a servo motor and precision mechanical structure to achieve precise positioning and adjustment of the sheet metal.

[0049] Furthermore, a machine vision-based wood feeding system is provided, wherein the automatic feeding system further includes a human-machine interface and an adaptive and learning module;

[0050] The human-computer interaction interface satisfies the operator's needs for inputting parameters, viewing status, and performing control.

[0051] The adaptive and learning modules automatically adjust parameters and strategies based on actual production conditions and environmental changes.

[0052] As attached Figure 2-3 As shown, a CNC positioning mechanism device includes a loading table frame 1, a conveyor chain assembly 2, a chain motor assembly 3, a reference positioning assembly 4, a baffle plate assembly 5, a conveyor roller assembly 6, a servo positioning assembly 7, and an upper pressure roller assembly 8.

[0053] The chain motor assembly 3 drives the parallel conveyor chain assembly 2 to move the timber laterally;

[0054] The baffle assembly 5 is located at the front end of the loading platform frame 1. The baffle assembly 5 controls the feeding cycle by extending and retracting the cylinder according to the signal.

[0055] The reference positioning component 4 is located at the rear end of the conveyor chain assembly 2, and the reference positioning component 4 is located behind the limit switch;

[0056] The conveying roller assembly 6 is positioned above the loading platform frame 1, and the timber is conveyed through the conveying roller assembly 6.

[0057] The servo positioning component 7 corresponds to the reference positioning component 4, and the upper pressure roller component 8 compacts the wood.

[0058] As attached Figure 4 As shown, a machine vision-based wood feeding method includes the following sub-steps:

[0059] S1: When the wood enters the scanning range of the vision system, a positioning reference point is selected according to the different lengths;

[0060] S2: The vision system scans the wood to obtain the location of the veneer and defect information, and then processes the information into data.

[0061] S3: The CNC positioning mechanism activates the corresponding servo positioning component 7 based on the reference positioning component 4 activated during vision system positioning, and moves the servo according to the results of vision inspection planning to straighten the board.

[0062] S4: After the CNC positioning mechanism is aligned, the conveyor chain assembly 2 is lowered, and the sheet material is sent to the subsequent process through the conveyor roller assembly 6.

[0063] Furthermore, in a machine vision-based wood feeding method, step S2 includes the following sub-steps:

[0064] S21: The vision system performs image sampling, stitches together images taken by multiple cameras, and then compares the stitched images with the models.

[0065] S22: The acquired image is converted to grayscale and filtered. Edge detection and morphological processing algorithms are used to extract the location and defect information of the wood bark.

[0066] S23: The vision system obtains the positioning dimensions through calculation, plans according to customer needs, converts the planning results into digital signals, and transmits them to the CNC positioning mechanism.

[0067] This solution utilizes a machine vision-based wood feeding system and method, combining a vision system with a CNC positioning and conveying system to automate the peeling, positioning, and optimal sawing of wood, reducing manual intervention and improving production efficiency. It employs visual inspection technology to accurately identify the location and defects of the wood veneer, automatically aligning the boards based on data, improving processing accuracy and reducing misjudgments. The system automatically adjusts feeding parameters according to different wood types and specifications, demonstrating strong adaptability and meeting the needs of large-scale production, thus improving the rapid response and efficient operation of the production line. It eliminates the need for manual loading, manual adjustment of laser marking, and manual alignment of wood, reducing labor intensity and improving the working environment.

[0068] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A wood feeding method based on machine vision, characterized in that, This is achieved through a wood feeding system that includes a vision system, a CNC positioning mechanism, and an automatic feeding system. The wood feeding method includes the following sub-steps: S1: When the wood enters the scanning range of the vision system, a positioning reference point is selected according to the different lengths; S2: The vision system scans the wood to obtain the location of the veneer and defect information, and then processes the information into data. S3: The CNC positioning mechanism activates the corresponding servo positioning component (7) based on the reference positioning component (4) activated during vision system positioning, and moves the servo positioning component (7) according to the results of vision inspection planning to straighten the board; S4: After the CNC positioning mechanism is aligned, the conveyor chain assembly (2) is lowered, and the plate is sent to the subsequent process through the conveyor roller assembly (6); The vision system scans the wood entering the system to obtain the location of the wood bark and defect information, and then processes the information into data. The vision system uses industrial cameras and image processing algorithms to perform high-precision imaging and identification of wood. The CNC positioning mechanism automatically aligns the boards based on the wood data acquired by the vision system; The automatic feeding system integrates a vision system and a CNC positioning mechanism to realize automatic feeding, scanning, alignment and sawing of timber. It also includes a human-machine interface and an adaptive and learning module. The human-machine interface allows operators to input parameters, view status and perform control. The adaptive and learning module automatically adjusts parameters and strategies according to actual production conditions and environmental changes. The CNC positioning mechanism includes a loading table frame (1), a conveyor chain assembly (2), a chain motor assembly (3), a reference positioning assembly (4), a baffle plate assembly (5), a conveyor roller assembly (6), a servo positioning assembly (7), and an upper pressure roller assembly (8). The chain motor assembly (3) drives the parallel conveyor chain assembly (2) to move the timber laterally; The baffle assembly (5) is located at the front end of the loading platform frame (1). The baffle assembly (5) controls the feeding cycle by extending and retracting the cylinder. The reference positioning component (4) is located at the rear end of the conveyor chain assembly (2), and the reference positioning component (4) is located behind the limit switch; The conveying roller assembly (6) is located above the loading platform frame (1), and the wood is conveyed through the conveying roller assembly (6); The servo positioning component (7) corresponds to the reference positioning component (4), and the upper pressure roller component (8) compacts the wood.

2. The wood feeding method based on machine vision according to claim 1, characterized in that, Step S2 includes the following sub-steps: S21: The vision system performs image sampling, stitches together images taken by multiple cameras, and then compares the stitched images with the models. S22: The acquired image is converted to grayscale and filtered. Edge detection and morphological processing algorithms are used to extract the location and defect information of the wood bark. S23: The vision system obtains the positioning dimensions through calculation, plans according to customer needs, converts the planning results into digital signals, and transmits them to the CNC positioning mechanism.

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