A method for constructing a warped cardboard template library for a cardboard production line

Abstract

The invention is applicable to the field of production quality control, and discloses a method for constructing a warping cardboard template library of a cardboard production line, comprising collecting cross-sectional images of cardboards with different warping directions and warping degrees as samples; identifying the warping directions and warping degrees of the samples and classifying the samples according to different warping types and warping levels to obtain classification results; establishing sub-image libraries corresponding to different warping types and warping levels according to the classification results; calculating the warping convexity of each sample in each sub-image library one by one, and determining the warping convexity range value of the warping type and warping level corresponding to each sub-image library according to the minimum value and maximum value of the warping convexity of the samples in each sub-image library. The method uses non-contact, low-cost and high-precision machine vision technology to collect cross-sectional images of cardboards with different warping directions and warping degrees as samples, and forms a warping cardboard template library in combination with the experience and knowledge of engineers, thereby providing a quantitative basis for subsequent online recognition of cardboard warping.

Description

Technical Field

[0001] The invention relates to the field of production quality control, and in particular to a method for constructing a warping cardboard template library for a cardboard production line. Background Art

[0002] Corrugated paper packaging is widely used in downstream consumer industries such as home appliances, electronic products, IT, food and beverages, books, daily chemicals, textiles, and logistics and express delivery companies. The production of corrugated board consists of key links such as base paper corrugation forming, board forming, cutting and stacking. Its quality control and efficiency assurance not only involve data analysis and intelligent control of equipment used in key links, but also involve effective process control of corrugated board production lines.

[0003] The warpage of export cardboard is an important indicator of the product quality of corrugated cardboard production line. The product quality of corrugated cardboard production line is mainly related to factors such as base paper material, moisture content, and temperature control during the production process. The process control of the corrugated cardboard production line is mainly to monitor the warpage of the export cardboard of the production line in real time online to achieve effective feedback control of the quality of the cardboard. Among them, the online detection of the warpage of the export cardboard of the production line and the identification of the warpage level are the key to achieving process control of the production line. At present, the domestic corrugated cardboard production lines that have been put into production mainly use the human eye judgment and identification of on-site engineers in the quality inspection and control of export products, and implement the method of manually inputting parameters to adjust and control product quality. However, the current production speed of the corrugated cardboard production line is generally several hundred meters per minute, and it is very difficult to rely on manual online detection of the warpage of the export cardboard and identification of the warpage level; moreover, the rapid development of industries such as online shopping and express delivery has brought about customized and personalized market demands, resulting in the production of corrugated cardboard. The production of multiple batches and small batches requires a large number of orders and the material change frequency in the production process is very high, resulting in high labor costs in the corrugated cardboard industry, affecting the automation and intelligence level of the corrugated cardboard manufacturing industry. Summary of the invention

[0004] The purpose of the present invention is to provide a method for constructing a warped cardboard template library for a cardboard production line, which collects samples through visual technology and combines the experience and knowledge of engineers to form a warped cardboard template library, providing a quantitative basis for the subsequent online identification of cardboard warpage.

[0005] To achieve the above object, the solution provided by the present invention is:

[0006] A method for constructing a warped cardboard template library for a cardboard production line, comprising:

[0007] Collect cross-sectional images of cardboard with different warping directions and degrees as samples;

[0008] Identify the warping direction and degree of the sample and classify the sample according to different warping types and warping levels to obtain classification results;

[0009] Establishing a sub-image library corresponding to different warping types and warping levels according to the classification results;

[0010] The warping convexity of each sample of each sub-image library is calculated one by one, and the warping convexity range value of the warping type and warping level corresponding to each sub-image library is determined according to the minimum value and maximum value of the warping convexity of each sub-image library sample.

[0011] Preferably, the cross-sectional image is collected by a camera, and the camera is arranged at the exit end of the production line.

[0012] Preferably, the calculation of the warping convexity of each sample includes:

[0013] Extracting a cross-sectional profile of the paperboard according to the cross-sectional image;

[0014] Data fitting is performed according to the extracted cross-sectional profile to obtain a quadratic function relationship between the horizontal pixel coordinates of the cross-sectional profile and the vertical pixel coordinates of the cross-sectional profile. The quadratic function relationship is:

[0015] f(x)=ax 2 +bx+c (1)

[0016] Where x represents the horizontal pixel coordinate of the cross-sectional profile, f(x) represents the vertical pixel coordinate of the cross-sectional profile corresponding to the x position, and a, b, and c represent constants;

[0017] The warping convexity of the sample is calculated based on the quadratic function relationship.

[0018] Preferably, a Canny edge detection algorithm is used to extract the cross-sectional profile of the paperboard.

[0019] Preferably, the acquisition of the univariate quadratic function relationship is achieved based on the least squares method.

[0020] Preferably, the warping convexity of the sample is calculated using formula (2), and the formula (2) is as follows:

[0021]

[0022] Where δ represents the warping convexity of the sample, x a and x b Respectively represent the pixel coordinates of the two endpoints of the horizontal pixel coordinates of the quadratic function of one variable, x 1 ,x 2 ,x 3They respectively represent the pixel coordinates of the three quarter-divided points of the horizontal pixel coordinates of the quadratic function of one variable.

[0023] Preferably, the calculation of the warping convexity of each sample further comprises performing image processing on the sample before extracting the cross-sectional profile of the paperboard, wherein the image processing comprises graying the sample and extracting a region of interest.

[0024] Preferably, the calculation of the warping convexity of each sample further comprises performing an image closing operation on the extracted cross-sectional profile before implementing the data fitting based on the extracted cross-sectional profile.

[0025] Preferably, the warping types include upward warping and downward warping, the upward warping includes at least three levels, and the downward warping includes at least three levels.

[0026] Preferably, the upward warping includes three levels, the downward warping includes three levels, and the classification results include upward warping-type 1, upward warping-type 2, upward warping-type 3, downward warping-type 1, downward warping-type 2 and downward warping-type 3.

[0027] The method for constructing a warped cardboard template library of a cardboard production line provided by the present invention uses a machine vision technology with the characteristics of non-contact, low cost and high precision to collect cross-sectional images of cardboards with different warping directions and warping degrees as samples, and combines the experience and knowledge of field engineers to construct a sub-image library corresponding to different warping types and warping levels, and then calculates and determines the preset range values ​​of the warping convexity of different warping types and warping levels, and forms a warped cardboard template library, which provides a quantitative basis for the subsequent online recognition of the warping degree of the cardboard, that is, when the same cardboard production line identifies the cardboard warping degree online, the preset range values ​​of the warping convexity of different warping types and warping levels of the warped cardboard template library can be directly used to compare with the warping convexity of the cardboard collected in real time to judge the quality of the cardboard during production. Moreover, the method for constructing a warped cardboard template library of a cardboard production line can be applied to different production lines, and a warped cardboard template library can be constructed according to different production conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0029] Figure 1 It is a flow chart of a method for constructing a warped cardboard template library for a cardboard production line provided by an embodiment of the present invention;

[0030] Figure 2 yes Figure 1 Schematic diagram of the process of calculating the warping convexity of each sample in each sub-image library in the method. DETAILED DESCRIPTION

[0031] 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.

[0032] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0033] It should also be noted that when an element is referred to as being "fixed on" or "disposed on" another element, it may be directly on the other element or there may be an intermediate element at the same time. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intermediate element at the same time.

[0034] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0035] like Figure 1 to Figure 2 As shown, it is a method for constructing a warped cardboard template library for a cardboard production line according to an embodiment of the present invention, which is particularly suitable for export cardboard of a corrugated cardboard production line.

[0036] See also Figure 1 and Figure 2 The method for constructing a warped cardboard template library for a cardboard production line according to an embodiment of the present invention includes:

[0037] Step S100: collecting cross-sectional images of paperboards with different warping directions and warping degrees as samples;

[0038] Step S200: identifying the warping direction and warping degree of the sample and classifying the sample according to different warping types and warping levels to obtain a classification result;

[0039] Step S300: establishing a sub-image library corresponding to different warping types and warping levels according to the classification results;

[0040] Step S400: Calculate the warping convexity of each sample of each sub-image library one by one, and determine the warping convexity range value of the warping type and warping level corresponding to each sub-image library according to the minimum and maximum values ​​of the warping convexity of the samples of each sub-image library.

[0041] The method for constructing a warped cardboard template library of a cardboard production line of the present invention utilizes a machine vision technology with the characteristics of non-contact, low cost and high precision to collect cross-sectional images of cardboards with different warping directions and warping degrees as samples, and combines the experience and knowledge of field engineers to construct a sub-image library corresponding to different warping types and warping levels, and then calculates and determines the preset range values ​​of the warping convexity of different warping types and warping levels, and forms a warped cardboard template library, which provides a quantitative basis for the subsequent online recognition of the warping degree of cardboard, that is, when the same cardboard production line identifies the warping degree of cardboard online, the preset range values ​​of the warping convexity of different warping types and warping levels of the warped cardboard template library can be directly used to compare with the warping convexity of the cardboard collected in real time to determine the quality of the cardboard during production. Moreover, the method for constructing a warped cardboard template library of a cardboard production line can be applied to different production lines, and a warped cardboard template library can be constructed according to different production conditions.

[0042] In step S100, a cross-sectional image of the cardboard is collected by a camera, and the camera is arranged at the exit of the production line. The focal length can be determined by calculating the straight-line distance according to the position of the measured cardboard and the position of the camera arrangement (the distance between the position of the camera arrangement and the end point of the cardboard slope is used as the focal length), and the variation range of the width of the cardboard order of the production line is obtained. Then, according to the above parameters, a camera is selected for installation and the cross-sectional image of the cardboard at the exit of the production line is collected. According to the above parameters, the camera is selected to ensure that the collected cross-sectional image has sufficient image clarity and vertical angle.

[0043] It is understandable that the cross-sectional image of the paperboard may also be acquired by other methods.

[0044] In step S200 , illustratively, the field engineer identifies the warping direction and degree of the sample based on knowledge and experience, and classifies the sample according to different warping types and warping levels.

[0045] See also Figure 2 In some embodiments, the calculation of the warpage convexity of each sample includes:

[0046] Step S402: extracting the cross-sectional profile of the paperboard;

[0047] Optionally, a Canny edge detection algorithm is used to extract the cross-sectional profile of the paperboard. It is understandable that other edge detection algorithms may also be used to extract the cross-sectional profile of the paperboard.

[0048] Step S404: Perform data fitting based on the extracted cross-sectional profile to obtain a quadratic function relationship between the horizontal pixel coordinates of the cross-sectional profile and the vertical pixel coordinates of the cross-sectional profile. The quadratic function relationship is:

[0049] f(x)=ax 2 +bx+c (1)

[0050] Where x represents the horizontal pixel coordinate of the cross-sectional profile, f(x) represents the vertical pixel coordinate of the cross-sectional profile corresponding to the x position, and a, b, and c represent constants.

[0051] Exemplarily, the acquisition of the quadratic function relationship is implemented based on the least squares method.

[0052] Step S405: Calculate the warping convexity of the sample based on a quadratic function relationship.

[0053] Specifically, the warpage convexity of the sample is calculated using formula (2), which is as follows:

[0054]

[0055] Where δ represents the warping convexity of the sample, x a and x b Respectively represent the pixel coordinates of the two endpoints of the horizontal pixel coordinates of the quadratic function of one variable, x 1 ,x 2 ,x 3 They respectively represent the pixel coordinates of the three quarter-divided points of the horizontal pixel coordinates of the quadratic function of one variable.

[0056] That is, during the calculation, the horizontal pixel range of the quadratic function is divided into four equal parts, and the convexity values ​​at each position are obtained by subtracting the average values ​​of the two end points from the three middle points. Then, the average values ​​of the three convexity values ​​are calculated to obtain the warping convexity of the sample.

[0057] By calculating the warping convexity of each sample in this implementation, the accuracy of the calculation results can be guaranteed and the processing steps can be simplified.

[0058] Optionally, the warping types include upward warping and downward warping, the upward warping includes at least three levels, and the downward warping includes at least three levels.

[0059] Exemplarily, when implementing the identification of the warping direction and degree of the sample and classifying the sample according to different warping types and warping levels to obtain the classification results, the classification results formed include upwarping-type 1, upwarping-type 2, upwarping-type 3, downwarping-type 1, downwarping-type 2, and downwarping-type 3, that is, upwarping includes three levels and downwarping also includes three levels. Then, six sub-image libraries are established according to the classification results, and each image library corresponds to upwarping-type 1, upwarping-type 2, upwarping-type 3, downwarping-type 1, downwarping-type 2, and downwarping-type 3. Then, the warping convexity of each sample in the six sub-image libraries is calculated one by one, and then the warping convexity range values ​​of upwarping-type 1, upwarping-type 2, upwarping-type 3, downwarping-type 1, downwarping-type 2, and downwarping-type 3 are determined, including: determining the warping convexity range value corresponding to upwarping-type 1 according to the minimum and maximum values ​​of the warping convexity of the samples in the image library corresponding to upwarping-type 1 Determine the range of warping convexity corresponding to Upward-Type 2 according to the minimum and maximum values ​​of the warping convexity of the samples in the image library corresponding to Upward-Type 2 Determine the range of warping convexity corresponding to Upward-Type 3 according to the minimum and maximum values ​​of the warping convexity of the samples in the image library corresponding to Upward-Type 3 Determine the range of warping convexity corresponding to downwarping-type 1 according to the minimum and maximum values ​​of the warping convexity of the samples in the image library corresponding to downwarping-type 1 Determine the range of warping convexity corresponding to Downward Warping-Type 2 according to the minimum and maximum values ​​of the warping convexity of the samples in the image library corresponding to Downward Warping-Type 2 Determine the range of warping convexity corresponding to downwarping-type 3 according to the minimum and maximum values ​​of the warping convexity of the samples in the image library corresponding to downwarping-type 3

[0060] See also Figure 2 In some embodiments, the calculation of the warping convexity of each sample also includes performing step 401 before extracting the cross-sectional profile of the paperboard: performing image processing on the sample, the image processing includes graying the image of the sample and extracting the region of interest, and extracting the region of interest is conducive to the next step of processing, so that the processing time can be reduced and the accuracy can be increased when extracting the cross-sectional profile of the paperboard.

[0061] See also Figure 2 In some embodiments, the calculation of the warping convexity of each sample also includes step S403 before data fitting based on the extracted cross-sectional profile: performing an image closing operation on the extracted cross-sectional profile, which can bridge narrow discontinuities and fine grooves, eliminate small holes, and fill cracks in the contour line to make the cross-sectional profile smooth.

[0062] It can be understood that when calculating the warpage convexity of each sample, the calculation of one sample can be completed before the calculation of another sample, or the first step operation can be performed on all samples first, and then the next step operation can be performed on all samples until all operations are completed.

[0063] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A method for constructing a warped cardboard template library for a cardboard production line, characterized in that: include: Collect cross-sectional images of cardboard with different warping directions and degrees as samples; Identify the warping direction and degree of the sample and classify the sample according to different warping types and warping levels to obtain classification results; Establishing a sub-image library corresponding to different warping types and warping levels according to the classification results; Calculating the warping convexity of each sample of each sub-image library one by one, and determining the warping convexity range value of the warping type and warping level corresponding to each sub-image library according to the minimum value and maximum value of the warping convexity of the samples of each sub-image library; The calculation of the warpage convexity of each sample includes: Extracting a cross-sectional profile of the paperboard according to the cross-sectional image; Data fitting is performed according to the extracted cross-sectional profile to obtain a quadratic function relationship between the horizontal pixel coordinates of the cross-sectional profile and the vertical pixel coordinates of the cross-sectional profile. The quadratic function relationship is: f(x)=ax 2 +bx+c (1) Where x represents the horizontal pixel coordinate of the cross-sectional profile, f(x) represents the vertical pixel coordinate of the cross-sectional profile corresponding to the x position, and a, b, and c represent constants; Calculating the warping convexity of the sample based on the quadratic function relationship specifically includes: using formula (2) to calculate the warping convexity of the sample, and the formula (2) is as follows: Among them, δ represents the warping convexity of the sample, x a and x b They respectively represent the pixel coordinates of the two endpoints of the horizontal pixel coordinates of the quadratic function of one variable, and x1, x2, and x3 respectively represent the pixel coordinates of the three quarter-divided points of the horizontal pixel coordinates of the quadratic function of one variable.

2. The method for constructing a warped cardboard template library for a cardboard production line according to claim 1, characterized in that: The cross-sectional image is collected by a camera, and the camera is arranged at the exit end of the production line.

3. The method for constructing a warped cardboard template library for a cardboard production line according to claim 1, characterized in that: The Canny edge detection algorithm is used to extract the cross-sectional profile of the cardboard.

4. The method for constructing a warped cardboard template library for a cardboard production line according to claim 1, characterized in that: The acquisition of the one-variable quadratic function relationship is achieved based on the least squares method.

5. The method for constructing a warped cardboard template library for a cardboard production line according to claim 1, characterized in that: The calculation of the warping convexity of each sample also includes performing image processing on the sample before extracting the cross-sectional profile of the paperboard, and the image processing includes graying the sample and extracting a region of interest.

6. The method for constructing a warped cardboard template library for a cardboard production line according to claim 1, characterized in that: The calculation of the warping convexity of each sample also includes performing an image closing operation on the extracted cross-sectional profile before implementing the data fitting based on the extracted cross-sectional profile.

7. The method for constructing a warped cardboard template library for a cardboard production line according to claim 1, characterized in that: The warping types include upward warping and downward warping, the upward warping includes at least three levels, and the downward warping includes at least three levels.

8. The method for constructing a warped cardboard template library for a cardboard production line according to claim 7, characterized in that: The upward warping includes three levels, the downward warping includes three levels, and the classification results include upward warping-type 1, upward warping-type 2, upward warping-type 3, downward warping-type 1, downward warping-type 2 and downward warping-type 3.

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