How to detect defects in cardboard sheets

Abstract

To provide a method for detecting defects of a corrugated board sheet capable of detecting the defects such as stain, tear, and wrinkle with higher accuracy in a shorter processing time in a manufacturing line of the corrugated board sheet.SOLUTION: A back liner surface or a front liner surface of a corrugated board sheet traveling on a manufacturing line is photographed by a camera, and the obtained two-dimensional image (imaging 1 of the corrugated board sheet) is partitioned in a lattice shape to set unit regions 4 each consisting of multiple and the same number of pixels. For each unit area 4, whether or not the corrugated board sheet has the defects is determined on the basis of addition processing for obtaining an addition processing value which is either the total value of gradation values of pixels or an average value obtained by dividing the total value by the number of pixels.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a method for detecting defects such as stains, tears, wrinkles, etc. in a production line for cardboard sheets. [Background technology]

[0002] Corrugated cardboard sheets are generally manufactured by a device called a corrugator. In the corrugator, a single facer bonds a corrugated core to a back liner to produce a single-faced cardboard sheet, and a double facer bonds a single-faced cardboard sheet to a front liner or bonds multiple single-faced cardboard sheets to a front liner to produce a cardboard sheet with a back liner on one side and a front liner on the other side, such as a double-sided cardboard sheet or a multi-sided cardboard sheet. The produced cardboard sheet is scored and cut parallel to the running direction in a slitter-scorer, and then cut to a predetermined length in a direction perpendicular to the running direction.

[0003] When cardboard sheets are manufactured in this manner, defects can occur, such as stains caused by the adhesion of machine oil or glue, tears or wrinkles in the back or front liner, etc. Conventionally, one method for detecting such defects has been to photograph the cardboard sheets with a digital camera and analyze the images.

[0004] Specifically, an image captured by a digital camera is binarized. At this time, a threshold value for detecting dark color defects that are darker than the background color of the cardboard sheet, such as stains caused by machine oil or shadows of wrinkles, and a threshold value for detecting light color defects that are lighter than the background color of the cardboard sheet, such as stains caused by glue adhesion, are set separately, thereby obtaining two types of binarized images. For example, as shown in FIG. 5(a), an image 100 including a dark color defect 101 is binarized, and pixels with a grayscale value equal to or greater than the threshold are converted to "1" and pixels with a grayscale value less than the threshold are converted to "0", thereby obtaining a binarized image 110 in which a black defect image 111 is displayed, as shown in FIG. 5(b). For light color defects, a binarized image in which the defect is displayed in black is obtained by converting pixels with a grayscale value equal to or greater than the threshold to "0" and pixels with a grayscale value less than the threshold to "1".

[0005] In the obtained binarized image, if a pixel determined to be defective (a pixel converted to "0") is isolated, it is considered to be noise, and if the pixels determined to be defective are grouped together in a predetermined range or more, it can be determined that the pixel is a defect that should be detected. For example, as shown in FIG. 5(c), adjacent pixels among the pixels determined to be defective are grouped together. In this example, for identification purposes, the pixels constituting each of the groups 201 to 204 are numbered 1 to 4, and the pixel 200 that is not defective is numbered 0. For the image subjected to such processing, the number of pixels constituting each group, or the length in the X direction, the length in the Y direction, or the area of ​​each group when the two-dimensional coordinate is the XY coordinate, can be compared with a predetermined threshold value to determine that the cardboard sheet has a defect that should be rejected as a defective product. However, in the case of such processing, if the number of pixels determined to be defective or the number of groups to be divided are large, there is a problem that the grouping process and the determination process take a long time.

[0006] In addition, since the image has already gone through a binarization process, there is a problem that defects (light defects) whose color is closer to the background color than the threshold cannot be detected at the binarization stage. In Fig. 5(b), the light parts of the dark color defect 101 in Fig. 5(a) are missing in the binarized image 110, which is shown by dashed lines.

[0007] Furthermore, in a manufacturing line for cardboard sheets, a running cardboard sheet is sandwiched and held from above and below by rotatable press rolls, so that a linear indentation caused by the pressure of the press rolls remains on the cardboard sheet. This indentation is called a "press mark." When a cardboard sheet on which a press mark has been formed is photographed, an image is obtained in which the shadow of the indentation appears as a dark line. Therefore, as shown in FIG. 6(a), when an image 100 having a press mark 105 and a dark color defect 101 is binarized, as shown in FIG. 6(b), an image 115 of the press mark, which is not a defect, is included in the binarized image 110 together with an image 111 of the defect. If a threshold value is set so that the image 115 of the press mark is not included in the binarized image 110, defects as dark as the press mark or lighter than the press mark cannot be detected. Summary of the Invention [Problem to be solved by the invention]

[0008] In view of the above-mentioned circumstances, an object of the present invention is to provide a method for detecting defects in cardboard sheets that can detect defects such as stains, tears, wrinkles, etc. with greater accuracy and in a shorter processing time in a cardboard sheet production line. [Means for solving the problem]

[0009] In order to solve the above problems, the method for detecting defects in cardboard sheets according to the present invention comprises: "The back or front liner of the cardboard sheet traveling on the production line is photographed with a digital camera, The obtained two-dimensional image is divided into a grid to set unit areas each consisting of a plurality of identical pixels; For each unit area, a determination is made as to whether or not the cardboard sheet has a defect based on an addition process that calculates an addition process value that is either the total sum of the pixel gradation values ​​or the average value obtained by dividing the total sum by the number of pixels.

[0010] Conventionally, the presence or absence of defects in a cardboard sheet has been determined by binarizing an image captured by a digital camera, but in the present invention, the presence or absence of defects in a cardboard sheet is determined without binarizing the image.

[0011] Specifically, a two-dimensional image obtained by a digital camera is divided into a grid pattern. The two-dimensional image may be an image captured by a two-dimensional camera, or may be an image captured by a one-dimensional camera synthesized into a two-dimensional image. The unit areas divided into a grid pattern are made to contain multiple and equal numbers of pixels. Then, an addition process is performed for each unit area. The addition process is a process of finding the total value of the gradation values ​​of the pixels contained in the unit area, or a process of finding the average value by dividing the total value by the number of pixels. The addition process value, whether it is the total value or the average value, is unified for all unit areas.

[0012] Since the summation process value (total value or average value) differs between a normal unit area without defects and a unit area with a defect, it is possible to detect defects based on this difference. In the conventional binarization method, it was inevitable that part of the gradation information (shade information) would be lost due to the setting of a threshold, but in the present invention, the information (gradation value) of all pixels is used in the summation process, so a more accurate judgment can be made.

[0013] In addition, while the above-mentioned conventional technology uses a pixel as a processing unit, the present invention uses a unit area consisting of a plurality of pixels as a processing unit, so that the time required for processing can be shortened.Furthermore, in the above-mentioned conventional technology, adjacent pixels among pixels determined to be defective are grouped together, so that if the number of pixels determined to be defective or the number of groups to be divided is large, the grouping process and judgment process take time, whereas the present invention performs addition processing for each unit area with a constant area, so that the time required for processing can be always constant regardless of the number of defects.

[0014] The method for detecting defects in cardboard sheets according to the present invention further comprises the steps of: "The judgment is made by comparing the sum of the unit area to be judged and the other unit areas. "Comparing the sum of the two areas with the sum of the two areas." Yes do.

[0015] The sum processing value of each unit area without defects is the same. On the other hand, if there is a defect in a unit area, the sum processing value of that unit area is different from the sum processing value of a unit area without defects. Here, in most cases, normal cardboard sheets are manufactured without defects at the manufacturing site of cardboard sheets, and defects rarely occur. Therefore, the sum processing value of the unit area to be judged is compared with the sum processing value of the other unit areas. Usually, there is no difference between the sum processing values ​​of the two, and it can be determined that there is no defect. On the other hand, if there is a difference between the sum processing values ​​of the two, it is determined that one of the unit areas has a defect. If there are multiple other unit areas to compare the sum processing value of the unit area to be judged with the unit area to be judged, the presence or absence of a defect in the unit area to be judged can be more accurately determined.

[0016] The method for detecting defects in cardboard sheets according to the present invention further comprises the steps of: "The cardboard sheet has linear press marks made by a press roll. In the determination, the unit area to be determined and the unit area to be compared are Note 2D painting "The image is set so that the positional relationship between the image and the press mark image is the same as that of the original image." Yes do.

[0017] Although a press mark is not a defect, the addition processing value differs between a unit area where a press mark exists and a unit area where a press mark does not exist, even if both are normal and defect-free. Therefore, the conditions related to the press mark must be the same between the unit areas to be compared. A press mark is a pressure mark made by a press roll, and since the position where the press roll is installed in the production line of the corrugated board sheet and the photographing position by the camera are known, it is possible to know where the image of the press mark appears in the photograph, and it is possible to set the unit area to be judged and the unit area to be compared with it so that the positional relationship with the image of the press mark in the two-dimensional image is the same. For example, since a press mark is formed in a straight line as the corrugated board sheet travels, the unit area to be judged and the unit area to be compared with it are set so that they are on the same line in the traveling direction of the corrugated board sheet. Alternatively, if the unit areas divided into a lattice pattern are considered as "rows" that are continuous in the traveling direction of the corrugated board sheet, and multiple rows are considered to be lined up in the width direction (direction perpendicular to the traveling direction) of the corrugated board sheet, it is possible to identify the rows that include the image of the press mark and the rows that do not include it. In this way, when a unit area in which a press mark is present is to be judged, the additive processing value is compared with a unit area belonging to a column in which a press mark is also present, and when a unit area in which a press mark is not present is to be judged, the additive processing value is compared with a unit area belonging to a column in which a press mark is also not present, thereby making it possible to detect defects without being affected by the presence of press marks.

[0018] As described above, the conventional technology that used binarization was unable to detect defects that were as dark as press marks or defects that were lighter than press marks, whereas the present invention is not affected by press marks and can therefore detect defects with greater accuracy than conventional image analysis that uses binarization. Effect of the Invention

[0019] As described above, according to the present invention, a method for detecting defects in cardboard sheets can be provided that can detect defects such as stains, tears, wrinkles, etc. with higher accuracy and in a shorter processing time in a cardboard sheet production line. [Brief description of the drawings]

[0020] [Figure 1] 1 is a diagram showing the arrangement of lighting and cameras relative to a cardboard sheet in a defect detection method according to one embodiment of the present invention; [Diagram 2] 1 is a configuration diagram of a defect detection device used in a defect detection method according to an embodiment of the present invention. [Diagram 3] FIG. 4A is an explanatory diagram of a process for setting a unit area in a two-dimensional image in the defect detection method according to one embodiment of the present invention, and FIG. 4B is an explanatory diagram of an image after addition processing. [Figure 4] 13A and 13B are diagrams illustrating the setting of another unit area to be compared with the unit area to be determined. [Diagram 5] 1A and 1B are diagrams illustrating a conventional defect detection method using binarization and problems associated therewith. [Figure 6] 1A and 1B are diagrams for explaining the problem of press marks in a conventional defect detection method using binarization. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] Hereinafter, a method for detecting defects in cardboard sheets according to one embodiment of the present invention and a defect detection device 20 used in this defect detection method will be described with reference to FIGS. 1 to 4. FIG.

[0022] First, we will explain the configuration of the defect detection device 20. As shown in Figures 1 and 2, the defect detection device 20 is equipped with a light 21 that projects light onto the cardboard sheet 30 while it is traveling on the production line, a camera 22 that takes an image of the cardboard sheet 30 onto which the light is projected, and a computer 40 that judges whether or not the cardboard sheet has a defect based on the image captured by the camera 22.

[0023] The corrugated cardboard sheet to be subjected to defect detection may be a corrugated cardboard sheet with one side being a back liner and the other side being a front liner, such as a double-sided corrugated cardboard sheet or a double-sided corrugated cardboard sheet in which one or more single-sided corrugated cardboard sheets and a front liner are bonded together, or a single-sided corrugated cardboard sheet in which a corrugated core and a back liner are bonded together. When a corrugated cardboard sheet with one side being a back liner and the other side being a front liner is to be subjected to defect detection, the lighting 21 and the camera 22 are installed between the double facer and the slitter scorer in the production line. In this case, both a set of lighting 21 and the camera 22 that projects light onto the back liner and takes an image, and a set of lighting 21 and the camera 22 that projects light onto the front liner and takes an image, may be provided. When a single-sided corrugated cardboard sheet is to be subjected to defect detection, the lighting 21 and the camera 22 are installed between the single facer and the double facer, and light is projected onto the back liner and taken.

[0024] The lighting 21 projects light from a direction inclined with respect to the perpendicular line of the back liner surface or the front liner surface of the cardboard sheet 30. This allows the shadow of a tear or wrinkle to be photographed if the defect is a tear or wrinkle.

[0025] In this embodiment, a line sensor camera is used as the camera 22, and a one-dimensional image is acquired in the width direction of the cardboard sheet, i.e., in the direction perpendicular to the running direction of the cardboard sheet (Y direction in the figure). The one-dimensional image acquired as the cardboard sheet runs is transmitted to the computer 40. The scanning period of the line sensor camera (the time it takes to store one line's worth of signals) is generally very short compared to the scanning period of a two-dimensional camera (area camera). One-dimensional images are continuously acquired as the cardboard sheet runs at high speed, and a two-dimensional image can be formed at high speed by arranging the acquired one-dimensional images. In addition, the camera 22 is one in which the light receiving elements are arranged in a length sufficient to capture one-dimensional images over the entire width of the cardboard sheet 30, even if the width length is changed due to a change in the type of the cardboard sheet 30.

[0026] The computer 40 comprises, as hardware components, a storage device made up of a main storage device and an auxiliary storage device, and a central processing unit (CPU) that performs processing according to programs stored in the storage device.

[0027] The memory device stores an image processing program that causes the computer 40 to function as image processing means 41 that forms a two-dimensional image from the one-dimensional image acquired by the camera 22, and a judgment processing program that causes the computer 40 to function as judgment means 42 that judges whether or not the cardboard sheet has a defect based on the formed two-dimensional image.

[0028] The storage device can store one-dimensional image data transmitted from the camera 22, two-dimensional image data after image processing, information on unit areas set on the two-dimensional image, reference values ​​such as thresholds used for judgment, information on defects detected as a result of the judgment, etc.

[0029] The defect inspection device 20 further comprises an output device 25 such as a monitor or printer that displays the process and results of processing by the computer 40, and an input device 24 such as a keyboard or pointing device that inputs various commands and reference values ​​such as thresholds to the computer 40. In addition, the defect inspection device 20 is equipped with an alarm device 26 that notifies of the occurrence of an abnormality based on the determination that a defect exists in the cardboard sheet 30.

[0030] The computer 40 of this embodiment is connected to the production management device 27 of the manufacturing line and the manufacturer's office computer 28 so as to be able to communicate by wire or wirelessly. Information about the cardboard sheets, such as width and length, can be input from the office computer 28 to the computer 40, and the process and results of processing by the computer 40 can be transmitted from the computer 40 to the office computer 28. Alternatively, the information about the cardboard sheets and the reference values ​​for judgment can be transmitted from the office computer 28 to the production management device 27, stored in the production management device 27, and transmitted from the production management device 27 to the computer 40.

[0031] In the mechanical configuration of the production line, an encoder 23 is attached to a point that rotates in synchronization with the mechanism that drives the travel of the cardboard sheet. An electrical signal from the encoder 23 is sent to a computer 40, and the coordinates in the two-dimensional image are associated with the actual position on the cardboard sheet 30 based on the positional relationship between the point photographed by the camera 22 and the encoder 23.

[0032] Next, a method for detecting defects in a cardboard sheet using the defect detection device 20 configured as described above will be described. In the method for detecting defects in a cardboard sheet of this embodiment, light is projected from a light source 21 onto a cardboard sheet 30 traveling on a production line, a one-dimensional image taken by a camera 22 is converted into a two-dimensional image by image processing, an image 1 of the cardboard sheet as shown in Fig. 3(a) is obtained, and a judgment is made as to whether or not the cardboard sheet has a defect by processing based on a judgment processing program. The image 1 of the cardboard sheet can be, for example, an 8-bit (256 gradations) image.

[0033] Here, Figure 3(a) shows a schematic diagram of a case where an image 1 of a cardboard sheet includes an image of a light-color defect 2 that is lighter than the background color of the cardboard sheet, an image of a dark-color defect 3 that is darker than the background color of the cardboard sheet, and an image of a press mark 5 that is a pressure mark made by a press roll.

[0034] First, as a determination process, as shown by the dashed lines in Fig. 3(a), the image 1 of the cardboard sheet is divided into a grid by multiple lines parallel to the running direction Y of the cardboard sheet and multiple lines perpendicular to the lines. Each unit area 4 divided into a grid contains multiple identical pixels.

[0035] Next, an addition process is performed to find an addition processing value for each of the unit areas 4 partitioned into a grid pattern. The addition processing value is the total grayscale value of the pixels contained in each unit area 4, or the average value obtained by dividing this total value by the number of pixels constituting the unit area. When the total value is used as the addition processing value, the total value is found for all unit areas, and when the average value is used as the addition processing value, the average value is found for all unit areas. By finding the addition processing value in this way, the image 1 of the cardboard sheet is converted into a post-addition processing image 10 as shown in Figure 3(b).

[0036] In image 10 after the addition process, the addition process value of unit areas 4 without defects is different from the addition process value of unit areas 4 where defects are present, but even in unit areas 4 without defects, the addition process value is different between unit areas 4 that include an image of a press mark 5 and unit areas 4 that do not include an image of a press mark 5. If we consider that "rows" of unit areas 4 continuing in the running direction Y of cardboard sheet 30 are lined up in multiple rows in the width direction of cardboard sheet 30, in image 10 after the addition process shown in Figure 3 (b), unit areas 4 belonging to rows L1, L3, and L5 contain images of press marks 5, and therefore have smaller addition process values ​​than unit areas 4 belonging to rows L2, L4, and L6 that do not include images of press marks 5.

[0037] In addition, unit area 12(4) including an image of a light-colored defect 2 has a larger additive processing value than unit area 4 without a defect, and unit area 13a(4) and unit area 13b(4) including images of a dark-colored defect 3 have smaller additive processing values ​​than unit area 4 without a defect.

[0038] The determination of whether a defect exists in a certain unit area can be performed by comparing the sum processing value of the unit area to be determined with that of other unit areas. In this case, the other unit areas to be compared can be unit areas adjacent to the unit area to be determined. For example, when the unit area 4a(4) is determined as the determination object as shown in FIG. 4(a), the sum processing value is compared with that of the adjacent unit areas 4b(4) and 4c(4) belonging to the same row L6. Since these three unit areas have the same positional relationship with the image of the press mark 5, the sum processing value is the same when no defect exists. Therefore, it can be determined that no defect exists in the unit area 4a(4) when the absolute values ​​of the difference between the sum processing value of the unit area 4a(4) and the sum processing value of the unit area 4b(4), and the difference between the sum processing value of the unit area 4a(4) and the sum processing value of the unit area 4c(4) are smaller than a predetermined threshold value.

[0039] On the other hand, when the unit area to be judged is one in which a defect exists, such as unit area 12(4), by comparing the sum processed values ​​with those of adjacent unit areas 4d(4) and 4e(4) belonging to the same column L2, the absolute values ​​of the differences in both cases are equal to or greater than a predetermined threshold value, and it can be determined that a defect exists in unit area 12(4).

[0040] Depending on the size of the unit area, the eight unit areas surrounding the unit area to be judged may be the same in terms of whether or not they contain an image of the press mark 5. In such a case, the difference between the summation processing value of the unit area to be judged and the summation processing values ​​of the eight surrounding unit areas is calculated, and if the number of times that the absolute value is equal to or greater than a predetermined threshold (the number of combinations of the unit area to be judged and the surrounding unit areas) is smaller than a predetermined number, it is judged that there is no defect in the unit area to be judged, and if the number is equal to or greater than the predetermined number, it is judged that there is a defect in the unit area to be judged. In this way, by increasing the number of the unit areas to be compared, it is possible to prevent the judgment result from being affected by a difference in the summation processing values ​​between the two due to a defect in the unit area to be compared, even if there is no defect in the unit area to be judged.

[0041] Furthermore, depending on the relationship between the size of the unit area and the size of the defect, when a defect exists in a certain unit area to be judged, there is a high probability that a defect also exists in an adjacent unit area. In such a case, a unit area that is the same as the unit area to be judged in terms of whether it contains an image of the press mark 5 or not and is separated from the unit area to be judged is set as a comparison target based on a certain rule. In this case, an example of the rule is "a unit area belonging to the same column and separated by N units." For example, in FIG. 4(b), when a unit area 13b(4) having a defect is to be judged, the addition processing value is compared with that of a unit area 4f(4) belonging to the same column L4 and separated from the unit area 13a(4) instead of being set as a comparison target. In this way, even if there is a high probability that the defect spans multiple unit areas, the defect can be accurately detected.

[0042] As described above, the judgment process by comparing the sum processing value of the unit area to be judged with the sum processing value of other unit areas is based on the assumption that in most cases, normal cardboard sheets are manufactured without defects at the manufacturing site of the cardboard sheets, and defects rarely occur, that is, the number of unit areas without defects is overwhelmingly greater than the number of unit areas with defects. If such a situation is not based on the assumption, defects can also be detected by comparing the sum processing value of the unit area to be judged itself with a predetermined threshold value without comparing it with other unit areas. In this case, the threshold value can be an upper threshold value and a lower threshold value obtained by plus or minus an allowable numerical range to the sum processing value of a normal unit area without a defect. In addition, a threshold value is separately determined for a normal unit area including an image of the press mark 5 and a normal unit area not including an image of the press mark 5, and the corresponding threshold value is used depending on whether the unit area to be judged is located at a position including the image of the press mark 5 or not.

[0043] In this way, by comparing the sum processed value itself of the unit area to be judged with the threshold value, it is possible to accurately detect defects, even when the defects exist over a relatively wide range.

[0044] Furthermore, when comparing the summed value of the unit area being judged with the threshold value in this manner, if the summed value is an average value rather than a total value, the same threshold value can be used regardless of the size of the unit area.

[0045] When a unit area containing a defect is detected, the number of unit areas containing defects within a certain range set in advance on the cardboard sheet is counted. Then, when the number reaches or exceeds a predetermined threshold, that range on the cardboard sheet is determined to be a defective product containing an unacceptable defect, and a defect determination signal is sent from computer 40 to alarm device 26. Upon receiving the signal, alarm device 26 issues an alarm by turning on or blinking a warning light or emitting an alarm sound. At the same time, the range of cardboard sheet 30 determined to be defective is identified based on the signal from encoder 23, and is output from output device 25.

[0046] As described above, according to the method for detecting defects in cardboard sheets of this embodiment, defects such as stains, tears, wrinkles, etc. can be detected more accurately and in a shorter processing time on a cardboard sheet production line.

[0047] The present invention has been described above with reference to preferred embodiments, but the present invention is not limited to the above embodiments, and various improvements and design changes are possible without departing from the spirit of the present invention, as described below.

[0048] For example, the shape of the unit area set by dividing the two-dimensional image into a grid is illustrated as a square, but is not limited to this and can be a rectangle. The dimensions and shape of the unit area can be set by taking into consideration the balance between the time required for the length in the Y direction of the two-dimensional image formed from the one-dimensional image captured by the line sensor camera as the cardboard sheet travels to become equal to the length in the Y direction of the unit area, and the time required to perform the determination process over the entire width of the cardboard sheet. [Explanation of symbols]

[0049] 1. Imaging of cardboard sheets 2. Light-colored defects 3. Dark color defects 4 Unit Area 5 Press Mark 10 Image after addition processing 21 Lighting 22 Camera 30 Corrugated cardboard sheets

Claims

[Claim 1] The back or front liner of the cardboard sheet traveling on the production line is photographed with a digital camera, The obtained two-dimensional image is divided into a grid to set unit areas each consisting of a plurality of identical pixels; For each of the unit areas, a determination is made as to whether or not the cardboard sheet has a defect based on an addition process that obtains an addition process value that is either a total sum of pixel gradation values ​​or an average value obtained by dividing the total sum by the number of pixels; The cardboard sheet has linear press marks which are impressions made by a press roll, When the determination is made by comparing the sum-processed value of the unit area to be determined with the sum-processed value of the other unit areas, The unit area to be judged and the unit area to be compared are set so that their positional relationship with the image of the press mark in the two-dimensional image is the same. A method for detecting defects in cardboard sheets.

Images