Method and system for automatic scrub resistance testing

Abstract

The present disclosure provides a method for automatic scrub resistance testing, the method comprising the steps of: (a) capturing a series of digital images of at least a portion of a test specimen, where the test specimen is located on a substrate surface of a machine and a scrubbing device is scrubbing the test specimen; (b) analyzing each section of the image to determine that the corresponding region is worn; (c) receiving a test result comprising a wear cycle. From the intensity values of a segment in at least m consecutive images in the series, the segment is detected as wear.

Description

Technical Field

[0001] This disclosure relates generally to the testing of materials, and more specifically to methods and systems for automatically testing the scrub resistance of coatings applied to a substrate. Background Technology

[0002] Scrub resistance is the ability of a paint or similar film or material coating to resist abrasive cleaning that can wear down or degrade the paint or film from its surface. Scrub resistance testing is a rigorous acceptance test for evaluating the performance of paint formulations.

[0003] Scrub resistance testing is typically performed according to standard ASTM D2486 or its industry-accepted variations, and requires significant time and operator attention during the test. Test specimens are prepared by scraping paint onto a black plastic sheet and then conditioning it in a temperature and humidity controlled chamber as needed. Different procedures may be used to prepare specimens depending on the specific test.

[0004] Typically, such specimens are then mounted in a scrubbing machine. The machine is started, and the scrubbing brush moves back and forth across the specimen. A scrubbing medium is applied during the test. The machine counts the number of cycles the scrubbing brush makes, and the operator observes the specimen to determine when a certain degree of wear is observed.

[0005] The aim is to provide an automated scrub resistance testing system for monitoring specimen wear, which requires no operator intervention during testing and provides rapid, consistent, and accurate test results. Summary of the Invention

[0006] The following is a simplified overview of one or more aspects to provide a basic understanding of these aspects. This overview is not an exhaustive summary of all anticipated aspects and is neither intended to identify key or essential elements of all aspects nor to describe the scope of any or all aspects. The sole purpose of this invention is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that follows.

[0007] According to one embodiment of this disclosure, a method for an automated scrub resistance test is provided, the method comprising the steps of: (a) capturing a series of digital images of at least a portion of a test specimen, wherein the test specimen is located on a substrate surface of a machine and a scrubbing device is scrubbing the test specimen; (b) analyzing each segment of the images to determine the corresponding area that is worn; and (c) receiving test results comprising multiple wear cycles; wherein a segment is detected as worn based on the intensity value of a segment in at least m consecutive images in the series; wherein m is an integer and 1 ≤ m ≤ 20, preferably 3 ≤ m ≤ 10.

[0008] According to one embodiment, an automated scrub resistance testing system for monitoring specimen wear is provided, the automated scrub resistance testing system comprising: a scrubbing machine having a scrubbing device mounted to move over a defined path, wherein a coated area on a substrate is adapted to be placed in the defined path on the scrubbing device; an image acquisition machine located over the defined path in a test monitoring area; and an image analysis system performing image analysis according to the method described in accordance with aspects of this disclosure.

[0009] According to one embodiment, a computer system is provided, the computer system including one or more processors and one or more storage devices storing computer-executable instructions, which, when executed, cause the one or more processors to perform the methods described according to aspects of this disclosure.

[0010] According to one embodiment, one or more computer-readable storage media are provided that store computer-executable instructions, which, when executed, cause one or more processors to perform the methods described according to aspects of this disclosure.

[0011] According to one embodiment, a computer program product including computer-executable instructions is provided, which, when executed, cause one or more processors to perform the method described according to aspects of this disclosure. Attached Figure Description

[0012] The disclosed aspects will be described below in conjunction with the accompanying drawings, which are provided for illustration and not limitation of the disclosed aspects.

[0013] Figure 1 A perspective view of an automated scrub resistance testing system according to one embodiment is shown.

[0014] Figure 2 An exemplary scrubbing machine according to one embodiment is shown.

[0015] Figure 3 An exemplary automated scrub resistance testing system according to one embodiment is shown.

[0016] Figure 4A and Figure 4B An exemplary scrubbing media delivery system according to one embodiment is shown.

[0017] Figure 5A and Figure 5B An exemplary process for image analysis of wear detection in an automated scrub resistance testing method according to one embodiment is shown.

[0018] Figure 6An exemplary process for image analysis of wear detection in an automated scrub resistance testing method according to one embodiment is shown.

[0019] Figure 7A and Figure 7B An exemplary process for determining the inspection area of ​​a single coating or parallel coatings, according to one embodiment, is shown.

[0020] Figures 8A to 8C An exemplary process for determining the inspection area of ​​a parallel coating, according to one embodiment, is shown.

[0021] Figure 9 An exemplary method for automated scrub resistance testing according to one embodiment is shown.

[0022] Figure 10 An exemplary computing system according to one implementation is shown. Detailed Implementation

[0023] This disclosure will now be discussed with reference to several exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and thus implement embodiments of this disclosure, and are not intended to imply any limitation on the scope of this disclosure.

[0024] Various embodiments will be described in detail with reference to the accompanying drawings. Wherever possible, the same reference numerals will be used throughout the drawings to refer to the same or similar parts. References to specific examples and embodiments are for illustrative purposes and are not intended to limit the scope of this disclosure.

[0025] Figure 1A perspective view of an automated scrub resistance testing system according to one embodiment is shown. The automated scrub resistance testing system 1 is used to monitor a sample comprising one or more test materials located on one or more substrate surfaces. The automated scrub resistance testing system 1 includes a scrubber 10, which includes four test beds 110 for simultaneously testing four substrates. It should be understood that in other embodiments, other numbers of test beds may be present in the automated scrub resistance testing system. The automated scrub resistance testing system 1 includes a robotic arm 20 configured for picking up and placing. For example, the robotic arm 20 can automatically pick up a substrate and place it onto the test beds 110 of the scrubber 10. The automated scrub resistance testing system 1 includes four cameras 30 configured to monitor the wear condition of the four substrates placed in the test beds during scrub testing. It should be understood that in other embodiments, other numbers of cameras may be present. The automated scrub resistance testing system 1 includes a scrubbing medium container 40 configured to deliver a scrubbing medium (such as a slurry) to the scrubber 10. In one example, the scrubbing medium container 40 is designed to perform ASTM scrubbing tests for up to 24 hours. The automated scrubbing resistance testing system 10 includes eight brushes 50, four of which are used for the current test, while the other four will be used for the next round of testing. That is, the first set of four brushes and the second set of four brushes are used alternately in the current test and the next round of testing. This configuration of brushes helps to eliminate brush fatigue when the automated scrubbing resistance testing system 10 operates continuously without stopping. The automated scrubbing resistance testing system 10 includes a substrate recycling bin 60. When the substrate has finished testing, it can be removed from the test bed 110 by a robotic arm 20 and stacked in the substrate recycling bin 60. The automated scrubbing resistance testing system 10 includes a new substrate loading bin 70. New substrates can be loaded into bin 70 for scrubbing tests. The automated scrubbing resistance testing system 10 may also include a recycling bin 80 for storing other reusable tools. The automated scrubbing resistance testing system 10 includes a control unit 90. The control device 90 can be communicatively connected to other parts of the automatic scrub resistance testing system 1 to control the operation of those other parts. The control device 90 can be implemented by a computer including at least one processor and at least one memory, which, when executing a computer program, can control the operation of the automatic scrub resistance testing system 1. By using... Figure 1 The wear testing system 1 of the implementation scheme can automatically and continuously perform the test of the sample, so it can perform a large number of test tasks in an efficient manner without requiring too much manpower.

[0026] Examples of test samples can be inks, coatings, and adhesives typically applied to various substrates, including plastic films, paper, metals, concrete, glass, and wood. According to a preferred embodiment, the test sample is a coating derived from a polymer dispersion.

[0027] Figure 2 A top view of an exemplary scrubbing machine according to one embodiment is shown. The scrubbing machine 10 includes a test bed 110 in which a sample or substrate to be tested is placed. The sample 130 includes one or more test materials located on a substrate surface 120 of the substrate. It should be understood that, for illustrative purposes, [the following is unclear and likely refers to a different document or diagram]. Figure 2 The embodiment shown only has one test bed 110. The scrubbing machine 10 may have one or more test beds 110. For example, in Figure 1 The scrubbing machine in the illustrated implementation has four test beds.

[0028] like Figure 2 As shown in the embodiment, sample 130 is in the form of four coatings, which are applied side-by-side to the substrate surface 120 of the substrate. The scrubbing machine 10 includes a scrubbing device 140, which is mounted to move over a defined path 150 on which sample 130 is placed. Although not in Figure 2 As shown, the scrubbing device 140 includes a brush that moves back and forth along a path 150 to repeatedly scrub the specimen 130, where the path 150 represents an area that can be scrubbed by the brush of the scrubbing device 140. During the scrubbing, the test inspection area 136 is monitored to check for abrasion on the coating 130. The brush can be one of the brushes 50 used in the current test. It should be understood that the scrubbing machine 10 can be any suitable scrubbing machine available on the market that moves the brush according to the requirements of a scrubbing resistance test standard. Examples of such scrubbing resistance test standards can include ASTM-D2486 or GB-T9266, such as ASTM-D2486 (2017) or GB-T9266 (2009). For example, the scrubbing machine 10 can move the brush at fixed intervals (such as 37 cycles per minute) and pump 10 grams of scrubbing media to the specimen 130 every 400 cycles.

[0029] Figure 3 This is a schematic block diagram illustrating an exemplary automated scrub resistance testing system according to one embodiment. The automated scrub resistance testing system 300 can be as follows: Figure 1 The diagram shows a simplified representation of the automated scrub resistance testing system 1. The automated scrub resistance testing system 300 includes a scrubbing machine 10, in... Figure 3 The middle shows along Figure 2 The sectional view of the scrubbing machine is taken from line 2-2, in which... Figures 1 to 3The same reference numerals in the figures denote the same parts. The scrubbing medium delivery system 40 is configured to deliver a scrubbing medium (such as a slurry) to the scrubbing machine 10. It should be understood that the scrubbing medium delivery system 40 may be part of the scrubbing machine 10 or may be part of the exterior of the scrubbing machine 10. The scrubbing medium may be a standard abrasive scrubbing medium used for testing paint samples, or it may be a polishing compound, abrasive grit, acid or etching medium, detergent, soap, or water. Testing can also be performed without a scrubbing medium, using only the scrubbing device 140. Although not explicitly stated in the figures... Figure 3 As shown, however, the scrubbing medium delivery system 40 may include a pump with hoses to load the scrubbing medium onto the sample 130. For example, the pump of the scrubbing medium delivery system 40 may draw scrubbing medium from a container and pump it through hoses to the scrubbing machine 10. A peristaltic pump is typically used to load the scrubbing medium onto the sample 130, pumping the scrubbing medium at fixed amounts and intervals according to commands from a controller. Although only one scrubbing machine 10 is shown in the automated scrubbing resistance testing system 300, it should be understood that the automated scrubbing resistance testing system 300 may include multiple scrubbing machines 100 operating in parallel, and the scrubbing medium delivery system 40 may utilize multiple hoses to simultaneously load the scrubbing medium onto multiple scrubbing machines 100.

[0030] Figure 4A and Figure 4B An exemplary scrubbing media delivery system according to one embodiment is shown. Peristaltic pumps typically operate by squeezing a hose, which is prone to clogging by scrubbing media such as slurry. When the hose is partially clogged, the amount of scrubbing media loaded is less than the target weight, resulting in variations for test loads of slurry. The scrubbing media delivery system 40 includes a scrubbing media container 1710, a valve 1720, and a cylinder 1730 with a movable seal 1735. The valve 1720 has two ports 1721 and 1722. Figure 4A In the indicated state, valve 1720 is positioned such that two ports 1721 and 1722 connect container 1710 to cylinder 1730, and the seal moves a fixed distance in the indicated direction to pump a fixed amount of scrubbing medium from container 1710 into cylinder 1730. Valve 1720 is then controlled to rotate as follows: Figure 4B The positions shown connect the cylinder 1730 to the output terminal 1723 via ports 1721 and 1722, and the seal moves a fixed distance in the indicated direction to pump a fixed amount of scrubbing medium from the cylinder 1730 to the output terminal 1723. Although not in Figure 4A and Figure 4BAs shown, however, a hose can be connected to the output end 1723 and deliver the scrubbing medium to the sample 130 being tested. By using the structure of the scrubbing medium delivery system 40, the scrubbing medium delivery system 40 can pump out the same amount of scrubbing medium, even when the hose connected to the output end is slightly blocked, because the seal 1735 and the cylinder 1730 can ensure the volume of the pumped-in and pumped-out cylinders.

[0031] The automated scrub resistance testing system 300 includes one or more cameras 30 positioned above a specimen 130. In one embodiment, multiple cameras 30 may be deployed, each configured to monitor one of a plurality of test areas 136, such as... Figure 2 As shown. In one embodiment, a camera 30 may be deployed to monitor all test areas 136. It should be understood that aspects of this disclosure are not limited to the number and deployment of cameras 30; one or more cameras 30 may be deployed to monitor test areas 136 of one or more coatings 130 on one or more scrubbing beds 110. A light source 190 may be deployed near the camera 30 to provide illumination for imaging by the camera 30. It should be understood that the light source 190 may also be integrated into the camera 30.

[0032] The automated scrub resistance testing system 300 includes a control device 90. The control device 90 can be communicatively connected to other parts of the automated scrub resistance testing system 300 to control the operation of those other parts. The control device 90 can be implemented by a computer including at least one processor and at least one memory, which, when executing a computer program, can control the operation of the automated scrub resistance testing system 300.

[0033] The control device 90 can control the scrubbing machine 10 and the camera 30 to operate in coordination. For example, when the scrubbing device 140 moves to the end of the path 150, the control device 90 controls the camera 30 to pick up an image of the sample 130, so that an image of the test area 136 can be obtained without being covered by the scrubbing device 140. In one example, a stroke position sensor can be deployed in the scrubbing machine 10 to detect the position of the scrubbing device 140 and send that position to the control device 90, which then controls the camera 30 to pick up an image when the brush 140 is at the end of its path 150. The control device 90 can further analyze the images received from the camera 30 to detect wear on the sample and provide analytical data such as the number of cycles the scrubbing device 140 moves back and forth until wear occurs and the magnitude of the wear. It should be understood that the control device 90 may include user input devices such as a keyboard and user output devices such as a display. For example, a user can set parameters for the operation of the automated scrubbing resistance testing system 300 via the input devices and can view data such as images and analysis results via the output devices.

[0034] Figure 5A and Figure 5B An exemplary process for image analysis for an automated scrub resistance testing method according to one embodiment is shown.

[0035] The control device 90 is configured to initiate an automated scrub resistance test process, including the operation of the scrubbing machine 10, the scrubbing medium delivery system 40, the camera 30, etc. Once the test process begins, the control device 90 receives an image from the camera 30 at step 510. As illustrated above, when the brush 140 is at the end of the path 150, the camera 30 can capture an image of the sample 130. For ease of explanation, we will use... Figure 2 The automatic scrub resistance test process is described using the leftmost test area 136 of the four test areas shown as an example. It should be understood that all test areas can be treated in a similar manner. In a first embodiment, an image of the leftmost test area 136 is captured when the brush 140 is at any end of path 150. In a second embodiment, an image of the leftmost test area 136 is captured when the brush 140 is at the opposite end of path 150, i.e., when the brush 140 is at the right end of path 150. In a third embodiment, an image of the leftmost test area 136 is captured when the brush 140 is at the same end of path 150, i.e., when the brush 140 is at the left end of path 150. Slurry accumulates at both ends of the brush movement path 150 because the brush 140 carries the slurry back and forth from one end to the other, in such a way that the opposite ends of the brush 140 are covered with a thicker slurry than the same ends of the brush. That is, when the brush 140 moves from the left end to the right end... Figure 2 and Figure 3 When the brush 140 is positioned at the right end, the test area at the left end, which is the opposite end of the brush 140, is covered with a thicker slurry than the test area at the right end, which is the same end of the brush 140. Similarly, when the brush 140 is positioned at the left end after being moved from the right end to the left end, the test area at the right end, which is the opposite end of the brush 140, is covered with a thicker slurry than the test area at the left end, which is the same end of the brush 140. Therefore, in the third embodiment, an image of the test area is captured when the brush 140 is located at the same end of the test area. Taking the leftmost test area 136 as an example, the image of the leftmost test area 136 is captured when the brush 140 is at the left end. In this way, an image of the leftmost test area 136 is captured when the leftmost test area 136 is covered with less slurry, which is advantageous for detecting worn pixels because less accumulated slurry covers the leftmost test area 136.

[0036] The control device 90 buffers the received images in an image queue at step 520 and calculates a standard image based on the number p of the buffered images at step 530. In one embodiment, the captured images are buffered at step 520. In another embodiment, an image region of the test area 136 may be obtained from the captured images, and only the images including the test area 136 are buffered. In one embodiment, at step 530, the intensities of the first p buffered images among the buffered images are averaged to obtain an average image, and then the intensity of the average image is multiplied by a factor f1 to obtain the standard image. The intensity of the corresponding pixel in the standard image can be used as the corresponding threshold to detect whether a pixel in the image can be used as a worn pixel. In the automatic scrub resistance test system 300, the problem is the uneven brightness above the test area 136. In particular, the closer to the light source 190, the higher the brightness, and the farther from the light source 190, the lower the brightness. The standard image obtained at step 530 provides a corresponding threshold for each pixel inside the test area 136, thereby solving the problem caused by the uneven brightness from the light source 190. The number p of the buffered images and the factor f1 can be preconfigured. In one embodiment, the number p can be an integer selected from the range 1 ≤ p < 200, and the factor f1 can be a floating-point number selected from the range 0.1 ≤ f1 < 1 or 1 < f1 < 10. The number p can be preconfigured based on the thickness of the test specimen 130. In one embodiment, when the thickness of the test specimen 130 is less than 50 micrometers (μm), the number p can be an integer selected from the range 1 ≤ p ≤ 20. In one embodiment, when the thickness of the test specimen 130 is between 50 μm and 150 μm, the number p can be an integer selected from the range 21 ≤ p ≤ 50. In one embodiment, when the thickness of the test specimen 130 is greater than 150 μm, the number p can be an integer selected from the range 51 ≤ p < 200. In one embodiment, when the intensity of the pixel of the average image is higher than the intensity of the substrate surface 120, the factor f1 can be a floating-point number selected from the range 0.1 ≤ f1 < 1. In one embodiment, when the intensity of the pixel of the average image is lower than the intensity of the substrate surface 120, the factor f1 can be a floating-point number selected from the range 1 < f1 < 10.

[0037] At step 540, the control device 90 continues to receive images from the camera 30 and buffers these images at step 550. As described above, the buffered images can be captured images or images that only include the test area 136. The buffer used at step 550 can be a first-in-first-out (FIFO) buffer, which can contain m of the latest consecutive images. At step 560, the control device 90 can average the intensity of the m buffered images to obtain an average image. In the automated scrub resistance testing system 300, air bubbles may appear and scrubbing media may temporarily accumulate in the test area 136 as the brush 140 moves with the provided scrubbing medium. The problem is that air bubbles and accumulated scrubbing medium (such as slurry) will create shadows inside the test area. The pixel values ​​inside these shadows may be smaller than the pixel values ​​inside the wear area, and therefore may introduce noise into the detection of wear pixels. Furthermore, as described in the third embodiment above, when the brush 140 is at the same end as the test area 136, acquiring an image of the test area 136 will be beneficial for detecting worn pixels because less accumulated slurry covers the test area. The problem with this embodiment is that synchronization between the camera 30 and the brush movement may be lost once in thousands of iterations. When this occurs, the brush's shadow or even the brush itself may enter the test area 136. Pixel values ​​inside the shadow or inside the brush may be smaller than pixel values ​​inside the worn area, and therefore may introduce noise into the detection of worn pixels. The average image obtained at step 560 is used to mitigate noise caused by possible bubbles and shadows, as explained in the embodiments above. In one embodiment, for most cases, the number m of the latest consecutive images is an integer chosen between 3 and 10. For example, the number m can be set to 5. In one embodiment, for high-noise situations, such as thick slurry accumulation, a large number of bubbles covering the test sample 130, frequent loss of synchronization between scrubbing brush movement and image acquisition, the number m of the latest consecutive images is an integer chosen between 10 and 20. In one implementation, the number m of the latest consecutive images is an integer chosen between 1 and 20.

[0038] At step 570, the control device 90 may perform a pixel-by-pixel analysis on the average image to identify worn pixels. Figure 5B The image analysis process at step 570 according to one embodiment is illustrated. At step 5710, for each pixel in the average image obtained at step 560, if 1) the intensity value of each pixel is lower than the intensity value of the corresponding pixel in the standard image obtained at step 530 and higher than the intensity of the substrate surface on which the sample is coated, or 2) the intensity value of each pixel is higher than the intensity value of the corresponding pixel in the standard image obtained at step 530 and lower than the intensity of the substrate surface on which the sample is coated, then the counter value of the corresponding pixel is incremented by 1. Figure 2 Taking the leftmost test area 136 as an example, the counter value of test area 136 can be implemented by a matrix having rows and columns of counter values ​​corresponding to the rows and columns of pixels in test area 136. This matrix with counter values ​​can be called a voting matrix. Then, at step 5710, for each pixel in the average image obtained at step 560, if 1) the intensity value of each pixel is lower than the intensity value of the corresponding pixel in the standard image obtained at step 530 and higher than the intensity of the substrate surface of the substrate on which the sample is coated, or 2) the intensity value of each pixel is higher than the intensity value of the corresponding pixel in the standard image obtained at step 530 and lower than the intensity of the substrate surface of the substrate on which the sample is coated, the counter value of the corresponding pixel is increased by 1. At step 5720, for each pixel in the average image obtained at step 560, if the counter value corresponding to each pixel reaches a counter threshold, the corresponding pixel is determined to be a worn pixel. The worn pixels can then be identified in the voting matrix. The averaged image obtained at step 560 is used to mitigate noise caused by possible bubbles and shadows, as explained in the above embodiments. However, using only the averaged image obtained at step 560 may not always reliably remove noise, especially for noise caused by random loss of synchronization between the scrubbing brush motion and image acquisition. A counter threshold employed at step 5720 is used to further remove noise caused by possible bubbles and shadows. In one embodiment, for most cases, the counter threshold is an integer chosen between 5 and 15. For example, when the quantity m can be set to 5, the counter threshold can be set to 10. In one embodiment, for high-noise cases, the counter threshold is an integer chosen between 15 and 30.

[0039] At step 580, the control device 90 determines the region formed by the wear pixels based on the voting matrix and determines the size of the region. For example, the control device 90 may identify one or more regions, each of which is formed by connected wear pixels in the voting matrix. The control device 90 may also determine the width and length of each region. Based on the image resolution and the camera's view size, the physical length and width of the test region can be converted into the number of pixels in the image; that is, one pixel in the captured image can represent a physical distance. For example, in one embodiment, one pixel corresponds to 0.0794 millimeters (mm). Therefore, the width and length of each region can be represented by the number of pixels in the horizontal and vertical directions of that region, and also by the physical distance converted from the number of pixels in the horizontal and vertical directions of that region. The horizontal direction may refer to the direction in which the brush 140 moves back and forth.

[0040] At step 590, control device 90 determines whether the size of any region formed by the connected worn pixels is greater than a threshold size, which may include a first threshold and a second threshold. The first and second thresholds may be predefined parameters. In one implementation, the first and second thresholds may be defined in a scrub resistance test standard, examples of which include ASTM-D2486, GB-T9266, etc. For example, in the example above, the first and second thresholds are set to 5 mm and 0.23 mm, corresponding to a length of 63 pixels and a width of 3 pixels, respectively, with one pixel corresponding to 0.0794 mm. If the width and length of the region identified in step 580 are both greater than the first and second thresholds, control device 90 determines that the test area 136 of coating 130 has been worn, and at step 595 records the number of cycles the brush 140 has moved back and forth since the start of the test. Furthermore, control device 90 may also record the size of the identified worn area. Control device 90 may perform other operations, such as displaying the test results to a user. If the judgment at step 590 is negative, the process returns to step 540 to repeat the operations from step 540 to step 590.

[0041] Figure 6 An exemplary process for an automated scrub resistance testing method according to one embodiment is shown.

[0042] The control device 90 is configured to initiate an automated scrub resistance test process, including the operation of the scrubbing machine 10, the scrubbing medium delivery system 40, the camera 30, etc. Once the test process begins, the control device 90 receives an image from the camera 30 at step 610. As illustrated above, the camera 30 can capture an image of the sample 130 when the brush 140 is at the end of the path 150.

[0043] At step 620, the control device 90 buffers the received images in an image queue. The control device 90 calculates a standard image based on the number q of the latest consecutive images of the buffered images at step 630, and calculates an average image based on the number m of the latest consecutive images of the buffered images at step 640, where m < q. In one embodiment, at step 630, the intensities of the last q buffered images in the buffered images are averaged to obtain an average image, and then the intensity of the average image is multiplied by a factor f2 to obtain a standard image. The intensity of the corresponding pixel in the standard image can be used as the corresponding threshold to detect whether a pixel in the image can be used as a worn pixel. The number q of the buffered images and the factor f2 can be pre-configured. In one embodiment, the number q can be an integer selected from the range 1 < q ≤ 200, and the factor f2 can be a floating point number selected from the range 0 < f2 < 1 or 1 < f2 < 10. The number q can be pre-configured based on the thickness of the test specimen 130. In one embodiment, when the thickness of the test specimen 130 is less than 50 μm, the number q can be an integer selected from the range 1 < q ≤ 20. In one embodiment, when the thickness of the test specimen 130 is between 50 μm and 150 μm, the number q can be an integer selected from the range 21 ≤ q ≤ 50. In one embodiment, when the thickness of the test specimen 130 is greater than 150 μm, the number q can be an integer selected from the range 51 ≤ q < 200. In one embodiment, when the intensity of the pixels of the average image of q images is higher than the intensity of the substrate surface 120, the factor f2 can be a floating point number selected from the range 0.1 ≤ f2 < 1. In one embodiment, when the intensity of the pixels of the average image of q images is lower than the intensity of the substrate surface 120, the factor f2 can be a floating point number selected from the range 1 < f2 < 10. <0000(此处原文似乎有误,推测应为

[0044] )133>The operations of steps 640, 650, 660, 670, 680 are similar to the operations of steps 560, 570, 580, 590, 595, and thus will not be explained in detail. If both the width and the length of the region identified in step 660 at step 670 are greater than a first threshold and a second threshold respectively, the control device 90 determines that the test region 136 of the coating 130 has been worn, and records the number of cycles that the brush 140 has moved back and forth from the start of the test at step 680. If the determination at step 670 is negative, the process returns to step 610 to repeat the operations at steps 610 to 670.

[0045] Figure 7A and Figure 7B shows an exemplary process for determining an inspection region of a parallel coating according to an embodiment. As Figure 7A shown, a single coating 130 is applied on the substrate surface 120. In this embodiment, only one coating is tested on one scrubbing device at a time. As Figure 7B As shown, multiple coatings 130 are applied to a substrate surface 120. In this embodiment, multiple coatings, such as the four shown, can be tested simultaneously using a single scrubbing device. This improves testing efficiency.

[0046] For example Figure 7B The side-by-side coatings shown can be used to identify coating boundaries 135, and test areas 136 can then be identified based on these boundaries. In the illustrated embodiment, the four coatings are drawn with different colors, thus allowing the coating boundaries 135 to be identified based on different colors. The central region of each coating area defined by boundary 135 can then be identified as the test area 136 for inspecting wear areas. That is, areas close to boundary 135 are excluded from test area 136. For example, areas where boundary 135 is a distance threshold from test area 136 are excluded.

[0047] Figures 8A to 8C An exemplary process for determining inspection areas for parallel coatings, according to one embodiment, is shown. Figure 8A As shown, multiple coatings 130 are applied to a substrate surface 120. In this embodiment, due to the application process of the multiple coatings 130, a "V" shape exists between the ends of the two coatings. Figure 8B As shown, the image of coating 130 can be binarized into a binary image, and then the outlines 131 of the coating regions of all coatings can be identified based on the binary image, and points 132 at the “v”-shaped outlines can be identified as possible boundary locations. It should be understood that the term “v”-shaped is used to describe an outline shape similar to the letter “v”, but does not require the shape of the outline portion to be a perfect “v” shape. Shapes of outline portions similar to a “v” shape, such as an outline shape like a “v” with a relatively flat bottom, can also be called “v”-shaped, and are therefore within the scope of “v”-shaped. Figure 8C As shown, the central region of each coating area defined by boundary 135 can then be identified as test area 136 for inspecting wear areas. In one embodiment, if the "V" shape is not identified, the process can determine that a single coating exists on the substrate surface 120 of the substrate, and the central region of the single coating area defined by contour 131 can then be identified as test area 136 for inspecting wear areas. In one embodiment, the central region of the test area 136 used as a single coating can be configured by the user.

[0048] Figure 9 An exemplary method for automated scrub resistance testing according to one embodiment is shown.

[0049] In step 910, a series of digital images of at least a portion of the test specimen are captured, wherein the test specimen is located on the substrate surface of the scrubbing machine and the scrubbing device is scrubbing the test specimen.

[0050] In step 920, each segment of the image is analyzed to determine the corresponding area that is worn.

[0051] At step 930, test results including multiple wear cycles are received. The test results may also include the width and length of the wear area.

[0052] In one implementation, a segment is detected as worn based on the intensity values ​​of the segment in at least m consecutive images in a series; where m is an integer and 1 ≤ m ≤ 20, preferably 3 ≤ m ≤ 10.

[0053] In one implementation, the image analysis at step 920 includes analyzing each segment of the image pixel-by-pixel by applying three values ​​to each pixel: an intensity standard, a counter, and a counter threshold; wherein the m consecutive images are the last m consecutive images in a series; the intensity value is the average intensity of pixels at the same location in the last m consecutive images; the intensity value is calculated and compared with the intensity standard; the counter is incremented when 1) the intensity value is lower than the intensity standard but higher than the intensity of the substrate surface of the substrate on which the sample is coated, or 2) the intensity value is higher than the intensity standard but lower than the intensity of the substrate surface of the substrate on which the sample is coated; and when the counter value reaches the counter threshold, the pixel is considered worn; each worn region is formed by connected worn pixels.

[0054] In one implementation, method 900 further includes applying the first p consecutive images obtained at the start of the test to the image series y, calculating the average intensity of pixels at the same location in the first p consecutive images and multiplying it by f1, and the result of the multiplication is the intensity criterion of step 920, where: p is an integer and 1 ≤ p < 200; f1 is a floating-point number and 0.1 ≤ f1 < 1 or 1. <f1<10。

[0055] In one embodiment, when the thickness of the test specimen is less than 50 μm, 1 ≤ p ≤ 20. In one embodiment, when the thickness of the test specimen is between 50 μm and 150 μm, 21 ≤ p ≤ 50. In one embodiment, when the thickness of the test specimen exceeds 150 μm, 51 ≤ p < 200.

[0056] In one embodiment, when the average intensity of pixels at the same position in the current p consecutive images is higher than the intensity of the substrate surface of the substrate on which the specimen is scraped, 0.1 ≤ f1 < 1. In one embodiment, when the average intensity of pixels at the same position in the current p consecutive images is lower than the intensity of the substrate surface of the substrate on which the specimen is scraped, 1 < f1 < 10.

[0057] In one embodiment, method 900 further includes applying the last q consecutive images to image series z, calculating the average intensity of pixels at the same position in the last q consecutive images, and multiplying the average intensity by f2, and the result of the multiplication is the intensity criterion for step 920, where: q is an integer and 1 < q ≤ 200; f2 is a floating-point number and 0 < f2 < 1 or 1 < f2 < 10; and q > m.

[0058] In one embodiment, when the thickness of the test specimen is less than 50 μm, 1 < q ≤ 20. In one embodiment, when the thickness of the test specimen is between 50 μm and 150 μm, 21 ≤ q ≤ 50. In one embodiment, when the thickness of the test specimen exceeds 150 μm, 51 ≤ q ≤ 200.

[0059] In one embodiment, when the average intensity of pixels at the same position in the last q consecutive images is higher than the intensity of the substrate surface of the substrate on which the specimen is scraped, 0.1 ≤ f2 < 1. In one embodiment, when the average intensity of pixels at the same position in the last q consecutive images is lower than the intensity of the substrate surface of the substrate on which the specimen is scraped, 1 < f2 < 10.

[0060] In a preferred embodiment, this method is used when the strength of the specimen is much higher or lower than the strength of the substrate surface of the substrate on which the specimen is scraped.

[0061] In one embodiment, for step 910, more than one test specimen is scraped on the substrate surface of the substrate.

[0062] Figure 10 An exemplary computing system 1000 according to one embodiment is shown. Computing system 1000 may include at least one processor 1010. Computing system 1000 may further include at least one storage device 1020. The storage device 1020 may store computer-executable instructions that, when executed, cause the processor 1010 to perform any operation according to an embodiment of the present disclosure as described in connection with Figures 1 to 9 any operation of the embodiments of the present disclosure.

[0063] Embodiments of this disclosure can be embodied in a computer-readable medium, such as a non-transitory computer-readable medium. A non-transitory computer-readable medium may include instructions that, when executed, cause one or more processors to perform actions according to the following combination... Figures 1 to 9 Any operation of the embodiments described in this disclosure.

[0064] Embodiments of this disclosure can be embodied in a computer program product including computer-executable instructions that, when executed, cause one or more processors to perform according to the following combination Figures 1 to 9 Any operation of the embodiments described in this disclosure.

[0065] The computing system 1000 can be Figure 1 or Figure 3 This is a part of the automatic scrub resistance testing system 1 or 300 shown, and specifically corresponds to the control device 90 of the automatic scrub resistance testing system 1 or 300.

[0066] In one embodiment, an automated scrub resistance testing system 1 or 300 for monitoring specimen wear may include: a scrubbing machine having a scrubbing device mounted to move over a defined path, on which a coated area on the substrate is adapted to be positioned at the center of the moving path; an image acquisition machine located over the defined path in the test monitoring area; a light source; and an image analysis system for determining, as in combination with... Figures 1 to 9 The methods described in this disclosure for an embodiment of the present invention include collecting images, performing image analysis, and displaying test results.

[0067] In one implementation, the image analysis system stores image data from the image acquisition machine.

[0068] In one implementation, the image acquisition device includes a camera.

[0069] In one embodiment, the automated scrub resistance testing system further includes a scrub media delivery system that delivers scrub media to the surface of the specimen.

[0070] In one embodiment, the automated scrub resistance testing system also includes an image display.

[0071] In one implementation scheme, such as combining Figures 1 to 10 The methods or automated scrub resistance testing systems described in this disclosure can be used to test the wear of specimens. In one embodiment, such as in combination Figure 1The method or automated scrub resistance testing system of the embodiments of this disclosure described up to Figure 8 can be used to test the wear of specimens according to the standard ASTM-D2486 or GB-T9266 (such as ASTM-D2486 (2017) or GB-T9266 (2009)).

[0072] It should be understood that all operations in the methods described above are merely exemplary, and this disclosure is not limited to any operation in the methods or the order of such operations, but should cover all other equivalents under the same or similar concepts.

[0073] It should also be understood that all modules in the device described above can be implemented in various ways. These modules can be implemented as hardware, software, or a combination thereof. Furthermore, any of these modules can be further functionally divided into sub-modules or combined together.

[0074] The preceding description is provided to enable those skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects. Therefore, the claims are not intended to be limited to the aspects shown herein. All structural and functional equivalents of elements throughout the various aspects described herein, known or to be known by those skilled in the art thereafter, are expressly incorporated herein by reference and are intended to be covered by the claims.

Claims

1. A method for automated scrub resistance testing, the method comprising the following steps: (a) Capturing a series of digital images of at least a portion of a test specimen, wherein the test specimen is located on a base surface of the machine and a scrubbing device is scrubbing the test specimen. (b) Analyze each segment of the image to determine the corresponding area that is worn; (c) Receive test results including multiple wear cycles; Among them, based on the intensity value of a segment in at least m consecutive images in the series, the segment is detected as worn; Where m is an integer, and 1≤m≤20, preferably 3≤m≤10.

2. The method of claim 1, step (b) comprises analyzing each segment of the image pixel-by-pixel by applying three values ​​to each pixel: an intensity standard, a counter, and a counter threshold; wherein the m consecutive images are the last m consecutive images in the series; the intensity value is the average intensity of the pixels at the same location in the last m consecutive images; calculating the intensity value and comparing the intensity value with the intensity standard; the counter incrementing when 1) the intensity value is lower than the intensity standard and higher than the intensity of the substrate surface of the substrate on which the sample is scraped, or 2) the intensity value is higher than the intensity standard and lower than the intensity of the substrate surface of the substrate on which the sample is scraped; and when the counter value reaches the counter threshold, the pixel is considered worn; each worn region is formed by connected worn pixels.

3. The method according to claim 2, wherein the average intensity of pixels at the same position in the first p consecutive images is calculated, and the average intensity is multiplied by f1, and the result of the multiplication is the intensity standard of step (b), wherein: p is an integer and 1 ≤ p < 200; and f1 is a floating-point number, and 0.1 ≤ f1 < 1 or 1. <f1<10。 4. The method according to claim 3, wherein when the thickness of the test sample is less than 50 μm, 1 ≤ p ≤ 20.

5. The method according to claim 3, wherein when the thickness of the test specimen is between 50 μm and 150 μm, 21 ≤ p ≤ 50.

6. The method according to claim 3, wherein when the thickness of the test specimen exceeds 150 μm, 51 ≤ p < 200.

7. The method according to any one of claims 3 to 6, wherein when the average intensity of the pixels at the same position in the preceding p consecutive images is higher than the intensity of the substrate surface on which the sample is scraped, 0.1 ≤ f1 < 1.

8. The method according to any one of claims 3 to 6, wherein when the average intensity of the pixels at the same location in the preceding p consecutive images is lower than the intensity of the substrate surface on which the sample is coated, 1 <f1<10。 9. The method according to claim 2, wherein the average intensity of pixels at the same position in the last q consecutive images is calculated, and the average intensity is multiplied by f2, and the result of the multiplication is the intensity standard of step (b), wherein: q is an integer and 1 < q ≤ 200; f2 is a floating-point number, and 0 < f2 < 1 or 1 < f2 < 10; and q > m.

10. The method according to claim 9, when the thickness of the test specimen is less than 50 μm, 1 < q ≤ 20.

11. The method according to claim 9, when the thickness of the test specimen is between 50 μm and 150 μm, 21 ≤ q ≤ 50.

12. The method according to claim 9, when the thickness of the test specimen exceeds 150 μm, 51 ≤ q ≤ 200.

13. The method according to any one of claims 9 to 12, when the average intensity of the pixels at the same position of the last q consecutive images is higher than the intensity of the base surface of the substrate on which the specimen is scraped, 0.1 ≤ f2 < 1.

14. The method according to any one of claims 9 to 12, when the average intensity of the pixels at the same position of the last q consecutive images is lower than the intensity of the base surface of the substrate on which the specimen is scraped, 1 < f2 < 10.

15. The method according to any one of claims 1 to 14, for step (a), more than one test specimen is scraped on the base surface of the substrate.

16. An automatic scrub resistance test system for monitoring specimen wear, the automatic scrub resistance test system comprising: (i) A scrubbing machine having a scrubbing device mounted to move above a defined path, on which a coated area on a substrate is adapted to be placed in the defined path; (ii) An image acquisition machine located above the defined path in a test monitoring area; (iii) And an image analysis system that performs image analysis according to the method of claims 1 to 15.

17. The automatic scrub resistance test system according to claim 16, wherein the image analysis system stores the image data from the image acquisition machine.

18. The automatic scrub resistance test system according to claim 16 or 17, wherein the image acquisition machine includes a camera.

19. The automatic scrub resistance test system according to any one of claims 16 to 18, the automatic scrub resistance test system further comprising a scrubbing medium delivery system that delivers a scrubbing medium to the surface of the specimen.

20. The automatic scrub resistance test system according to any one of claims 16 to 19, the automatic scrub resistance test system further comprising an image display.

21. Use of the method according to claims 1 to 15 for testing specimen wear.

22. Use of the method according to claims 1 to 15 for testing specimen wear according to standard ASTM-D2486 or GB-T9266.

23. Use of the automatic scrub resistance test system according to any one of claims 16 to 19 for testing specimen wear.

24. A computer program product comprising computer-executable instructions that, when executed, cause one or more processors to perform the method according to claims 1 to 15.

Images