Method for fully automatically detecting scrubbing resistance

Abstract

The invention discloses a method for full-automatically detecting scrubbing resistance, and belongs to the technical field of coating performance detection.The method comprises the steps that a to-be-detected coating sample is fixed through a machine table clamping mechanism, a brush is driven by a motor to execute automatic reciprocating scrubbing, and after each scrubbing cycle, a camera is triggered to collect a coating image; the method comprises the following steps: selecting a detection area, identifying and calculating the exposed length of the selected detection area in real time by using an image processing algorithm, automatically judging whether to terminate the test by a system according to various stop conditions preset by a user, and outputting a test result including the exposed length and the scrubbing times, thereby overcoming the defects of low efficiency and large subjective error of traditional manual detection, and improving the detection accuracy. Efficient, accurate and standardized full-automatic detection of the scrubbing resistance of the coating is realized, and the test consistency and reliability are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of coating performance testing technology, specifically a fully automated method for testing washability. Background Technology

[0002] Scrub resistance is a key technical indicator for evaluating the durability, service life, and quality grade of coating materials, and it has crucial application value in many fields such as building decoration, home furniture, automotive industry, shipbuilding, rail transportation, and industrial protection. Traditional methods for testing the scrub resistance of coatings, such as those described in the national standard GB / T9266 "Determination of Scrub Resistance of Architectural Coatings," mainly rely on manual operation. Operators use brushes or simple mechanical devices to repeatedly scrub the coating prepared on a test panel. During or after the process, they visually observe and determine whether the coating has been worn through to the substrate (i.e., "exposed substrate"), and record the total number of scrubs as the basis for the coating's scrub resistance.

[0003] However, this traditional manual or semi-automated testing method has a series of inherent and insurmountable defects and limitations: The testing efficiency is extremely low: manual washing is slow, labor-intensive, and has a long testing cycle, which cannot meet the needs of modern industrial production for rapid quality inspection and control of large batches of samples, and seriously restricts the efficiency of product development and factory inspection.

[0004] The test results are highly subjective and have poor repeatability: the judgment of whether or not the sample is "exposed" depends entirely on the operator's subjective visual experience. Different operators, and even the same operator at different times and under different lighting conditions, may make different judgments about the state of the same test sample, resulting in poor comparability and repeatability of the test results, making it difficult to form an objective and unified evaluation standard.

[0005] Human error introduces numerous points of error: During the brushing process, it is difficult for humans to precisely control and maintain consistent brushing force, speed, stroke, and the contact angle between the brush and the coating surface for each stroke. These uncontrollable factors directly introduce systematic or random errors, affecting the accuracy and reliability of the test data.

[0006] Lack of real-time, quantitative process monitoring: Traditional methods typically make a one-time judgment after the test, failing to monitor the changes in the coating's wear state in real time and dynamically during the brushing process, and even less able to accurately quantify the degree of "exposed substrate" (e.g., the length and area of ​​the exposed substrate). This results in a lack of process control during the testing process and makes it impossible to obtain complete data curves of the coating wear process.

[0007] Limited functionality and lack of flexibility: While some existing automated equipment achieves mechanical brushing, it often has limited functionality and struggles to support parallel testing of multiple test channels (such as simultaneously testing two or more samples) and multiple sample areas (such as coatings of different materials on the same test plate). Furthermore, the stopping condition for testing is usually a preset fixed number of brushing cycles, unable to intelligently judge and automatically stop based on the actual wear state of the coating (such as reaching a specific exposed substrate length), resulting in poor adaptability.

[0008] In summary, those skilled in the art have long been committed to solving the aforementioned problems, but the difficulty lies in the need to highly integrate precise mechanical transmission and control, a stable image acquisition system, robust image processing algorithms, and flexible logical judgment strategies into a unified system. Specific technical challenges include: how to ensure precise synchronization between the high-speed reciprocating brushing mechanism and high-resolution image acquisition; how to develop a versatile exposed substrate identification algorithm that can adapt to different coating colors, textures, and reflective properties; how to design a stable and reliable clamping and positioning mechanism to ensure repeatability and consistency in the test area; and how to construct a flexibly configurable control system that supports various complex test logics (such as multi-channel, multi-area, and multi-condition stop). Therefore, developing a method for testing washability that can achieve full-process automation, objectively quantify test results, and possess high flexibility and reliability has become an urgent and clear need in this technical field. Summary of the Invention

[0009] To address the aforementioned shortcomings in existing technologies, this invention aims to provide a fully automated, high-precision, quantifiable method for testing the washability of coatings under multiple channels and conditions. The core technical problem this invention addresses is how to overcome the limitations of manual operation and existing semi-automatic equipment in terms of testing efficiency, result consistency, process monitoring, and testing flexibility. This is achieved by integrating automated brushing, real-time machine vision inspection, and intelligent decision control to realize complete automation, standardization, and intelligence in testing the washability of coatings.

[0010] To achieve the above objectives, the present invention provides the following technical solution: A fully automated method for testing washability includes the following steps: S1: System initialization. The user sets test parameters through the control interface, including the number of brushing cycles (the test will stop when the number of cycles is reached), brushing speed, stopping conditions (e.g., select "Channel 1 reaches the exposed material condition and stops"), detection area (e.g., select "Channel 1 Material 1" and "Channel 2 Material 1"), and exposed material length threshold (e.g., 12.7mm). S2: Clamp the coating to be tested. The clamping mechanism (mechanical fixture) at the bottom of the machine fixes the coating sample to be tested on the test platform, ensuring that the coating surface is flat and in uniform contact with the brush. S3: Start the brushing process. The control unit starts the motor and drives the brush to perform brushing action at a set speed (e.g., 60 back and forth per minute). After each brushing cycle is completed (i.e., the brush goes back and forth once), the control software sends a signal to trigger the camera to take a picture. S4: Image acquisition and exposed substrate length recognition. The camera triggers a photo capture every time it completes a brushing cycle, acquiring an image of the coating.

[0011] As a further improvement to the above technical solution: To reduce shadows and reflections, the image processing algorithm runs on the control unit (PC); S5: Stop judgment and control. The control unit compares the exposed bottom length with the set threshold in real time: If the stop condition is set to "Channel 1 reaches the exposed bottom condition and stops", then the test stops when the exposed bottom length of Channel 1 is greater than or equal to the threshold; if the stop condition is set to "Any channel reaches the exposed bottom condition and stops", then the test stops when the exposed bottom length of Channel 1 or Channel 2 is greater than or equal to the threshold.

[0012] If the stopping condition is not met, the control unit continues to the next brushing cycle; otherwise, the motor is stopped immediately, and the number of brushing cycles and the length of exposed substrate are recorded. S6: Data output and post-processing. After the test, the control unit outputs the results, including the exposed length of each area, the number of times the conditions were met, and the corresponding images. The data is automatically saved to the database for archiving and analysis.

[0013] Preferably, in step S1, the stopping condition is set by the user from a set of predefined conditions, which include: First stopping condition: Stop when the real-time exposed length of the area corresponding to "Channel 1" reaches or exceeds the threshold; Second stopping condition: Stop when the real-time exposed length of the area corresponding to "Channel Two" reaches or exceeds the threshold. The third stopping condition is to stop when the real-time exposed length of any area corresponding to "Channel 1" or "Channel 2" reaches or exceeds the threshold. Fourth stopping condition: Stop when the real-time exposed length of all areas corresponding to "Channel 1" and "Channel 2" reaches or exceeds the threshold.

[0014] Preferably, in step S1, the region to be detected is selected by the user from a predefined plurality of regions, including: "Channel One" represents the entire area of ​​the first test channel; "Channel Two" represents the entire area of ​​the second test channel; The first material sub-region, "Channel One Material One," is located within the first test channel. The second material sub-region, "Channel One Material Two," is located within the first test channel. The first material sub-region, "Channel Two Material One," is located within the second test channel. The second material sub-region, "Channel Two Material Two," is located within the second test channel.

[0015] Preferably, the image processing and recognition steps in step S4 specifically include: S41. Image preprocessing: Perform grayscale conversion and filtering denoising on the acquired current image to enhance image contrast and reduce interference; S42. Exposed Area Segmentation: A threshold segmentation algorithm is used to perform global threshold segmentation on the preprocessed image to distinguish between the exposed bottom layer area after coating wear and the unworn coating area. S43. Length Calculation: Within the user-selected detection area, the pixel width of the exposed area in the brushing direction is calculated, and the pixel width is converted into the actual physical exposed length according to the pre-calibrated ratio between pixels and actual length.

[0016] Preferably, in step S1, the test parameters also include the maximum number of brushing cycles; in step S5, if the stopping condition based on the exposed bottom length is not met when the maximum number of brushing cycles is reached, the motor is also controlled to stop working, and the test is terminated.

[0017] Preferably, in step S3, the completion of a brushing cycle is determined by the position sensor linked to the control unit. After receiving the position signal, the control software sends a signal to trigger the camera to take a picture and generates a trigger signal to the image acquisition device.

[0018] A fully automated scrub resistance testing system for implementing the above method, the system comprising: Mechanical platform used to support and hold coating samples; A clamping mechanism, mounted on the mechanical platform, is used to clamp and fix the coating sample. The brushing actuator includes a brush driven by a motor for reciprocating brushing of the surface of the coating sample; The image acquisition unit includes a light source and a camera, wherein the camera acquires an image of the coating when it receives a trigger signal; A control unit, communicatively connected to the motor and the image acquisition unit, is configured to execute a computer program to implement the steps of the method as described in any one of claims 1 to 6.

[0019] Preferably, the control unit includes an image processing module and a logic judgment module; The image processing module is used to perform image preprocessing, exposed area segmentation, and exposed length calculation. The logic judgment module is used to issue a stop control command or maintain the running state based on the calculated exposed length and the stop conditions set by the user.

[0020] Compared with the prior art, the beneficial effects of the present invention are: 1. High degree of automation and efficiency improvement: It realizes full-process automation from clamping, washing, monitoring, judgment to result output, which greatly reduces manual operation links, liberates labor, and improves testing efficiency many times over. It is especially suitable for rapid testing of batch samples. 2. Objective, accurate, and consistent test results: Using machine vision to replace the human eye for exposure identification and measurement completely eliminates errors and uncertainties caused by subjective human factors. Image processing algorithms can measure with pixel-level precision, ensuring data accuracy and repeatability, making test results from different laboratories and at different time points comparable. 3. Real-time monitoring and intelligent decision-making: It can immediately "check up" the coating condition after each brushing cycle, capturing the occurrence and development of substrate exposure in real time. Combined with flexible and configurable stop conditions, it can automatically terminate the test at the most precise moment (such as when the substrate exposure standard is just reached), thereby obtaining the most accurate "brush resistance count" and avoiding over-testing or under-testing; 4. Excellent flexibility and adaptability: Supports multi-channel, multi-area detection configurations and various stop logics, enabling flexible handling of complex testing scenarios, such as simultaneously testing two different coatings on a sample or testing different areas of a composite coating. This design greatly enhances the equipment's versatility and scalability.

[0021] 5. Promotes Standardization and Data-Driven Management: This method standardizes and proceduralizes the testing process, reducing variations caused by different operators. The automatically generated electronic test reports are easy to store, retrieve, and statistically analyze, providing strong and reliable data support for product quality control, process improvement, and new product development. Attached Figure Description

[0022] Figure 1 This is a flowchart of the present invention; Figure 2 This is a flowchart of the image processing and stop determination sub-process of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1 and Figure 2 The core technical solution adopted in this invention is a fully automated method for testing washability, which is based on a system integrating mechanical execution, image acquisition, and intelligent control. The method mainly includes the following steps: 1) Initial Setup: Users set various parameters for this test through a human-computer interaction interface (such as a touchscreen or host computer software). These parameters include, but are not limited to: Stop condition: Defines the trigger logic for test termination. For example, you can choose "Stop when channel 1 reaches the bottom exposure condition", "Stop when channel 2 reaches the bottom exposure condition", "Stop when any channel reaches the bottom exposure condition", or "Stop when both channel 1 and channel 2 reach the bottom exposure condition".

[0025] Detection Area: Select one or more predefined areas as the focus of this detection. Predefined areas may include "Channel 1" (representing the entire area of ​​the first test channel), "Channel 2" (representing the entire area of ​​the second test channel), and more subdivided sub-areas such as "Channel 1 Material 1", "Channel 1 Material 2", "Channel 2 Material 1", and "Channel 2 Material 2" to accommodate cases where the test sample has different material coatings.

[0026] Exposed length threshold: Set the critical length value (e.g., 12.7 mm) for determining whether the bottom is "exposed". This is the benchmark for determining whether the stopping condition is met.

[0027] Other parameters include: brushing speed, maximum number of brushing cycles (as a safety stop condition to prevent infinite looping), etc.

[0028] 2) Clamping and Brushing: Place the coating sample to be tested on the testing platform of the testing machine and firmly fix it in place using a precision mechanical clamping mechanism to ensure that the sample does not shift during the brushing process. Start the drive motor to drive the brush to perform precise and countable reciprocating brushing on the coating surface at a set speed.

[0029] 3) Image acquisition: This step is strictly synchronized with the brushing action. After each complete brushing cycle (e.g., the brush moves from the starting point to the ending point and back), an industrial camera mounted in a suitable location automatically generates a trigger signal when the position sensor detects the completion of a brushing cycle, triggering the automatic acquisition of a high-resolution digital image of the current coating surface. To ensure image quality, the system is equipped with a uniform lighting source to eliminate shadows and reflections.

[0030] 4) Image processing and recognition, which is the key step in this invention. The acquired images are transmitted to the control unit (usually an industrial computer or a high-performance embedded processor) to run specialized image processing algorithms. The process is as follows: Image preprocessing: The original image is converted to grayscale and filtered (such as median filtering and Gaussian filtering) to remove noise and enhance contrast, laying the foundation for subsequent processing.

[0031] Exposed region segmentation: An image segmentation algorithm (preferably a threshold segmentation method, such as segmentation based on a fixed threshold) is used to perform global threshold segmentation of the image, thereby clearly separating the underlying regions exposed by washing that differ in color or grayscale from the unworn coating.

[0032] Exposed Background Length Calculation: Within one or more pre-selected "detection areas," the segmented exposed background areas are analyzed. Specifically, discontinuous exposed background areas are divided into multiple continuous independent areas, and the pixel width of the largest continuous exposed background area within each area is calculated. Then, using a pre-calibrated "pixel-to-actual-size" conversion factor (e.g., 1 pixel corresponds to 0.1 mm), the pixel width is converted into the actual physical exposed background length.

[0033] 5) Stop Judgment: The control unit compares the real-time exposed length of each selected detection area calculated in step S4 with the user-defined "exposed length threshold". Simultaneously, it performs a logical judgment based on the user-defined "stop condition". For example: If the stopping condition is "Channel 1 reaches the bottom exposure condition and stops", then as long as the real-time bottom exposure length of the "Channel 1" area (or its sub-areas, if selected) is greater than or equal to the threshold, a stop command will be issued.

[0034] If the stopping condition is "stop when any channel reaches the bottom exposure condition", then if either "Channel 1" or "Channel 2" meets the above condition, a stop command will be issued.

[0035] Other conditions follow the same logic.

[0036] If the stopping condition is met, the motor will be stopped immediately, and the test will end; otherwise, the system will automatically enter the next brushing cycle and repeat the brushing, image acquisition, recognition and judgment process.

[0037] 6) Data Output Steps: After the test is completed, the system automatically compiles and generates a detailed test report. The report typically includes: the final number of washes, the final exposed length of each test area, the image at which the stopping condition was met, and the test time. This data can be displayed on the screen, stored in a local database, or exported to external devices for subsequent quality analysis and traceability.

[0038] To achieve the above method, the present invention also provides a corresponding fully automatic scrub resistance testing system, which mainly includes: Mechanical structure components: including a robust machine frame, a test platform and clamping mechanism for placing and securing the sample, and a brush head driven by a motor and transmission mechanism.

[0039] The visual imaging component includes a high-resolution industrial camera, a matching lens, and a light source system that provides uniform illumination to the coated surface.

[0040] Control and processing section: The core is the control unit, which integrates a circuit board (for precise motor control) and an industrial computer (for issuing commands and triggering image capture); the industrial computer runs control software, which integrates a motor control module, an image acquisition trigger module, an image processing algorithm module, a logic judgment module, and a human-machine interface.

[0041] Example 1: This embodiment describes the complete process of testing the washability of a single-coated sample using the method of the present invention. The test system hardware mainly includes: the machine body, a stepper motor and driver, a mechanical clamping fixture, a CMOS industrial camera, a square LED light source, and an industrial control computer (IPC).

[0042] Step 1: System Preparation and Parameter Initialization Place the coating sample to be tested (e.g., a cement board coated with white latex paint) steadily on the test platform.

[0043] Power on the system and run the control software. The main interface of the software displays the parameter setting area.

[0044] Users can configure the following parameters: Stop condition: Select "Stop when any channel reaches the exposure condition" from the drop-down menu. (In this example, although only one sample is being tested, it is logically classified as "Channel 1").

[0045] Detection Area: In the area selection, select "Channel 1". (Assuming the sample has a single coating, there is no need to use material sub-regions).

[0046] Exposed length threshold: Enter "12.7" (unit: mm). This value is set according to relevant test standards.

[0047] Maximum number of washes: Enter "20000" as the safety limit.

[0048] Scrub speed: Set to "37 times / minute".

[0049] System initialization complete.

[0050] Step Two: Sample Clamping and Scrubbing Start The pneumatic (or mechanical) clamping mechanism operates automatically to reliably press the sample onto the platform, ensuring that there is no loosening during the brushing process.

[0051] Clicking the "Start Test" button sends a command to the stepper motor driver, starting the motor and driving the brush to perform reciprocating linear brushing at a frequency of 37 times per minute via the crank-connecting rod mechanism. The brushing counter increments from 0.

[0052] Step 3: Synchronous Image Acquisition Each time the motor completes a full round trip (i.e., one cycle), the position sensor sends a signal to the IPC.

[0053] After receiving the signal, the host computer triggers the industrial camera via a soft trigger.

[0054] The camera takes an exposure at the moment of triggering, capturing a clear image of the currently being washed area. Simultaneously, the square LED light source remains constantly lit, providing stable and uniform illumination.

[0055] Step 4: Real-time Image Processing and Background Recognition The acquired images are transmitted to the IPC's memory in real time.

[0056] The image processing module running on the IPC is invoked to perform the following sub-steps (see flowchart). Figure 2 ): a. Image preprocessing: Convert the color image to a grayscale image (if it is already a grayscale image, no conversion is needed); then, apply a Gaussian filter to smooth the grayscale image to suppress random noise.

[0057] b. Threshold segmentation: A fixed threshold segmentation is used to divide the area to be detected into two parts: exposed substrate and non-exposed substrate. In this embodiment, since the exposed substrate (cement board) is darker than the white coating, the darker area is detected as the exposed substrate area.

[0058] c. Length Calculation: The software locates the entire rectangular area of ​​"Channel 1" selected by the user. Within this area, the discontinuous exposed area is divided into multiple continuous independent regions, and the pixel width of the widest exposed region is calculated. Assuming the system has been pre-calibrated and it is known that under this imaging configuration, 1 pixel corresponds to an actual length of 0.08mm. If the measured width of the continuous black area is 159 pixels, then the real-time exposed length is calculated as: 159 × 0.08 = 12.72mm.

[0059] Step 5: Intelligent Stop Judgment The logic judgment module compares the calculated real-time exposed length (12.72mm) with the preset threshold (12.7mm).

[0060] Since 12.72mm > 12.7mm, the condition for exposing the substrate is met.

[0061] Based on the user-defined stop condition "stop when any channel reaches the exposure condition" (currently, channel one meets the condition), the logic judgment module immediately determines that the test should be terminated.

[0062] The IPC then sends a stop command to the motor driver, the motor brakes rapidly, and the brushing action stops. At this point, the brushing counter displays N times.

[0063] Step Six: Data Recording and Output After the test stops, the control software automatically generates a test report, which includes: Test sample number (can be pre-entered).

[0064] Stop condition: Stop when any channel reaches the bottom exposure condition.

[0065] Final number of scrubbing cycles: N times.

[0066] Exposed length of channel 1: 12.72mm.

[0067] Test status: Completed normally (stopped because the bottom layer was exposed).

[0068] The final image thumbnail.

[0069] The report is automatically saved to a database or Excel file at a specified path and can be previewed in the software interface.

[0070] Example 2: This embodiment demonstrates the application of the present invention under multi-region, complex stopping conditions. The test sample is a composite sample on which two different coatings (coating A and coating B) are prepared side by side, corresponding to "channel one material one" and "channel one material two" of the system, respectively; the user wants to test these two coatings and wants to stop the test when either coating first reaches the substrate exposure standard, in order to compare their relative abrasion resistance.

[0071] Step 1: Parameter Initialization Stop condition: Select "Stop when any channel reaches the bottom exposure condition".

[0072] Detection area: Select "Channel 1", enable "Channel 1 Dual Material" and select "Channel 1 Material 1" and "Channel 1 Material 2"; (the system will monitor these two logical areas simultaneously).

[0073] Exposed length threshold: set to 10.0mm.

[0074] Other parameters are the same as in Example 1.

[0075] Steps two through four: Similar to Example 1, the system performs brushing, image acquisition, and processing. The key difference lies in the image processing in step four, where the algorithm independently performs background exposure identification and length calculation within the image regions corresponding to "Channel 1 Material 1" and "Channel 1 Material 2," respectively, obtaining two real-time length values, L1 and L2.

[0076] Step 5: Intelligent Stop Judgment (Multiple Conditions) After each flushing cycle, the logic judgment module will simultaneously compare the relationship between L1 and L2 and the threshold (10.0mm).

[0077] Assuming that after M washes, the calculated values ​​are L1=9.5mm and L2=8.8mm, both of which fail to meet the standard, the test continues.

[0078] After washing for M+1 times, L1 = 10.2 mm and L2 = 9.0 mm were calculated. At this point, L1 ≥ 10.0 mm, which satisfies the condition that "channel one reaches the bottom exposure condition".

[0079] Since the stopping condition is "stop when any channel reaches the bottom exposure condition", the system immediately determines that the test is terminated.

[0080] Step Six: Data Output The final report will clearly record: Material of the channel - exposed bottom length: 10.2mm (meets the standard).

[0081] Material 2 of Channel 1: Exposed bottom length: 9.0mm (not up to standard).

[0082] Number of times to stop scrubbing: M+1 times.

[0083] Reason for termination: Material 1 of channel 1 has reached the condition of being exposed.

[0084] This embodiment clearly demonstrates that the method of the present invention can efficiently and accurately complete parallel testing of multiple samples or multiple regions, and perform intelligent control according to preset complex logic, greatly enriching testing capabilities.

[0085] In summary, this invention, through mechatronics design and intelligent algorithms, successfully upgrades the washability testing from a traditional manual mode to a fully automated, high-precision, and intelligent modern testing mode, providing an effective technical solution to address industry pain points. Any equivalent transformations or modifications made by those skilled in the art based on the concept of this invention should be covered within the scope of protection of this invention.

[0086] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0087] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0088] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0089] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0090] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0091] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for fully automatically implementing detection of scrub resistance, characterized in that, The method comprises the following steps: S1: system initialization, the user sets the test parameters through the control interface: including the brushing times (the test will also stop when the number of times is reached), brushing speed, stop condition (for example, select "channel one reaches the bare bottom condition to stop"), detection area (for example, select "channel one material one" and "channel two material one"), and bare bottom length threshold (such as 12.7 mm); S2: clamp the coating to be tested, the clamping mechanism (mechanical clamp) at the bottom of the machine fixes the coating sample to be tested on the test platform, ensuring that the coating surface is flat and uniform in contact with the brush; S3: start the brushing process, the control unit starts the motor to drive the brush to brush at the set speed (for example, 60 times / minute), and the position sensor is triggered after each brushing cycle (i.e., the brush goes back and forth once), and the control software sends a signal to trigger the camera to take a picture after receiving the position signal; S4: image acquisition and bare bottom length identification, the washing process light source provides uniform illumination to reduce shadows and reflections, the camera triggers to take a picture every time a brushing cycle is completed, the software collects the coating image, and the image processing algorithm runs in real time on the control unit (PC); S5: stop judgment and control, the control unit compares the bare bottom length with the set threshold in real time: if the stop condition is set to "channel one reaches the bare bottom condition to stop", the test is stopped when the bare bottom length of channel one is greater than or equal to the threshold; if the stop condition is set to "any one channel reaches the bare bottom condition to stop", the test is stopped when the bare bottom length of channel one or channel two is greater than or equal to the threshold. Other conditions are processed similarly, if the stop condition is not reached, the control unit continues the next brushing cycle; otherwise, the motor is immediately stopped, and the brushing times and bare bottom length are recorded; S6: data output and post-processing, after the test is completed, the control unit outputs the results, including the bare bottom length of each area, the brushing times when the condition is reached, and the corresponding pictures, and the data is automatically saved to the database for archiving and analysis.

2. The method for automatically realizing detection of scrub resistance according to claim 1, characterized in that, In step S1, the stop condition is set by the user from a plurality of predefined conditions, including: First stop condition: stop when the real-time bare bottom length of the area corresponding to "channel one" reaches or exceeds the threshold; Second stop condition: stop when the real-time bare bottom length of the area corresponding to "channel two" reaches or exceeds the threshold; Third stop condition: stop when the real-time bare bottom length of any area corresponding to "channel one" or "channel two" reaches or exceeds the threshold; Fourth stop condition: stop when the real-time bare bottom length of all areas corresponding to "channel one" and "channel two" reaches or exceeds the threshold.

3. The method for automatically realizing detection of scrub resistance according to claim 1, characterized in that, In step S1, the user selects one or more of the predefined areas, including: "Channel one" representing the entire first test channel area; "Channel two" representing the entire second test channel area; "Channel one material one" located in the first test channel; "Channel one material two" located in the first test channel; A first material region in the second test channel "channel two material one"; A second material region in the second test channel "channel two material two".

4. The method for automatically realizing detection of scrub resistance according to claim 1, characterized in that, The image processing and recognition step of step S4 specifically includes: S41, image preprocessing: the collected current image is subjected to gray scale conversion and filtering denoising processing to enhance the image contrast and reduce interference; S42, exposed base area segmentation: a threshold segmentation algorithm is used to globally threshold segment the preprocessed image to distinguish the exposed base area after coating wear from the un-worn coating area; S43, length calculation: in the user-selected detection area, the pixel width of the exposed base area in the brushing direction is counted, and the pixel width is converted into the actual physical exposed base length according to the pre-calibrated pixel-to-actual length ratio.

5. The method for automatically realizing detection of scrub resistance according to claim 1, characterized in that, In step S1, the test parameters further include the maximum brushing times; in step S5, if the stop condition based on the exposed base length is not met when the maximum brushing times are reached, the motor is also controlled to stop working, and the test is terminated.

6. The method for automatically realizing detection of scrub resistance according to claim 1, characterized in that, In step S3, the completion of one brushing cycle is determined by the position sensor linked with the control unit, and the control software sends a signal to trigger the camera to take a picture after receiving the position signal.

7. A fully automated scrub resistance detection system for implementing the method of any one of claims 1 to 6, characterized in that, The system comprises: A mechanical platform for carrying and fixing the coating sample; A clamping mechanism arranged on the mechanical platform for clamping and fixing the coating sample; A brushing execution mechanism including a brush driven by a motor for reciprocating brushing on the surface of the coating sample; An image acquisition unit including a light source and a camera, the camera acquires a coating image when receiving a trigger signal; A control unit in communication connection with the motor and the image acquisition unit, the control unit is configured to execute a computer program to realize the method steps of any one of claims 1 to 6.

8. The system for automatically achieving detection of scrub resistance according to claim 7, wherein, The control unit includes an image processing module and a logic judgment module; The image processing module is used to perform image preprocessing, exposed base area segmentation and exposed base length calculation; The logic judgment module is used to issue a stop control instruction or maintain a running state according to the calculated exposed base length and the user-set stop condition.

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