Environment-friendly non-woven fabric surface coating detection method and system

Abstract

The invention relates to an environment-friendly non-woven fabric surface coating detection method and system, and belongs to the technical field of non-special measurement of specific variables, and the method comprises the following steps: 1) cleaning all coating surfaces, and scanning each edge surface in the coating surfaces to detect whether the thickness of each edge of the coating is uniform or not; (2) scanning the coating surfaces except the edge surfaces in the coating surfaces by adopting a transverse and longitudinal linear distribution method; step 3), converting the collected coating surface image except each edge surface in the coating surface into a gray level image, and calculating gray level value distribution of the gray level image; 4) evaluating all the coating surfaces, and detecting whether all the coating surfaces have flatness defects or not; the method has the beneficial effects that whether flatness defects exist on all the coating surfaces or not is detected according to whether the thicknesses of the first planes are uniform or not and according to gray value distribution of the gray images of the second planes or not.

Description

Technical Field

[0001] The present invention belongs to the field of measurement technology that is not dedicated to a specific variable, and in particular relates to a method and system for detecting surface coatings of environmentally friendly non-woven fabrics. Background Art

[0002] Non-woven fabric is a kind of non-woven fabric, which is directly made of polymer chips, short fibers and filaments, and then woven into a net through airflow or machinery, and then reinforced by spunlace, needle punching and hot rolling, and finally finished to form a non-woven fabric. Non-woven fabric is a new type of fiber product with soft, breathable and flat forming structure. The advantages are that it does not produce fiber scraps, is strong, durable and silky soft. It is a reinforcing material and has a cotton feel. Compared with cotton fabrics, non-woven fabrics are easier to process into formed products.

[0003] Most non-woven fabrics have a relatively smooth surface, but during the production process, some minor unevenness or wrinkles may appear on the surface of the non-woven fabric due to improper control of process parameters. For example, in the hot pressing process, if the temperature and pressure are uneven, some minor unevenness will appear on the surface of the non-woven fabric, affecting the flatness of the non-woven fabric surface.

[0004] A coating can be added to the surface of the non-woven fabric. The surface coating of the non-woven fabric is a coating material used to improve the performance and function of the non-woven fabric. The surface coating of the non-woven fabric can be a waterproof coating, an anti-static coating or a flame retardant coating. However, if there are some slight unevenness on the surface of the non-woven fabric, the smoothness of the entire non-woven fabric surface coating will be affected. Summary of the invention

[0005] The technical problem to be solved by the present invention is how to detect the flatness of the surface coating of a non-woven fabric. The present invention provides an environmentally friendly non-woven fabric surface coating detection method and system, which can detect whether all coating surfaces have flatness defects based on whether the edge thickness of each edge surface in the coating surface is uniform and based on the grayscale value distribution of the grayscale image of the coating surface other than each edge surface in the coating surface.

[0006] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0007] A method for detecting surface coating of environmentally friendly non-woven fabrics, comprising the following steps:

[0008] Step 1): clean all coating surfaces, scan each edge surface of the coating surface to detect whether the thickness of each edge of the coating is uniform; wherein, an edge thickness detection method is used to detect whether the thickness of each edge of the coating is uniform;

[0009] Step 2): Scan the coating surface other than each edge surface of the coating surface using a horizontal and vertical linear distribution method;

[0010] Step 3): converting the collected coating surface images other than the edge surfaces into grayscale images, and calculating the grayscale value distribution of the grayscale images; wherein the grayscale images are analyzed by a grayscale depth analysis method;

[0011] Step 4): Evaluate all coating surfaces and detect whether there are any flatness defects on all coating surfaces.

[0012] Optionally, in step 1), during all the cleaning processes of the coating surface, a soft brush on a vacuum cleaner is used to lightly brush the dust on the coating surface to avoid damaging the fibers on the coating surface, while the vacuum cleaner absorbs the dust.

[0013] Optionally, the edge thickness detection method is as follows:

[0014] (1);

[0015] in, is a scanning straight line on a certain edge surface of the coating surface, the direction of the scanning straight line is from one direction to another direction, or the direction of the scanning straight line is from another direction to one direction, To perform an action for a scan, Scanning a certain edge surface of the coating surface along a scanning straight line direction;

[0016] For the A height point, After scanning, A collection of height points, For scanning A height point, for The scanning direction of the height points, The scanning direction of the height point is from arrive or from arrive ;

[0017] is the direction along the scanning line, scanning out height points;

[0018] Calculate the average height of each height point obtained; The average height of a certain edge surface in the coating surface is obtained as the edge thickness of a certain edge surface in the coating surface.

[0019] Optionally, in step 2), the horizontal and vertical linear distribution method is as follows:

[0020] Step 01): Scan along a straight line on the coating surface;

[0021] Step 02): During the scanning process, multiple scanning points are obtained, wherein each moment corresponds to a respective scanning point;

[0022] Step 03): Decompose each scanning point into two mutually perpendicular directions for scanning.

[0023] Optionally, in step 2), the horizontal and vertical straight line distribution method is the following formula (2):

[0024] (2);

[0025] in, For straight line On points, the scanning direction is in a straight line superior, Scanning line Each scanning point on For straight line Has Scan points; To follow the straight line Scan to get Scan points;

[0026] For straight line On The point decomposition Straight line in direction , along Direction scanning; For straight line On The point decomposition Straight line in direction , along Direction scanning; For a straight line Scan, Line Each scanning point on the Direction and decomposition Operation of scanning in direction;

[0027] For the straight line When scanning each scanning point on the Direction and decomposition Scan in the direction;

[0028] for time, To collect Moment , For the time period, Collection time period every moment within;

[0029] For time period Each moment in the corresponding straight line Each scanning point on It is the scanning result of horizontal and vertical straight line distribution.

[0030] Optionally, in step 3), the grayscale image is analyzed by a grayscale depth analysis method, using the following formula (3):

[0031] (3);

[0032] in, is the area of ​​the grayscale image, is the grayscale image The depth of the grayscale point, is the total number of grayscale points, To calculate the total number of gray points, is the depth recognition operation of grayscale points, To identify the grayscale points and calculate the total number of grayscale points on the grayscale image;

[0033] is the total number of grayscale points in the area of ​​the grayscale image The proportion of

[0034] is the area of ​​the grayscale image based on the total number of grayscale points Analyze the distribution of grayscale values ​​on the grayscale image by using the proportion on the grayscale image; The result is the gray value distribution.

[0035] Optionally, in step 4), whether all coating surfaces have flatness defects is detected based on whether the edge thickness of each edge surface in the coating surface is uniform and based on the grayscale value distribution of the grayscale image of the coating surface other than each edge surface in the coating surface.

[0036] An environmentally friendly non-woven fabric surface coating detection system, comprising:

[0037] A scanning module, used for scanning each edge surface and a coating surface other than each edge surface;

[0038] An image generation module, used to generate images of each edge surface and images of coating surfaces other than each edge surface;

[0039] An image processing module, used for processing each edge surface image and processing the coating surface image other than each edge surface;

[0040] Data processing module to evaluate all coating surfaces for flatness defects;

[0041] The scanning module, image generation module, image processing module and data processing module are connected in sequence.

[0042] Beneficial effects of the present invention:

[0043] The present invention scans each edge surface in the coating surface, and each edge surface is converted into an image to detect whether the thickness of each edge of the coating is uniform; the collected coating surface image other than each edge surface in the coating surface is converted into an image, which is a grayscale image, and the grayscale value distribution of the grayscale image is calculated; all coating surfaces are evaluated, and whether all coating surfaces have flatness defects according to whether the edge thickness of each edge surface in the coating surface is uniform and according to the grayscale value distribution of the grayscale image of the coating surface other than each edge surface in the coating surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0046] Figure 2 It is a work flow chart of the present invention;

[0047] Figure 3 It is a schematic diagram of the cross-sectional structure of the non-woven fabric of the present invention covered by the coating;

[0048] Figure 4 This is a schematic diagram of the image processing principle after the first plane is scanned according to the present invention;

[0049] Figure 5 This is a schematic diagram of the image processing principle after the second plane scanning of the present invention.

[0050] Icon: 1- nonwoven fabric, 2- coating, 3- first plane, 4- second plane. DETAILED DESCRIPTION

[0051] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0052] Embodiment 1;

[0053] like Figure 1 As shown, this embodiment provides an environmentally friendly non-woven fabric surface coating detection system, including:

[0054] A scanning module, used for scanning each edge surface and a coating surface other than each edge surface;

[0055] An image generation module, used to generate images of each edge surface and images of coating surfaces other than each edge surface;

[0056] An image processing module, used for processing each edge surface image and processing the coating surface image other than each edge surface;

[0057] Data processing module to evaluate all coating surfaces for flatness defects;

[0058] The scanning module, image generation module, image processing module and data processing module are connected in sequence.

[0059] The scanning module scans each edge surface of the coating surface, the image generation module generates images of each edge surface, and the image processing module detects whether the thickness of each edge of the coating is uniform.

[0060] The scanning module scans the coating surface except the edge surfaces in the coating surface, the image generation module generates an image of the coating surface except the edge surfaces in the coating surface, and the image processing module calculates the gray value distribution of the gray image.

[0061] The data processing module evaluates all coating surfaces and detects whether there are any flatness defects on all coating surfaces.

[0062] Embodiment 2;

[0063] like Figure 3 As shown, the outer surface of the nonwoven fabric 1 is coated with a coating 2, a first plane 3 is defined as an edge surface of the coating surface, and a second plane 4 is defined as a coating surface other than each edge surface of the coating surface.

[0064] Embodiment 3;

[0065] Based on Example 1-Example 2, Figure 2 As shown, this embodiment provides a method for detecting the surface coating of an environmentally friendly non-woven fabric, comprising the following steps:

[0066] Step 1): clean all coating surfaces (i.e., the first plane 3 and the second plane 4), scan each edge surface (i.e., the first plane 3) in the coating surface to detect whether the thickness of each edge of the coating is uniform; wherein, an edge thickness detection method is used to detect whether the thickness of each edge of the coating is uniform;

[0067] Step 2): Scanning the coating surface other than each edge surface of the coating surface (i.e., the second plane 4) by using a transverse and longitudinal linear distribution method;

[0068] Step 3): converting the collected coating surface images other than the edge surfaces into grayscale images, and calculating the grayscale value distribution of the grayscale images; wherein the grayscale images are analyzed by a grayscale depth analysis method;

[0069] Step 4): Evaluate all coating surfaces and detect whether there are any flatness defects on all coating surfaces.

[0070] In step 1), during all the cleaning processes of the coating surface, the dust on the coating surface is lightly brushed with a soft brush on a vacuum cleaner to avoid damaging the fibers on the coating surface, while the vacuum cleaner absorbs the dust.

[0071] Specifically, the edge thickness detection method in step 1) is the following formula (1):

[0072] (1);

[0073] in, is a scanning straight line on a certain edge surface of the coating surface, the direction of the scanning straight line is from one direction to another direction, or the direction of the scanning straight line is from another direction to one direction, To perform an action for a scan, Scanning a certain edge surface of the coating surface along a scanning straight line direction;

[0074] For the A height point, After scanning, A collection of height points, For scanning A height point, for The scanning direction of the height points, The scanning direction of the height point is from arrive or from arrive ;

[0075] is the direction along the scanning line, scanning out height points;

[0076] Calculate the average height of each height point obtained; In order to obtain the average height of a certain edge surface in the coating surface as the edge thickness of a certain edge surface in the coating surface (because after comparing the average height of the first plane 3 with each height point, if the average height of the first plane 3 is not much different from or the same as the height of each height point, the average height is used as the thickness of the first plane 3; otherwise, if the average height of the first plane 3 is very different from the height of each height point, the average height is not used as the thickness of the first plane 3).

[0077] In step 2), the horizontal and vertical linear distribution method is as follows:

[0078] Step 01): Scan along a straight line on the coating surface;

[0079] Step 02): During the scanning process, multiple scanning points are obtained, wherein each moment corresponds to a respective scanning point;

[0080] Step 03): Decompose each scanning point into two mutually perpendicular directions for scanning.

[0081] Or, in step 2), the horizontal and vertical linear distribution method is the following formula (2):

[0082] (2);

[0083] in, For straight line On points, the scanning direction is in a straight line superior, Scanning line Each scanning point on For straight line Has Scan points; To follow the straight line Scan to get Scan points;

[0084] For straight line On The point decomposition Straight line in direction , along Direction scanning; For straight line On The point decomposition Straight line in direction , along Direction scanning; For a straight line Scan, Line Each scanning point on the Direction and decomposition Operation of scanning in direction;

[0085] For the straight line When scanning each scanning point on the Direction and decomposition Scan in the direction;

[0086] for time, To collect Moment , For the time period, Collection time period every moment within;

[0087] For time period Each moment in the corresponding straight line Each scanning point on It is the scanning result of horizontal and vertical straight line distribution.

[0088] In step 3), the grayscale depth analysis method analyzes the grayscale image using the following formula (3):

[0089] (3);

[0090] in, is the area of ​​the grayscale image, is the grayscale image The depth of the grayscale point, is the total number of grayscale points, To calculate the total number of gray points, is the depth recognition operation of grayscale points, To identify the grayscale points and calculate the total number of grayscale points on the grayscale image;

[0091] is the total number of grayscale points in the area of ​​the grayscale image The proportion of

[0092] is the area of ​​the grayscale image based on the total number of grayscale points Analyze the distribution of grayscale values ​​on the grayscale image by using the proportion on the grayscale image; The result is the gray value distribution.

[0093] In step 4), whether all coating surfaces have flatness defects is detected based on whether the edge thickness of each edge surface in the coating surface (i.e., each first plane 3) is uniform, and based on the grayscale value distribution of the grayscale image of the coating surface other than each edge surface in the coating surface (i.e., each second plane 4).

[0094] Embodiment 4;

[0095] Based on Example 2, by combining formula (1) Figure 4 illustrate, Figure 4 is a schematic diagram of scanning the first plane 3 of the coating 2 .

[0096] Scan Line The scanning direction is from left to right, or from right to left.

[0097] Along the scan line After scanning the first plane 3 in the scanning direction, we can get The set of height points is ; If the scanning line The scanning direction is from left to right, then The height point is from arrive Arrangement; if scanning straight line The scanning direction is from right to left, then The height point is from arrive arrangement;

[0098] By obtaining the height of each height point (the height is Figure 2 The distance between the top end surface and the bottom end surface of the first plane 3, the height of each height point is The average height is calculated by calculating the distance between each height point of the first plane 3 and the bottom end surface of the first plane 3; the average height of each height point of the first plane 3 is used as the edge thickness of a certain edge surface in the coating surface, that is, the edge thickness of the first plane 3.

[0099] Embodiment 5;

[0100] Based on Example 2, by combining formula (2) Figure 5 illustrate, Figure 5 is a schematic diagram of scanning the second plane 4 of the coating 2 .

[0101] In a straight line Has scanning points, that is, along the straight line Scan to get Scan points;

[0102] straight line The first point on decomposes into There is a straight line in the direction ,straight line exist Scan direction, straight line The first point on decomposes into There is a straight line in the direction ,straight line exist Scan in the direction; and so on, straight line On The point decomposition There is a straight line in the direction ,straight line exist Scan direction, straight line On The point decomposition There is a straight line in the direction ,straight line exist Scan in the direction until a straight line is scanned On points.

[0103] Time period Inside, with At each moment, on the straight line During the scanning process, Corresponding to the straight line The first point on Corresponding to the straight line On points, and so on. Corresponding to the straight line On points, and finally obtain the scanning results of horizontal and vertical straight line distribution .

[0104] Embodiment 6;

[0105] Based on Example 2, by combining formula (3) Figure 5 Explanation: After scanning the horizontal and vertical straight line distribution, we get Figure 5 The scanning area, Figure 5 The scanned area can be converted into a grayscale image, i.e., a straight line The first point on the line On The rectangular area between the points can be converted into a grayscale image.

[0106] The area of ​​the grayscale image is , each point in the grayscale image is identified by its color. The grayer the point, the deeper the depth of the point in the grayscale image. Then a depth threshold is set for the depth of the point. If the point in the grayscale image is deeper than the depth threshold, it is a grayscale point in the grayscale image. Find the grayscale point on the grayscale image.

[0107] Finally, according to the total number of gray points in the area of ​​the grayscale image The distribution of grayscale values ​​on the grayscale image is analyzed by the ratio of the grayscale values ​​on the grayscale image.

[0108] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope of the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for detecting surface coating of environmentally friendly non-woven fabrics, characterized in that: The steps include: Step 1): clean all coating surfaces, scan each edge surface of the coating surface to detect whether the thickness of each edge of the coating is uniform; wherein, an edge thickness detection method is used to detect whether the thickness of each edge of the coating is uniform; Step 2): Scan the coating surface other than each edge surface of the coating surface using a horizontal and vertical linear distribution method; Step 3): converting the collected coating surface images other than the edge surfaces into grayscale images, and calculating the grayscale value distribution of the grayscale images; wherein the grayscale images are analyzed by a grayscale depth analysis method; Step 4): Evaluate all coating surfaces and detect whether there are any flatness defects on all coating surfaces.

2. The method for detecting surface coating of environmentally friendly nonwoven fabric according to claim 1, characterized in that: In the step 1), during the cleaning process of all the coating surfaces, the dust on the coating surface is lightly brushed with a soft brush on a vacuum cleaner to avoid damaging the fibers on the coating surface, while the vacuum cleaner absorbs the dust.

3. The method for detecting the surface coating of an environmentally friendly non-woven fabric according to claim 2, characterized in that: The edge thickness detection method is as follows: (1)； in, is a scanning straight line on a certain edge surface of the coating surface, the direction of the scanning straight line is from one direction to another direction, or the direction of the scanning straight line is from another direction to one direction, To perform an action for a scan, Scanning a certain edge surface of the coating surface along a scanning straight line direction; For the A height point, After scanning, A collection of height points, For scanning A height point, for The scanning direction of the height points, The scanning direction of the height point is from arrive or from arrive ; is the direction along the scanning line, scanning out height points; Calculate the average height of each height point obtained; The average height of a certain edge surface in the coating surface is obtained as the edge thickness of a certain edge surface in the coating surface.

4. The method for detecting surface coating of environmentally friendly non-woven fabrics according to claim 1, characterized in that: In step 2), the horizontal and vertical linear distribution method is as follows: Step 01): Scan along a straight line on the coating surface; Step 02): During the scanning process, a plurality of scanning points are obtained; wherein each moment corresponds to a respective scanning point; Step 03): Decompose each scanning point into two mutually perpendicular directions for scanning.

5. The method for detecting surface coating of environmentally friendly non-woven fabric according to claim 1, characterized in that: In the step 2), the horizontal and vertical linear distribution method is the following formula (2): (2)； in, For straight line On points, the scanning direction is in a straight line superior, Scanning line Each scanning point on For straight line Has Scan points; To follow the straight line Scan to get Scan points; For straight line On The point decomposition Straight line in direction , along Direction scanning; For straight line On The point decomposition Straight line in direction , along Direction scanning; For a straight line Scan, Line Each scanning point on the Direction and decomposition Operation of scanning in direction; For the straight line When scanning each scanning point on the Direction and decomposition Scan in the direction; for time, To collect Moment , For the time period, Collection time period every moment within; For time period Each moment in the corresponding straight line Each scanning point on It is the scanning result of horizontal and vertical straight line distribution.

6. The method for detecting surface coating of environmentally friendly nonwoven fabric according to claim 1, characterized in that: In step 3), the grayscale depth analysis method analyzes the grayscale image using the following formula (3): (3)； in, is the area of ​​the grayscale image, is the grayscale image The depth of the grayscale point, is the total number of grayscale points, To calculate the total number of gray points, is the depth recognition operation of grayscale points, To identify the grayscale points and calculate the total number of grayscale points on the grayscale image; is the total number of grayscale points in the area of ​​the grayscale image The proportion of is the area of ​​the grayscale image based on the total number of grayscale points Analyze the distribution of grayscale values ​​on the grayscale image by using the proportion on the grayscale image; The result is the gray value distribution.

7. The method for detecting surface coating of environmentally friendly nonwoven fabrics according to claim 1, characterized in that: In the step 4), whether all the coating surfaces have flatness defects is detected based on whether the edge thickness of each edge surface in the coating surface is uniform, and based on the grayscale value distribution of the grayscale image of the coating surface other than each edge surface in the coating surface.

8. An environmentally friendly non-woven fabric surface coating detection system, used to perform an environmentally friendly non-woven fabric surface coating detection method according to any one of claims 1 to 7, characterized in that: include: A scanning module, used for scanning each edge surface and a coating surface other than each edge surface; An image generation module, used to generate images of each edge surface and images of coating surfaces other than each edge surface; An image processing module, used for processing each edge surface image and processing the coating surface image other than each edge surface; Data processing module to evaluate all coating surfaces for flatness defects; The scanning module, the image generating module, the image processing module and the data processing module are connected in sequence.

Images