CN117606371A - Coating thickness online monitoring system and method based on visual detection - Google Patents
Coating thickness online monitoring system and method based on visual detection Download PDFInfo
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- 239000011248 coating agent Substances 0.000 title claims abstract description 135
- 238000000576 coating method Methods 0.000 title claims abstract description 135
- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000012544 monitoring process Methods 0.000 title claims abstract description 27
- 238000001514 detection method Methods 0.000 title claims abstract description 22
- 230000000007 visual effect Effects 0.000 title claims abstract description 16
- 230000009466 transformation Effects 0.000 claims abstract description 50
- 239000002002 slurry Substances 0.000 claims description 77
- 238000005286 illumination Methods 0.000 claims description 35
- 238000006243 chemical reaction Methods 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 12
- 238000004458 analytical method Methods 0.000 claims description 11
- 238000011179 visual inspection Methods 0.000 claims description 10
- 238000004422 calculation algorithm Methods 0.000 claims description 7
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- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 4
- 229910052710 silicon Inorganic materials 0.000 description 4
- 239000010703 silicon Substances 0.000 description 4
- 239000003086 colorant Substances 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000001035 drying Methods 0.000 description 3
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- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000005250 beta ray Effects 0.000 description 1
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- 238000013135 deep learning Methods 0.000 description 1
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- 238000007711 solidification Methods 0.000 description 1
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
- G01B11/0616—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material of coating
- G01B11/0683—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material of coating measurement during deposition or removal of the layer
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30232—Surveillance
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- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Geometry (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention provides a coating thickness online monitoring system and a method based on visual detection, wherein the method comprises the following steps: and acquiring image information of the object after coating, calculating a minimum transformation parameter and a maximum transformation parameter according to the change condition of each pixel point of the object in the image, measuring thickness information of the corresponding first target pixel point and second target pixel point, and judging whether coating is qualified or not according to the thickness information. The invention has the beneficial effects that: the method has the advantages that whether the coating is qualified or not can be judged only by measuring the thickness values corresponding to the two target pixel points, so that manpower resources are saved, the detection efficiency is improved, and the production efficiency is further improved.
Description
Technical Field
The invention relates to the field of artificial intelligence, in particular to a coating thickness online monitoring system and method based on visual detection.
Background
Coating is the uniform application of one or more layers of coating material to the surface of a substrate in order to improve the surface properties of the substrate, such as brightness, smoothness and barrier properties. The thickness of the coating is critical to ensure product quality. A uniform thickness represents that the surface properties of the product remain uniform, and is particularly important for high quality products, as the uniformity of the coating directly affects the performance of the product.
At present, the quality of a coated product is monitored mainly by manual measurement, and the method is time-consuming and labor-consuming, can not realize automatic measurement, and seriously affects the production efficiency.
Disclosure of Invention
The invention mainly aims to provide a coating thickness online monitoring system and method based on visual detection, and aims to solve the problems that manual measurement is time-consuming and labor-consuming and production efficiency is seriously affected.
The invention also provides a coating thickness online monitoring system based on visual detection, which comprises:
the judging module is used for judging whether the coating of the object slurry is finished or not;
the first acquisition module is used for acquiring a first image of an object after coating is completed if coating of the object slurry is completed, and acquiring pixel values of corresponding pixel points of the object in the first image;
the calculating module is used for calculating the maximum color value difference of the pixel values in the first image and judging whether the maximum color value difference is smaller than a preset maximum color value difference or not;
the second acquisition module is used for acquiring picture information of the object at n moments after coating is completed through a preset camera device if the object is coated;
the analysis module is used for analyzing the pixel information of each pixel point of the object in the picture information through a preset picture analysis method so as to obtain the pixel information of each pixel point at n moments 、/>、...、/>、...、Obtaining a pixel information set of each pixel point; wherein (1)>The expression time is +.>Pixel information of the ith pixel point, and +.>；
An input module for inputting RGB values in the pixel information into preset formulas respectivelyIn (1) obtaining the corresponding transformation parameter of each pixel information set +.>The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Transformation parameter +_representing the set of pixel information corresponding to the ith pixel point>；
The acquisition module is used for acquiring the minimum transformation parameter value and the maximum transformation parameter value in each pixel transformation parameter;
the measuring module is used for measuring thickness information of the first target pixel point corresponding to the minimum transformation parameter value and thickness information of the second target pixel point corresponding to the maximum transformation parameter value based on a preset thickness measuring device;
and the comparison module is used for comparing the thickness information of the first target pixel point and the second target pixel point and judging whether the coating is qualified or not according to the comparison result.
Further, the first acquisition module includes:
the object placing sub-module is used for placing the object at a preset position on a preset conveyor belt after coating of the object slurry is completed;
the slurry type acquisition sub-module is used for acquiring the type of the slurry and acquiring a target illumination parameter based on the type of the slurry;
The light generator control submodule is used for controlling a preset light generator according to the target illumination parameter to enable the illumination parameter of the light environment where the object is located at the preset position to be the target illumination parameter;
the first image acquisition sub-module is used for acquiring a first image of an object at the preset position by using a preset camera;
and the pixel value acquisition sub-module is used for acquiring the pixel value of the pixel point corresponding to the object in the first image.
Further, the computing module includes:
an RGB value obtaining sub-module for obtaining RGB values of each pixel value;
a maximum pixel calculation sub-module for passing through the formulaCalculating the maximum colour value difference, wherein +_>Representing the maximum colour difference +.>Representation ofTwo pixel points with maximum value (++)>，/>，/>) And (/ ->，/>，/>）；
And the maximum color value difference judging sub-module is used for judging whether the maximum color value difference is smaller than a preset maximum color value difference.
Further, the on-line monitoring system for coating thickness based on visual detection further comprises:
the pixel point acquisition module is used for acquiring two pixel points with the largest pixel error in the current image of the object, and the two pixel points are respectively marked as a third target pixel point and a fourth target pixel point;
The thickness information measuring module is used for measuring thickness information of the third target pixel point and the fourth target pixel point based on a preset thickness measuring device;
the maximum value acquisition module is used for acquiring the maximum value and the minimum value of the first target pixel point, the second target pixel point, the third target pixel point and the fourth target pixel point;
the target difference value calculation module is used for calculating a target difference value of the maximum value and the minimum value;
the target difference judging module is used for judging whether the target difference is smaller than a preset difference or not;
and the judging module is used for judging that the coating of the object is qualified if the difference value is smaller than the preset difference value, and judging that the coating of the object is unqualified if the difference value is not smaller than the preset difference value.
Further, the on-line monitoring system for coating thickness based on visual detection further comprises:
the position marking module is used for marking the positions of the first target pixel point and the second target pixel point on the object image if the coating is unqualified and uploading the positions to an unqualified database;
the data judging module is used for judging whether the unqualified data in the unqualified database reaches a preset value or not;
the position acquisition module is used for acquiring the positions of the first target pixel points and the second target pixel points in each object image if the object images are the same;
The coordinate system marking module is used for marking all first target pixel points on a first coordinate system according to the positions of the first target pixel points in the object image, and marking all second target pixel points on a second coordinate system according to the positions of the second target pixel points in the object image;
the pixel point density calculation module is used for calculating the pixel point density in a first coordinate system and the second coordinate system by using a preset kernel density estimation algorithm;
the pixel density judging module is used for judging whether the pixel density is greater than a preset density;
and the pixel density sending module is used for sending the pixel density to a worker to adjust the coating parameters if the pixel density is larger than the preset density.
The invention also provides a coating thickness online monitoring method based on visual detection, which comprises the following steps:
judging whether the coating of the object slurry is finished or not;
if the coating of the object slurry is finished, acquiring a first image of the object after the coating is finished, and acquiring a pixel value of a pixel point corresponding to the object in the first image;
calculating the maximum color value difference of pixel values in the first image, and judging whether the maximum color value difference is smaller than a preset maximum color value difference or not;
If yes, acquiring picture information of the object at n moments after coating is completed through a preset camera device;
analyzing pixel information of each pixel point of the object in the picture information by a preset picture analysis method to obtain the pixel information of each pixel point at n times、/>、...、/>、...、/>Obtaining a pixel information set of each pixel point; wherein (1)>The expression time is +.>Pixel information of the ith pixel point, and；
respectively inputting RGB values in the pixel information into a preset formulaIn (1) obtaining the corresponding transformation parameter of each pixel information set +.>The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Transformation parameter +_representing the set of pixel information corresponding to the ith pixel point>；
Acquiring a minimum transformation parameter value and a maximum transformation parameter value in each pixel transformation parameter;
based on a preset thickness measuring device, measuring thickness information of a first target pixel point corresponding to a minimum conversion parameter value and thickness information of a second target pixel point corresponding to a maximum conversion parameter value;
and comparing the thickness information of the first target pixel point and the second target pixel point, and judging whether the coating is qualified or not according to the comparison result.
Further, the step of acquiring a first image of the object after the coating is completed and acquiring a pixel value of a pixel point corresponding to the object in the first image if the coating of the object slurry is completed includes:
If the coating of the object slurry is finished, placing the coated object at a preset position on a preset conveyor belt;
acquiring the type of the slurry, and acquiring a target illumination parameter based on the type of the slurry;
controlling a preset light generator according to the target illumination parameter to enable the illumination parameter of the light environment where the object is located at the preset position to be the target illumination parameter;
acquiring a first image of an object at the preset position by using a preset camera;
and acquiring pixel values of corresponding pixel points of the object in the first image.
Further, the step of calculating a maximum color value difference of pixel values in the first image and determining whether the maximum color value difference is smaller than a preset maximum color value difference includes:
acquiring RGB values of each pixel value;
by the formulaCalculating the maximum colour value difference, wherein +_>Representing the maximum colour difference +.>Representation ofTwo pixel points with maximum value (++)>，/>，/>) And (/ ->，/>，/>）；
And judging whether the maximum color value difference is smaller than a preset maximum color value difference or not.
Further, after the step of measuring the thickness information of the first target pixel point corresponding to the minimum transformation parameter value and the thickness information of the second target pixel point corresponding to the maximum transformation parameter value based on the preset thickness measurement device, the method further includes:
Acquiring two pixel points with the largest pixel error in the current image of the object, and respectively marking the two pixel points as a third target pixel point and a fourth target pixel point;
measuring thickness information of the third target pixel point and the fourth target pixel point based on a preset thickness measuring device;
obtaining maximum values and minimum values in the first target pixel point, the second target pixel point, the third target pixel point and the fourth target pixel point;
calculating a target difference value of the maximum value and the minimum value;
judging whether the target difference value is smaller than a preset difference value or not;
if the difference value is smaller than the preset difference value, judging that the coating of the object is qualified, otherwise, judging that the coating of the object is unqualified.
Further, after the step of comparing the thickness information of the first target pixel point and the second target pixel point and judging whether the coating is qualified according to the comparison result, the method further comprises:
if the coating is unqualified, marking the positions of the first target pixel point and the second target pixel point on the object image, and uploading the positions to an unqualified database;
judging whether the unqualified data in the unqualified database reaches a preset value or not;
if yes, the positions of the first target pixel points and the second target pixel points in the object images are obtained;
Marking all first target pixel points on a first coordinate system according to the positions of the first target pixel points in the object image, and marking all second target pixel points on a second coordinate system according to the positions of the second target pixel points in the object image;
calculating pixel point densities in a first coordinate system and the second coordinate system by using a preset kernel density estimation algorithm;
judging whether the pixel density is greater than a preset density;
and if the pixel density is greater than the preset density, sending the pixel density to a worker to adjust the coating parameters.
The invention has the beneficial effects that: the method comprises the steps of obtaining image information of an object after coating, calculating minimum transformation parameters and maximum transformation parameters according to the change condition of each pixel point of the object in the image, measuring thickness information of a first target pixel point and a second target pixel point corresponding to the minimum transformation parameters and judging whether coating is qualified according to the thickness information, so that judgment on whether coating is qualified or not can be realized by only measuring thickness values corresponding to the two target pixel points, manpower resources are saved, detection efficiency is improved, and production efficiency is further improved.
Drawings
FIG. 1 is a block diagram schematically illustrating the structure of an on-line monitoring system for coating thickness based on visual inspection according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for online monitoring of coating thickness based on visual inspection according to an embodiment of the invention;
fig. 3 is a block diagram schematically illustrating a structure of a computer device according to an embodiment of the present application.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that, in the embodiments of the present invention, all directional indicators (such as up, down, left, right, front, and back) are merely used to explain the relative positional relationship, movement conditions, and the like between the components in a specific posture (as shown in the drawings), if the specific posture is changed, the directional indicators correspondingly change, and the connection may be a direct connection or an indirect connection.
The term "and/or" is herein merely an association relation describing an associated object, meaning that there may be three relations, e.g., a and B, may represent: a exists alone, A and B exist together, and B exists alone.
Furthermore, descriptions such as those referred to as "first," "second," and the like, are provided for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implying an order of magnitude of the indicated technical features in the present disclosure. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present invention.
Referring to fig. 1, the present invention proposes an online monitoring system for coating thickness based on visual detection, comprising:
a judging module 10 for judging whether the coating of the object slurry is completed;
the first collecting module 20 is configured to collect a first image of the object after the coating is completed if the coating of the slurry of the object is completed, and obtain a pixel value of a pixel point corresponding to the object in the first image;
The calculating module 30 is configured to calculate a maximum color value difference of pixel values in the first image, and determine whether the maximum color value difference is smaller than a preset maximum color value difference;
the second collecting module 40 is configured to collect, if yes, image information of n times after the object is coated by using a preset camera device;
the analysis module 50 is configured to analyze pixel information of each pixel point of the object in the picture information by using a preset picture analysis method, so as to obtain pixel information of each pixel point at n times、/>、...、/>、...、Obtaining a pixel information set of each pixel point; wherein (1)>The expression time is +.>Pixel information of the ith pixel point, and +.>；
An input module 60 for inputting the RGB values in the pixel information into preset formulasIn (1) obtaining the corresponding transformation parameter of each pixel information set +.>The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Transformation parameter +_representing the set of pixel information corresponding to the ith pixel point>；
An acquisition module 70 for acquiring a minimum conversion parameter value and a maximum conversion parameter value among the respective pixel conversion parameters;
the measurement module 80 is configured to measure thickness information of the first target pixel point corresponding to the minimum conversion parameter value and thickness information of the second target pixel point corresponding to the maximum conversion parameter value based on a preset thickness measurement device;
The comparison module 90 is configured to compare thickness information of the first target pixel point and the second target pixel point, and determine whether the coating is qualified according to the comparison result.
As described in the determination module 10, whether the coating of the slurry is completed or not is determined, wherein the determination mode of the completion of the coating of the slurry may be that the slurry is received after the slurry is coated, so that the coating of the slurry is determined to be completed, or the coating of the slurry is manually input. The object may in particular be a different substrate, such as a semiconductor substrate or the like; the applied slurry is, for example, a photosensitive dry film.
As described in the first acquisition module 20, if the coating of the object slurry is completed, a first image of the object after the coating is completed is acquired, and a pixel value of a corresponding pixel point of the object in the first image is acquired. After the coating of the object slurry is completed, a first image of the object can be acquired, and since the object slurry needs to be detected to be coated uniformly when the coating is just completed, the first image can be acquired, and the first image is judged through the pixel value, so that whether the coating is uniform or not is primarily judged, if the pixel error is larger, the coating of the object is indicated to be nonuniform, otherwise, the coating of the object is regarded to be uniform, and in addition, the application is only applicable to objects with pure colors, such as silicon substrates with pure colors, and the application is not applicable to objects with various color combinations.
As described in the calculation module 30, after the errors of each pixel point are collected, the corresponding maximum color value difference may be calculated by three RGB values of the pixel point, that is, all the pixel values are sequentially input into a preset calculation formula, and detailed description of the calculation formula is omitted herein, in some embodiments, the calculation may be performed in the CIELAB color space, the calculation manner is the same as that of RGB, and then the calculated maximum color value difference is compared with the preset maximum color value difference, so as to further determine according to the comparison result.
As described in the second collecting module 40, if yes, the preset camera device collects the picture information of n times after the object is coated, when the maximum color value difference is smaller than the preset maximum color value difference, it indicates that the coating of the slurry is uniform, so that the picture information of n times after the coating of the object is finished can be collected in real time through the camera, where n times are preset times, and since the object needs to be dried or aired after the slurry is coated, if the slurry material is not closed or the placing position of the object is not in a horizontal state during drying, the coating may be aggregated or inclined, so that the coating thickness of the slurry is inconsistent when the object is finished, and n times may be times of a preset interval time, for example, 5 minutes, because the coating thickness at each position of the slurry generally does not change after the slurry is solidified, the pixel error of the slurry does not change after a certain time, and therefore, n times do not include the subsequent time, that is, that the n times should be before the coating solidification.
As described in the analysis module 50, the pixel information of each pixel point of the object in the picture information is analyzed by a preset picture analysis method to obtain the pixel information of each pixel point at n times、/>、...、/>、...、/>Obtaining a pixel information set of each pixel point; wherein (1)>The expression time is +.>Pixel information of the ith pixel point, and +.>. The pixel information set may reflect the corresponding change condition of each pixel, so that the slurry of the pixel at the position where the pixel value changes fast is either a solidified block or reduced fast, and the slurry condition at the position of each pixel may be inconsistent, so that statistics may be performed according to the change condition of each pixel.
As described in the input module 60, the RGB values in the pixel information are respectively input into a preset formulaIn (1) obtaining the corresponding transformation parameter of each pixel information set +.>The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Transformation parameter +_representing the set of pixel information corresponding to the ith pixel point>. That is, the transformation parameters can reflect the change condition of each pixel point, if the pixel value of the pixel point changes rapidly, the slurry changes greatly, for example, the slurry is the fastest, or the slurry moves, and in general, the slurry changes and the slurry is coated The thickness of the cloth is related and can therefore be determined based thereon.
As described in the acquisition module 70 and the measurement module 80, the minimum transform parameter value and the maximum transform parameter value among the respective pixel transform parameters are acquired. I.e. the smallest transformation parameter is counted, the thickness difference between the two locations is generally the largest, and thus the thickness information of the first target pixel and the second target pixel can be measured. The measurement can be performed by a thickness measuring beta-ray sensor. In particular, since the foregoing and the description illustrate that the transformation parameter values are according to preset formulasAs a result, in the actual process, the position where the maximum transformation parameter is located is generally the position where the slurry is coated thickest, because the slurry undergoes color transformation during the drying process, and the color influence of the silicon substrate is larger immediately after the slurry is coated, so that the color change of the position where the coating thickness is thickest is also the largest, i.e. the corresponding transformation parameter is correspondingly larger, while the color influence of the silicon substrate is larger for the position where the coating thickness is smaller, and if the coated slurry is smaller, the color is more similar to the ground color of the silicon substrate, i.e. the degree of color change is far lower than the normal value, the degree of color change of the slurry dried is lower, and therefore the coating thickness of the position corresponding to the minimum transformation parameter is the smallest, and the coating thickness of the position corresponding to the maximum transformation parameter is the largest. In some other embodiments, if the slurry moves during the drying process, the conversion parameter may be the largest, where the first is the position of the largest coating thickness, and the second is the position of the smallest coating thickness, which is shown in the experiment, generally is the position of the largest coating thickness, and of course, if the slurry moves significantly, the color difference of the whole finished product may reach a significant step, which may even be observed artificially, in some specific embodiments, the subsequent step may also be calculated according to the color difference value, so as to detect the error, and in particular, the scheme of detecting the color difference of the finished product is described in detail later herein, which is not repeated herein.
As described in the comparison module 90, the thickness difference between the first target pixel point and the second target pixel point is calculated according to the measurement result, and then the judgment is performed according to the thickness difference, so that the judgment of whether the coating is qualified or not can be realized by measuring the thickness values corresponding to the two target pixel points, not only saving human resources, but also improving the detection efficiency and further improving the production efficiency.
In one embodiment, the first acquisition module 20 includes:
an object placement sub-module 201, configured to place the object at a preset position on a preset conveyor belt after the coating of the object slurry is completed;
a slurry type obtaining sub-module 202, configured to obtain a type of the slurry, and obtain a target illumination parameter based on the type of the slurry;
a light generator control submodule 203, configured to control a preset light generator according to the target illumination parameter so that the illumination parameter of the light environment where the object is located at the preset position is the target illumination parameter;
a first image acquisition sub-module 204, configured to acquire a first image of an object at the preset position by using a preset camera;
the pixel value obtaining sub-module 205 is configured to obtain a pixel value of a pixel point corresponding to the object in the first image.
As described in the object placement sub-module 201, the slurry is generally transferred by a conveyor belt after being applied, so that the slurry can be placed at a preset position of the conveyor belt, so that the camera can take pictures to obtain data.
As described in the slurry type acquisition sub-module 202, the type of the slurry is acquired, and the target illumination parameter is acquired based on the type of the slurry. Because different slurries may have different colors, pixel values possibly obtained in different illumination environments cannot reflect specific situations, so that illumination parameters need to be adjusted according to the types of the slurries so as to obtain the pixel values better, specifically, the corresponding relation between the slurry types and the illumination parameters can be preset, and after the slurry types are obtained, the target illumination parameters can be directly obtained according to the corresponding relation.
As described in the light generator control submodule 203, a preset light generator is controlled according to the target illumination parameter so that the illumination parameter of the light environment where the object is located at the preset position is the target illumination parameter. The illumination parameters are adjusted to be target illumination parameters, so that the object is under the illumination condition.
As described in the first image acquisition sub-module 204 and the pixel value acquisition sub-module 205, a preset camera is used to acquire a first image of an object at the preset position; and acquiring pixel values of corresponding pixel points of the object in the first image. So that the obtained pixel value can reflect the change condition of the slurry.
In one embodiment, the computing module 30 includes:
an RGB value acquiring sub-module 301, configured to acquire RGB values of each pixel value;
a maximum pixel computation sub-module 302 for passing through the formulaCalculating the maximum colour value difference, wherein +_>Representing the maximum colour difference +.>Representation ofTwo pixel points with maximum value (++)>，/>，/>) And (/ ->，/>，/>）；
The maximum color value difference judging sub-module 303 is configured to judge whether the maximum color value difference is smaller than a preset maximum color value difference.
And acquiring RGB values of each pixel value, calculating the maximum color value difference, and judging whether the maximum color value difference is smaller than a preset maximum color value difference or not. I.e. the pixels are represented by RGB values by a preset tri-valued method, and then by the formulaAnd calculating the maximum color value difference, and if the maximum color value difference is smaller than the preset maximum color value difference, continuing to detect the next step, otherwise, directly judging that the product is unqualified and needing to be coated again.
In one embodiment, the visual detection-based coating thickness online monitoring system further comprises:
the pixel point obtaining module 901 is configured to obtain two pixel points with the largest pixel error in the current image of the object, which are respectively denoted as a third target pixel point and a fourth target pixel point;
a thickness information measurement module 902, configured to measure thickness information of the third target pixel point and the fourth target pixel point based on a preset thickness measurement device;
a maximum value obtaining module 903, configured to obtain a maximum value and a minimum value of the first target pixel point, the second target pixel point, the third target pixel point, and the fourth target pixel point;
a target difference calculation module 904, configured to calculate a target difference between the maximum value and the minimum value;
a target difference judging module 905, configured to judge whether the target difference is smaller than a preset difference;
a determining module 906, configured to determine that the coating of the object is acceptable if the difference is smaller than the preset difference, and determine that the coating of the object is unacceptable if the difference is not smaller than the preset difference.
In order to better detect the data, the two pixel points with the largest error in the current image can be obtained, the thickness information of the two pixel points is measured, the maximum value and the minimum value are found according to the thickness information of the first target pixel point, the second target pixel point, the third target pixel point and the fourth target pixel point, and then the coating qualification condition of the object is judged according to the calculated target difference value, so that further detection can be performed, and the detection accuracy is improved.
In one embodiment, the visual detection-based coating thickness online monitoring system further comprises:
a position marking module 1001, configured to mark positions of the first target pixel point and the second target pixel point on the object image if the coating is not qualified, and upload the positions to a failure database;
a data judging module 1002, configured to judge whether the reject data in the reject database reaches a preset value;
a position obtaining module 1003, configured to obtain, if yes, positions of the first target pixel point and the second target pixel point in each object image;
a coordinate system marking module 1004, configured to mark all first target pixels on a first coordinate system according to the positions of the first target pixels in the object image, and mark all second target pixels on a second coordinate system according to the positions of the second target pixels in the object image;
a pixel density calculating module 1005, configured to calculate pixel densities in a first coordinate system and the second coordinate system using a preset kernel density estimation algorithm;
a pixel density judging module 1006, configured to judge whether the pixel density is greater than a preset density;
And the pixel density sending module 1007 is configured to send the pixel density to a worker to adjust the coating parameters if the pixel density is greater than a preset density.
As described in the above module, if the first target pixel point and the second target pixel point of the unqualified coated object within a certain period of time are both at the same position or at similar positions, it may be determined that the parameter setting of the device is unreasonable, specifically, according to the position of the first target pixel point in the object image, all the first target pixel points are marked on the first coordinate system, and according to the position of the second target pixel point in the object image, all the second target pixel points are marked on the second coordinate system, the pixel point densities in the first coordinate system and the second coordinate system are calculated by using a preset kernel density estimation algorithm, and the kernel density estimation may be used to estimate the density of the points in an area. By placing a kernel (typically a gaussian kernel) at each point, a point density estimate for each location in the space can be calculated. The high density region indicates dot aggregation. Judging whether the pixel density is greater than a preset density, and if so, sending the pixel density to a worker to adjust the coating parameters.
Referring to fig. 2, the invention further provides an online monitoring method for coating thickness based on visual detection, which comprises the following steps:
s1: judging whether the coating of the object slurry is finished or not;
s2: if the coating of the object slurry is finished, acquiring a first image of the object after the coating is finished, and acquiring a pixel value of a pixel point corresponding to the object in the first image;
s3: calculating the maximum color value difference of pixel values in the first image, and judging whether the maximum color value difference is smaller than a preset maximum color value difference or not;
s4: if yes, acquiring picture information of the object at n moments after coating is completed through a preset camera device;
s5: analyzing pixel information of each pixel point of the object in the picture information by a preset picture analysis method to obtain the pixel information of each pixel point at n times、/>、...、/>、...、/>Obtaining a pixel information set of each pixel point; wherein (1)>The expression time is +.>Pixel information of the ith pixel point, and；
s6: respectively inputting RGB values in the pixel information into a preset formulaIn (1) obtaining the corresponding transformation parameter of each pixel information set +.>The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Transformation parameter +_representing the set of pixel information corresponding to the ith pixel point >；
S7: acquiring a minimum transformation parameter value and a maximum transformation parameter value in each pixel transformation parameter;
s8: based on a preset thickness measuring device, measuring thickness information of a first target pixel point corresponding to a minimum conversion parameter value and thickness information of a second target pixel point corresponding to a maximum conversion parameter value;
s9: and comparing the thickness information of the first target pixel point and the second target pixel point, and judging whether the coating is qualified or not according to the comparison result.
In one embodiment, the step S2 of acquiring the first image of the object after the coating is completed and acquiring the pixel value of the corresponding pixel point of the object in the first image if the coating of the object slurry is completed includes:
s201: if the coating of the object slurry is finished, placing the coated object at a preset position on a preset conveyor belt;
s202: acquiring the type of the slurry, and acquiring a target illumination parameter based on the type of the slurry;
s203: controlling a preset light generator according to the target illumination parameter to enable the illumination parameter of the light environment where the object is located at the preset position to be the target illumination parameter;
s204: acquiring a first image of an object at the preset position by using a preset camera;
S205: and acquiring pixel values of corresponding pixel points of the object in the first image.
In one embodiment, the step S3 of calculating the maximum color value difference of the pixel values in the first image and determining whether the maximum color value difference is smaller than a preset maximum color value difference includes:
s301: acquiring RGB values of each pixel value;
s302: by the formulaCalculating the maximum colour value difference, wherein +_>Representing the maximum colour difference +.>Representation ofTwo pixel points with maximum value (++)>，/>，/>) And (/ ->，/>，/>）；
S303: and judging whether the maximum color value difference is smaller than a preset maximum color value difference or not.
In one embodiment, after the step S8 of measuring the thickness information of the first target pixel point corresponding to the minimum conversion parameter value and the thickness information of the second target pixel point corresponding to the maximum conversion parameter value based on the preset thickness measurement device, the method further includes:
s901: acquiring two pixel points with the largest pixel error in the current image of the object, and respectively marking the two pixel points as a third target pixel point and a fourth target pixel point;
s902: measuring thickness information of the third target pixel point and the fourth target pixel point based on a preset thickness measuring device;
s903: obtaining maximum values and minimum values in the first target pixel point, the second target pixel point, the third target pixel point and the fourth target pixel point;
S904: calculating a target difference value of the maximum value and the minimum value;
s905: judging whether the target difference value is smaller than a preset difference value or not;
s906: if the difference value is smaller than the preset difference value, judging that the coating of the object is qualified, otherwise, judging that the coating of the object is unqualified.
In one embodiment, after the step S9 of comparing the thickness information of the first target pixel point and the second target pixel point and determining whether the coating is qualified according to the comparison result, the method further includes:
s10001: if the coating is unqualified, marking the positions of the first target pixel point and the second target pixel point on the object image, and uploading the positions to an unqualified database;
s1002: judging whether the unqualified data in the unqualified database reaches a preset value or not;
s1003: if yes, the positions of the first target pixel points and the second target pixel points in the object images are obtained;
s1004: marking all first target pixel points on a first coordinate system according to the positions of the first target pixel points in the object image, and marking all second target pixel points on a second coordinate system according to the positions of the second target pixel points in the object image;
S1005: calculating pixel point densities in a first coordinate system and the second coordinate system by using a preset kernel density estimation algorithm;
s1006: judging whether the pixel density is greater than a preset density;
s1007: and if the pixel density is greater than the preset density, sending the pixel density to a worker to adjust the coating parameters.
The invention has the beneficial effects that: the method comprises the steps of obtaining image information of an object after coating, calculating minimum transformation parameters and maximum transformation parameters according to the change condition of each pixel point of the object in the image, measuring thickness information of a first target pixel point and a second target pixel point corresponding to the minimum transformation parameters and judging whether coating is qualified according to the thickness information, so that judgment on whether coating is qualified or not can be realized by only measuring thickness values corresponding to the two target pixel points, manpower resources are saved, detection efficiency is improved, and production efficiency is further improved.
Referring to fig. 3, a computer device is further provided in the embodiment of the present application, where the computer device may be a server, and the internal structure of the computer device may be as shown in fig. 3. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the computer is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing various picture information and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, can implement the method for monitoring the coating thickness on line based on visual detection according to any one of the embodiments.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is merely a block diagram of a portion of the architecture in connection with the present application and is not intended to limit the computer device to which the present application is applied.
The embodiment of the application further provides a computer readable storage medium, on which a computer program is stored, where the computer program can implement the online monitoring method for coating thickness based on visual detection according to any one of the above embodiments when executed by a processor.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium provided herein and used in embodiments may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, apparatus, article or method that comprises the element.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (10)
1. An on-line monitoring system for coating thickness based on visual inspection, comprising:
the judging module is used for judging whether the coating of the object slurry is finished or not;
the first acquisition module is used for acquiring a first image of an object after coating is completed if coating of the object slurry is completed, and acquiring pixel values of corresponding pixel points of the object in the first image;
the calculating module is used for calculating the maximum color value difference of the pixel values in the first image and judging whether the maximum color value difference is smaller than a preset maximum color value difference or not;
the second acquisition module is used for acquiring picture information of the object at n moments after coating is completed through a preset camera device if the object is coated;
the analysis module is used for analyzing the pixel information of each pixel point of the object in the picture information through a preset picture analysis method so as to obtain the pixel information of each pixel point at n moments 、/>、...、/>、...、/>Obtaining a pixel information set of each pixel point; wherein (1)>The expression time is +.>Pixel information of the ith pixel point, and；
an input module for inputting RGB values in the pixel information into preset formulas respectivelyIn the method, the information set of each pixel is obtained to correspond toTransformation parameters of->The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Transformation parameter +_representing the set of pixel information corresponding to the ith pixel point>；
The acquisition module is used for acquiring the minimum transformation parameter value and the maximum transformation parameter value in each pixel transformation parameter;
the measuring module is used for measuring thickness information of the first target pixel point corresponding to the minimum transformation parameter value and thickness information of the second target pixel point corresponding to the maximum transformation parameter value based on a preset thickness measuring device;
and the comparison module is used for comparing the thickness information of the first target pixel point and the second target pixel point and judging whether the coating is qualified or not according to the comparison result.
2. The vision-based coating thickness online monitoring system of claim 1, wherein the first acquisition module comprises:
the object placing sub-module is used for placing the object at a preset position on a preset conveyor belt after coating of the object slurry is completed;
The slurry type acquisition sub-module is used for acquiring the type of the slurry and acquiring a target illumination parameter based on the type of the slurry;
the light generator control submodule is used for controlling a preset light generator according to the target illumination parameter to enable the illumination parameter of the light environment where the object is located at the preset position to be the target illumination parameter;
the first image acquisition sub-module is used for acquiring a first image of an object at the preset position by using a preset camera;
and the pixel value acquisition sub-module is used for acquiring the pixel value of the pixel point corresponding to the object in the first image.
3. The visual inspection-based coating thickness online monitoring system of claim 1, wherein the computing module comprises:
an RGB value obtaining sub-module for obtaining RGB values of each pixel value;
a maximum pixel calculation sub-module for passing through the formulaCalculating the maximum colour value difference, wherein +_>The maximum difference in color value is indicated,representation->Two pixel points with maximum value (++)>，/>，/>) And (/ ->，/>，/>）；
And the maximum color value difference judging sub-module is used for judging whether the maximum color value difference is smaller than a preset maximum color value difference.
4. The visual inspection-based coating thickness online monitoring system of claim 1, further comprising:
The pixel point acquisition module is used for acquiring two pixel points with the largest pixel error in the current image of the object, and the two pixel points are respectively marked as a third target pixel point and a fourth target pixel point;
the thickness information measuring module is used for measuring thickness information of the third target pixel point and the fourth target pixel point based on a preset thickness measuring device;
the maximum value acquisition module is used for acquiring the maximum value and the minimum value of the first target pixel point, the second target pixel point, the third target pixel point and the fourth target pixel point;
the target difference value calculation module is used for calculating a target difference value of the maximum value and the minimum value;
the target difference judging module is used for judging whether the target difference is smaller than a preset difference or not;
and the judging module is used for judging that the coating of the object is qualified if the difference value is smaller than the preset difference value, and judging that the coating of the object is unqualified if the difference value is not smaller than the preset difference value.
5. The visual inspection-based coating thickness online monitoring system of claim 1, further comprising:
the position marking module is used for marking the positions of the first target pixel point and the second target pixel point on the object image if the coating is unqualified and uploading the positions to an unqualified database;
The data judging module is used for judging whether the unqualified data in the unqualified database reaches a preset value or not;
the position acquisition module is used for acquiring the positions of the first target pixel points and the second target pixel points in each object image if the object images are the same;
the coordinate system marking module is used for marking all first target pixel points on a first coordinate system according to the positions of the first target pixel points in the object image, and marking all second target pixel points on a second coordinate system according to the positions of the second target pixel points in the object image;
the pixel point density calculation module is used for calculating the pixel point density in a first coordinate system and the second coordinate system by using a preset kernel density estimation algorithm;
the pixel density judging module is used for judging whether the pixel density is greater than a preset density;
and the pixel density sending module is used for sending the pixel density to a worker to adjust the coating parameters if the pixel density is larger than the preset density.
6. An online monitoring method for coating thickness based on visual detection is characterized by comprising the following steps:
judging whether the coating of the object slurry is finished or not;
If the coating of the object slurry is finished, acquiring a first image of the object after the coating is finished, and acquiring a pixel value of a pixel point corresponding to the object in the first image;
calculating the maximum color value difference of pixel values in the first image, and judging whether the maximum color value difference is smaller than a preset maximum color value difference or not;
if yes, acquiring picture information of the object at n moments after coating is completed through a preset camera device;
analyzing pixel information of each pixel point of the object in the picture information by a preset picture analysis method to obtain the pixel information of each pixel point at n times、/>、...、/>、...、/>Obtaining a pixel information set of each pixel point; wherein (1)>The expression time is +.>Pixel information of the ith pixel point, and；
respectively inputting RGB values in the pixel information into a preset formulaIn (1) obtaining the corresponding transformation parameter of each pixel information set +.>The method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Transformation parameter +_representing the set of pixel information corresponding to the ith pixel point>；
Acquiring a minimum transformation parameter value and a maximum transformation parameter value in each pixel transformation parameter;
based on a preset thickness measuring device, measuring thickness information of a first target pixel point corresponding to a minimum conversion parameter value and thickness information of a second target pixel point corresponding to a maximum conversion parameter value;
And comparing the thickness information of the first target pixel point and the second target pixel point, and judging whether the coating is qualified or not according to the comparison result.
7. The method for online monitoring of coating thickness based on visual inspection according to claim 6, wherein the step of acquiring a first image of the object after coating is completed and acquiring pixel values of corresponding pixels of the object in the first image if coating of the object slurry is completed comprises:
if the coating of the object slurry is finished, placing the coated object at a preset position on a preset conveyor belt;
acquiring the type of the slurry, and acquiring a target illumination parameter based on the type of the slurry;
controlling a preset light generator according to the target illumination parameter to enable the illumination parameter of the light environment where the object is located at the preset position to be the target illumination parameter;
acquiring a first image of an object at the preset position by using a preset camera;
and acquiring pixel values of corresponding pixel points of the object in the first image.
8. The method for online monitoring of coating thickness based on visual inspection according to claim 6, wherein the step of calculating a maximum color value difference of pixel values in the first image and judging whether the maximum color value difference is smaller than a preset maximum color value difference comprises:
Acquiring RGB values of each pixel value;
by the formulaCalculating the maximum colour value difference, wherein +_>Representing the maximum colour difference +.>Representation ofTwo pixel points with maximum value (++)>，/>，/>) And (/ ->，/>，/>）；
And judging whether the maximum color value difference is smaller than a preset maximum color value difference or not.
9. The method for online monitoring of coating thickness based on visual inspection according to claim 6, wherein after the step of measuring thickness information of the first target pixel point corresponding to the minimum conversion parameter value and thickness information of the second target pixel point corresponding to the maximum conversion parameter value based on the preset thickness measuring device, further comprising:
acquiring two pixel points with the largest pixel error in the current image of the object, and respectively marking the two pixel points as a third target pixel point and a fourth target pixel point;
measuring thickness information of the third target pixel point and the fourth target pixel point based on a preset thickness measuring device;
obtaining maximum values and minimum values in the first target pixel point, the second target pixel point, the third target pixel point and the fourth target pixel point;
calculating a target difference value of the maximum value and the minimum value;
judging whether the target difference value is smaller than a preset difference value or not;
If the difference value is smaller than the preset difference value, judging that the coating of the object is qualified, otherwise, judging that the coating of the object is unqualified.
10. The method for online monitoring of coating thickness based on visual inspection according to claim 6, wherein after the step of comparing thickness information of the first target pixel point and the second target pixel point and judging whether coating is qualified according to the comparison result, further comprising:
if the coating is unqualified, marking the positions of the first target pixel point and the second target pixel point on the object image, and uploading the positions to an unqualified database;
judging whether the unqualified data in the unqualified database reaches a preset value or not;
if yes, the positions of the first target pixel points and the second target pixel points in the object images are obtained;
marking all first target pixel points on a first coordinate system according to the positions of the first target pixel points in the object image, and marking all second target pixel points on a second coordinate system according to the positions of the second target pixel points in the object image;
calculating pixel point densities in a first coordinate system and the second coordinate system by using a preset kernel density estimation algorithm;
Judging whether the pixel density is greater than a preset density;
and if the pixel density is greater than the preset density, sending the pixel density to a worker to adjust the coating parameters.
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