CN111696102B - Paint coating detection system and method based on big data - Google Patents
Paint coating detection system and method based on big data Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 204
- 239000011248 coating agent Substances 0.000 title claims abstract description 117
- 238000000576 coating method Methods 0.000 title claims abstract description 117
- 239000003973 paint Substances 0.000 title claims abstract description 34
- 238000000034 method Methods 0.000 title abstract description 12
- 238000012544 monitoring process Methods 0.000 claims abstract description 90
- 238000011156 evaluation Methods 0.000 claims description 18
- 238000005192 partition Methods 0.000 claims description 6
- 238000012163 sequencing technique Methods 0.000 claims description 6
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- 230000000694 effects Effects 0.000 description 1
- 239000000839 emulsion Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000945 filler Substances 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 230000000873 masking effect Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000003921 oil Substances 0.000 description 1
- 239000003960 organic solvent Substances 0.000 description 1
- 239000000049 pigment Substances 0.000 description 1
- 239000011347 resin Substances 0.000 description 1
- 229920005989 resin Polymers 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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Abstract
The invention discloses a paint coating detection system and method based on big data, wherein the detection system comprises a to-be-coated plane surface information acquisition module, a coating condition comparison module and a coating result output module, the to-be-coated plane surface information acquisition module is used for acquiring the leveling condition of the to-be-coated plane surface of paint in advance and determining a monitoring area and a reference area of the to-be-coated plane surface according to the leveling condition, the coating condition comparison module is used for acquiring and comparing color images before and after the coating monitoring area of the paint and before and after the coating reference area, the coating result output module is used for outputting information whether the coating of the paint meets requirements according to the comparison result of the coating condition comparison module, and the to-be-coated plane surface information acquisition module comprises a partitioning module, a relative distance acquisition module, a monitoring area generation module and a reference area generation module.
Description
Technical Field
The invention relates to the field of coating, in particular to a coating detection system and method based on big data.
Background
The coating is traditionally named as paint in China. The coating is a continuous film which is coated on the surface of an object to be protected or decorated and can form firm adhesion with the object to be coated, and is a viscous liquid which is prepared by taking resin, oil or emulsion as a main material, adding or not adding pigments and fillers, adding corresponding auxiliaries and using an organic solvent or water. The coating can play a role in protecting, decorating, masking the defects of products and the like. In the process of coating the surface of an object, the phenomenon that the coating is not satisfactory frequently occurs, and the prior art lacks a detection technology for the coating condition of the coating
Disclosure of Invention
The invention aims to provide a paint coating detection system and method based on big data, so as to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme:
the utility model provides a coating application detecting system based on big data, detecting system includes the plane surface information acquisition module of waiting to scribble, coating condition comparison module and coating result output module, the plane surface information acquisition module of waiting to scribble is used for gathering in advance the coating and waits to scribble the leveling condition of plane surface and confirm the monitoring area and the reference area of plane surface of waiting to scribble according to this, coating condition comparison module is used for gathering and comparing the coating and scribbles the color image around the monitoring area, before and after the coating reference area, coating result output module is according to the information that whether the coating of coating meets the demands of the comparison result output of coating condition comparison module.
Preferably, the information acquisition module of the planar surface to be coated comprises a partition module, a relative distance acquisition module, a monitoring area generation module and a reference area generation module, wherein the partition module averagely divides the planar surface to be coated into a plurality of rectangular detection areas, averagely divides each rectangular detection area into a plurality of detection subareas, the relative distance acquisition module is used for focusing the center of each rectangular detection area and the center of each detection subarea by an image acquisition device, the distance of each center relative to the image acquisition device is determined according to the focal length data when focusing is completed, and the monitoring area generation module divides the monitoring area on the planar surface to be coated according to the distance acquired by the relative distance acquisition module; and the reference area generating module divides a reference area on the surface of the plane to be coated according to the distance acquired by the relative distance acquisition module.
Preferably, the monitoring area generating module includes a first distance comparing module, a second distance comparing module, a third distance comparing module and a monitoring area dividing module, wherein the first distance comparing module is used for comparing the relative distance difference between the centers of two adjacent rectangular detection areas and transmitting information to the second distance comparing module when the average value X1 of the relative distance difference between the center of one rectangular detection area and the centers of other adjacent rectangular detection areas is greater than or equal to the difference threshold value of the first distance, the second distance comparing module is used for comparing the average value X2 of the relative distance difference between the center of the rectangular detection area and the centers of each detection sub-area of the rectangular detection area with the third distance comparing module, and the third distance comparing module is used for comparing the relative distance between the center of each detection sub-area of the rectangular detection area and the center of each detection sub-area of other adjacent rectangular detection area And when the average difference value is smaller than the difference threshold value of the third distance, transmitting information to a monitoring area division module, wherein the monitoring area division module draws a circle by taking the center of the rectangular detection area as the center of a circle and taking the first preset value as the radius to form a circular area, namely the monitoring area.
Preferably, the reference area generating module includes a first average value calculating module, a second average value calculating module, a comprehensive evaluation value calculating module and a sorting module, the first average value calculating module is configured to acquire an average value of differences between relative distances between centers of each rectangular detection area and centers of other adjacent rectangular detection areas as a first average value, the second average value calculating module is configured to acquire an average value of differences between the centers of each rectangular detection area and centers of each detection sub-area of the rectangular detection area as a second average value, the comprehensive evaluation value calculating module calculates a comprehensive evaluation value of each rectangular detection area according to the first average value and the second average value, the sorting module sorts the comprehensive evaluation values in order from small to large, and the first corresponding rectangular detection area is the reference area.
Preferably, the coating condition comparison module comprises a chromaticity acquisition module, a first chromaticity comparison module and a second chromaticity comparison module, the chromaticity acquisition module acquires the chromaticity of color images of a monitoring area and a reference area before and after coating, the first chromaticity comparison module is used for comparing the difference value of the chromaticity difference between the monitoring area and the reference area before and after coating, and transmitting information to the second chromaticity comparison module for further detecting the edge of the monitoring area when the difference value is less than or equal to a difference threshold value, the second chromaticity comparison module comprises a detection area division module and a detection area chromaticity comparison module, the detection area division module takes the edge line of the monitoring area as a boundary, divides the first comparison area into the monitoring area, divides the second area out of the monitoring area, and the detection area chromaticity comparison module is used for acquiring and comparing the average chromaticity of the images between the first comparison area and the second comparison area, and transmitting information to a coating result output module according to the comparison result to output information whether the coating of the coating meets the requirements.
A big data based paint application inspection method, the inspection method comprising:
step S1: acquiring the flatness of the surface of a plane to be coated with the coating in advance, and determining a monitoring area and a reference area of the surface of the plane to be coated according to the flatness;
step S2: and collecting and comparing color images before and after the coating monitoring area and before and after the coating reference area, and outputting information whether the coating of the coating meets the requirements according to the comparison result.
Preferably, the step S1 further includes:
averagely dividing the surface of a plane to be coated into n rectangular detection areas, and averagely dividing each rectangular detection area into m detection subareas;
setting an image acquisition device at a fixed height position, respectively focusing the center of each rectangular detection area and the center of each detection subarea, acquiring focus data when focusing is finished, and determining the distance of each center relative to the fixed height position according to the focus data, wherein the distance of the center of the jth rectangular detection area relative to the fixed height position is a relative distance Lj0The distance of the center of the ith detection subarea in the jth rectangular detection area relative to the fixed height position is a relative distance LjiWherein j ranges from 1 to n, and i ranges from 1 to m;
comparing the relative distance difference between the centers of two adjacent rectangular detection areas, if the average value X1 of the relative distance difference between the center of one rectangular detection area and the centers of other adjacent rectangular detection areas is larger than or equal to the first distance difference threshold value, acquiring the relative distance difference between the center of the rectangular detection area and the center of each detection subarea of the rectangular detection area,
if the average value X2 of the relative distance differences between the center of the rectangular detection area and the centers of the detection sub-areas of the rectangular detection area is larger than or equal to the difference threshold of the second distance, drawing a circle by taking the center of the rectangular detection area as the center of the circle and taking a first preset value as the radius to form a circular area, namely the monitoring area, wherein the length of the long diagonal of the rectangular detection area is larger than or equal to one half of the first preset value;
if the average value X2 of the relative distance difference between the center of the rectangular detection area and the center of each detection subarea of the rectangular detection area is smaller than the difference threshold value of the second distance, the average value X3 of the relative distance difference between the center of each detection subarea of the rectangular detection area and the centers of the detection subareas of other adjacent rectangular detection areas is obtained, if the average value X3 of the relative distance difference is larger than or equal to the difference threshold value of the third distance, the rectangular detection area is a monitoring area, and if the average value X3 of the relative distance difference is smaller than the difference threshold value of the third distance, a circle is drawn by taking the center of the rectangular detection area as the center of the circle and taking the first preset value as the radius, and a circular area is formed as the monitoring area.
Preferably, the step S1 further includes:
the average X1 of the differences in relative distances between the center of each rectangular detection zone and the centers of other adjacent rectangular detection zones is collected,
the average X2 of the differences in relative distances between the center of each rectangular detection zone and the center of each detection sub-zone of its rectangular detection zone is collected,
the integrated evaluation value P of the center of each rectangular detection area is calculated to be 0.5X 1+ 0.5X 2,
and sequencing the comprehensive evaluation values from small to large, wherein the first rectangular detection area corresponding to the sequencing is the reference area.
Preferably, the step S2 includes:
collecting the chromaticity of the color image of the monitoring area before the paint is applied and the chromaticity of the color image of the reference area, and calculating the difference H1 between the chromaticities of the monitoring area before the paint is applied and the reference area,
collecting the chromaticity of the color image before the monitoring area and the chromaticity of the color image before the reference area after the paint is coated, and calculating the difference H2 between the chromaticities of the monitoring area and the reference area before the paint is coated,
if the difference value between the chromaticity difference H2 and the chromaticity difference H1 is larger than the difference threshold value, outputting the information that the coating of the coating is not qualified, and if the difference value is smaller than or equal to the difference threshold value, further detecting the edge of the monitored area.
Preferably, the step S2 of further detecting the edge of the monitored area includes:
respectively drawing a first reference circle and a second reference circle by taking the center of the monitoring area as the circle center and taking a second preset value and a third preset value as radii, wherein the second preset value is smaller than the first preset value, the third preset value is larger than the first preset value, the area between the edge line of the first reference circle and the edge line of the monitoring area is a first comparison area, and the area between the edge line of the second reference circle and the edge line of the monitoring area is a second comparison area;
acquiring the average chroma of the image between the first comparison area and the second comparison area, and outputting information that the coating of the coating meets the requirement if the chroma difference of the average chroma of the image between the first comparison area and the second comparison area is less than a chroma difference threshold;
otherwise, outputting information that the application of the coating is not satisfactory.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the flatness of the surface of the plane to be coated with the coating is detected to obtain the monitoring area on the surface of the plane to be coated, which is easy to cause the coating of the coating to be unqualified, and then the monitoring area which is easy to cause the coating of the coating to be unqualified is detected after the coating of the coating, so that the detection efficiency of the coating effect of the coating can be improved.
Drawings
FIG. 1 is a block schematic diagram of a big data based paint application detection system of the present invention;
fig. 2 is a schematic flow chart of a paint coating detection method based on big data according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, in an embodiment of the present invention, a paint coating detection system based on big data includes a to-be-coated planar surface information acquisition module, a coating condition comparison module, and a coating result output module, where the to-be-coated planar surface information acquisition module is configured to acquire a leveling condition of a to-be-coated planar surface of a paint in advance and determine a monitoring area and a reference area of the to-be-coated planar surface according to the leveling condition, the coating condition comparison module is configured to acquire and compare color images before and after the coating monitoring area and before and after the coating reference area, and the coating result output module outputs information whether coating of the paint meets requirements according to a comparison result of the coating condition comparison module.
The information acquisition module of the plane surface to be coated comprises a partition module, a relative distance acquisition module, a monitoring area generation module and a reference area generation module, wherein the partition module averagely divides the plane surface to be coated into a plurality of rectangular detection areas, averagely divides each rectangular detection area into a plurality of detection subareas, the relative distance acquisition module is used for focusing the center of each rectangular detection area and the center of each detection subarea by an image acquisition device, the distance of each center relative to the image acquisition device is determined according to focal length data when focusing is finished, and the monitoring area generation module divides the monitoring area on the plane surface to be coated according to the distance acquired by the relative distance acquisition module; and the reference area generating module divides a reference area on the surface of the plane to be coated according to the distance acquired by the relative distance acquisition module.
The monitoring area generation module comprises a first distance comparison module, a second distance comparison module, a third distance comparison module and a monitoring area division module, wherein the first distance comparison module is used for comparing the relative distance difference between the centers of two adjacent rectangular detection areas and transmitting information to the second distance comparison module when the average value X1 of the relative distance difference between the center of one rectangular detection area and the centers of other adjacent rectangular detection areas is greater than or equal to the difference threshold value of the first distance, the second distance comparison module is used for comparing the average value X2 of the relative distance difference between the center of the rectangular detection area and the centers of all detection subareas of the rectangular detection areas is greater than or equal to the difference threshold value of the second distance, and the third distance comparison module is used for comparing the average value of the relative distance difference between the center of each detection subarea of the rectangular detection area and the center of other detection subareas of other adjacent rectangular detection areas And transmitting information to a monitoring area division module when the distance is smaller than the difference threshold of the third distance, wherein the monitoring area division module draws a circle by taking the center of the rectangular detection area as the center of the circle and taking the first preset value as the radius to form a circular area, namely the monitoring area.
The reference area generating module comprises a first average value calculating module, a second average value calculating module, a comprehensive evaluation value calculating module and a sorting module, wherein the first average value calculating module is used for acquiring the average value of the relative distance difference between the center of each rectangular detection area and the centers of other adjacent rectangular detection areas as a first average value, the second average value calculating module is used for acquiring the average value of the relative distance difference between the center of each rectangular detection area and the center of each detection sub-area of the rectangular detection area as a second average value, the comprehensive evaluation value calculating module calculates the comprehensive evaluation value of each rectangular detection area according to the first average value and the second average value, the sorting module sorts the comprehensive evaluation values in the descending order, and the first corresponding rectangular detection area is the reference area.
The coating condition comparison module comprises a chromaticity acquisition module, a first chromaticity comparison module and a second chromaticity comparison module, wherein the chromaticity acquisition module acquires the chromaticity of color images of a monitoring area and a reference area before and after coating of a coating, the first chromaticity comparison module is used for comparing the difference value of the chromaticity between the monitoring area and the reference area before and after coating of the coating, and transmitting information to the second chromaticity comparison module for further detecting the edge of the monitoring area when the difference value is less than or equal to a difference threshold value, the second chromaticity comparison module comprises a detection area dividing module and a detection area chromaticity comparison module, the detection area dividing module takes the edge line of the monitoring area as a boundary, divides the first comparison area into the monitoring area, divides the second area out of the monitoring area, and the detection area chromaticity comparison module is used for acquiring and comparing the average chromaticity of the images between the first comparison area and the second comparison area, and transmitting information to a coating result output module according to the comparison result to output information whether the coating of the coating meets the requirements.
A big data based paint application inspection method, the inspection method comprising:
step S1: the method comprises the following steps of collecting the flatness of the surface of a plane to be coated with the coating in advance and determining a monitoring area and a reference area of the surface of the plane to be coated according to the flatness:
determining the monitoring area of the planar surface to be coated comprises the following:
averagely dividing the surface of a plane to be coated into n rectangular detection areas, and averagely dividing each rectangular detection area into m detection subareas;
setting an image acquisition device at a fixed height position, respectively focusing the center of each rectangular detection area and the center of each detection subarea, acquiring focus data when focusing is finished, and determining the distance of each center relative to the fixed height position according to the focus data, wherein the distance of the center of the jth rectangular detection area relative to the fixed height position is a relative distance Lj0The distance of the center of the ith detection subarea in the jth rectangular detection area relative to the fixed height position is a relative distance LjiWherein j ranges from 1 to n, and i ranges from 1 to m;
comparing the relative distance difference between the centers of two adjacent rectangular detection areas, if the average value X1 of the relative distance difference between the center of one rectangular detection area and the centers of other adjacent rectangular detection areas is larger than or equal to the first distance difference threshold value, acquiring the relative distance difference between the center of the rectangular detection area and the center of each detection subarea of the rectangular detection area,
if the average value X2 of the relative distance differences between the center of the rectangular detection area and the centers of the detection sub-areas of the rectangular detection area is larger than or equal to the difference threshold of the second distance, drawing a circle by taking the center of the rectangular detection area as the center of the circle and taking a first preset value as the radius to form a circular area, namely the monitoring area, wherein the length of the long diagonal of the rectangular detection area is larger than or equal to one half of the first preset value;
if the average value X2 of the relative distance difference between the center of the rectangular detection area and the center of each detection subarea of the rectangular detection area is smaller than the difference threshold value of the second distance, obtaining the average value X3 of the relative distance difference between the center of each detection subarea of the rectangular detection area and the centers of the detection subareas of other adjacent rectangular detection areas, if the average value X3 of the relative distance difference is larger than or equal to the difference threshold value of the third distance, the rectangular detection area is a monitoring area, and if the average value X3 of the relative distance difference is smaller than the difference threshold value of the third distance, a circle is drawn by taking the center of the rectangular detection area as the center of the circle and taking the first preset value as the radius, and a circular area is formed as the monitoring area;
determining the reference area of the planar surface to be coated comprises the following:
the average X1 of the differences in relative distances between the center of each rectangular detection zone and the centers of other adjacent rectangular detection zones is collected,
the average X2 of the differences in relative distances between the center of each rectangular detection zone and the center of each detection sub-zone of its rectangular detection zone is collected,
the integrated evaluation value P of the center of each rectangular detection area is calculated to be 0.5X 1+ 0.5X 2,
and sequencing the comprehensive evaluation values from small to large, wherein the first rectangular detection area corresponding to the sequencing is the reference area. In the process of coating the paint, the coating of the paint is often not satisfactory at the positions of the projections or the depressions on the surface of the plane surface to be coated and the positions where the projections or the depressions are connected with other positions, so that the positions need to be detected.
Step S2: collecting and comparing color images before and after the coating monitoring area and before and after the coating reference area, and outputting information whether the coating of the coating meets the requirements according to the comparison result, wherein the step comprises the following steps:
collecting the chromaticity of the color image of the monitoring area before the paint is applied and the chromaticity of the color image of the reference area, and calculating the difference H1 between the chromaticities of the monitoring area before the paint is applied and the reference area,
collecting the chromaticity of the color image before the monitoring area and the chromaticity of the color image before the reference area after the paint is coated, and calculating the difference H2 between the chromaticities of the monitoring area and the reference area before the paint is coated,
if the difference value between the chromaticity difference H2 and the chromaticity difference H1 is larger than the difference threshold value, outputting the information that the coating of the coating is not qualified, and if the difference value is smaller than or equal to the difference threshold value, further detecting the edge of the monitored area.
The step S2 of further detecting the edge of the monitored area includes:
respectively drawing a first reference circle and a second reference circle by taking the center of the monitoring area as the circle center and taking a second preset value and a third preset value as radii, wherein the second preset value is smaller than the first preset value, the third preset value is larger than the first preset value, the area between the edge line of the first reference circle and the edge line of the monitoring area is a first comparison area, and the area between the edge line of the second reference circle and the edge line of the monitoring area is a second comparison area;
acquiring the average chroma of the image between the first comparison area and the second comparison area, and outputting information that the coating of the coating meets the requirement if the chroma difference of the average chroma of the image between the first comparison area and the second comparison area is less than a chroma difference threshold; otherwise, outputting information that the application of the coating is not satisfactory.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (6)
1. A coating coats detecting system based on big data which characterized in that: the detection system comprises a to-be-coated plane surface information acquisition module, a coating condition comparison module and a coating result output module, wherein the to-be-coated plane surface information acquisition module is used for acquiring the leveling condition of the to-be-coated plane surface of the coating in advance and determining a monitoring area and a reference area of the to-be-coated plane surface according to the leveling condition, the coating condition comparison module is used for acquiring and comparing color images before and after the coating monitoring area is coated with the coating and before and after the reference area is coated with the coating, and the coating result output module outputs information whether the coating of the coating meets requirements according to the comparison result of the coating condition comparison module;
the information acquisition module of the plane surface to be coated comprises a partition module, a relative distance acquisition module, a monitoring area generation module and a reference area generation module, wherein the partition module averagely divides the plane surface to be coated into a plurality of rectangular detection areas, averagely divides each rectangular detection area into a plurality of detection subareas, the relative distance acquisition module is used for focusing the center of each rectangular detection area and the center of each detection subarea by an image acquisition device, the distance of each center relative to the image acquisition device is determined according to focal length data when focusing is finished, and the monitoring area generation module divides the monitoring area on the plane surface to be coated according to the distance acquired by the relative distance acquisition module; the reference region generation module divides a reference region on the surface of the plane to be coated according to the distance acquired by the relative distance acquisition module;
the monitoring area generation module comprises a first distance comparison module, a second distance comparison module, a third distance comparison module and a monitoring area division module, wherein the first distance comparison module is used for comparing the relative distance difference between the centers of two adjacent rectangular detection areas and transmitting information to the second distance comparison module when the average value X1 of the relative distance difference between the center of one rectangular detection area and the centers of other adjacent rectangular detection areas is greater than or equal to the difference threshold value of the first distance, the second distance comparison module is used for comparing the average value X2 of the relative distance difference between the center of the rectangular detection area and the centers of all detection subareas of the rectangular detection areas is greater than or equal to the difference threshold value of the second distance, and the third distance comparison module is used for comparing the average value of the relative distance difference between the center of each detection subarea of the rectangular detection area and the center of other detection subareas of other adjacent rectangular detection areas Transmitting information to a monitoring area division module when the distance is smaller than the difference threshold of the third distance, wherein the monitoring area division module draws a circle by taking the center of the rectangular detection area as the center of the circle and taking the first preset value as the radius to form a circular area which is the monitoring area;
the reference area generating module comprises a first average value calculating module, a second average value calculating module, a comprehensive evaluation value calculating module and a sorting module, wherein the first average value calculating module is used for acquiring the average value of the relative distance difference between the center of each rectangular detection area and the centers of other adjacent rectangular detection areas as a first average value, the second average value calculating module is used for acquiring the average value of the relative distance difference between the center of each rectangular detection area and the center of each detection sub-area of the rectangular detection area as a second average value, the comprehensive evaluation value calculating module calculates the comprehensive evaluation value of each rectangular detection area according to the first average value and the second average value, the sorting module sorts the comprehensive evaluation values in the descending order, and the first corresponding rectangular detection area is the reference area.
2. The big-data based paint application detection system according to claim 1, wherein: the coating condition comparison module comprises a chromaticity acquisition module, a first chromaticity comparison module and a second chromaticity comparison module, wherein the chromaticity acquisition module acquires the chromaticity of color images of a monitoring area and a reference area before and after coating of a coating, the first chromaticity comparison module is used for comparing the difference value of the chromaticity between the monitoring area and the reference area before and after coating of the coating, and transmitting information to the second chromaticity comparison module for further detecting the edge of the monitoring area when the difference value is less than or equal to a difference threshold value, the second chromaticity comparison module comprises a detection area dividing module and a detection area chromaticity comparison module, the detection area dividing module takes the edge line of the monitoring area as a boundary, divides the first comparison area into the monitoring area, divides the second area out of the monitoring area, and the detection area chromaticity comparison module is used for acquiring and comparing the average chromaticity of the images between the first comparison area and the second comparison area, and transmitting information to a coating result output module according to the comparison result to output information whether the coating of the coating meets the requirements.
3. A paint coating detection method based on big data is characterized in that: the detection method comprises the following steps:
step S1: acquiring the flatness of the surface of a plane to be coated with the coating in advance, and determining a monitoring area and a reference area of the surface of the plane to be coated according to the flatness;
step S2: collecting and comparing color images before and after the coating monitoring area and the reference area are coated, and outputting information whether the coating of the coating meets the requirements according to the comparison result;
the step S1 further includes:
averagely dividing the surface of a plane to be coated into n rectangular detection areas, and averagely dividing each rectangular detection area into m detection subareas;
setting an image acquisition device at a fixed height position, respectively focusing the center of each rectangular detection area and the center of each detection subarea, acquiring focus data when focusing is finished, and determining the distance of each center relative to the fixed height position according to the focus data, wherein the distance of the center of the jth rectangular detection area relative to the fixed height position is a relative distance Lj0The distance of the center of the ith detection subarea in the jth rectangular detection area relative to the fixed height position is a relative distance LjiWherein j ranges from 1 to n, and i ranges from 1 to m;
comparing the relative distance difference between the centers of two adjacent rectangular detection areas, if the average value X1 of the relative distance difference between the center of one rectangular detection area and the centers of other adjacent rectangular detection areas is larger than or equal to the first distance difference threshold value, acquiring the relative distance difference between the center of the rectangular detection area and the center of each detection subarea of the rectangular detection area,
if the average value X2 of the relative distance differences between the center of the rectangular detection area and the centers of the detection sub-areas of the rectangular detection area is larger than or equal to the difference threshold of the second distance, drawing a circle by taking the center of the rectangular detection area as the center of the circle and taking a first preset value as the radius to form a circular area, namely the monitoring area, wherein the length of the long diagonal of the rectangular detection area is larger than or equal to one half of the first preset value;
if the average value X2 of the relative distance difference between the center of the rectangular detection area and the center of each detection subarea of the rectangular detection area is smaller than the difference threshold value of the second distance, the average value X3 of the relative distance difference between the center of each detection subarea of the rectangular detection area and the centers of the detection subareas of other adjacent rectangular detection areas is obtained, if the average value X3 of the relative distance difference is larger than or equal to the difference threshold value of the third distance, the rectangular detection area is a monitoring area, and if the average value X3 of the relative distance difference is smaller than the difference threshold value of the third distance, a circle is drawn by taking the center of the rectangular detection area as the center of the circle and taking the first preset value as the radius, and a circular area is formed as the monitoring area.
4. The big data based paint application detection method according to claim 3, wherein: the step S1 further includes:
the average X1 of the differences in relative distances between the center of each rectangular detection zone and the centers of other adjacent rectangular detection zones is collected,
the average X2 of the differences in relative distances between the center of each rectangular detection zone and the center of each detection sub-zone of its rectangular detection zone is collected,
the integrated evaluation value P of the center of each rectangular detection area is calculated to be 0.5X 1+ 0.5X 2,
and sequencing the comprehensive evaluation values from small to large, wherein the first rectangular detection area corresponding to the sequencing is the reference area.
5. The big data based paint application detection method according to claim 4, wherein: the step S2 includes:
collecting the chromaticity of the color image of the monitoring area before the paint is applied and the chromaticity of the color image of the reference area, and calculating the difference H1 between the chromaticities of the monitoring area before the paint is applied and the reference area,
collecting the chromaticity of the color image before the monitoring area and the chromaticity of the color image before the reference area after the paint is coated, and calculating the difference H2 between the chromaticities of the monitoring area and the reference area before the paint is coated,
if the difference value between the chromaticity difference H2 and the chromaticity difference H1 is larger than the difference threshold value, outputting the information that the coating of the coating is not qualified, and if the difference value is smaller than or equal to the difference threshold value, further detecting the edge of the monitored area.
6. The big data based paint application detection method according to claim 5, wherein: the step S2 of further detecting the edge of the monitored area includes:
respectively drawing a first reference circle and a second reference circle by taking the center of the monitoring area as the circle center and taking a second preset value and a third preset value as radii, wherein the second preset value is smaller than the first preset value, the third preset value is larger than the first preset value, the area between the edge line of the first reference circle and the edge line of the monitoring area is a first comparison area, and the area between the edge line of the second reference circle and the edge line of the monitoring area is a second comparison area;
acquiring the average chroma of the image between the first comparison area and the second comparison area, and outputting information that the coating of the coating meets the requirement if the chroma difference of the average chroma of the image between the first comparison area and the second comparison area is less than a chroma difference threshold;
otherwise, outputting information that the application of the coating is not satisfactory.
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