CN116909216A - Quality inspection line automatic control method, computer equipment and readable storage medium - Google Patents
Quality inspection line automatic control method, computer equipment and readable storage medium Download PDFInfo
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- CN116909216A CN116909216A CN202310693160.8A CN202310693160A CN116909216A CN 116909216 A CN116909216 A CN 116909216A CN 202310693160 A CN202310693160 A CN 202310693160A CN 116909216 A CN116909216 A CN 116909216A
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- 238000000034 method Methods 0.000 title claims abstract description 44
- 238000007689 inspection Methods 0.000 title claims abstract description 29
- 238000003860 storage Methods 0.000 title claims abstract description 9
- 238000001514 detection method Methods 0.000 claims abstract description 84
- 239000000919 ceramic Substances 0.000 claims abstract description 80
- 238000012545 processing Methods 0.000 claims abstract description 45
- 238000000926 separation method Methods 0.000 claims abstract description 24
- 238000005507 spraying Methods 0.000 claims abstract description 19
- 239000007921 spray Substances 0.000 claims abstract description 6
- 238000003708 edge detection Methods 0.000 claims abstract description 4
- 230000007547 defect Effects 0.000 claims description 35
- 239000011449 brick Substances 0.000 claims description 27
- 238000004422 calculation algorithm Methods 0.000 claims description 26
- 238000005498 polishing Methods 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 12
- 238000013135 deep learning Methods 0.000 claims description 12
- 238000007688 edging Methods 0.000 claims description 12
- 238000004806 packaging method and process Methods 0.000 claims description 11
- 238000004140 cleaning Methods 0.000 claims description 9
- 238000010304 firing Methods 0.000 claims description 9
- 238000007605 air drying Methods 0.000 claims description 8
- 238000003909 pattern recognition Methods 0.000 claims description 6
- 238000007639 printing Methods 0.000 claims description 6
- 230000003044 adaptive effect Effects 0.000 claims description 3
- 238000007635 classification algorithm Methods 0.000 claims description 3
- 230000004927 fusion Effects 0.000 claims description 3
- 238000007499 fusion processing Methods 0.000 claims description 3
- 238000007526 fusion splicing Methods 0.000 claims description 3
- 238000003908 quality control method Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 description 9
- 230000006872 improvement Effects 0.000 description 7
- 230000008569 process Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 238000000227 grinding Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012567 pattern recognition method Methods 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000002787 reinforcement Effects 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 238000013526 transfer learning Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by quality surveillance of production
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32368—Quality control
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Automation & Control Theory (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention discloses a quality inspection line automatic control method, computer equipment and a readable storage medium, and relates to the technical field of tile detection, wherein the method comprises the following steps: driving a flatness detector to perform flatness detection on the ceramic tile to generate detection information, wherein the flatness detection comprises any one or more of four-edge detection, diagonal dimension detection and tile surface flatness detection of the ceramic tile; driving the hierarchical color separation detector to perform color separation detection on the ceramic tile so as to generate identification information; driving a code spraying recognition machine to spray codes on the ceramic tile according to the detection information and the recognition information so as to form an information code on the ceramic tile; driving an identification equipment identification information code to acquire parameter information; and feeding the parameter information back to the cloud platform so that the cloud platform adjusts the processing parameters of the processing equipment according to the parameter information and feeds the processing parameters back to the processing equipment. The invention can construct a complete closed-loop control system to realize the automatic control of the quality inspection line.
Description
Technical Field
The invention relates to the technical field of tile detection, in particular to an automatic control method of a quality inspection line, computer equipment and a readable storage medium.
Background
As the demand and application of ceramic tiles continue to increase, the quality of ceramic tiles is also increasing. The ceramic tiles produced are detected and classified on line so as to ensure the standard of geometric dimensions of the ceramic tiles, the integrity of the appearance and the color balance of the surfaces of the ceramic tiles in the same batch, and the ceramic tiles are an important link in the manufacturing process of building ceramic enterprises.
Under the heavy tide of intelligent manufacturing and green development, the traditional labor-intensive ceramic industry gradually replaces manual work in the processes of machine glazing, grinding, polishing and the like, and even intelligent manufacturing factories are continuously emerging. At present, various devices of the ceramic tile production line basically realize automatic production, but the various devices are relatively independent, and the technical bottleneck is not broken through yet in the partial detection work of the ceramic tile.
For example, in the patent "a tile detecting and sorting system (CN 204448634U)", although automatic classification of tiles can be achieved, it is still necessary for a quality inspector to determine tile grades and then mark them; for another example, in the patent "a tile surface defect detection system (CN 215727750U)", although automatic defect detection can be realized, the detection result is only recorded in a computer hard disk, and the whole production link (polishing, quality inspection and packaging) cannot form a closed-loop real-time quality feedback system, so that the production and decision-making efficiency of ceramic production enterprises are affected.
Disclosure of Invention
The invention aims to solve the technical problem of providing an automatic control method of a quality inspection line, computer equipment and a readable storage medium, which can construct a complete closed-loop control system to realize the automatic control of the quality inspection line.
In order to solve the technical problems, the invention provides an automatic control method of a quality inspection line, which comprises the following steps: driving a flatness detector to perform flatness detection on the ceramic tile to generate detection information, wherein the flatness detection comprises any one or more of four-edge detection, diagonal dimension detection and tile surface flatness detection of the ceramic tile; driving a hierarchical color separation detector to perform color separation detection on the ceramic tile to generate identification information, wherein the color separation detection comprises any one or more of surface defect detection, surface color difference detection and layout pattern identification; driving a code spraying recognition machine to spray codes on the ceramic tile according to the detection information and the recognition information so as to form an information code on the ceramic tile; driving a recognition device to recognize the information code to acquire parameter information; and feeding the parameter information back to a cloud platform, so that the cloud platform adjusts the processing parameters of the processing equipment according to the parameter information and feeds the processing parameters back to the processing equipment.
As an improvement of the above scheme, the method for detecting the surface defects of the ceramic tile comprises the following steps: collecting a brick surface image; positioning a defect position in the brick surface image by adopting a target defect positioning method based on an OSTU threshold and significance detection; fusing the defect positions by adopting a fusion defect detection algorithm based on a deep learning target detection algorithm of Faster R-CNN; and classifying the fused defects by adopting a deep learning algorithm based on the tile defect detection model.
As an improvement of the above scheme, the method for detecting the surface color difference of the ceramic tile comprises the following steps: collecting a brick surface image; dividing the brick face image by adopting a dividing algorithm based on a U-net deep learning network; performing color classification processing on the segmented tile face image by adopting a tile color classification algorithm based on deep learning; and carrying out tile color difference fusion processing on the classified tile surface images by adopting a recommendation algorithm.
As an improvement of the above scheme, the method for identifying the layout pattern of the tile comprises the following steps: collecting a brick surface image; calibrating the brick surface image; performing initial registration processing on the calibrated brick face image by adopting a cuFFT-based ultra-high resolution image rapid registration algorithm: performing secondary registration processing on the initially registered brick face image by adopting an image optimal registration algorithm based on a local search strategy; and adopting an adaptive image fusion splicing algorithm based on a multi-scale transformation idea to splice the brick surface images subjected to the secondary registration treatment so as to identify the layout pattern.
As an improvement of the scheme, when the tile surface image is acquired, the focal length of the color linear array camera, the real-time position of the black-and-white linear array camera and the real-time position of the light source in the grading color separation detector are adjusted according to the tile thickness information.
As an improvement of the above scheme, the quality inspection line automatic control method further includes: and driving the packaging equipment to split, package and lower the plate for the ceramic tiles after code spraying according to the parameter information.
As an improvement of the above scheme, before the driving flatness detector detects the four sides of the tile, the diagonal dimension and the flatness of the tile surface to generate detection information, the driving flatness detector further includes: driving the polishing line to polish the ceramic tile; and driving the cleaning and air drying equipment to clean and dry the ceramic tile.
As an improvement of the above scheme, before the polishing line is driven to polish the tile, the polishing line further comprises: driving forming equipment to perform forming treatment on the ceramic tile; driving the glaze spraying equipment to perform glaze spraying treatment on the ceramic tile; driving printing equipment to print the ceramic tile; driving firing equipment to perform firing treatment on the ceramic tile; and driving the edging equipment to edging the ceramic tile.
Correspondingly, the invention also provides computer equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the quality inspection line automatic control method when executing the computer program.
Correspondingly, the invention further provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and the computer program realizes the steps of the quality inspection line automatic control method when being executed by a processor.
The implementation of the invention has the following beneficial effects:
the invention detects the detection information and the identification information of the ceramic tile through the flatness detector and the grading color separation detector, records the detection information and the identification information on the ceramic tile in the form of information codes, and sends the parameter information to the cloud platform after the parameter information is identified by the identification equipment; the cloud platform follows the parameter information to feed corresponding adjustment information back to each process link so as to remotely control and adjust the processing parameters of the processing equipment in each link, thereby forming a complete closed-loop control system.
Meanwhile, the special surface defect detection, surface color difference detection and layout pattern recognition methods are adopted to detect the ceramic tile in a targeted manner, so that the accuracy is high.
Furthermore, the automatic distribution, packaging and plate feeding of the ceramic tiles are realized through data transmission with a packaging line, the whole line automation is further realized, the labor intensity of workers is greatly reduced, and the detection efficiency and accuracy are greatly improved.
Drawings
FIG. 1 is a flow chart of a first embodiment of the quality control line automatic control method of the present invention;
FIG. 2 is a flow chart of a second embodiment of the quality control line automatic control method of the present invention;
fig. 3 is a flowchart of a third embodiment of the quality inspection line automatic control method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings, for the purpose of making the objects, technical solutions and advantages of the present invention more apparent.
Referring to fig. 1, fig. 1 shows a flowchart of a first embodiment of the quality inspection line automatic control method of the present invention, including:
s101, driving a flatness detector to perform flatness detection on the ceramic tile to generate detection information;
specifically, the flatness detection comprises any one or more of tile four-edge detection, diagonal line size detection and tile surface flatness detection;
s102, driving a hierarchical color separation detector to perform color separation detection on the tile so as to generate identification information;
specifically, the color separation detection comprises any one or more of surface defect detection, surface color difference detection and layout pattern recognition processing; the surface defects include cracks, grinding, corner chipping, pinholes and the like, but are not limited thereto.
The grading color separation detector is internally provided with a color linear array camera, a black-and-white linear array camera and a light source; wherein, the color line camera and the detection point are arranged in the same vertical direction, and the black-and-white line camera and the light source are respectively arranged at two sides of the color line camera. When the tile surface image is collected, the focal length of the color linear array camera in the grading color separation detector, the real-time position of the black-and-white linear array camera and the real-time position of the light source can be adjusted according to the tile thickness information, so that the light emitted by the light source can directly enter the black-and-white linear array camera after being reflected by the tile on the detection point, and the imaging point is always converged on the upper surface of the tile.
Therefore, after the tile enters the grading color separation detector, black and white and color complete tile face images can be respectively obtained through the black and white linear array camera and the color linear array camera, so that surface defect detection, surface color difference detection and layout pattern recognition processing can be carried out on the tile.
The following describes the surface defect detection, surface color difference detection and layout pattern recognition processing in further detail:
1. surface defect detection
When shooting, the black-and-white linear array camera forms a certain imaging included angle with the surface of the ceramic tile, so that a black-and-white image is shot, if the surface of the ceramic tile has a convex or concave condition, the black-and-white image can have a shadow part at a corresponding position, and therefore, the defect type of the convex or concave can be analyzed by combining the shadow condition; meanwhile, the defect type can be further confirmed through the color pictures obtained by the color line camera.
Specifically, the method for detecting the surface defects of the ceramic tile comprises the following steps:
(1) Collecting a brick surface image;
(2) Positioning a defect position in a brick surface image by adopting a target defect positioning method based on an OSTU (maximum inter-class variance method) threshold and significance detection;
(3) Adopting a fusion defect detection algorithm based on a deep learning target detection algorithm of Faster R-CNN to fuse the defect positions;
(4) And classifying the fused defects by adopting a deep learning algorithm based on the tile defect detection model.
2. Surface color difference detection
In the ceramic tile color difference detection, complex textures and patterns of the ceramic tile have larger interference on the color difference detection, and the invention adopts an artificial intelligence-based color difference classification detection algorithm to detect on the basis of realizing a multi-camera optical system calibration and supplement algorithm by considering the influence of factors such as brightness, color temperature uniformity, consistency and the like, the influence of subjective factors on color number classification and the like.
Specifically, the method for detecting the surface color difference of the ceramic tile comprises the following steps:
(1) Collecting a brick surface image;
(2) Dividing the brick face image by adopting a dividing algorithm based on a U-net deep learning network;
(3) Performing color classification processing on the segmented tile face images by adopting a tile color classification algorithm based on deep learning (including transfer learning and reinforcement learning);
(4) And carrying out tile color difference fusion processing on the classified tile surface images by adopting a recommendation algorithm.
3. Layout pattern recognition
In large-format tile visual detection, online real-time shooting is often required to be carried out by adopting a multi-camera array with ultra-high resolution (8K, even 16K), and besides image preprocessing such as pattern color correction, filtering and the like, the invention introduces key technologies such as high-precision multi-image self-adaptive rapid registration, splicing and the like to realize pattern recognition.
Specifically, the method for identifying the layout pattern of the tile comprises the following steps:
(1) Collecting a brick surface image;
(2) Calibrating the brick surface image;
(3) Performing initial registration processing on the calibrated brick face image by adopting a cuFFT-based ultra-high resolution image rapid registration algorithm:
(4) Performing secondary registration processing on the initially registered brick face image by adopting an image optimal registration algorithm based on a local search strategy;
(5) And adopting an adaptive image fusion splicing algorithm based on a multi-scale transformation idea to splice the brick surface images subjected to the secondary registration treatment so as to identify the layout pattern.
S103, driving a code spraying recognition machine to spray codes on the ceramic tile according to the detection information and the recognition information so as to form an information code on the ceramic tile;
the code spraying recognition machine is used for generating information codes by a preset coding mode according to detection information and recognition information (such as size, flatness, defects and the like) detected by the flatness detector and the grading color separation detector, and spraying the information codes to specific positions of the ceramic tiles.
S104, driving an identification equipment identification information code to acquire parameter information;
and S105, feeding the parameter information back to the cloud platform, so that the cloud platform adjusts the processing parameters of the processing equipment according to the parameter information and feeds the processing parameters back to the processing equipment.
It should be noted that, corresponding processing equipment on the production line can provide effective adjustment information according to the cloud platform, automatically adjust processing parameters, finally form the control closed loop of system.
That is, the flatness detector and the grading color separation detector record the detected detection information and identification information on the ceramic tile in the form of information codes, and the identification equipment identifies parameter information and then sends the parameter information to the cloud platform; the cloud platform feeds corresponding adjustment information back to each process link through processing and analysis so as to remotely control and adjust the processing parameters of processing equipment in each link.
Referring to fig. 2, fig. 2 shows a flowchart of a second embodiment of the quality inspection line automatic control method of the present invention, including:
s201, driving a polishing line to polish the ceramic tile;
s202, driving a cleaning and air drying device to clean and dry the ceramic tile.
The cleaning and air-drying equipment is used for cleaning dust on the ceramic tile and drying surface watermarks, and interference items are eliminated for subsequent detection.
S203, driving a flatness detector to perform flatness detection on the ceramic tile to generate detection information;
s204, driving a hierarchical color separation detector to perform color separation detection on the ceramic tile so as to generate identification information;
s205, driving a code spraying recognition machine to spray codes on the ceramic tile according to the detection information and the recognition information so as to form an information code on the ceramic tile;
s206, driving the identification equipment identification information code to acquire parameter information;
s207, feeding the parameter information back to the cloud platform, so that the cloud platform adjusts the processing parameters of the processing equipment according to the parameter information and feeds the processing parameters back to the processing equipment.
S208, driving the packaging equipment to split, package and lower the plate for the ceramic tiles after code spraying according to the parameter information.
Therefore, the invention can realize the direct and effective connection of the polishing line and the packaging line, and the invention can feed back the information data such as the size, the flatness, the color difference, the defects and the like of the ceramic tile to the polishing line at the front end, adjust corresponding parameters, divide the collected information into corresponding grades according to clients, and realize the automatic distribution, the packaging and the lower plate of the ceramic tile through the data transmission with the packaging line; thereby forming a complete closed-loop control system and further realizing the whole-line automation.
Referring to fig. 3, fig. 3 shows a flowchart of a third embodiment of the quality inspection line automatic control method of the present invention, including:
s301, driving a forming device to perform forming treatment on the ceramic tile;
s302, driving glaze spraying equipment to perform glaze spraying treatment on the ceramic tile;
s303, driving a printing device to print the ceramic tile;
s304, driving a firing device to perform firing treatment on the ceramic tile;
s305, driving an edging device to edging the ceramic tile;
s306, driving the polishing line to polish the ceramic tile;
s307, driving the cleaning and air drying equipment to clean and dry the ceramic tile.
S308, driving a flatness detector to perform flatness detection on the ceramic tile to generate detection information;
s309, driving a hierarchical color separation detector to perform color separation detection on the tile to generate identification information;
s310, driving a code spraying recognition machine to spray codes on the ceramic tile according to the detection information and the recognition information so as to form an information code on the ceramic tile;
s311, driving an identification equipment identification information code to acquire parameter information;
and S312, feeding the parameter information back to the cloud platform, so that the cloud platform adjusts the processing parameters of the processing equipment according to the parameter information and feeds the processing parameters back to the processing equipment.
The processing equipment can be forming equipment, glazing equipment, printing equipment, firing equipment, polishing equipment, edging equipment, cleaning and air drying equipment and the like, but is not limited to the forming equipment, glazing equipment, printing equipment, firing equipment, polishing equipment, edging equipment, cleaning and air drying equipment and the like, and can be adjusted according to actual conditions.
S313, driving the packaging equipment to split, package and lower the ceramic tile after code spraying according to the parameter information.
For example, edging equipment is the most significant cause of affecting tile size parameters. After the flatness detector detects that the size of the tile does not meet the requirements, the flatness detector automatically records the size information on the tile in the form of an information code, and after the identification equipment identifies the parameter information, the parameter information is sent to the cloud platform; after the parameter information is analyzed and processed by the cloud platform, the adjusted adjusting information is sent to the edging equipment, and the edging equipment adjusts the processing parameters according to the adjusting information, so that the self structural position is adjusted, and the automatic adjustment of errors such as tile size, diagonal line and the like is achieved.
Therefore, the invention connects the forming equipment, the glazing equipment, the printing equipment, the firing equipment, the edging equipment, the polishing equipment, the cleaning and air-drying equipment, the flatness detector, the grading color separation detector, the code spraying identification machine, the identification equipment, the packaging equipment, the cloud platform and the like through the communication among the equipment to form closed-loop control, can monitor the running condition of each equipment in real time and can remotely control and modify parameters.
Correspondingly, the invention also discloses a computer device, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the quality inspection line automatic control method when executing the computer program. Meanwhile, the invention also discloses a computer readable storage medium, on which a computer program is stored, wherein the computer program realizes the steps of the quality inspection line automatic control method when being executed by a processor.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles of the invention, such changes and modifications are also intended to be within the scope of the invention.
Claims (10)
1. An automatic control method of a quality inspection line is characterized by comprising the following steps:
driving a flatness detector to perform flatness detection on the ceramic tile to generate detection information, wherein the flatness detection comprises any one or more of four-edge detection, diagonal dimension detection and tile surface flatness detection of the ceramic tile;
driving a hierarchical color separation detector to perform color separation detection on the ceramic tile to generate identification information, wherein the color separation detection comprises any one or more of surface defect detection, surface color difference detection and layout pattern identification;
driving a code spraying recognition machine to spray codes on the ceramic tile according to the detection information and the recognition information so as to form an information code on the ceramic tile;
driving a recognition device to recognize the information code to acquire parameter information;
and feeding the parameter information back to a cloud platform, so that the cloud platform adjusts the processing parameters of the processing equipment according to the parameter information and feeds the processing parameters back to the processing equipment.
2. The automatic quality inspection line control method according to claim 1, wherein the method for detecting surface defects of the tile comprises:
collecting a brick surface image;
positioning a defect position in the brick surface image by adopting a target defect positioning method based on an OSTU threshold and significance detection;
fusing the defect positions by adopting a fusion defect detection algorithm based on a deep learning target detection algorithm of Faster R-CNN;
and classifying the fused defects by adopting a deep learning algorithm based on the tile defect detection model.
3. The automatic quality inspection line control method according to claim 1, wherein the method for detecting the surface color difference of the tile comprises the steps of:
collecting a brick surface image;
dividing the brick face image by adopting a dividing algorithm based on a U-net deep learning network;
performing color classification processing on the segmented tile face image by adopting a tile color classification algorithm based on deep learning;
and carrying out tile color difference fusion processing on the classified tile surface images by adopting a recommendation algorithm.
4. The automatic quality inspection line control method according to claim 1, wherein the method for performing layout pattern recognition on the tile comprises:
collecting a brick surface image;
calibrating the brick surface image;
performing initial registration processing on the calibrated brick face image by adopting a cuFFT-based ultra-high resolution image rapid registration algorithm:
performing secondary registration processing on the initially registered brick face image by adopting an image optimal registration algorithm based on a local search strategy;
and adopting an adaptive image fusion splicing algorithm based on a multi-scale transformation idea to splice the brick surface images subjected to the secondary registration treatment so as to identify the layout pattern.
5. The automatic quality control line control method according to any one of claims 1 to 4, wherein when the tile surface image is collected, the focal length of the color line camera, the real-time position of the black-and-white line camera, and the real-time position of the light source in the hierarchical color separation detector are adjusted according to the tile thickness information.
6. The automated quality inspection line control method of claim 1, further comprising: and driving the packaging equipment to split, package and lower the plate for the ceramic tiles after code spraying according to the parameter information.
7. The automated quality inspection line control method of claim 1, wherein the driving flatness detector further comprises, prior to performing tile four-edge inspection, diagonal dimension inspection, and tile face flatness inspection on the tile to generate inspection information:
driving the polishing line to polish the ceramic tile;
and driving the cleaning and air drying equipment to clean and dry the ceramic tile.
8. The automated quality inspection line control method of claim 7, wherein the driving polishing line further comprises, prior to polishing the tile:
driving forming equipment to perform forming treatment on the ceramic tile;
driving the glaze spraying equipment to perform glaze spraying treatment on the ceramic tile;
driving printing equipment to print the ceramic tile;
driving firing equipment to perform firing treatment on the ceramic tile;
and driving the edging equipment to edging the ceramic tile.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 8 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310693160.8A CN116909216A (en) | 2023-06-12 | 2023-06-12 | Quality inspection line automatic control method, computer equipment and readable storage medium |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310693160.8A CN116909216A (en) | 2023-06-12 | 2023-06-12 | Quality inspection line automatic control method, computer equipment and readable storage medium |
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| Publication Number | Publication Date |
|---|---|
| CN116909216A true CN116909216A (en) | 2023-10-20 |
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| CN202310693160.8A Pending CN116909216A (en) | 2023-06-12 | 2023-06-12 | Quality inspection line automatic control method, computer equipment and readable storage medium |
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| CN (1) | CN116909216A (en) |
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- 2023-06-12 CN CN202310693160.8A patent/CN116909216A/en active Pending
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