CN117853480A - Material correction method, equipment and storage medium based on machine vision - Google Patents
Material correction method, equipment and storage medium based on machine vision Download PDFInfo
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Abstract
The invention relates to the field of industrial automation, and discloses a material correction method, equipment and a storage medium based on machine vision. The method comprises the following steps: when the machine detects the material to be processed, detecting the relative coordinates of the material to be processed on the machine; according to the relative coordinates and a preset process instruction document, processing operation is carried out on the material to be processed, and the material to be rechecked is obtained; scanning the material to be rechecked to obtain a target hub; comparing the target profile with a preset profile to obtain a comparison result; judging whether the material to be rechecked is qualified or not according to the comparison result; if the material to be rechecked is unqualified, executing the generation operation of the correction coefficient according to the comparison result; and performing secondary processing operation on the material to be re-inspected according to the correction coefficient to obtain the target material. In the embodiment of the invention, the yield of material processing is improved.
Description
Technical Field
The present invention relates to the field of industrial automation, and in particular, to a material correction method, apparatus, and storage medium based on machine vision.
Background
In the production and processing industry, after a CNC technician takes a program, clamping raw materials on a machine table, finding four sides of the raw materials by using a dividing rod to determine the relative size of the raw materials on the machine table, and manually inputting the relative size to a machine operation panel to finish parameter setting.
After the product is processed, the dimension is measured manually, the dimension is not processed in place after the dimension is measured with high precision, the cutter is opened for compensation, and the product is reprocessed. Once the product is taken off the machine table, the product is machined again, repeated positioning is performed, the machining standard is found, the size is difficult to ensure, the debugging time is long, the scrapping risk exists, and the yield of production and machining is reduced.
Disclosure of Invention
The invention mainly aims to solve the technical problem of low yield of production and processing.
The first aspect of the present invention provides a machine vision-based material correction method, including:
when a machine detects a material to be processed, detecting the relative coordinates of the material to be processed on the machine;
according to the relative coordinates and a preset process instruction document, processing operation is carried out on the material to be processed, and a material to be rechecked is obtained;
scanning the material to be rechecked to obtain a target hub;
comparing the target profile with a preset profile to obtain a comparison result;
judging whether the material to be rechecked is qualified or not according to the comparison result;
if the material to be rechecked is unqualified, executing the generation operation of the correction coefficient according to the comparison result;
and carrying out secondary processing operation on the material to be rechecked according to the correction coefficient to obtain a target material.
Optionally, in a first implementation manner of the first aspect of the present invention, the step of performing a processing operation on the material to be processed according to the relative coordinates and a preset process guidance document to obtain a material to be retested includes:
scanning the material to be processed to obtain a material hub, and judging whether the material profile is symmetrical or not;
and if the material profile is symmetrical, executing processing operation on the material to be processed according to the relative coordinates and a preset process instruction document to obtain the material to be rechecked.
Optionally, in a second implementation manner of the first aspect of the present invention, after the step of scanning the material to be processed to obtain a material hub and determining whether the material profile is symmetrical, the method further includes:
and if the profile of the material is asymmetric, outputting prompt information of the material to be processed needing fine adjustment.
Optionally, in a third implementation manner of the first aspect of the present invention, the step of performing a processing operation on the material to be processed according to the relative coordinates and a preset process guidance document to obtain a material to be retested includes:
extracting processing information from the process guidance document;
and according to the relative coordinates and the processing steps in the processing information, calling a processing tool corresponding to the processing steps to execute processing operation on the material to be processed, and obtaining the material to be rechecked.
Optionally, in a fourth implementation manner of the first aspect of the present invention, if the material to be processed does not need fine adjustment, performing a processing operation on the material to be processed according to the relative coordinates and a preset process instruction document, and the step of obtaining the material to be rechecked includes:
if the material to be processed does not need fine adjustment, extracting processing information from a process instruction book document;
and according to the relative coordinates and the processing steps in the processing information, calling a processing tool corresponding to the processing steps to execute processing operation on the material to be processed, and obtaining the material to be rechecked.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the step of comparing the target profile with the preset profile to obtain a comparison result includes:
and calculating the contour difference of the target contour relative to the preset contour to obtain a comparison result.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the step of calculating a contour difference of the target contour with respect to the preset contour, to obtain a comparison result includes:
performing 3D comparison on the target contour and the preset contour to obtain a 3D comparison result, and performing dimensional tolerance comparison on the target contour and the preset contour to obtain a dimensional deviation;
and calculating a difference region and a difference parameter corresponding to the difference region according to the 3D comparison result and the size deviation to obtain a contour difference, and taking the contour difference as the comparison result.
Optionally, in a seventh implementation manner of the first aspect of the present invention, according to the 3D comparison result and the dimensional deviation, calculating a difference region and a difference parameter corresponding to the difference region, to obtain a contour difference, and before the step of taking the contour difference as the comparison result, the method further includes:
performing 3D comparison on the target contour and the preset contour to obtain a 3D comparison result, and performing dimensional tolerance comparison on the target contour and the preset contour to obtain a dimensional deviation;
integrating the 3D comparison result and the size deviation into prompt information and outputting the prompt information;
executing the processing instruction when the processing instruction responding to the prompt information is detected within the preset time;
and when the processing instruction responding to the prompt information is not detected within the preset time, executing the step of calculating a difference region and a difference parameter corresponding to the difference region according to the 3D comparison result and the size deviation.
A second aspect of the present invention provides a machine vision based material correction apparatus comprising: a memory and at least one processor, the memory having instructions stored therein, the memory and the at least one processor being interconnected by a line; the at least one processor invokes the instructions in the memory to cause the machine vision based material correction device to perform the machine vision based material correction method described above.
A third aspect of the present invention provides a computer readable storage medium having instructions stored therein which, when run on a computer, cause the computer to perform the machine vision based material correction method described above.
In the embodiment of the invention, the material correction equipment based on machine vision automatically executes processing operation on the material to be processed according to the relative coordinates and the preset process instruction document. After the processing is finished, the material is scanned by utilizing a machine vision technology, the target contour of the material is obtained, and the target contour is compared with a preset contour, so that whether the material is qualified or not is rapidly judged. And automatically generating correction coefficients according to the comparison result for unqualified materials, and executing secondary processing operation. By the material correction method, problems can be found and adjusted in time in the processing process, and the condition that the final finished product is unqualified is avoided, so that the scrapping risk is reduced, and the yield of material processing is improved.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a machine vision-based material correction method according to an embodiment of the present invention;
FIG. 2 is a diagram of one embodiment of step 103 of a machine vision based material correction method in accordance with an embodiment of the present invention;
FIG. 3 is a diagram of one embodiment of the steps 1061 of a machine vision based material correction method in accordance with an embodiment of the present invention;
FIG. 4 is a diagram of one embodiment of a step 108 of a machine vision based material correction method in accordance with an embodiment of the present invention;
FIG. 5 is a schematic diagram of an embodiment of a machine vision-based material correction apparatus in accordance with an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a material correction method, equipment and a storage medium based on machine vision.
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the present disclosure has been illustrated in the drawings in some form, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and examples of the present disclosure are for illustrative purposes only and are not intended to limit the scope of the present disclosure.
In describing embodiments of the present disclosure, the term "comprising" and its like should be taken to be open-ended, i.e., including, but not limited to. The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first," "second," and the like, may refer to different or the same object. Other explicit and implicit definitions are also possible below.
For ease of understanding, a specific flow of an embodiment of the present invention is described below with reference to fig. 1, and an embodiment of a machine vision-based material correction method in an embodiment of the present invention includes:
101. when a machine detects a material to be processed, detecting the relative coordinates of the material to be processed on the machine;
specifically, after raw materials are clamped on a workbench surface of the equipment, the relative positions of the raw materials are input to the equipment for processing, and the embodiment has the function of detecting the relative coordinates of the materials to be processed on the workbench.
Further, the machine vision-based material correction apparatus scans three-dimensional coordinate data of the raw material, which may include X, Y, Z coordinate values, point cloud data representing the surface of the object. And filtering and denoising the obtained point cloud data, and eliminating noise and redundant information in the data so as to improve the accuracy and reliability of the data.
Optionally, scanning the material to be processed to obtain a material hub, and comparing the material profile with a preset profile to obtain the similarity; a comparison algorithm, such as Euclidean distance, cosine similarity, and the like, can be used to calculate the similarity between the profile of the material and the preset profile. Can be selected according to actual requirements.
The similarity is compared with a set threshold. If the comparison result is within the threshold range, the material to be processed is considered to need fine adjustment; if the threshold range is exceeded, then the material to be processed is considered to require fine tuning.
Further, the extracted feature points are analyzed. For example, if the pre-set profile should have a particular feature point, but the comparison shows that this feature point is not present or is not correctly positioned in the profile of the material, it may be determined that the material needs to be trimmed.
Further, if the mark in the preset profile should be at a specific position, but the position of the mark is displayed by the comparison result is incorrect, it can be judged that the material needs to be finely tuned.
Specifically, the step of comparing further includes: judging whether the material profile is symmetrical; if the material profile is symmetrical, determining that the material does not need fine adjustment; if the profile of the material is asymmetric, the material to be processed is judged to need fine adjustment.
Specifically, if the material to be processed needs fine adjustment, a prompt message that the material to be processed needs fine adjustment is output.
102. According to the relative coordinates and a preset process instruction document, processing operation is carried out on the material to be processed, and a material to be rechecked is obtained;
specifically, according to the relative coordinates and a preset process instruction document, a processing process suitable for the material to be processed is selected. The process instructions will typically provide detailed steps and parameter settings to guide the operator in properly performing the process.
And calling corresponding processing equipment according to the selected processing technology. Ensure that the equipment is in good condition, carry out necessary debugging and calibration to ensure the accuracy and the stability of processing.
The material to be processed is positioned and fixed, so that the material is ensured to be stable in the processing process and cannot move or deform. According to the characteristics of the materials and the processing requirements, corresponding positioning and fixing modes are selected.
And according to the parameter setting provided in the process instruction document, carrying out parameter adjustment on the processing equipment based on the relative position of the material to be processed in the machine table. Including but not limited to cutting speed, feed rate, depth, etc., to ensure smooth progress of the machining process. After the parameters are set, verification and calibration are carried out, and the accuracy and the effectiveness of the parameters are ensured.
After confirming that the material positioning, fixing and parameter setting are correct, the machining process is started. The operation state of the processing equipment is monitored, the cutting condition is observed, and the abnormal condition is found and processed in time.
And after finishing processing, obtaining the material to be rechecked.
Specifically, step 102 includes the following embodiments:
1021. extracting processing information from the process guidance document;
1022. and according to the relative coordinates and the processing steps in the processing information, calling a processing tool corresponding to the processing steps to execute processing operation on the material to be processed, and obtaining the material to be rechecked.
In steps 1021-1022, standardization and normalization of the machining process is ensured by using the process guidance document as a basis for extracting machining information. This helps to ensure consistency in product quality and performance. By automatically extracting and executing the process information, the likelihood of human intervention and human error is reduced. Is beneficial to improving the stability and consistency of the processing process.
103. Scanning the material to be rechecked to obtain a target hub;
specifically, a 3D laser scanner is invoked to generate the target hub.
104. Comparing the target profile with the preset profile to obtain a comparison result;
specifically, a comparison algorithm is adopted to calculate the difference between the material profile and the preset profile.
And (3) evaluating the similarity or the difference between the profile of the material and the preset profile according to the result of the comparison algorithm to obtain a comparison result. The degree of difference is calculated, for example, using the euclidean distance (Euclidean Distance):
and normalizing the target contour and the preset contour, and converting the target contour and the preset contour into numerical vectors with the same size and range.
The euclidean distance between corresponding points in the two contours is calculated. This can be done by calculating the linear distance between two points, i.e. using the formula:
wherein A and B are corresponding points in the two contours, (x) 1 ,x 2 ) And (y) 1 ,y 2 ) Are their coordinates.
The Euclidean distances between all corresponding pairs of points are added to obtain the total distance between the two contours.
And finally, dividing the total distance by the number of corresponding point pairs to obtain an average Euclidean distance, namely the difference degree between the target contour and the preset contour.
Specifically, the step 104 further includes the following specific embodiments:
1041. and calculating the contour difference of the target contour relative to the preset contour to obtain a comparison result.
In step 1041, by calculating the profile differences, an accurate measure of the similarity or difference between the target profile and the preset profile may be made. Quantitative data is provided regarding the degree of matching or the degree of deviation between the two.
Specifically, referring to fig. 2, fig. 2 is a schematic diagram showing a specific embodiment of a step 1041 of a material correction method based on machine vision in an embodiment of the present invention, where the step 1041 includes the following specific embodiments:
10411. performing 3D comparison on the target contour and the preset contour to obtain a 3D comparison result, and performing dimensional tolerance comparison on the target contour and the preset contour to obtain a dimensional deviation;
10412. and calculating a difference region and a difference parameter corresponding to the difference region according to the 3D comparison result and the size deviation to obtain a contour difference, and taking the contour difference as the comparison result.
In steps 10411-10412, the target profile and the preset profile may be comprehensively evaluated by 3D comparison and dimensional tolerance comparison. The assessment method takes both shape and size into account, providing a more comprehensive analysis of differences. The 3D alignment technique can provide a high accuracy profile matching metric, while the dimensional tolerance alignment is used to determine the deviation between the actual dimension and the design dimension. The difference region and the difference parameter can be determined more accurately by combining the two.
Specifically, referring to fig. 3, fig. 3 is a schematic diagram showing a specific embodiment before step 10411 of the machine vision-based material correction method according to an embodiment of the present invention, and the following specific embodiments are further included before step 10411:
10413. performing 3D comparison on the target contour and the preset contour to obtain a 3D comparison result, and performing dimensional tolerance comparison on the target contour and the preset contour to obtain a dimensional deviation;
specifically, 3D data of the target profile and the preset profile is acquired, and may be obtained by a scanning device.
And 3D data of the target contour and the preset contour are compared by adopting point cloud registration, the similarity or difference between the target contour and the preset contour is evaluated, the 3D comparison result comprises registration errors, the registration errors are indexes for measuring the alignment precision of the target contour and the preset contour, and the registration errors are expressed in modes of average distance, root Mean Square Error (RMSE) and the like. The smaller the registration error, the higher the alignment accuracy. The point cloud registration is to map one point cloud onto another point cloud by searching for a spatial transformation so that corresponding points in the two point clouds coincide as much as possible. Algorithms that may be used include the ICP (Iterative Closest Point) algorithm.
And after the 3D comparison result is obtained, further carrying out dimensional tolerance comparison on the target contour and the preset contour. The dimensional deviation can be obtained by extracting feature sizes in the 3D data and comparing differences between the feature sizes.
10414. Integrating the 3D comparison result and the size deviation into prompt information and outputting the prompt information;
10415. executing the processing instruction when the processing instruction responding to the prompt information is detected within the preset time;
10416. and when the processing instruction responding to the prompt information is not detected within the preset time, executing the step of calculating a difference region and a difference parameter corresponding to the difference region according to the 3D comparison result and the size deviation.
In steps 10413-10416, feedback about the machining process is provided through data analysis and calculation based on the 3D comparison result and the dimensional deviation. These data may provide basis for decisions, supporting data-driven decision-making.
105. And judging whether the material to be rechecked is qualified or not according to the comparison result.
Specifically, the comparison results were analyzed. The comparison result may be an indicator of the degree of difference or similarity between the material to be retested and the predetermined profile.
And setting a judging threshold according to a preset machining precision requirement. The decision threshold may be used to determine whether the material to be retested is within an acceptable error range.
And comparing the comparison result with a set threshold value. If the comparison result is within the threshold range, the material to be rechecked is qualified; and if the material to be rechecked is out of the threshold range, the material to be rechecked is considered to be unqualified.
Outputting a judging result, and if the material to be rechecked is qualified, carrying out subsequent treatment or entering the next procedure; if the material to be rechecked is unqualified, secondary processing or scrapping treatment is needed.
106. If the material to be rechecked is unqualified, executing the generation operation of the correction coefficient according to the comparison result;
specifically, the comparison results were analyzed. The comparison result includes an index of the degree of difference or similarity between the material to be retested and the preset profile, for example, a difference parameter corresponding to the difference region.
And generating corresponding correction coefficients according to the difference parameters corresponding to the difference areas. These correction factors may include adjusting cutting parameters, optimizing machining paths, correcting positioning and fixing patterns, etc.
Specifically, referring to fig. 4, fig. 4 is a schematic diagram showing a specific embodiment of a step 106 of a material correction method based on machine vision according to an embodiment of the present invention, where the step 106 includes the following specific embodiments:
1061. if the material to be rechecked is unqualified, performing distance measurement calculation according to the data points in the comparison result to obtain a difference result of the material to be rechecked and the preset contour;
1062. and calculating a correction coefficient corresponding to the difference result.
In steps 1061-1062, the difference between the material to be retested and the preset profile may be accurately measured by using the distance metric calculation. A more comprehensive assessment of the differences can be provided taking into account the plurality of data points.
107. And carrying out secondary processing operation on the material to be rechecked according to the correction coefficient to obtain a target material.
Specifically, according to the generated correction coefficient, the processing parameters, equipment parameters and the like of the material to be retested are adjusted. Ensuring that the correction coefficient is correctly applied to the secondary processing process. Starting the processing equipment, and carrying out secondary processing on the material to be rechecked according to the corrected parameters and settings. The running state and the cutting process of the equipment are monitored, and the smooth proceeding of the processing process is ensured. In the secondary processing process, parameters are adjusted and controlled according to actual conditions. The processing quality and efficiency are improved by means of monitoring processing data, observing cutting conditions and the like.
After the secondary processing is completed, the processing result is checked and evaluated. And comparing the preset contours, and evaluating the conformity degree of the target material. And if the evaluation result shows that the target material meets the requirements, judging that the target material is qualified. And if the evaluation result shows that the target material still has unqualified parts, repeating processing by taking the target material as the first material until the target material is qualified.
In the embodiment of the invention, the material correction equipment based on machine vision automatically executes processing operation on the material to be processed according to the relative coordinates and the preset process instruction document. After the processing is finished, the material is scanned by utilizing a machine vision technology, the target contour of the material is obtained, and the target contour is compared with a preset contour, so that whether the material is qualified or not is rapidly judged. And automatically generating correction coefficients according to the comparison result for unqualified materials, and executing secondary processing operation. By the material correction method, problems can be found and adjusted in time in the processing process, and the condition that the final finished product is unqualified is avoided, so that the scrapping risk is reduced, and the yield of material processing is improved.
Fig. 5 is a schematic structural diagram of a machine vision-based material correction device 500 according to an embodiment of the present invention, where the machine vision-based material correction device 500 may have a relatively large difference due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (e.g., one or more processors) and a memory 520, and one or more storage media 530 (e.g., one or more mass storage devices) storing application programs 533 or data 532. Wherein memory 520 and storage medium 530 may be transitory or persistent storage. The program stored on the storage medium 530 may include one or more modules (not shown), each of which may include a series of instruction operations for the machine vision based material correction device 500. Still further, the processor 510 may be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the machine vision based material correction device 500.
The machine vision based material modification apparatus 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input/output interfaces 560, and/or one or more operating systems 531, such as Windows Serve, mac OS X, unix, linux, free BSD, and the like. It will be appreciated by those skilled in the art that the machine vision based material modification apparatus structure shown in fig. 5 does not constitute a limitation of the machine vision based material modification apparatus, and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, and may also be a volatile computer readable storage medium, having stored therein instructions that, when executed on a computer, cause the computer to perform the steps of the machine vision based material correction method.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Moreover, although operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.
Claims (10)
1. A machine vision-based material correction method, characterized in that the machine vision-based material correction method comprises:
when a machine detects a material to be processed, detecting the relative coordinates of the material to be processed on the machine;
according to the relative coordinates and a preset process instruction document, processing operation is carried out on the material to be processed, and a material to be rechecked is obtained;
scanning the material to be rechecked to obtain a target hub;
comparing the target profile with a preset profile to obtain a comparison result;
judging whether the material to be rechecked is qualified or not according to the comparison result;
if the material to be rechecked is unqualified, executing the generation operation of the correction coefficient according to the comparison result;
and carrying out secondary processing operation on the material to be rechecked according to the correction coefficient to obtain a target material.
2. The machine vision-based material correction method according to claim 1, wherein the step of performing the correction coefficient generation operation according to the comparison result if the material to be retested is not acceptable comprises:
if the material to be rechecked is unqualified, performing distance measurement calculation according to the data points in the comparison result to obtain a difference result of the material to be rechecked and the preset contour;
and calculating a correction coefficient corresponding to the difference result.
3. The machine vision-based material correction method according to claim 1, wherein the step of performing a processing operation on the material to be processed according to the relative coordinates and a preset process guidance document to obtain a material to be rechecked includes:
scanning the material to be processed to obtain a material hub, and judging whether the material profile is symmetrical or not;
and if the material profile is symmetrical, executing processing operation on the material to be processed according to the relative coordinates and a preset process instruction document to obtain the material to be rechecked.
4. The machine vision based material correction method as set forth in claim 3, wherein after the step of scanning the material to be processed to obtain a material hub and determining whether the material profile is symmetrical, further comprising:
and if the profile of the material is asymmetric, outputting prompt information of the material to be processed needing fine adjustment.
5. The machine vision-based material correction method according to claim 1, wherein the step of performing a processing operation on the material to be processed according to the relative coordinates and a preset process guidance document to obtain a material to be rechecked includes:
extracting processing information from the process guidance document;
and according to the relative coordinates and the processing steps in the processing information, calling a processing tool corresponding to the processing steps to execute processing operation on the material to be processed, and obtaining the material to be rechecked.
6. The machine vision based material correction method according to any one of claims 1 to 5, wherein the step of comparing the target profile with the preset profile to obtain a comparison result includes:
and calculating the contour difference of the target contour relative to the preset contour to obtain a comparison result.
7. The machine vision based material correction method of claim 6, wherein the step of calculating a contour difference of the target contour with respect to the preset contour to obtain a comparison result comprises:
performing 3D comparison on the target contour and the preset contour to obtain a 3D comparison result, and performing dimensional tolerance comparison on the target contour and the preset contour to obtain a dimensional deviation;
and calculating a difference region and a difference parameter corresponding to the difference region according to the 3D comparison result and the size deviation to obtain a contour difference, and taking the contour difference as the comparison result.
8. The machine vision based material correction method according to claim 7, wherein, before the step of calculating a difference region and a difference parameter corresponding to the difference region according to the 3D comparison result and the dimensional deviation to obtain a contour difference, and taking the contour difference as the comparison result, the method further comprises:
performing 3D comparison on the target contour and the preset contour to obtain a 3D comparison result, and performing dimensional tolerance comparison on the target contour and the preset contour to obtain a dimensional deviation;
integrating the 3D comparison result and the size deviation into prompt information and outputting the prompt information;
executing the processing instruction when the processing instruction responding to the prompt information is detected within the preset time;
and when the processing instruction responding to the prompt information is not detected within the preset time, executing the step of calculating a difference region and a difference parameter corresponding to the difference region according to the 3D comparison result and the size deviation.
9. A machine vision-based material correction apparatus, the machine vision-based material correction apparatus comprising: a memory and at least one processor, the memory having instructions stored therein, the memory and the at least one processor being interconnected by a line;
the at least one processor invokes the instructions in the memory to cause the machine vision based material correction device to perform the machine vision based material correction method of any one of claims 1-8.
10. A computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the machine vision based material correction method according to any one of claims 1-8.
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