CN117173156A - Pole piece burr detection method, device, equipment and medium based on machine vision - Google Patents
Pole piece burr detection method, device, equipment and medium based on machine vision Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 79
- 238000000034 method Methods 0.000 claims abstract description 41
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- 239000011159 matrix material Substances 0.000 claims description 48
- 239000012530 fluid Substances 0.000 claims description 45
- 238000004422 calculation algorithm Methods 0.000 claims description 18
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Abstract
The invention discloses a machine vision-based pole piece burr detection method, a machine vision-based pole piece burr detection device, a machine vision-based pole piece burr detection equipment and a machine vision-based pole piece burr detection medium. The method comprises the following steps: sha Mcheng images are carried out on the slice to be detected through an area array camera, and a picture to be detected is obtained; carrying out distortion correction on the picture to be detected; dividing and cutting the picture to be detected after distortion correction to position the area; and detecting burrs in each cutting area to obtain a burr detection result. The scheme of the invention provides a pole piece slitting burr detection method based on visual detection, which solves the problems that detection by using an area array camera and telecentric lens imaging is limited by small depth of field, normal imaging cannot be performed, detection is affected, and the stability requirement of detection cannot be met.
Description
Technical Field
The invention relates to the technical field of lithium battery detection, in particular to a machine vision-based pole piece burr detection method, a machine vision-based pole piece burr detection device, a machine vision-based pole piece burr detection equipment and a machine vision-based pole piece burr detection medium.
Background
In the production process of the lithium battery, a slitting process is required to be used for slitting the pole piece, and burrs are often generated on the battery pole fluid due to the influences of abrasion or material process and the like in the pole piece slitting process of the slitting knife. These burrs are extremely small, typically in microns in length. Because the positive electrode and the negative electrode of the cut battery pole piece need to be separated by the diaphragm when being packaged, if the height of the burrs is higher than the upper limit of the thickness tolerance of the diaphragm, the diaphragm can be pierced, so that the battery is short-circuited, and serious potential safety hazards of the battery are formed. The burr length must be tightly controlled during the production process.
At present, detection of burrs is generally carried out by using an area-array camera and a telecentric lens for imaging, but the detection cannot be influenced by normal imaging due to the problem of small depth of field, and the stability requirement of detection cannot be met.
In summary, based on the technical defects in the prior art, a method for detecting the burrs of the pole piece based on machine vision is needed to meet the detection stability requirement.
Disclosure of Invention
The invention provides a machine vision-based pole piece burr detection method, a machine vision-based pole piece burr detection device, a machine vision-based pole piece burr detection equipment and a machine vision-based pole piece burr detection medium, so as to meet the stability requirement of lithium battery pole piece burr detection.
According to an aspect of the invention, there is provided a machine vision-based pole piece burr detection method, comprising:
sha Mcheng images are carried out on the slice to be detected through an area array camera, and a picture to be detected is obtained;
carrying out distortion correction on the picture to be detected;
dividing and cutting the picture to be detected after distortion correction to position the area;
and detecting burrs in each cutting area to obtain a burr detection result.
Optionally, the performing distortion correction on the to-be-detected picture includes:
determining an internal reference matrix, an external reference matrix and a distortion coefficient of the area array camera;
and carrying out distortion correction on the picture to be detected through the internal reference matrix, the external reference matrix and the distortion coefficient.
Optionally, the determining the internal parameter matrix, the external parameter matrix and the distortion coefficient of the area array camera includes:
manufacturing a checkerboard with corresponding precision according to the single pixel precision requirement of burr detection;
shooting the checkerboard at least one angle of the area array camera to obtain a checkerboard image;
calibrating through a preset calibration algorithm, determining a calibration relation among a camera coordinate system of an area array camera, a world coordinate system serving as a reference standard and a pixel coordinate system, so as to determine the internal reference matrix and the external reference matrix;
and obtaining a distortion coefficient through an image distortion model.
Optionally, the positioning the splitting area of the picture to be detected after the distortion correction includes:
obtaining a separation threshold of the picture to be detected through a threshold segmentation model of an otsu algorithm;
dividing the picture to be detected through the separation threshold value to obtain a polar fluid image corresponding to the foreground;
positioning a slit region included in the polar fluid image.
Optionally, the positioning the splitting area included in the polar fluid includes:
skeletonizing the polar fluid image;
performing contour searching and positioning on the polar fluid image subjected to skeletonization treatment, and determining the mass center of the searched contour point set;
performing straight line fitting on the mass center to obtain a target straight line;
setting a standard width dimension of the polar fluid and taking the standard width dimension as an offset value;
and (3) vertically shifting the target straight line to find the upper and lower boundaries of the polar fluid, thereby obtaining the slitting area.
Optionally, burr detection is performed on each slit area to obtain a burr detection result, including:
setting the pixel value of each slitting area to 0 to obtain a burr part;
and determining at least one attribute value of the burr, and taking the attribute value as the burr detection result.
Optionally, the determining at least one attribute value of the burr includes:
when the attribute value is a burr area value, locating a single burr through profile searching, and carrying out area statistics on the profile to obtain the burr area value;
and when the attribute value is a burr length value, skeletonizing burrs, and performing non-closed length calculation on the skeletonized burr profile to obtain the burr length value.
According to another aspect of the present invention, there is provided a machine vision-based pole piece burr detection apparatus, comprising:
the image acquisition unit is used for carrying out Sha Mcheng images on the slice to be detected through the area array camera to obtain an image to be detected;
the picture processing unit is used for carrying out distortion correction on the picture to be detected;
the splitting area positioning unit is used for positioning splitting areas of the picture to be detected after distortion correction;
and the cutting area detection unit is used for detecting burrs of each cutting area to obtain a burr detection result.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores a computer program executable by the at least one processor, so that the at least one processor can execute the pole piece burr detection method based on machine vision according to any embodiment of the invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the machine vision-based pole piece burr detection method according to any one of the embodiments of the present invention when executed.
According to the technical scheme, sha Mcheng images are carried out on the slice to be detected through the area array camera, so that a picture to be detected is obtained; carrying out distortion correction on the picture to be detected; dividing and cutting the picture to be detected after distortion correction to position the area; and detecting burrs in each cutting area to obtain a burr detection result. The invention provides a pole piece slitting burr detection method based on machine vision, which solves the problems that detection by using an area array camera and telecentric lens imaging is limited by small depth of field, normal imaging cannot be performed, detection is affected, and the stability requirement of detection cannot be met.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a pole piece burr detection method based on machine vision according to a first embodiment of the present invention;
FIG. 2 is an imaging schematic diagram of a sand-based imaging system to which an embodiment of the present invention is applied;
FIG. 3 is a schematic diagram of a sand mechanism to which an embodiment of the present invention is applicable;
FIG. 4 is a schematic diagram of a shooting original image according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a corrected photographic artwork according to one embodiment of the present invention;
FIG. 6 is a schematic diagram of an image segmentation method according to an embodiment of the present invention;
FIG. 7 is a schematic illustration of a polar fluid skeletonization method according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of a centroid suitable for use in accordance with one embodiment of the present invention;
FIG. 9 is a schematic diagram of a centroid map fitting straight line according to an embodiment of the present invention;
FIG. 10 is a schematic illustration of the position of a polar fluid of one type to which an embodiment of the present invention is applicable;
FIG. 11 is a schematic diagram of a burr area according to an embodiment of the invention;
fig. 12 is a schematic structural diagram of a pole piece burr detection device based on machine vision according to a second embodiment of the present invention;
fig. 13 is a schematic structural diagram of an electronic device for implementing the machine vision-based pole piece burr detection method according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of a machine vision-based pole piece burr detection method provided in an embodiment of the invention, where the embodiment is applicable to a situation of performing burr detection on pole fluid after cutting a lithium battery pole piece, the method may be performed by a machine vision-based pole piece burr detection device, the machine vision-based pole piece burr detection device may be implemented in a form of hardware and/or software, and the machine vision-based pole piece burr detection device may be configured in an electronic device. As shown in fig. 1, the method includes:
s110, sha Mcheng images are carried out on the slice to be detected through the area array camera, and the picture to be detected is obtained.
The area array camera mainly adopts continuous and planar scanning light rays to realize detection of products, can acquire complete target images at one time, and can acquire images in time. Considering that the traditional visual shooting mode can not meet the definition requirement, the imaging depth of field is enlarged by utilizing the principle of the imaging of the poloxamer and combining the adjusting mechanism of the poloxamer and the telecentric lens. Fig. 2 is an imaging schematic diagram of a sham imaging device according to an embodiment of the present invention, and fig. 3 is a schematic diagram of a sham mechanism according to an embodiment of the present invention. The principles of the magnetic field sensor are that when the extension planes of the lens plane, the image plane and the object plane are compared with a straight line, the overall and clear image can be obtained. Through the angle between the camera and the lens of the poloxamer adjusting mechanism, when the distance between the pole piece and the camera lens changes, the pole piece is still in the depth of field range. Therefore, the edges on the two sides of the pole piece can be always in the visual field range of the camera, and the pole piece can be clearly displayed.
S120, carrying out distortion correction on the picture to be detected.
The requirements of definition are met by using the law of Moire, but the geometric distortion problem exists because the image plane, the mirror plane and the object are not the same, and the parallel and vertical relationship of the original patterns in the image is kept by a distortion correction method.
In an embodiment of the present invention, the performing distortion correction on the to-be-detected picture includes:
determining an internal reference matrix, an external reference matrix and a distortion coefficient of the area array camera;
and carrying out distortion correction on the picture to be detected through the internal reference matrix, the external reference matrix and the distortion coefficient.
The internal reference matrix is an important matrix used for describing optical parameters and image acquisition rules of the camera in computer vision, and comprises internal parameters of the camera, such as focal length, pixel size, principal point position and the like, and geometric deformation parameters of the camera, such as radial distortion, tangential distortion and the like. The image pixel coordinates with the camera coordinate system as the reference system are proportional to the three-dimensional physical coordinates, and the relationship is described by the internal reference matrix. The internal reference matrix is an important calibration parameter in the field of computer vision, and can be obtained by calibrating the camera, so that the functions of camera self calibration, image structure reconstruction, relative position determination and the like are realized. The camera extrinsic matrix refers to a matrix for determining the position and orientation of a camera in three-dimensional space, and generally includes a 3x3 rotation matrix and a 3x1 translation matrix, and the extrinsic matrix represents a transformation matrix of an object between a world coordinate system and a camera coordinate system, and is only related to the position of the camera in the world coordinate system. Distortion is an image distortion that the camera inevitably generates due to its own imaging characteristics. The distortion can be divided into two types, tangential distortion and radial distortion, respectively, which occurs because the light rays are bent to a greater extent when they are far from the center of the lens than when they are near the center. The internal reference matrix, the external reference matrix and the distortion coefficient are important parameters in camera calibration for distortion correction.
In an embodiment of the present invention, the determining the internal parameter matrix, the external parameter matrix and the distortion coefficient of the area array camera includes:
manufacturing a checkerboard with corresponding precision according to the single pixel precision requirement of burr detection;
shooting the checkerboard at least one angle of the area array camera to obtain a checkerboard image;
calibrating through a preset calibration algorithm, determining a calibration relation among a camera coordinate system of an area array camera, a world coordinate system serving as a reference standard and a pixel coordinate system, so as to determine the internal reference matrix and the external reference matrix;
and obtaining a distortion coefficient through an image distortion model.
In the embodiment of the invention, the checkerboard is preferably used for correcting the distortion of the image, and the checkerboard with corresponding precision is manufactured according to the single-pixel precision requirement. Under the condition of meeting the field of view of the camera, the checkerboard is placed at each angle of the camera to shoot, and calibration is carried out through a calibration algorithm, which means the process that the pixel corresponds to the coordinate of the object under the world coordinate system in the pixel coordinate system and in the real situation. The coordinate system is converted from a world coordinate system to a camera coordinate system, from the camera coordinate system to an image coordinate system, and from the image coordinate system to a pixel coordinate system.
The following is the mapping relation between one point of the world coordinate system and the corresponding point on the image coordinate system:
；
the above formula can be expressed as:；
wherein the image coordinatesThe method comprises the steps of carrying out a first treatment on the surface of the Scale factor->Internal reference matrix->External reference matrixWorld coordinates->。
Due toThe world physical coordinates of (2) need to be defined by human, so +.>For 0, i.e., assuming that all coordinate points are in the same plane, the z-axis coordinate may be omitted.
In this way, the world coordinate system becomesWhile the corresponding external matrix is converted into +.>The above->Equivalent to->；
Because ofAnd->Is a known quantity, so the calibration procedure is to solve +.>Is a process of (2).
Since the solution of the equation involves multiple sets of unknowns, it is particularly necessary to take multiple sets of checkerboard pictures at different angles at the time of implementation to provide a sufficient known quantity for the equation solution. When the calibration is completed,i.e. matrix H completes the solution. Through type sonWhich translates into actual physical dimensions. The above is the whole calibration procedure, but the problem of image distortion is also required to be considered. The following is a model of image distortion:
radial distortion:；
tangent distortion:；
in the above-mentioned method, the step of,representing the coordinate position in the camera coordinate system under ideal conditions. />Representing the coordinates in the camera coordinate system under distortion, r being the distance of the coordinate from the imaging center,/->Parameters are described for 5 distortions, and the correction of the distortion occurs in the image coordinate system.
After the process is finished, an internal reference matrix, an external reference matrix and corresponding distortion coefficients of the camera can be obtained, the data are stored, and then each time a new image is shot from the camera end, the data are converted to obtain a de-distorted picture.
S130, positioning a cutting area of the picture to be detected after distortion correction.
In the embodiment of the present invention, the positioning the splitting area of the picture to be detected after distortion correction includes:
obtaining a separation threshold of the picture to be detected through a threshold segmentation model of an otsu algorithm;
dividing the picture to be detected through the separation threshold value to obtain a polar fluid image corresponding to the foreground;
positioning a slit region included in the polar fluid image.
Fig. 4 is a schematic diagram of a shooting original image according to an embodiment of the present invention, and fig. 5 is a schematic diagram of a corrected shooting original image according to an embodiment of the present invention. First, binarization processing is performed on an image. According to the embodiment of the invention, an otsu algorithm is adopted to carry out automatic threshold solving on the image, and image binarization is carried out. The so-called otsu algorithm uses the gray level distribution characteristics of an image to look at the image as a foreground and a background, and then uses the variance to measure the difference between the foreground and the background. Ideally, for the same object region, the intra-class variance of the pixel values is smaller, and the inter-class variance of the pixel values of different object regions, namely the foreground and the background, is larger, which means that the difference between the two is larger, when the difference reaches the maximum, but when the foreground and the background are staggered, the inter-class variance is gradually reduced, so that when the difference reaches the maximum, namely the inter-class variance is the maximum, the optimal segmentation point is the threshold segmentation model of the otsu algorithm, and the following is the threshold segmentation model of the otsu algorithm:
assuming that the size of the image isThe threshold T is used for separating the front and rear background images of the image, and the number of foreground pixel points is set to be +.>The number of pixels of the background +.>The pixel average gray value of the foreground is +.>Pixel average gray value of background +.>The following models exist:
；
；
；
in the above-mentioned method, the step of,for the ratio of the number of target pixels to the total number of pixels of the total picture, +.>The number of the background pixels is the ratio of the total number of the pixels of the total image, and the number of the background pixels is +.>For the average gray value of the whole picture, +.>The variance value is the variance value of foreground and background values of the inter-class variance, namely the areas of different classes of objects. By traversing each gray value (0-255), the best T can be found to segment the foreground and background, i.e., polar and non-polar fluids. Fig. 6 is a schematic diagram of an image segmentation method according to an embodiment of the invention.
In an embodiment of the present invention, the positioning the splitting area included in the polar fluid includes:
skeletonizing the polar fluid image;
performing contour searching and positioning on the polar fluid image subjected to skeletonization treatment, and determining the mass center of the searched contour point set;
performing straight line fitting on the mass center to obtain a target straight line;
setting a standard width dimension of the polar fluid and taking the standard width dimension as an offset value;
and (3) vertically shifting the target straight line to find the upper and lower boundaries of the polar fluid, thereby obtaining the slitting area.
After the front and rear backgrounds are segmented, the area of the block needs to be found. Since the polar fluid is not a continuous complete region but is divided into a plurality of discrete segment-shaped blocks under camera imaging, and the blocks show an irregular direction form, the interval of the whole region needs to be positioned first. The specific flow is as follows:
1. firstly, skeletonizing a foreground, namely the polar fluid, so that the polar fluid block becomes more refined, and interference of redundant contour pixels is eliminated. Skeletonization can be achieved using the Zhang algorithm. FIG. 7 is a schematic diagram of an exemplary polar fluid skeletonization method according to an embodiment of the present invention.
2. And carrying out contour searching and positioning on the skeletonized image, and calculating the mass center of the found contour point set. The following are calculation models of centroid:
；
above-mentionedIs the x-axis coordinate of the centroid,>is the y-axis coordinate of the centroid,>is the zero order moment of the contour, +.>For the moment of the profile about the x-axis +.>Is the moment of the profile about the y-axis. By solving the moment, the centroid of the final contour can be obtained in combination with the above equation. Fig. 8 is a schematic diagram of a centroid suitable for use in accordance with an embodiment of the present invention.
3. The centroids are subjected to linear fitting, and the linear fitting mode of ransac is adopted until the best straight line is found, namely the error value is minimum.
The ransac algorithm is a random sampling statistical algorithm, and the final parameter result is solved through iteration of a model.
The parameters required to be set are as follows: 1. a least number of participating straight line points fit threshold; 2. iteration times of straight line solving; 3. the point fitting number threshold value of the optimal straight line; 4. intra-office fetch probability. The specific flow is as follows:
the method comprises the steps of obtaining a sample point set through intra-office point removal probability, wherein the obtained point set sample needs to meet the threshold value of the number of points fitting of the least participated straight line, then conducting straight line fitting on the straight lines, then conducting error analysis on all the point sets and the straight line which is well fitted at present, conducting iterative fitting continuously, obtaining a straight line solution with small error, and obtaining the straight line which is the finally solved model when the iteration times are met and the straight line which participates in the least error fitting meets the threshold value of the number of points fitting of the best straight line.
In the above description, the straight line fitting algorithm adopts a least square straight line fitting algorithm in an analytic solution mode, specifically, a solution target equation is solved, and when the target equation reaches the minimum value, the straight line is the straight line on fitting. Fig. 9 is a schematic diagram of a centroid map fitting straight line according to an embodiment of the present invention.
4. The standard width dimension of the polar fluid is set, and the value is taken as an offset value, and the positioned straight line is offset up and down to find the upper and lower boundaries of the polar fluid. Through the above operation, the position of the polar fluid can be finally located. FIG. 10 is a schematic diagram of the position of a polar fluid according to one embodiment of the present invention.
S140, detecting burrs of each cutting area to obtain a burr detection result.
After the above steps, the part inside the upper and lower boundaries is the normal polar fluid part, and the part beyond the upper and lower boundaries is the burr which needs to be found finally.
In the embodiment of the invention, burr detection is performed on each slitting area to obtain a burr detection result, and the method comprises the following steps:
setting the pixel value of each slitting area to 0 to obtain a burr part;
and determining at least one attribute value of the burr, and taking the attribute value as the burr detection result.
In the image, the polar fluid region is first found, and the pixel value of the polar fluid region is set to 0, so that the polar fluid region is shielded, and only the burr part is left. The final required spur attribute value is then calculated. Fig. 11 is a schematic view of a burr area according to an embodiment of the invention.
In an embodiment of the present invention, the determining at least one attribute value of the burr includes:
when the attribute value is a burr area value, locating a single burr through profile searching, and carrying out area statistics on the profile to obtain the burr area value;
and when the attribute value is a burr length value, skeletonizing burrs, and performing non-closed length calculation on the skeletonized burr profile to obtain the burr length value.
Specifically, the burr area value: by means of contour finding, a single burr is located. And carrying out area statistics on the profile, wherein the counted area value is the area value of the final burr.
Burr length value: since burrs are likely to bend, conventionally solving the smallest outside rectangle, and taking the rectangle side length as the length of the final burr is error-prone. The embodiment of the invention adopts the same skeletonizing mode of the burrs, skeletonizes the burrs, presents an elongated profile state after skeletonizing, and then carries out non-closed type length calculation on the treated profile to obtain the final burr length.
The method solves the problem that the picture is unclear due to the problem of depth of field, so that the picture cannot be detected. Not only reduces too much human cost, but also can realize real-time monitoring, effectively reduces the risk of missed detection of the battery pole piece, and ensures the quality safety of the product.
Example two
Fig. 12 is a schematic structural diagram of a pole piece burr detection device based on machine vision according to a second embodiment of the present invention. As shown in fig. 12, the apparatus includes:
the image obtaining unit 1210 is configured to obtain an image to be detected by performing Sha Mcheng images on a slice to be detected through an area array camera;
a picture processing unit 1220, configured to correct distortion of the picture to be detected;
the splitting area positioning unit 1230 is used for splitting area positioning of the picture to be detected after distortion correction;
and the cutting area detecting unit 1240 is configured to perform burr detection on each cutting area, so as to obtain a burr detection result.
Optionally, the picture processing unit 1220 is configured to perform:
determining an internal reference matrix, an external reference matrix and a distortion coefficient of the area array camera;
and carrying out distortion correction on the picture to be detected through the internal reference matrix, the external reference matrix and the distortion coefficient.
Optionally, the image processing unit 1220, when executing the determining the internal parameter matrix, the external parameter matrix and the distortion coefficient of the area-array camera, specifically executes:
manufacturing a checkerboard with corresponding precision according to the single pixel precision requirement of burr detection;
shooting the checkerboard at least one angle of the area array camera to obtain a checkerboard image;
calibrating through a preset calibration algorithm, determining a calibration relation among a camera coordinate system of an area array camera, a world coordinate system serving as a reference standard and a pixel coordinate system, so as to determine the internal reference matrix and the external reference matrix;
and obtaining a distortion coefficient through an image distortion model.
Optionally, the splitting area positioning unit 1230 is configured to perform:
obtaining a separation threshold of the picture to be detected through a threshold segmentation model of an otsu algorithm;
dividing the picture to be detected through the separation threshold value to obtain a polar fluid image corresponding to the foreground;
positioning a slit region included in the polar fluid image.
Optionally, the splitting area positioning unit 1230 specifically performs, when performing the positioning of the splitting area included in the polar fluid:
skeletonizing the polar fluid image;
performing contour searching and positioning on the polar fluid image subjected to skeletonization treatment, and determining the mass center of the searched contour point set;
performing straight line fitting on the mass center to obtain a target straight line;
setting a standard width dimension of the polar fluid and taking the standard width dimension as an offset value;
and (3) vertically shifting the target straight line to find the upper and lower boundaries of the polar fluid, thereby obtaining the slitting area.
Optionally, the slitting area detecting unit 1240 is configured to perform:
setting the pixel value of each slitting area to 0 to obtain a burr part;
and determining at least one attribute value of the burr, and taking the attribute value as the burr detection result.
Optionally, the slitting area detecting unit 1240 specifically performs, when performing the determining the at least one attribute value of the burr:
when the attribute value is a burr area value, locating a single burr through profile searching, and carrying out area statistics on the profile to obtain the burr area value;
and when the attribute value is a burr length value, skeletonizing burrs, and performing non-closed length calculation on the skeletonized burr profile to obtain the burr length value.
The pole piece burr detection device based on machine vision provided by the embodiment of the invention can execute the pole piece burr detection method based on machine vision provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example III
Fig. 13 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 13, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM12 and the RAM13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the machine vision-based pole piece burr detection method.
In some embodiments, the machine vision based pole piece spur detection method may be implemented as a computer program, tangibly embodied on a computer readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM12 and/or the communication unit 19. When the computer program is loaded into RAM13 and executed by processor 11, one or more steps of the machine vision based pole piece burr detection method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the machine vision based pole piece burr detection method in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage 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. Alternatively, the computer readable storage medium may be a machine readable signal medium. 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.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. The machine vision-based pole piece burr detection method is characterized by comprising the following steps of:
sha Mcheng images are carried out on the slice to be detected through an area array camera, and a picture to be detected is obtained;
carrying out distortion correction on the picture to be detected;
dividing and cutting the picture to be detected after distortion correction to position the area;
and detecting burrs in each cutting area to obtain a burr detection result.
2. The method according to claim 1, wherein the distortion correcting of the picture to be detected comprises:
determining an internal reference matrix, an external reference matrix and a distortion coefficient of the area array camera;
and carrying out distortion correction on the picture to be detected through the internal reference matrix, the external reference matrix and the distortion coefficient.
3. The method of claim 2, wherein the determining the reference matrix, and the distortion coefficients of the area array camera comprises:
manufacturing a checkerboard with corresponding precision according to the single pixel precision requirement of burr detection;
shooting the checkerboard at least one angle of the area array camera to obtain a checkerboard image;
calibrating through a preset calibration algorithm, determining a calibration relation among a camera coordinate system of an area array camera, a world coordinate system serving as a reference standard and a pixel coordinate system, so as to determine the internal reference matrix and the external reference matrix;
and obtaining a distortion coefficient through an image distortion model.
4. The method according to claim 1, wherein the splitting area positioning the picture to be detected after distortion correction includes:
obtaining a separation threshold of the picture to be detected through a threshold segmentation model of an otsu algorithm;
dividing the picture to be detected through the separation threshold value to obtain a polar fluid image corresponding to the foreground;
positioning a slit region included in the polar fluid image.
5. The method of claim 4, wherein said locating a split area included in said pole fluid comprises:
skeletonizing the polar fluid image;
performing contour searching and positioning on the polar fluid image subjected to skeletonization treatment, and determining the mass center of the searched contour point set;
performing straight line fitting on the mass center to obtain a target straight line;
setting a standard width dimension of the polar fluid and taking the standard width dimension as an offset value;
and (3) vertically shifting the target straight line to find the upper and lower boundaries of the polar fluid, thereby obtaining the slitting area.
6. The method of claim 5, wherein performing the burr detection on each slit area to obtain a burr detection result comprises:
setting the pixel value of each slitting area to 0 to obtain a burr part;
and determining at least one attribute value of the burr, and taking the attribute value as the burr detection result.
7. The method of claim 6, wherein said determining at least one attribute value of the spur comprises:
when the attribute value is a burr area value, locating a single burr through profile searching, and carrying out area statistics on the profile to obtain the burr area value;
and when the attribute value is a burr length value, skeletonizing burrs, and performing non-closed length calculation on the skeletonized burr profile to obtain the burr length value.
8. Pole piece burr detection device based on machine vision, its characterized in that includes:
the image acquisition unit is used for carrying out Sha Mcheng images on the slice to be detected through the area array camera to obtain an image to be detected;
the picture processing unit is used for carrying out distortion correction on the picture to be detected;
the splitting area positioning unit is used for positioning splitting areas of the picture to be detected after distortion correction;
and the cutting area detection unit is used for detecting burrs of each cutting area to obtain a burr detection result.
9. An electronic device, the electronic device comprising:
at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the machine vision-based pole piece flash detection method of any one of claims 1-7.
10. A computer readable storage medium storing computer instructions for causing a processor to implement the machine vision-based pole piece spur detection method of any one of claims 1 to 7 when executed.
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