CN220140534U - Full-automatic living lobster sorting and grading complete equipment based on machine vision - Google Patents
Full-automatic living lobster sorting and grading complete equipment based on machine vision Download PDFInfo
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- 241000238565 lobster Species 0.000 title claims description 22
- 241000238017 Astacoidea Species 0.000 claims abstract description 125
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 claims abstract description 19
- 229910052782 aluminium Inorganic materials 0.000 claims abstract description 19
- 239000000463 material Substances 0.000 claims abstract description 16
- 238000003860 storage Methods 0.000 claims abstract description 14
- 238000007599 discharging Methods 0.000 claims abstract description 8
- 238000012545 processing Methods 0.000 claims description 24
- 238000011282 treatment Methods 0.000 claims description 23
- 241000238557 Decapoda Species 0.000 claims description 16
- 239000004677 Nylon Substances 0.000 claims description 15
- 229920001778 nylon Polymers 0.000 claims description 15
- 230000005540 biological transmission Effects 0.000 claims description 11
- 229910000838 Al alloy Inorganic materials 0.000 claims description 10
- 238000005286 illumination Methods 0.000 claims description 10
- 230000001174 ascending effect Effects 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 claims description 6
- 230000009467 reduction Effects 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 3
- 238000001514 detection method Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000000034 method Methods 0.000 description 47
- 238000001816 cooling Methods 0.000 description 10
- 210000000078 claw Anatomy 0.000 description 8
- 230000009286 beneficial effect Effects 0.000 description 7
- 238000003708 edge detection Methods 0.000 description 6
- 238000004140 cleaning Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 238000000926 separation method Methods 0.000 description 3
- 206010039897 Sedation Diseases 0.000 description 2
- 238000012790 confirmation Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000036280 sedation Effects 0.000 description 2
- 230000001624 sedative effect Effects 0.000 description 2
- 241000238424 Crustacea Species 0.000 description 1
- 241000196324 Embryophyta Species 0.000 description 1
- 241000519995 Stachys sylvatica Species 0.000 description 1
- 210000001015 abdomen Anatomy 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000005587 bubbling Effects 0.000 description 1
- 230000009920 chelation Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000000932 sedative agent Substances 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/80—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in fisheries management
- Y02A40/81—Aquaculture, e.g. of fish
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Abstract
The utility model relates to full-automatic living crayfish sorting and grading complete equipment based on machine vision, which comprises a material separating device and an aluminum profile rack, wherein one side of the material separating device is provided with the aluminum profile rack, the inner top of the aluminum profile rack is provided with an image acquisition module, the inner part of the aluminum profile rack is provided with a sorting conveyor belt, the inner top of the aluminum profile rack is provided with a small sorting robot, the bottom of the small sorting robot is provided with a flexible paw, one side of the sorting conveyor belt is provided with a discharging groove, the driving end of the sorting conveyor belt is provided with a servo motor, and the tail end of the sorting conveyor belt is provided with a temporary storage box.
Description
Technical Field
The utility model relates to the field of sorting and grading production of living crayfish, in particular to full-automatic sorting and grading complete equipment for the living crayfish based on machine vision.
Background
Crayfish is shrimp-like and crustacean is hard. The length of the finished product is about 5.6-11.9 cm, and the overall color comprises red, reddish brown and pink. The back is dark red with pink on both sides and orange or white spots. The crust is black, and a wedge-shaped stripe is arranged on the back of the abdomen. The shrimp larvae are uniformly gray and sometimes have black ripples. Long and narrow chelation.
With the crayfish becoming a delicious food, the demand for the crayfish's yield is higher and higher, and in the crayfish production process, many crayfish manufacturers spend more and more time in processing the crayfish, and because the crayfish's yield is great, the manual processing is obviously less efficient, and on the one hand causes crayfish manufacturers to adopt the machine to sort crayfish according to weight and not satisfy the sorting according to weight, size classification and classification to crayfish, also can not sort fast and sort crayfish, influences crayfish and sorts efficiency.
Disclosure of Invention
The utility model provides full-automatic living lobster sorting and grading complete equipment based on machine vision, which solves the technical problems.
The scheme for solving the technical problems is as follows: full-automatic living body crayfish letter sorting classification complete sets based on machine vision, including feed divider and aluminium alloy frame, feed divider one side is provided with aluminium alloy frame, and image acquisition module is installed at the inside top of aluminium alloy frame, and the internally mounted of aluminium alloy frame has letter sorting conveyer belt, and small-size letter sorting robot is installed at the inside top of aluminium alloy frame, and flexible paw is installed to the bottom of small-size letter sorting robot, and the blown down tank is installed to one side of letter sorting conveyer belt, and servo motor is installed to the drive end of letter sorting conveyer belt, and the tail end of letter sorting conveyer belt is provided with the temporary storage case.
The beneficial effects of the utility model are as follows: the method comprises the steps of sedating, cleaning and feeding, namely cooling, dispersing and region conveying the crayfish, namely judging, grading and sorting devices and methods based on mechanical sensors, receiving position information of the crayfish given by a vision system, and judging and grabbing weight grading of the crayfish according to the mechanical sensors carried by flexible claws; the other is to judge the grading sorting device and method based on the image database, receive the position information and state information of the crayfish given by the vision system, grasp the crayfish meeting the requirements by using the flexible hand claw at the bottom of the small sorting robot, acquire the size of the crayfish body by using the vision system, then clamp and sort the crayfish with different body types by using the flexible hand claw, store the crayfish with different body types in a sorting way, and after the primary sorting is finished, periodically and automatically reject the crayfish in the temporary storage box into the sorting device, reenter the sorting link, and has more obvious weight data, more accurate measurement and effectively improved sorting efficiency of the crayfish.
On the basis of the technical scheme, the utility model can be improved as follows.
Further, feed divider includes pan feeding end frame, ascending frame, discharge end frame, link joint drive arrangement and nylon link joint, and pan feeding end frame, ascending frame, discharge end frame connect gradually, and the discharge end frame end is provided with link joint drive arrangement, and link joint drive arrangement includes driving motor, driving shaft, driven shaft, nylon sprocket and nylon link joint, and driving motor drives driving shaft and driven shaft drive nylon sprocket and drives nylon link joint parallel slip.
The beneficial effects of adopting the further scheme are as follows: the material distributing device adopts a calm cleaning and feeding procedure to realize cooling, dispersing and regional conveying treatment and separating conveying of the crayfish.
Further, the image acquisition module is fixed on the aluminum profile frame, and the industrial camera and the lens are opposite to the front end of the sorting conveyor belt.
Preferably, the image acquisition module comprises a stable light illumination system, an industrial lens, a standard resolution camera, an image acquisition card and a vision processor, wherein the stable light illumination system, the industrial lens, the standard resolution camera and the image acquisition card acquire information to provide real-time instructions for the vision processor, the vision processor processes the information through vision image analysis software, and the vision image analysis software has the functions of image acquisition and display, image preprocessing, image processing, analysis processing results and data display and storage.
The beneficial effects of adopting the further scheme are as follows: the method comprises the steps of firstly cooling, dispersing, carrying out regional conveying treatment, carrying out material separation treatment and carrying out separation conveying on living crayfish, then entering a positioning process based on machine vision identification, receiving position information and state information of the crayfish given by a vision system, transmitting identification, entering an image database judging and grading process, feeding back signals to a vision processor by an image acquisition module, so as to acquire contrast and size of an image of the crayfish, acquiring high-contrast image signals, carrying out hysteresis thresholding treatment when the pixel point is confirmed to be a local maximum value, carrying out edge point confirmation, reserving edge points of a threshold interval, carrying out secondary judgment on the edge points of the threshold, reserving when the edge points are continuous, discarding when the edge points are discontinuous, thus obtaining image data of which one pixel point is processed, and carrying out multiple threshold different treatments on the image in the hysteresis thresholding treatment, so as to reduce noise of the image information and acquire a final edge detection result. The flexible claws at the bottom of the small sorting robot are utilized to grasp and clamp for re-grading treatment, and the crayfish with different sizes are classified and stored. The image acquisition module is fixed on the aluminum profile frame, the industrial camera and the lens are opposite to the front end of the sorting conveyor belt, the influence of the robot and the environmental light on the image acquisition module is reduced, and the recognition of the crayfish is facilitated. The image database judges the grading sorting, receives the positioning and body type signals, uses the flexible paw at the bottom of the small sorting robot to grasp and clip the grading treatment, and grades the crayfish with different body types.
Further, the small sorting robot comprises a base station, an inner balance arm, a lower arm, a transmission shaft, a bottom layer platform and a flexible paw, wherein the base station is arranged on the aluminum profile frame, the inner balance arm and the transmission shaft are arranged on the base station, one end of the lower arm is rotationally connected with the inner balance arm, and the other end of the lower arm is rotationally connected with the bottom layer platform; one end of the transmission shaft is rotationally connected with the base station, and the other end is rotationally connected with the bottom layer platform.
Preferably, the flexible gripper is a flexible gripper, which determines the spatial position of the gripper center by three parallel servo shafts.
The beneficial effects of adopting the further scheme are as follows: the flexible gripper is in a normally open state, when the bottom plane of the gripper is lower than a corresponding threshold value, the gripper tip is closed, and after the gripper clamps the crayfish, the sorting robot lifts the crayfish to the position outside the height threshold value and moves in the horizontal direction.
Preferably, the image acquisition module applies Gaussian blur technology to carry out noise reduction treatment on new image information, and most crayfish and residual limbs can be distinguished by combining the current image recognition technology, wherein the addition of angular point detection in the image acquisition module mainly carries out directional treatment on the heads and the tails of the crayfish.
The beneficial effects of adopting the further scheme are as follows: the accuracy of image acquisition and processing is increased.
Further, the grading sorting method using the full-automatic living lobster sorting grading complete equipment based on machine vision comprises the following steps:
s1, pretreating crayfishes through a material distributing device, cooling, dispersing and carrying out regional conveying treatment on crayfishes to be sorted, and distributing the crayfishes;
s2, after the separating device finishes separating the crayfish, the crayfish is conveyed to a sorting conveyor belt, the separating device receives position and state information of the crayfish read by a vision system, when the crayfish is used as a sorted object to be conveyed on the conveyor belt, the shooting position of the image acquisition module for the crayfish is always positioned in the plane of the conveyor belt, and an illumination system can increase image contrast between the crayfish and the conveyor belt to obtain pixel point information with high contrast;
s3, grabbing the crayfish meeting the requirements by using a flexible gripper at the bottom of the small sorting robot, wherein the flexible gripper is in a normally open state, the gripper tip is closed when the plane of the bottom layer of the gripper is lower than a corresponding threshold value, after the crayfish is clamped by the gripper, the small sorting robot lifts the crayfish to a position outside a height threshold value to do horizontal movement, the flexible gripper is carried with a mechanical sensor to judge the weight of grabbing the crayfish, and the mechanical sensor carried by the flexible gripper judges the grading sorting; the sorting robot lifts the crayfish to the outside of the height threshold value to move in the horizontal direction, sorts and stores the crayfish according to the weight classification, and the crayfish which is not successfully identified in the temporary storage box can be poured into the material distributing device again, periodically and automatically overrules the crayfish, and reenters the sorting link, so that the crayfish is circulated to accurate disposal.
The beneficial effects of adopting the further scheme are as follows: the device adopts different grading sorting line disposal methods respectively, one of the methods is to adopt the position information of the crayfish given by a receiving vision system to the living crayfish, judge the grading sorting device and the method based on a mechanical sensor, judge and grasp the crayfish to store according to the mechanical sensor carried by the hand claw, automatically and periodically reject the crayfish which is not identified and is not successfully identified in the temporary storage box to the starting position of the sorting line, reenter the sorting link, and circulate to the accurate disposal.
Further, the grading sorting method using the full-automatic living lobster sorting grading complete equipment based on machine vision comprises the following steps:
s1, pretreating crayfishes through a material distributing device, cooling, dispersing and carrying out regional conveying treatment on crayfishes to be sorted, and distributing the crayfishes;
s2, after the separating device finishes separating the crayfish, the crayfish is conveyed to a sorting conveyor belt, the separating device receives position and state information of the crayfish read by a vision system, when the crayfish is used as a sorted object to be conveyed on the conveyor belt, the shooting position of the image acquisition module for the crayfish is always positioned in the plane of the conveyor belt, and an illumination system can increase image contrast between the crayfish and the conveyor belt to obtain pixel point information with high contrast;
and S4, when the pixel point is confirmed to be a local maximum value, performing hysteresis thresholding processing to confirm the edge point, reserving the edge point of a threshold interval, performing secondary judgment on the edge point of the threshold, reserving the edge point when the edge point is continuous, discarding the edge point when the edge point is discontinuous, thus obtaining image data of a pixel point after processing, and when the hysteresis thresholding processing is performed, the image is subjected to multiple times of processing with different thresholds, thereby reducing noise of the image information, obtaining a final edge detection result, utilizing a flexible paw at the bottom of the small sorting robot to grasp and re-classify crayfish with different sizes, and performing grading sorting.
The beneficial effects of adopting the further scheme are as follows: the device adopts different grading sorting line treatment methods respectively, the second method is to accept positioning and body type signals, and the grading sorting device and method are judged based on an image database, and flexible claws at the bottom of a small sorting robot are used for grabbing clamping and grading treatment to store crayfish with different body types in a classified manner.
The foregoing description is only an overview of the present utility model, and is intended to provide a better understanding of the present utility model, as it is embodied in the following description, with reference to the preferred embodiments of the present utility model and the accompanying drawings. Specific embodiments of the present utility model are given in detail by the following examples and the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the utility model and are incorporated in and constitute a part of this specification, illustrate embodiments of the utility model and together with the description serve to explain the utility model and do not constitute a limitation on the utility model. In the drawings:
fig. 1 is a schematic flow diagram of a fully automatic living lobster sorting and grading complete equipment based on machine vision according to an embodiment of the present utility model;
fig. 2 is a schematic diagram of a visual disposal principle of a full-automatic living lobster sorting and grading complete equipment based on machine vision according to an embodiment of the present utility model;
fig. 3 is a schematic diagram of an aluminum profile frame structure in a full-automatic living lobster sorting and grading complete equipment based on machine vision according to an embodiment of the present utility model;
fig. 4 is a schematic top view of a small and medium-sized sorting robot in a full-automatic living lobster sorting and grading complete equipment based on machine vision according to an embodiment of the present utility model;
fig. 5 is a schematic perspective view of a small and medium-sized sorting robot in a full-automatic living lobster sorting and grading complete equipment based on machine vision according to an embodiment of the present utility model;
FIG. 6 is a schematic perspective view of a flexible gripper in a fully automated live lobster sorting and grading plant based on machine vision according to one embodiment of the present utility model;
fig. 7 is a schematic view of a flexible paw in a fully-automatic living lobster sorting and grading complete equipment based on machine vision according to an embodiment of the utility model.
In the drawings, the list of components represented by the various numbers is as follows:
1. a material distributing device; 2. an aluminum profile frame; 3. an image acquisition module; 4. sorting the conveyor belt; 5. a small sorting robot; 501. a base station; 502. an inner balance arm; 503. a lower arm; 504. a transmission shaft; 505. a bottom layer platform; 6. a flexible gripper; 7. a discharge chute; 8. a servo motor; 9. temporary storage box.
Detailed Description
The principles and features of the present utility model are described below with reference to fig. 1-7, the examples being provided for illustration only and not for limitation of the scope of the utility model. The utility model is more particularly described by way of example in the following paragraphs with reference to the drawings. Advantages and features of the utility model will become more apparent from the following description and from the claims. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for convenience and clarity in aiding in the description of embodiments of the utility model.
It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or intervening elements may also be present. When a component is considered to be "connected" to another component, it can be directly connected to the other component or intervening components may also be present. When an element is referred to as being "disposed on" another element, it can be directly on the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for illustrative purposes only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this utility model belongs. The terminology used herein in the description of the utility model is for the purpose of describing particular embodiments only and is not intended to be limiting of the utility model. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
As shown in fig. 1, the utility model provides a grading sorting method of a full-automatic living lobster sorting grading complete equipment based on machine vision, which comprises a grading sorting method based on a mechanical sensor judgment and a grading sorting method based on an image database judgment.
The mechanical sensor-based judging, grading and sorting method comprises a sedation cleaning and feeding procedure, a machine vision-based identification and positioning procedure and a mechanical sensor-based judging and grading procedure which are sequentially arranged; the sorting method based on the image database judgment and grading comprises a sedation cleaning feeding procedure, a positioning procedure based on machine vision identification and a grading procedure based on the image database judgment and grading which are sequentially arranged.
According to the mechanical sensor-based classifying and sorting method, through the sedative cleaning and feeding procedures, firstly, cooling, dispersing, regional conveying, material dividing, separating and conveying living crayfish, then, a machine-vision-based identifying and positioning procedure is carried out, position information of crayfish given by a vision system is received, a positioning signal is received, a flexible mechanical gripper is in a normally open state, the space position of a grabbing center is determined by three parallel servo shafts, a gripper tip is closed when the bottom plane of the flexible mechanical gripper is lower than a corresponding threshold value, after crayfish is clamped by a gripper, the mechanical sensor-based classifying and sorting procedure is carried out, and the mechanical sensor carried by the flexible mechanical gripper is used for classifying and sorting; the sorting robot lifts the crayfish to the outside of the height threshold value to move in the horizontal direction, the crayfish is stored in a grading mode according to weight, the crayfish which is not successfully identified in the temporary storage box can be automatically and periodically rejected to the starting position of the sorting line, the crayfish reenters the sorting link, and the crayfish is circulated to accurate disposal.
According to the image database judgment grading sorting method, firstly, cooling, dispersing, regional conveying, material separation and conveying are carried out on living crayfish, then, the working procedure is carried out based on machine vision recognition and positioning, position information and state information of the crayfish given by a vision system are received, the working procedure is carried out for judging and grading the crayfish through the image database, an image acquisition module feeds back signals to a vision processor, so that contrast and size of an image of the crayfish are obtained, a high-contrast image signal is obtained, when the pixel point is confirmed to be a local maximum value, hysteresis thresholding is carried out for edge point confirmation, edge points of a threshold interval are reserved, then, secondary judgment is carried out on the edge points of the threshold, when the edge points are continuous, the edge points are reserved, and then, the image is discarded when the edge points are discontinuous, so that image data of one pixel point after being processed are obtained, when hysteresis thresholding is carried out, the image is processed through multiple times of different threshold values, so that noise of the image information is reduced, and a final edge detection result is obtained. The flexible claws at the bottom of the small sorting robot are utilized to grasp and clamp for re-grading treatment, and the crayfish with different sizes are graded and sorted.
Preferably, in one embodiment of the utility model, the robot vision-based fully automated live lobster sorting and grading kit is shown in FIG. 3.
Specifically, as shown in fig. 3 and 4, full-automatic living crayfish sorting and grading complete equipment based on machine vision comprises a material distributing device 1 and an aluminum profile frame 2, wherein one side of the material distributing device 1 is provided with the aluminum profile frame 2, an image acquisition module 3 is installed at the inner top of the aluminum profile frame 2, a sorting conveyor belt 4 is installed at the inner top of the aluminum profile frame 2, a small sorting robot 5 is installed at the inner top of the aluminum profile frame 2, a flexible paw 6 is installed at the bottom of the small sorting robot 5, a discharging chute 7 is installed at one side of the sorting conveyor belt 4, a servo motor 8 is installed at the driving end of the sorting conveyor belt 4, and a temporary storage box 9 is arranged at the tail end of the sorting conveyor belt 4.
Specifically, as shown in fig. 3, the material distributing device 1 comprises a feeding end frame, an ascending frame, a discharging end frame, a chain plate driving device and a nylon chain plate, wherein the feeding end frame, the ascending frame and the discharging end frame are sequentially connected, the chain plate driving device is arranged at the tail end of the discharging end frame and comprises a driving motor, a driving shaft, a driven shaft, a nylon chain wheel and the nylon chain plate, and the driving motor drives the driving shaft and the driven shaft to drive the nylon chain wheel to drive the nylon chain plate to slide in parallel. The crayfish pretreatment is carried out through the separating device 1, the crayfish to be sorted is subjected to cooling, dispersing and regional conveying treatment, and the crayfish is subjected to separating treatment.
Specifically, as shown in fig. 2, the image acquisition module 3 is fixed on the aluminum profile frame 2, the industrial camera and the lens are opposite to the front end of the sorting conveyor belt 4, the influence of the robot and the ambient light on the image acquisition module 3 is reduced, and the recognition of the crayfish is facilitated.
Specifically, as shown in fig. 3, the image acquisition module 3 includes a stable light illumination system, an industrial lens, a standard resolution camera, an image acquisition card, and a vision processor, where the stable light illumination system, the industrial lens, the standard resolution camera, and the image acquisition card acquire information to provide real-time instructions for the vision processor, and the vision processor processes the information through a vision image analysis software, and the vision image analysis software has functions of image acquisition and display, image preprocessing, image processing, analysis processing results, and data display and storage. After the focal length, the target height, the image height, the center point, the distortion and Jing Kuan are set, the industrial camera can start to collect pixel point information on the conveying belt, when the pixel point is confirmed to be a local maximum value, hysteresis thresholding is conducted to confirm the edge point, the edge point of a threshold value interval is reserved, secondary judgment is conducted on the edge point of the threshold value, when the edge point is continuous, the edge point is reserved, the image is discarded when the edge point is discontinuous, and therefore image data of a pixel point after processing is obtained, when hysteresis thresholding is conducted, the image is processed with different thresholds for a plurality of times, noise of the image information is reduced, and a final edge detection result is obtained.
It should be noted that: the industrial camera can start to collect the pixel point information on the conveying belt after the industrial lens is set with the focal length, the target height, the image height, the center point, the distortion and Jing Kuan.
The plurality of industrial cameras are connected with a capture card, process a plurality of transmission signals, further improve contrast and gray level aiming at the images of the crayfish on the conveyor belt, and realize noise reduction processing on new image information by using a Gaussian blur technology.
And obtaining the image gradient through a sobel operator. And detecting each pixel point and surrounding pixel points by using the obtained gradient, and carrying out bubbling sequencing on each pixel point to confirm whether the pixel point is a local maximum value in the local pixel points. If not the local maximum, the pixel value is set to zero (i.e., black).
When the pixel is determined to be a local maximum, hysteresis thresholding is performed to determine an edge point. And reserving edge points of a threshold interval, then performing secondary judgment on the edge points of the threshold, reserving when the edge points are continuous, discarding when the edge points are discontinuous, so as to obtain processed image data of one pixel, and performing different threshold processing on the image for a plurality of times when the hysteresis thresholding is performed, thereby reducing noise of the image information and obtaining a final edge detection result.
Specifically, as shown in fig. 5, the small sorting robot 5 includes a base 501, an inner balance arm 502, a lower arm 503, a transmission shaft 504, a bottom layer platform 505 and a flexible gripper 6, the base 501 is mounted on the aluminum profile frame 2, the base 501 is provided with the inner balance arm 502 and the transmission shaft 504, one end of the lower arm 503 is rotationally connected with the inner balance arm 502, and the other end is rotationally connected with the bottom layer platform 505; one end of the transmission shaft 504 is rotatably connected with the base 501, and the other end is rotatably connected with the bottom layer platform 505.
Specifically, as shown in fig. 5 and 6, the flexible gripper 6 is a flexible gripper, the flexible gripper 6 determines the spatial position of the center of the gripper by three parallel servo shafts, the flexible gripper 6 is in a normally open state, when the bottom level of the gripper is lower than a corresponding threshold value, the gripper tip is closed, and when the gripper grips the crayfish, the sorting robot lifts the crayfish to a position outside the height threshold value for movement in the horizontal direction.
Specifically, as shown in fig. 3, the image acquisition module 3 applies a gaussian blur technique to perform noise reduction processing on new image information, and combines with the existing image recognition technique to distinguish most crayfish from residual limbs, so as to improve the working efficiency of the manipulator, wherein the addition of the corner point detection in the image acquisition module 3 mainly performs directional processing on the head and the tail of the crayfish, and after corresponding image data is obtained through image processing, the image data can be applied to a plane coordinate axis, and the position of the center point of the manipulator and the clamping angle of the manipulator are confirmed through the head and the tail positioning data, so that the middle of the crayfish can be clamped.
The specific working principle and the using method of the utility model are as follows:
as shown in fig. 1-7, when using a fully automated living lobster sorting and grading kit based on machine vision, two grading sort line methods are preferred:
one method is based on mechanical sensor decision sorting:
s1, pretreating crayfishes by a distributing device 1, cooling, dispersing and carrying out regional conveying treatment on crayfishes to be sorted, and distributing the crayfishes;
s2, after the separating device 1 finishes separating the crayfish, the crayfish is conveyed to the sorting conveyor belt 4, the separating device 1 receives position and state information of the crayfish read by a vision system, when the crayfish is used as a sorted object to be conveyed on the conveyor belt, the shooting position of the image acquisition module 3 for the crayfish is always positioned in the plane of the conveyor belt, and an illumination system can increase image contrast between the crayfish and the conveyor belt to obtain pixel point information with high contrast;
s3, grabbing the crayfish meeting the requirements by using a flexible gripper 6 at the bottom of the small sorting robot 5, enabling the flexible gripper 6 to be in a normally open state, enabling the gripper tip to be closed when the bottom plane of the gripper is lower than a corresponding threshold value, lifting the crayfish to be outside a height threshold value by the small sorting robot 5 to move horizontally after the crayfish is clamped by the gripper, carrying a mechanical sensor on the flexible gripper 6 to judge the weight of grabbing the crayfish, setting the sorting range to be 10-19g, 20-29g, 30-39g, 40-49g and more than 50g (including 50 g), and disposing all the crayfish above 50g, wherein the mechanical sensor carried by the flexible gripper judges the grading sorting; the sorting robot lifts the crayfish to the outside of the height threshold value to move in the horizontal direction, sorts and stores the crayfish according to the weight classification, the crayfish which is not successfully identified in the temporary storage box 9 can be poured into the material distributing device again, the crayfish is automatically and periodically rejected to the material distributing device, the crayfish enters the sorting link again, and the crayfish is circulated to the precise disposal.
The device adopts different grading sorting line disposal methods respectively, one of the methods is to adopt the method for receiving the position information of the lobsters given by the vision system for the living lobsters, and judging grading sorting complete equipment based on the mechanical sensor, judging the weight grading of the grabbing lobsters according to the mechanical sensor carried by the paw, automatically and periodically rejecting the lobsters which are not successfully identified in the temporary storage box to the starting position of the sorting line, reentering the sorting link, and circulating to accurate disposal.
Another approach is to determine hierarchical sorting based on an image database:
s1, pretreating crayfishes by a distributing device 1, cooling, dispersing and carrying out regional conveying treatment on crayfishes to be sorted, and distributing the crayfishes;
s2, after the separating device 1 finishes separating the crayfish, the crayfish is conveyed to the sorting conveyor belt 4, the separating device 1 receives position and state information of the crayfish read by a vision system, when the crayfish is used as a sorted object to be conveyed on the conveyor belt, the shooting position of the image acquisition module 3 for the crayfish is always positioned in the plane of the conveyor belt, and an illumination system can increase image contrast between the crayfish and the conveyor belt to obtain pixel point information with high contrast;
s4, when the pixel point is confirmed to be a local maximum value, performing hysteresis thresholding processing to confirm the edge point, reserving the edge point of a threshold interval, performing secondary judgment on the edge point of the threshold, reserving the edge point of the threshold when the edge point is continuous, discarding the edge point of the threshold, so as to obtain image data of one pixel point after processing, performing multiple times of different threshold processing on the image during hysteresis thresholding processing, reducing noise of the image information, obtaining a final edge detection result, grabbing and re-grading the small lobsters with different sizes by using a flexible paw 6 at the bottom of a small sorting robot 5, classifying and storing the small lobsters with different sizes, capturing and counting the small lobsters with the pixel point, wherein the number of the small lobsters with the larger size is larger than that of the small lobsters with the small size, and discarding the small pixels of the small lobsters with the small size, and counting the small lobsters with different grades in the image database after scanning, counting the small lobsters with different sizes, and the small number of the small lobsters in the image database, and re-entering a sorting link after the first sorting is finished, so that the sorting link is circulated to the precise disposal.
The device adopts different grading sorting line treatment methods respectively, the second method is to accept positioning and body type signals, and the grading sorting device and method are judged based on an image database, and flexible claws at the bottom of a small sorting robot are used for grabbing clamping and grading treatment to store crayfish with different body types in a classified manner.
The above description is only of the preferred embodiments of the present utility model, and is not intended to limit the present utility model in any way; those skilled in the art will readily appreciate that the present utility model may be implemented as shown in the drawings and described above; however, those skilled in the art will appreciate that many modifications, adaptations, and variations of the present utility model are possible in light of the above teachings without departing from the scope of the utility model; meanwhile, any equivalent changes, modifications and evolution of the above embodiments according to the essential technology of the present utility model still fall within the scope of the present utility model.
Claims (8)
1. The utility model provides a hierarchical complete sets of full-automatic live body crayfish letter sorting based on machine vision, its characterized in that, including feed divider (1) and aluminium alloy frame (2), feed divider (1) one side is provided with aluminium alloy frame (2), image acquisition module (3) are installed at the inside top of aluminium alloy frame (2), sorting conveyer belt (4) are installed at the internally mounted of aluminium alloy frame (2), small-size letter sorting robot (5) are installed at the inside top of aluminium alloy frame (2), flexible paw (6) are installed to the bottom of small-size letter sorting robot (5), blown down tank (7) are installed to one side of letter sorting conveyer belt (4), servo motor (8) are installed to the drive end of letter sorting conveyer belt (4), the tail end of letter sorting conveyer belt (4) is provided with temporary storage case (9).
2. The full-automatic living lobster sorting and grading complete equipment based on machine vision according to claim 1, wherein the material separating device (1) comprises a feeding end frame, an ascending frame, a discharging end frame, a chain plate driving device and a nylon chain plate, the feeding end frame, the ascending frame and the discharging end frame are sequentially connected, the chain plate driving device is arranged at the tail end of the discharging end frame and comprises a driving motor, a driving shaft, a driven shaft, a nylon chain wheel and the nylon chain plate, and the driving motor drives the driving shaft and the driven shaft to drive the nylon chain wheel to drive the nylon chain plate to slide in parallel.
3. The full-automatic living lobster sorting and grading complete equipment based on machine vision according to claim 1, wherein the image acquisition module (3) is fixed on the aluminum profile frame (2), and the industrial camera and the lens are opposite to the front end of the sorting conveyor belt (4).
4. The full-automatic living lobster sorting and grading complete equipment based on machine vision according to claim 1, wherein the image acquisition module (3) comprises a stable light illumination system, an industrial lens, a standard resolution camera, an image acquisition card and a vision processor, the stable light illumination system, the industrial lens, the standard resolution camera and the image acquisition card acquire information to provide real-time instructions for the vision processor, the vision processor performs processing through vision image analysis software, and the vision image analysis software has functions of image acquisition and display, image preprocessing, image processing, analysis processing results and data display and storage.
5. The full-automatic living lobster sorting and grading complete equipment based on machine vision according to claim 1, wherein the small sorting robot (5) comprises a base (501), an inner balance arm (502), a lower arm (503), a transmission shaft (504), a bottom layer platform (505) and a flexible paw (6), the base (501) is mounted on the aluminum profile frame (2), the base (501) is provided with the inner balance arm (502) and the transmission shaft (504), one end of the lower arm (503) is rotationally connected with the inner balance arm (502), and the other end is rotationally connected with the bottom layer platform (505); one end of the transmission shaft (504) is rotationally connected with the base platform (501), and the other end is rotationally connected with the bottom layer platform (505).
6. The full-automatic living lobster sorting and grading complete equipment based on machine vision according to claim 1, wherein the flexible gripper (6) is a flexible gripper, and the flexible gripper (6) determines the spatial position of the gripper center by three parallel servo shafts.
7. The full-automatic living lobster sorting and grading complete equipment based on machine vision according to claim 1, wherein the image acquisition module (3) applies Gaussian blur technology to perform noise reduction treatment on new image information, most of the lobsters and the residual limbs can be distinguished by combining the existing image recognition technology, and the addition of corner point detection in the image acquisition module (3) mainly performs directional treatment on the heads and the tails of the lobsters.
8. The full-automatic living lobster sorting and grading complete equipment based on machine vision according to claim 1, wherein the flexible gripper (6) is a flexible gripper, the flexible gripper (6) comprises three servo shafts connected in parallel, and the flexible gripper (6) is in a normally open state.
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