CN111685356A - Tobacco leaf grading and sorting system based on image processing - Google Patents
Tobacco leaf grading and sorting system based on image processing Download PDFInfo
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- CN111685356A CN111685356A CN202010463716.0A CN202010463716A CN111685356A CN 111685356 A CN111685356 A CN 111685356A CN 202010463716 A CN202010463716 A CN 202010463716A CN 111685356 A CN111685356 A CN 111685356A
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- tobacco leaf
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- 235000002637 Nicotiana tabacum Nutrition 0.000 title claims abstract description 50
- 244000061176 Nicotiana tabacum Species 0.000 title 1
- 241000208125 Nicotiana Species 0.000 claims abstract description 49
- 238000013500 data storage Methods 0.000 claims abstract description 29
- 239000000523 sample Substances 0.000 claims abstract description 28
- 238000013528 artificial neural network Methods 0.000 claims abstract description 7
- 230000005540 biological transmission Effects 0.000 claims description 34
- 238000006243 chemical reaction Methods 0.000 claims description 21
- 239000000428 dust Substances 0.000 claims description 18
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims description 12
- 229910052744 lithium Inorganic materials 0.000 claims description 12
- 239000000084 colloidal system Substances 0.000 claims description 8
- 229910021420 polycrystalline silicon Inorganic materials 0.000 claims description 8
- 239000005341 toughened glass Substances 0.000 claims description 3
- 238000004146 energy storage Methods 0.000 claims 1
- 238000007726 management method Methods 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 3
- 230000006399 behavior Effects 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 239000002994 raw material Substances 0.000 description 3
- 235000019505 tobacco product Nutrition 0.000 description 3
- 238000000034 method Methods 0.000 description 2
- 230000000391 smoking effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000007795 chemical reaction product Substances 0.000 description 1
- 230000001055 chewing effect Effects 0.000 description 1
- 235000019506 cigar Nutrition 0.000 description 1
- 235000019504 cigarettes Nutrition 0.000 description 1
- 238000012272 crop production Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000006748 scratching Methods 0.000 description 1
- 230000002393 scratching effect Effects 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A24—TOBACCO; CIGARS; CIGARETTES; SIMULATED SMOKING DEVICES; SMOKERS' REQUISITES
- A24B—MANUFACTURE OR PREPARATION OF TOBACCO FOR SMOKING OR CHEWING; TOBACCO; SNUFF
- A24B1/00—Preparation of tobacco on the plantation
- A24B1/04—Sifting, sorting, cleaning or removing impurities from tobacco
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Agronomy & Crop Science (AREA)
- Manufacture Of Tobacco Products (AREA)
Abstract
The invention relates to the field of image processing, and discloses a tobacco leaf grading and sorting system based on image processing, which comprises a data processing box and a box module, wherein the box module is positioned right above the data processing box, a radar and a picture recognition probe are sequentially fixed on the front surface in the box module from left to right, the front end of the radar and the front end of the picture recognition probe are both positioned on the front surface of the box module, an electric control chip loading module is fixed on the lower surface in the box module, and a special data storage chip for picture recognition is fixed on the upper surface of the electric control chip loading module; technical support is provided for tobacco leaf picture identification by arranging a radar, a picture identification probe and a special data storage chip for picture identification, wherein a neural network is arranged in the special data storage chip for picture identification.
Description
Technical Field
The invention relates to the field of image processing, in particular to a tobacco leaf grading and sorting system based on image processing.
Background
Tobacco production differs from other crop production in many ways, the end product of tobacco production is tobacco leaf, which is a specific raw material for tobacco products. Smoking articles are known in a wide variety, such as cigarettes, cigars, pipes, chewing tobacco, snuff. Different tobacco products have different requirements on tobacco raw materials. How to adapt to the requirements of the tobacco products on the tobacco leaf raw materials is the grading task. In other words, classification is the provision of desirable materials for various smoking articles. Many sorting operations currently have a relatively high error rate and therefore do not meet the actual production requirements.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a tobacco leaf grading and sorting system based on image processing.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides a tobacco leaf classification letter sorting system based on image processing, includes data processing case and quick-witted box module, quick-witted box module is located directly over the data processing case, just the inside front surface of quick-witted box module from left to right is fixed with radar and picture identification probe in proper order, the front end of radar with the front end of picture identification probe all is located the front surface of quick-witted box module, the inside lower fixed surface of quick-witted box module has automatically controlled chip to load the module, the last fixed surface of automatically controlled chip loading module has the special data storage chip of picture identification, be equipped with many first neural networks in the inside of the special data storage chip of picture identification, the upper surface that automatically controlled chip loaded the module is located the right side of the special data storage chip of picture identification is fixed with wireless image transmission module, just the upper surface of automatically controlled chip loading module is located the special data storage chip of picture identification with the place ahead of wireless image transmission module is fixed with direct current The radar, the image recognition probe and the direct current power supply conversion piece are electrically connected with the special data storage chip for image recognition, the direct current power supply conversion piece is electrically connected with the wireless image transmission module, the center of the upper surface of the data processing box is rotatably connected with a workpiece module, the upper surface of the workpiece module is fixedly connected with the center of the lower surface of the case module, a servo motor C is fixed at the center of the upper surface inside the data processing box, the top end of an output shaft of the servo motor C is fixedly connected with the center of the lower surface of the workpiece module, speed reduction transmission pieces are fixed at the bottoms of two sides of the inner surface of the data processing box, driven transmission wheels are symmetrically and rotatably connected with the front and the back inside of the speed reduction transmission pieces, a main wheel disc drive is rotatably connected between the two driven transmission wheels, and the two driven transmission wheels are meshed with the main drive wheel disc, one side of speed reduction driving spare is fixed with servo motor B, servo motor B's output shaft one end with the middle part fixed connection of main drive rim plate, two the middle part of passive transfer wheel all is fixed with the drive wheel through the connecting axle, the drive wheel is located the outside of data processing case, the inside lower surface of data processing case is fixed with the lithium cell.
Preferably, a colloid belt is fixed on the outer side walls of the two driving wheels which are positioned on the same side, and the outer side walls of the colloid belt are subjected to rough treatment.
Preferably, light-transmitting plates are fixed on the front surfaces of the radar and the image recognition probe, and the light-transmitting plates are made of tempered glass with good transparency.
Preferably, a polycrystalline silicon solar sailboard is fixed on the upper surface of the case module, a photovoltaic power conversion piece is fixed on the upper surface of the lithium battery, the output end of the polycrystalline silicon solar sailboard is electrically connected with the input end of the photovoltaic power conversion piece, and the output end of the photovoltaic power conversion piece is electrically connected with the input end of the lithium battery.
Preferably, the front surface of the case module is rotationally connected with dust removing pieces in a left-right symmetrical manner, the two dust removing pieces are respectively located above the radar and the picture recognition probe, servo motors A are symmetrically fixed on the front surface of the inside of the case module in a left-right symmetrical manner, and opposite sides of the two dust removing pieces are respectively fixedly connected with output ends of the two servo motors A.
Preferably, the rear surface of the dust removing piece is a soft rubber sheet.
(III) advantageous effects
The invention provides a tobacco leaf grading and sorting system based on image processing, which has the following beneficial effects:
according to the invention, the radar, the picture recognition probe and the picture recognition special data storage chip internally provided with the polynary neural network are arranged to automatically control the tobacco pile tobacco leaf characteristic point positions, so that the quantity of the tobacco leaf characteristic point positions, whether the tobacco leaf characteristic point position behaviors are normal or not and whether the tobacco pile environment is appropriate or not can be picture-recognized, data can be uploaded to a background for professional analysis through the wireless image transmission module while automatic monitoring and judgment are carried out, and the picture recognition efficiency is improved.
Drawings
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a schematic side view of the present invention;
FIG. 3 is a schematic top view of the internal structure of the case module according to the present invention;
FIG. 4 is a schematic diagram of the internal structure of the data processing box of the present invention;
FIG. 5 is a side view of the internal structure of the speed reducing transmission of the present invention;
fig. 6 is a schematic flow chart of the present invention.
In the figure: 1. a colloid belt; 2. a data processing box; 3. a workpiece module; 4. a case module; 5. a radar; 6. a polycrystalline silicon solar sailboard; 7. a dust removal member; 8. a light-transmitting plate; 9. a picture recognition probe; 10. a drive wheel; 11. an electronic control chip loading module; 12. a data storage chip special for picture identification; 13. a wireless image transmission module; 14. a DC power conversion element; 15. a servo motor A; 16. a reduction drive member; 17. a servo motor B; 18. a servo motor C; 19. a photovoltaic power conversion element; 20. a lithium battery; 21. a passive transfer wheel; 22. the main drive wheel disc.
Detailed Description
As shown in fig. 1 to 6, the present invention provides a technical solution: a tobacco leaf grading sorting system based on image processing comprises a data processing box 2 and a box module 4, wherein the box module 4 is positioned right above the data processing box 2, the front surface in the box module 4 is sequentially fixed with a radar 5 and a picture recognition probe 9 from left to right, the front end of the radar 5 and the front end of the picture recognition probe 9 are both positioned on the front surface of the box module 4, the lower surface in the box module 4 is fixed with an electric control chip loading module 11, the upper surface of the electric control chip loading module 11 is fixed with a picture recognition special data storage chip 12, a polynary neural network is arranged in the picture recognition special data storage chip 12, the upper surface of the electric control chip loading module 11 is positioned on the right side of the picture recognition special data storage chip 12 and is fixed with a wireless image transmission module 13, and the upper surface of the electric control chip loading module 11 is positioned in front of the picture recognition special data storage chip 12 and the wireless image transmission module 13 and is fixed with a direct current power supply conversion piece 14, the radar 5, the picture recognition probe 9 and the direct current power supply conversion piece 14 are electrically connected with a special data storage chip 12 for picture recognition, the direct current power supply conversion piece 14 is electrically connected with a wireless image transmission module 13, the center of the upper surface of the data processing box 2 is rotatably connected with a workpiece module 3, the upper surface of the workpiece module 3 is fixedly connected with the center of the lower surface of the box module 4, the center of the inner upper surface of the data processing box 2 is fixedly provided with a servo motor C18, the top end of an output shaft of the servo motor C18 is fixedly connected with the center of the lower surface of the workpiece module 3, the bottoms of two sides of the inner surface of the data processing box 2 are respectively fixedly provided with a speed reduction transmission piece 16, the inner part of the speed reduction transmission piece 16 is symmetrically and rotatably connected with driven transmission wheels 21 in front and back, a main driving wheel disc 22 is rotatably connected between the two driven transmission wheels 21, a servo motor B17 is fixed on one side of the speed reducing transmission piece 16, one end of an output shaft of a servo motor B17 is fixedly connected with the middle part of the main driving wheel disc 22, driving wheels 10 are fixed on the middle parts of the two driven transmission wheels 21 through connecting shafts, the driving wheels 10 are positioned on the outer side of the data processing box 2, a lithium battery 20 is fixed on the lower surface inside the data processing box 2, when the data processing device is used, the quantity and behaviors of the characteristic points of tobacco leaves inside a tobacco pile can be shot through the picture recognition probe 9 and the radar 5 and are processed by a picture recognition special data storage chip 12 with a built-in polynary neural network, so that the characteristic points of the tobacco leaves in the tobacco pile can be automatically controlled, and meanwhile, the picture recognition special data storage chip 12 can convert the data shot by the picture recognition probe 9 and the radar 5 into analog signals through the direct-, the tobacco leaf characteristic point management and control device is further transmitted to a background through the wireless image transmission module 13, analysis is provided for professionals, the image recognition efficiency is improved, and when the tobacco leaf management and control device is used, the servo motor C18 can be controlled to drive the workpiece module 3 to rotate through the image recognition special data storage chip 12, the box module 4 can be driven to rotate, tobacco leaf characteristic point management and control in a tobacco pile can be carried out on a larger scale, two servo motors B17 can be controlled to drive the driving wheel 10 to rotate through the image recognition special data storage chip 12, the position of the tobacco leaf management and control device can be changed, management and control of tobacco leaf characteristic point positions in the tobacco pile in different positions are facilitated, the situation that a traditional image recognition mode is mainly based on personnel supervision is avoided, personnel fatigue exists, the image recognition efficiency is low, and image recognition is not timely is achieved.
Further, the outer side walls of the two driving wheels 10 positioned on the same side are fixed with the colloid belt 1, the outer side walls of the colloid belt 1 are subjected to rough treatment, the contact area between the driving wheels 10 and the ground can be increased through the colloid belt 1, the pressure between the driving wheels 10 and the ground is reduced, the situation that the device is sunken can be avoided, and meanwhile the device can be better moved.
Further, the front surfaces of the radar 5 and the picture recognition probe 9 are both fixed with light-transmitting plates 8, the light-transmitting plates 8 are made of tempered glass with good transparency, the light-transmitting plates 8 can protect the radar 5 and the picture recognition probe 9, the radar 5 and the picture recognition probe 9 are prevented from being damaged, and meanwhile shooting of the radar 5 and the picture recognition probe 9 is not influenced.
Further, the last fixed surface of machine box module 4 has polycrystalline silicon solar array sail 6, the last fixed surface of lithium cell 20 has photovoltaic power supply conversion piece 19, polycrystalline silicon solar array sail 6's output and photovoltaic power supply conversion piece 19's input electric connection, photovoltaic power supply conversion piece 19's output and lithium cell 20's input electric connection, when using, can receive solar energy through polycrystalline silicon solar array sail 6, and can be the electric energy with receiving solar energy conversion through photovoltaic dress changer 19, and store in lithium cell 20, rethread lithium cell 20 supplies power for the electrical part in the device, make the use that the device can be more nimble.
Furthermore, the left and right symmetrical rotation of the front surface of the case module 4 is connected with the dust removing pieces 7, the two dust removing pieces 7 are respectively positioned above the radar 5 and the picture recognition probe 9, the servo motors A15 are symmetrically fixed on the left and right of the front surface inside the case module 4, the opposite sides of the two dust removing pieces 7 are respectively fixedly connected with the output ends of the two servo motors A15, and in the using process, when dust stains are adhered to the light transmission plate 8, the two servo motors A15 can be controlled by the picture recognition special data storage chip 12 to respectively drive the two dust removing pieces 7 to rotate between 0 degrees and 90 degrees, so that the dust and stains on the light transmission plate 8 can be cleaned, the situation that the device cannot accurately judge the characteristic point of the tobacco leaves is avoided, and the situation that the device recognizes the picture of the characteristic point of the tobacco leaves is reduced.
Furthermore, the rear surface of the dust removing part 7 is made of soft rubber sheets, so that the dust removing part 7 is prevented from scratching the light-transmitting plate 8, the radar 5 and the picture recognition probe 9 cannot well shoot the tobacco leaf characteristic point positions in the tobacco pile, and the condition of the device for recognizing the tobacco leaf characteristic point position pictures is reduced.
In conclusion, the working process of the invention is as follows: when the device is used, the quantity and behavior of the tobacco leaf characteristic points in the tobacco pile can be shot through the picture recognition probe 9 and the radar 5 and are processed by the picture recognition special data storage chip 12 with the built-in polynary neural network, so that the tobacco leaf characteristic points in the tobacco pile can be automatically controlled, meanwhile, the picture recognition special data storage chip 12 can convert the data shot by the picture recognition probe 9 and the radar 5 into analog signals through the direct-current power supply conversion piece 14 and then transmit the analog signals to the background through the wireless picture transmission module 13 for analysis of professionals, the picture recognition efficiency is improved, and when the device is used, the servo motor C18 can be controlled through the picture recognition special data storage chip 12 to drive the workpiece module 3 to rotate, so that the box module 4 can be driven to rotate, and the tobacco leaf characteristic points in the tobacco pile can be controlled in a wider range, and the special data storage chip 12 for picture identification can control the two servo motors B17 to drive the driving wheels 10 to rotate, so that the device can change the position, and the tobacco leaf characteristic point positions in the tobacco pile can be conveniently controlled at different positions.
Claims (6)
1. The utility model provides a tobacco leaf grading letter sorting system based on image processing, includes data processing case (2) and machine box module (4), its characterized in that: the machine box module (4) is positioned right above the data processing box (2), a radar (5) and a picture recognition probe (9) are sequentially fixed on the front surface in the machine box module (4) from left to right, the front end of the radar (5) and the front end of the picture recognition probe (9) are both positioned on the front surface of the machine box module (4), an electric control chip loading module (11) is fixed on the lower surface in the machine box module (4), a special data storage chip (12) for picture recognition is fixed on the upper surface of the electric control chip loading module (11), a polynary neural network is arranged in the special data storage chip (12) for picture recognition, a wireless image transmission module (13) is fixed on the right side of the special data storage chip (12) for picture recognition on the upper surface of the electric control chip loading module (11), and the upper surface of the electric control chip loading module (11) is positioned in front of the special data storage chip (12) for picture recognition and the wireless image transmission module (13) and is fixedly provided with a direct current power supply conversion piece (14), the radar (5), the picture recognition probe (9) and the direct current power supply conversion piece (14) are electrically connected with the special data storage chip (12) for picture recognition, the direct current power supply conversion piece (14) is electrically connected with the wireless image transmission module (13), the upper surface center of the data processing box (2) is rotatably connected with a workpiece module (3), the upper surface of the workpiece module (3) is fixedly connected with the lower surface center of the box module (4), the inner upper surface center of the data processing box (2) is fixedly provided with a servo motor C (18), the top end of an output shaft of the servo motor C (18) is fixedly connected with the lower surface center of the workpiece module (3), the bottom parts of the two sides of the inner surface of the data processing box (2) are respectively fixed with a speed reducing transmission part (16), the interior of the speed reducing transmission piece (16) is symmetrically and rotationally connected with driven transmission wheels (21) in a front-back manner, a main driving wheel disc (22) is rotationally connected between the two driven transmission wheels (21), and the two driven transmission wheels (21) are meshed and connected with the main driving wheel disc (22), a servo motor B (17) is fixed on one side of the speed reducing transmission part (16), one end of an output shaft of the servo motor B (17) is fixedly connected with the middle part of the main driving wheel disc (22), driving wheels (10) are fixed on the middle parts of the two driven transmission wheels (21) through connecting shafts, the driving wheel (10) is located on the outer side of the data processing box (2), and a lithium battery (20) is fixed on the lower surface of the inner portion of the data processing box (2).
2. The tobacco leaf grading and sorting system based on image processing according to claim 1, characterized in that: the outer side walls of the two driving wheels (10) which are positioned on the same side are fixedly provided with a colloid belt (1), and the outer side wall of the colloid belt (1) is subjected to rough treatment.
3. The tobacco leaf grading and sorting system based on image processing according to claim 1, characterized in that: light-transmitting plates (8) are fixed on the front surfaces of the radar (5) and the picture recognition probe (9), and the light-transmitting plates (8) are made of tempered glass with good transparency.
4. The tobacco leaf grading and sorting system based on image processing according to claim 1, characterized in that: the solar energy storage battery box is characterized in that a polycrystalline silicon solar sailboard (6) is fixed on the upper surface of the box module (4), a photovoltaic power supply conversion piece (19) is fixed on the upper surface of the lithium battery (20), the output end of the polycrystalline silicon solar sailboard (6) is electrically connected with the input end of the photovoltaic power supply conversion piece (19), and the output end of the photovoltaic power supply conversion piece (19) is electrically connected with the input end of the lithium battery (20).
5. The tobacco leaf grading and sorting system based on image processing according to claim 1, characterized in that: the left and right symmetrical dust removing device is characterized in that the left and right of the front surface of the case module (4) are rotatably connected with dust removing pieces (7), the two dust removing pieces (7) are respectively located above the radar (5) and the picture recognition probe (9), servo motors A (15) are symmetrically fixed on the left and right of the front surface inside the case module (4), and the opposite sides of the two dust removing pieces (7) are respectively fixedly connected with the output ends of the two servo motors A (15).
6. The tobacco leaf grading and sorting system based on image processing according to claim 1, characterized in that: the rear surface of the dust removing piece (7) is a soft rubber sheet.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010463716.0A CN111685356A (en) | 2020-05-27 | 2020-05-27 | Tobacco leaf grading and sorting system based on image processing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010463716.0A CN111685356A (en) | 2020-05-27 | 2020-05-27 | Tobacco leaf grading and sorting system based on image processing |
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| Publication Number | Publication Date |
|---|---|
| CN111685356A true CN111685356A (en) | 2020-09-22 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010463716.0A Pending CN111685356A (en) | 2020-05-27 | 2020-05-27 | Tobacco leaf grading and sorting system based on image processing |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112954126A (en) * | 2021-01-25 | 2021-06-11 | 安徽农业大学 | Tracking and scanning system capable of monitoring growth and sale of organic products in real time |
| CN114128915A (en) * | 2021-11-30 | 2022-03-04 | 云南省烟草农业科学研究院 | Automatic grading method for fresh cigar leaves based on image recognition |
-
2020
- 2020-05-27 CN CN202010463716.0A patent/CN111685356A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112954126A (en) * | 2021-01-25 | 2021-06-11 | 安徽农业大学 | Tracking and scanning system capable of monitoring growth and sale of organic products in real time |
| CN114128915A (en) * | 2021-11-30 | 2022-03-04 | 云南省烟草农业科学研究院 | Automatic grading method for fresh cigar leaves based on image recognition |
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Application publication date: 20200922 |