CN208288480U - A kind of tealeaves exterior quality self-grading device based on computer vision technique - Google Patents
A kind of tealeaves exterior quality self-grading device based on computer vision technique Download PDFInfo
- Publication number
- CN208288480U CN208288480U CN201820361234.2U CN201820361234U CN208288480U CN 208288480 U CN208288480 U CN 208288480U CN 201820361234 U CN201820361234 U CN 201820361234U CN 208288480 U CN208288480 U CN 208288480U
- Authority
- CN
- China
- Prior art keywords
- tealeaves
- falsework
- sliding block
- fixedly mounted
- computer vision
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Landscapes
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The utility model discloses a kind of tealeaves exterior quality self-grading device based on computer vision technique, including material transmitting device, control system, optical imaging system, automatic classification module, wherein: the transmitting device is equipped with optical imaging system, transmitting device rear end is equipped with control system, and right side is equipped with automatic classification module.The defects of technical effect and advantage of the utility model: replacing human eye using computer vision, replaces manually evaluating by establishing effective identification model in computer, the subjectivity existing for tealeaves sensory evaluation, ambiguity of forgoing；It is taken pictures by CCD industrial camera to tealeaves, and coupled computer carries out ranking to tea leaf quality, real-time automatic classification is carried out to the tealeaves to be detected, reduces labor intensity, improves working efficiency.
Description
Technical field
The utility model relates to tea leaf quality classification technique field more particularly to a kind of tea based on computer vision technique
Leaf exterior quality self-grading device.
Background technique
Tealeaves is a kind of important agricultural economy crop, antioxidant and antioxidants containing there are many, for disappearing
Except free radical has certain effect.Due to environmental condition, tea tree breed, cultivation technique, picking season, picked technology and processing work
The influence of the factors such as skill, tea leaf quality is irregular, while also directly determining the price of tealeaves.Tea dry sorting marketing, not only
The competitiveness of product in market can be improved, economic benefit can also be increased.Therefore tea leaf quality is evaluated, and divided rank
With important value.
Tea leaf quality is that various composition cooperates in tealeaves, it is coordinated with each other after concentrated expression, but the ingredient of tealeaves is very
Complexity, quality can not carry out quantitative expression simply by certain internal components.At home and abroad, the quality of tea leaf quality, etc.
Grade divides and the decision of value height mainly passes through artificial sense and evaluates method progress, and this method need to put into a large amount of professional manpower
Resource, and its result is easily affected by various factors, subjective, consistency is poor, is classified unstable quality.
Tealeaves shape quality reflects tealeaves internal component situation, and tealeaves Appearance color is the synthesis of a variety of colors
Reflection；For tealeaves shape organoleptic quality mainly by commenting tea teacher to complete by the organs of vision, entirely evaluating process is to pass through cerebral nerve
One complexing action mechanism of system carries out.Computer vision technique is that human eye is simulated by instrument to realize that the part mankind regard
The function of feel, therefore it is quantified using computer vision technique, stable, reliable expert's identification model is established, it can be to tealeaves
Quality carries out quick, nondestructive evaluation, to traditional evaluation method is solved to the professional Dependence Problem for commenting tea teacher, improves working efficiency,
Labor intensity is reduced, guarantees quick detection, the automatic classification important in inhibiting of product.
Utility model content
The purpose of this utility model is to provide a kind of tealeaves exterior quality automatic classification based on computer vision technique
Device provides a kind of device that simultaneously Accurate Classification can be conveyed automatically with tealeaves to overcome above-mentioned deficiency.
To achieve the above object, the utility model provides the following technical solutions: a kind of tea based on computer vision technique
Leaf exterior quality self-grading device, including material transmitting device, control system, optical imaging system, automatic classification module,
In: the transmitting device is equipped with optical imaging system, and transmitting device rear end is equipped with control system, and right side is equipped with automatic classification mould
Block, the material transmitting device include falsework, motor, transmission belt, bearing spider and roller bearing and container, and the falsework is gone forward
It is symmetrically fixedly installed with several bearing spiders afterwards, roller bearing is equipped between the front and back bearings support, is arranged with biography on the roller bearing
Defeated band, the symmetrical centre of the transmission belt are decorated with centre of location line, and the container is located on transmission belt centre of location line, the electricity
Machine is fixedly mounted under falsework, and the motor and active roller bearing are located on the falsework by driving belt transmission connection
Optical imaging system is equipped with above transmission belt, the optical imaging system includes CCD industrial camera, camera bellows of taking pictures, strip source
And optoelectronic switch, the camera bellows of taking pictures are fixedly mounted on the middle part of falsework, are located above transmission belt, take pictures camera bellows left wall and the right side
It is equipped with the opening that container passes through below wall, is equipped with optoelectronic switch below antetheca, strip source is equipped in the middle part of camera bellows of taking pictures, it is described
CCD industrial camera is fixedly mounted on camera bellows inner tip of taking pictures, and the control system includes workbench, computer and control plane
Plate, the workbench are fixedly mounted on rear side of falsework, and the computer is set on workbench, and the control panel is set to work
On platform, automatic classification module includes classification mechanism, log washer, photoelectric sensor and stabilizer blade, and the classification mechanism is fixedly mounted on
Above falsework right end, the photoelectric sensor is fixedly mounted on classification mechanism front end, and the log washer is equipped with 4 sliding slots,
It is respectively used to after tealeaves automatic classification to be checked into the channel of each grade (I grade, II grade, III grade, IV grade), log washer one end is fixed
It is mounted on falsework lower right, it is industrial with motor, computer, CCD respectively that the control panel on stabilizer blade is fixedly mounted in the other end
Camera, strip source, optoelectronic switch and photoelectric sensor are electrically connected.
Preferably, the classification mechanism includes stepper motor, guide rail, sliding block, screw rod, clamping plate and bracket, and the guide rail is solid
On falsework, the sliding block is threadedly coupled with guide rail for Dingan County, realizes worm drive, and the initial position of the sliding block, which is located at, to be passed
Above defeated band center line, described screw rod one end is fixedly connected by shaft coupling with stepper motor, and the other end passes through sliding block and bracket
Connection, stepper motor and control panel are electrically connected, and the clamping plate is installed on sliding block, hold tealeaves to be detected for driving
Container realization moves left and right.
Preferably, the roller bearing is 4.
Preferably, the strip source has 4 groups.
Preferably, the sliding block is equipped with internal thread through hole, and screw rod is realized by cooperating with the internal thread through hole on sliding block
The movement of sliding block.
The technical effect and advantage of the utility model: replacing human eye using computer vision, is established by computer effective
Identification model replace artificial evaluation, the defects of the subjectivity existing for tealeaves sensory evaluation, ambiguity of forgoing；Pass through CCD industry
Camera takes pictures to tealeaves, and coupled computer carries out ranking to tea leaf quality, carries out to the tealeaves to be detected real-time
Automatic classification reduces labor intensity, improves working efficiency.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of the utility model.
Fig. 2 is the optical imaging system structural schematic diagram of the utility model.
Fig. 3 is the classification mechanism structural schematic diagram of the utility model.
In figure: 1 transmitting device, 1-1 falsework, 1-2 motor, 1-3 transmission belt, 1-4 bearing spider, 1-5 roller bearing, 1-6 hold
Device, 2 control systems, 2-1 workbench, 2-2 computer, 2-3 control panel, 3 optical imaging systems, 3-1CCD industrial camera, 3-2
Take pictures camera bellows, 3-3 strip source, 3-4 optoelectronic switch, 4 automatic classification modules, 4-1 classification sliding block, 4-2 log washer, 4-3 photoelectricity
Sensor, 4-4 stabilizer blade, 4-1-1 stepper motor, 4-1-2 guide rail, 4-1-3 sliding block, 4-1-4 screw rod, 4-1-5 clamping plate, 4-1-6 branch
Frame.
Specific embodiment
The following will be combined with the drawings in the embodiments of the present invention, carries out the technical scheme in the embodiment of the utility model
Clearly and completely describe, it is clear that the described embodiments are only a part of the embodiments of the utility model, rather than whole
Embodiment.Based on the embodiments of the present invention, those of ordinary skill in the art are without making creative work
Every other embodiment obtained, fall within the protection scope of the utility model.
Please refer to Fig. 1 and Fig. 2, a kind of tealeaves exterior quality self-grading device based on computer vision technique, including
Material transmitting device 1, control system 2, optical imaging system 3, automatic classification module 4, in which: the transmitting device 1 is equipped with
Optical imaging system 3,1 rear end of transmitting device are equipped with control system 2, and right side is equipped with automatic classification module 4, the material transferring dress
Setting 1 includes falsework 1-1, motor 1-2, transmission belt 1-3, bearing spider 1-4 and roller bearing 1-5 and container 1-6, the falsework 1-
Front and back is symmetrically fixedly installed with several bearing spider 1-4 on 1, and roller bearing 1-5 is equipped between the front and back bearings support 1-4, described
Transmission belt 1-3 is arranged on roller bearing 1-5, the symmetrical centre of the transmission belt 1-3 is decorated with centre of location line 1-7, the container 1-6
On transmission belt 1-3 centre of location line 1-7, the motor 1-2 is fixedly mounted under falsework 1-1, the motor 1-2 and master
Dynamic roller bearing 1-5 is located above transmission belt 1-3 on the falsework 1-1 by driving belt transmission connection and is equipped with optical imagery system
System 3, the optical imaging system 3 include CCD industrial camera 3-1, the camera bellows 3-2 that takes pictures, strip source 3-3 and optoelectronic switch 3-4,
The camera bellows 3-2 that takes pictures is fixedly mounted on the middle part of falsework 1-1, be located at transmission belt 1-3 above, camera bellows 3-2 left wall of taking pictures and
It is equipped with the opening that container 1-6 passes through below right wall, is equipped with optoelectronic switch 3-4 below antetheca, is equipped with bar shaped in the middle part of the camera bellows 3-2 that takes pictures
Light source 3-3, the CCD industrial camera 3-1 are fixedly mounted on camera bellows 3-2 inner tip of taking pictures, and the control system 2 includes work
Platform 2-1, computer 2-2 and control panel 2-3, the workbench 2-1 are fixedly mounted on falsework 1-1 rear side, the computer
2-2 is set on workbench 2-1, and the control panel 2-3 is set on workbench 2-1, and automatic classification module 4 includes classification mechanism 4-
1, log washer 4-2, photoelectric sensor 4-3 and stabilizer blade 4-4, the classification mechanism 4-1 are fixedly mounted on falsework 1-1 right end
Side, the photoelectric sensor 4-3 are fixedly mounted on the front end classification mechanism 4-1, and the log washer 4-2 is equipped with 4 sliding slots, respectively
For entering the channel of each grade (I grade, II grade, III grade, IV grade) after tealeaves automatic classification to be checked, log washer 4-2 is fixed one end
Be mounted on the lower right falsework 1-1, the other end be fixedly mounted the upper control panel 2-3 of stabilizer blade 4-4 respectively with motor 1-2, count
Calculation machine 2-2, CCD industrial camera 3-1, strip source 3-3, optoelectronic switch 3-4 and photoelectric sensor 4-3 are electrically connected.
Referring to Fig. 3, classification mechanism 4-1 include stepper motor 4-1-1, guide rail 4-1-2, sliding block 4-1-3, screw rod 4-1-4,
Clamping plate 4-1-5 and bracket 4-1-6, the guide rail 4-1-2 are fixedly mounted on falsework 1-1, the sliding block 4-1-3 and guide rail 4-
1-2 is threadedly coupled, and the initial position of the sliding block 4-1-3 is located above transmission belt 1-3 center line, the one end the screw rod 4-1-4
It is fixedly connected by shaft coupling with stepper motor 4-1-1, the other end passes through sliding block 4-1-3 and connect with bracket 4-1-6, stepper motor
4-1-1 and control panel 2-3 is electrically connected, and the clamping plate 4-1-5 is installed on sliding block 4-1-3, is held for drive to be detected
The container 1-6 realization of tealeaves moves left and right.
Further, the roller bearing 1-5 is 4, it is ensured that tealeaves steadily conveys.
Further, the strip source 3-3 has 4 groups, guarantees the brightness taken pictures in camera bellows 3-2, is conducive to CCD industry phase
Taking pictures for machine 3-1 is clear, is convenient for system level.
Further, the sliding block 4-1-3 be equipped with internal thread through hole, screw rod 4-1-4 by on sliding block 4-1-3 in
The movement of sliding block 4-1-3 is realized in tapped through hole cooperation, it is ensured that the automatic classification fast accurate of tealeaves.
Utility model works principle: firstly, equity tealeaves to be fractionated carries out expert's identification model on computer 2-2
It establishes, motor 1-2 is then started by control panel 2-3, motor 1-2 drives conveyer belt 1-3 work, when the container for filling tealeaves
Entering the camera bellows 3-2 that takes pictures under the drive of transmission belt 1-3, when by optoelectronic switch 3-4, triggering CCD industrial camera 3-1 takes pictures,
And tealeaves surface image is transmitted to the image processing system built in computer 2-2.Image processing system is to the tealeaves received
Surface image carries out image preprocessing, region of interesting extraction and shape color, shape Texture eigenvalue extracts, then by data
Expert's identification model that tealeaves feature input after change pre-establishes compares, and is commented in real time with this tealeaves exterior quality
Valence, and will test result and be transported to control panel 2-3, transmission belt 1-3 drives the container for filling tealeaves to continue onwards transmission, works as light
When electric transducer 4-3 detects that tealeaves enters classification guide rail 4-1, control panel 2-3 is according to the recognition result of expert's identification model
It controls stepper motor 4-1-1 and drives screw rod 4-1-4 rotation, and sliding block 4-1-3 is slided, sliding block 4-1-3 drives tealeaves movement
To corresponding log washer 4-2, and slide down in collection device.Hereafter stepper motor 4-1-1 drives screw rod 4-1-4 to turn
It is dynamic, it is reset to sliding block 4-1-3 above transmission belt 1-3 center line, repeats the above steps and product are carried out to the tealeaves in subsequent vessel
Matter automatic classification.
Claims (5)
1. a kind of tealeaves exterior quality self-grading device based on computer vision technique, including material transmitting device (1), control
System (2) processed, optical imaging system (3), automatic classification module (4), it is characterised in that: the transmitting device (1) is equipped with light
It learns imaging system (3), transmitting device (1) rear end is equipped with control system (2), and right side is equipped with automatic classification module (4), the material
Transmitting device (1) includes falsework (1-1), motor (1-2), transmission belt (1-3), bearing spider (1-4) and roller bearing (1-5) and holds
Device (1-6), front and back is symmetrically fixedly installed with several bearing spiders (1-4) on the falsework (1-1), the front and back bearings support
Be equipped with roller bearing (1-5) between (1-4), be arranged with transmission belt (1-3) on the roller bearing (1-5), the transmission belt (1-3) it is symmetrical
Center is decorated with centre of location line (1-7), and the container (1-6) is located on transmission belt (1-3) centre of location line (1-7), the electricity
Machine (1-2) is fixedly mounted under falsework (1-1), and the motor (1-2) and active roller bearing (1-5) are by driving belt transmission to connect
It connects, is located above transmission belt (1-3) on the falsework (1-1) and is equipped with optical imaging system (3), the optical imaging system
(3) include CCD industrial camera (3-1), camera bellows of taking pictures (3-2), strip source (3-3) and optoelectronic switch (3-4), it is described take pictures it is dark
Case (3-2) is fixedly mounted on the middle part of falsework (1-1), is located above transmission belt (1-3), camera bellows of taking pictures (3-2) left wall and the right side
It is equipped with the opening that container (1-6) passes through below wall, is equipped with optoelectronic switch (3-4) below antetheca, is equipped in the middle part of camera bellows of taking pictures (3-2)
Strip source (3-3), the CCD industrial camera (3-1) are fixedly mounted on camera bellows of taking pictures (3-2) inner tip, the control system
System (2) includes workbench (2-1), computer (2-2) and control panel (2-3), and the workbench (2-1) is fixedly mounted on work
On rear side of frame (1-1), the computer (2-2) is set on workbench (2-1), and the control panel (2-3) is set to workbench (2-1)
On, automatic classification module (4) includes classification mechanism (4-1), log washer (4-2), photoelectric sensor (4-3) and stabilizer blade (4-4), institute
It states classification mechanism (4-1) to be fixedly mounted on above falsework (1-1) right end, the photoelectric sensor (4-3) is fixedly mounted on point
Grade front end mechanism (4-1), the log washer (4-2) are equipped with 4 sliding slots, enter respectively after being respectively used to tealeaves automatic classification to be checked
The channel of grade (I grade, II grade, III grade, IV grade), the one end log washer (4-2) are fixedly mounted on the lower right falsework (1-1), separately
One end is fixedly mounted on stabilizer blade (4-4), and the control panel (2-3) is industrial with motor (1-2), computer (2-2), CCD respectively
Camera (3-1), strip source (3-3), optoelectronic switch (3-4) and photoelectric sensor (4-3) are electrically connected.
2. a kind of tealeaves exterior quality self-grading device based on computer vision technique according to claim 1,
Be characterized in that: the classification mechanism (4-1) includes stepper motor (4-1-1), guide rail (4-1-2), sliding block (4-1-3), screw rod (4-
1-4), clamping plate (4-1-5) and bracket (4-1-6), the guide rail (4-1-2) are fixedly mounted on falsework (1-1), the sliding block
(4-1-3) is threadedly coupled with guide rail (4-1-2), realizes worm drive, and the initial position of the sliding block (4-1-3) is located at transmission belt
Above (1-3) center line, described screw rod one end (4-1-4) is fixedly connected by shaft coupling with stepper motor (4-1-1), the other end
It is connect across sliding block (4-1-3) with bracket (4-1-6), stepper motor (4-1-1) and control panel (2-3) are electrically connected, described
Clamping plate (4-1-5) is installed on sliding block (4-1-3), for driving the container for holding tealeaves to be detected (1-6) realization to move left and right.
3. a kind of tealeaves exterior quality self-grading device based on computer vision technique according to claim 1,
Be characterized in that: the roller bearing (1-5) is 4.
4. a kind of tealeaves exterior quality self-grading device based on computer vision technique according to claim 1,
Be characterized in that: the strip source (3-3) has 4 groups.
5. a kind of tealeaves exterior quality self-grading device based on computer vision technique according to claim 2,
Be characterized in that: the sliding block (4-1-3) be equipped with internal thread through hole, screw rod (4-1-4) by with the interior spiral shell on sliding block (4-1-3)
The movement of sliding block (4-1-3) is realized in the cooperation of line through-hole.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201820361234.2U CN208288480U (en) | 2018-03-16 | 2018-03-16 | A kind of tealeaves exterior quality self-grading device based on computer vision technique |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201820361234.2U CN208288480U (en) | 2018-03-16 | 2018-03-16 | A kind of tealeaves exterior quality self-grading device based on computer vision technique |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN208288480U true CN208288480U (en) | 2018-12-28 |
Family
ID=64695320
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201820361234.2U Expired - Fee Related CN208288480U (en) | 2018-03-16 | 2018-03-16 | A kind of tealeaves exterior quality self-grading device based on computer vision technique |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN208288480U (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109886170A (en) * | 2019-02-01 | 2019-06-14 | 长江水利委员会长江科学院 | A kind of identification of oncomelania intelligent measurement and statistical system |
| CN110802045A (en) * | 2019-12-12 | 2020-02-18 | 安徽农业大学 | Tea leaf separation device and control method thereof |
| CN110877014A (en) * | 2019-10-28 | 2020-03-13 | 哈尔滨工大智慧工厂有限公司 | Machine vision-based small-size product sorting line ambient light influence preventing device |
-
2018
- 2018-03-16 CN CN201820361234.2U patent/CN208288480U/en not_active Expired - Fee Related
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109886170A (en) * | 2019-02-01 | 2019-06-14 | 长江水利委员会长江科学院 | A kind of identification of oncomelania intelligent measurement and statistical system |
| CN110877014A (en) * | 2019-10-28 | 2020-03-13 | 哈尔滨工大智慧工厂有限公司 | Machine vision-based small-size product sorting line ambient light influence preventing device |
| CN110802045A (en) * | 2019-12-12 | 2020-02-18 | 安徽农业大学 | Tea leaf separation device and control method thereof |
| CN110802045B (en) * | 2019-12-12 | 2024-04-12 | 安徽农业大学 | Tea leaf separating device and control method thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN208288480U (en) | A kind of tealeaves exterior quality self-grading device based on computer vision technique | |
| CN101627832B (en) | On-line automatic tobacco recognition and classification system | |
| CN206229716U (en) | A kind of apple exterior quality self-grading device based on computer vision technique | |
| CN207057050U (en) | A kind of micro parts Appearance quality defect optical detection apparatus | |
| CN1868610B (en) | Small movable intelligent grading device for fruit and poultry egg | |
| CN110694921A (en) | Vegetable sorting system and control method thereof | |
| CN100569389C (en) | A kind of device for sizing spike-like fruits | |
| CN107952696A (en) | A kind of detection grading plant and detection method suitable for fresh tobacco leaf | |
| CN103111427A (en) | Fruit grader based on image processing | |
| CN210059040U (en) | Based on RGB fruit sorter | |
| CN105466950A (en) | Bamboo dice online detection method and system based on vision | |
| CN106370667A (en) | Visual detection apparatus and method for quality of corn kernel | |
| CN104132945A (en) | On-line surface quality visual inspection device for bar based on optical fiber conduction | |
| CN102890093A (en) | Machine vision detecting device of surface quality of master cylinder piston of automobile brake | |
| CN107993203B (en) | Poultry carcass image grading method and grading system thereof | |
| CN103760166A (en) | Flue-cured tobacco appearance information collecting device | |
| CN203672794U (en) | Flue-cured tobacco appearance information acquisition device | |
| CN206353137U (en) | A kind of testing drum workbench based on machine vision | |
| CN208513101U (en) | A kind of two-sided vision-based detection mango grading plant | |
| CN211185838U (en) | Tobacco leaf rapid detection grading plant based on image and spectral characteristics | |
| CN108204977A (en) | Corn kernel quality automatic detection device based on machine vision | |
| CN206331487U (en) | A kind of agricultural product volume rapid measurement device based on machine vision | |
| CN205056491U (en) | Tea bag image acquisition and sorting device | |
| CN202083645U (en) | FPGA (field programmable gate array)-based food quality on-line detector | |
| CN112676195B (en) | Color sorting device and method for solid wood floor based on linear array CMOS camera |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20181228 Termination date: 20200316 |