CN108465649A - Artificial intelligence corn quality inspection robot and quality detecting method - Google Patents
Artificial intelligence corn quality inspection robot and quality detecting method Download PDFInfo
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- CN108465649A CN108465649A CN201810830694.XA CN201810830694A CN108465649A CN 108465649 A CN108465649 A CN 108465649A CN 201810830694 A CN201810830694 A CN 201810830694A CN 108465649 A CN108465649 A CN 108465649A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/02—Measures preceding sorting, e.g. arranging articles in a stream orientating
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/04—Sorting according to size
- B07C5/08—Sorting according to size measured electrically or electronically
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
- B07C5/342—Sorting according to other particular properties according to optical properties, e.g. colour
- B07C5/3425—Sorting according to other particular properties according to optical properties, e.g. colour of granular material, e.g. ore particles, grain
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/36—Sorting apparatus characterised by the means used for distribution
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C2501/00—Sorting according to a characteristic or feature of the articles or material to be sorted
- B07C2501/0063—Using robots
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2201/00—Features of devices classified in G01N21/00
- G01N2201/12—Circuits of general importance; Signal processing
- G01N2201/129—Using chemometrical methods
- G01N2201/1296—Using chemometrical methods using neural networks
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Abstract
Artificial intelligence corn quality inspection robot and quality detecting method, including artificial intelligence corn quality inspection robot body and system server；Artificial intelligence corn quality inspection robot body includes babinet, babinet is equipped with feeding mouth and discharge port, two-way feeding mechanism is equipped in babinet, transport mechanism, upper and lower two-sided machine visual mechanisms and two-way mechanism for sorting, feeding mouth is connected with two-way feeding mechanism, two-way feeding mechanism is connected with transport mechanism, transport mechanism passes through upper and lower two-sided machine visual mechanisms, transport mechanism is connected with discharge port, two-way mechanism for sorting is located at upper and lower two-sided machine visual mechanisms rear, upper and lower two-sided machine visual mechanisms, two-way mechanism for sorting is connected with system server, two-way feeding mechanism takes sensor to add the mode of intelligent control.The invention also includes a kind of corn quality detecting methods.Using the present invention, it can effectively solve the problems, such as that artificial sense detection by human factor and external environment is influenced that Testing index is caused to drift about, realize quickly detection.
Description
Technical field
The present invention relates to corn quality physical detection apparatus and method fors, and in particular to a kind of artificial intelligence corn quality inspection machine
People and quality detecting method.
Background technology
Currently, corn detection is differentiated by artificial sense without modernization means and equipment and completes corn detection, and artificial sense
There are many uncertain factors for identification, and analogy, with portion sample, same inspector repeatedly identifies that the data identified every time are all
Can be different, with portion sample, the same standard of different testing staff, the findings data of identification can also be not quite similar；Therefore, difficult
With it is objective, fair, accurately distinguish, " have a standard and without the technological means of the standard of execution " to come true.
The detection of corn unsound grain is completed in existing artificial sense identification, is had the following disadvantages：1）Easily by environment and personnel
Factor is interfered；2）Without unified measurement facility；3）Inefficiency.
CN207188252U disclosed a kind of grain unsound grain quality inspection system on April 6th, 2018, was by with spiral
Mechanism feeding, the feeding of optical glass disk, upper and lower double vision feel opposite intake material image, then by detected object and image library
Middle image carries out the identification of mechanical comparison mode, sorts and weigh in glass disk, is finally completed the detection of grain unsound grain.It is this
Detection device has the following problems with means：
（1）Screw mechanism feeding manner is usually applicable only to standard component, when material is the non-standard component of grain class, because of particle
Size, shape, length, proportion, integrated degree difference and be susceptible to putty, material leakage, the discharging situations such as not to the utmost, thus make
The sample that must be conveyed is incomplete and seriously affects efficiency.
（2）Optical glass disk feeding style, when disk rotational reaches certain rotating speed, material is easy to slip, meanwhile, by
It jumps so that the sample deficient in stability in field of vision is sent into, thus further such that the object obtained at the end generated when disk rotational
Severe deviations occur for the raw information of the measurement spatial distortion of material, detected material.
（3）Visual manner opposing upper and lower causes top and bottom visual information to interfere between each other, further causes to be detected
It surveys the distortion of object raw information and generates more large deviation.
（4）The image library of the original image of detected material and master sample progress mechanical comparison is not adapted into grain
Non-standard feature identifies that it is linear to carry out hardness not according to linear relationship using mechanical comparison for grain unsound grain granules
Relationship differentiation misses by a mile in actual operation.
（5）When detected particle reaches sorting area from identified area, physical location is often because of sliding and disk end
It jumps and makes sorting accuracy that can not ensure.
Invention content
The technical problem to be solved by the invention is to provide a kind of to corn unsound grain（It damages by worms, go mouldy, embryo becomes, broken
Grain）The artificial intelligence corn quality inspection robot being detected with impurity.
The present invention is further the technical problem to be solved is that, offer is a kind of to utilize the artificial intelligence corn quality inspection machine
The method that people carries out quality inspection to corn.
The technical solution adopted by the present invention to solve the technical problems is：A kind of artificial intelligence corn quality inspection robot, packet
Include artificial intelligence corn quality inspection robot body and system server；The artificial intelligence corn quality inspection robot body includes case
Body, the babinet are equipped with feeding mouth and discharge port, and two-way feeding mechanism, transport mechanism, upper and lower two-sided is equipped in the babinet
Machine vision Agency road mechanism for sorting, the feeding mouth are connected with two-way feeding mechanism, the two-way feeding mechanism with
Transport mechanism is connected, and the transport mechanism passes through upper and lower two-sided machine visual mechanisms, the transport mechanism to be connected with discharge port
Logical, the two-way mechanism for sorting is located at upper and lower two-sided machine visual mechanisms rear, two-sided machine visual mechanisms, the two-way up and down
Mechanism for sorting is connected with system server；
The two-way feeding mechanism includes feeding box, and a partition board is equipped in the feeding box, the cavity of feeding box is divided into ante-chamber
And back cavity, the feeding box bottom are equipped with two-way hopper, the two-way hopper runs through ante-chamber and back cavity, and partition board and ante-chamber it
Between be divided into two-way all the way, the back cavity is equipped with whether monitoring back cavity has the sensor I of material, the back cavity close to baffle material trough rim
Monitor whether the sensor II of material position, hopper center of the ante-chamber at partition board are equipped with monitoring back cavity equipped with a horizontal direction
The sensor III of discharging, ante-chamber hopper exit upper limb be equipped with monitoring ante-chamber whether the sensor IV of putty, the feeding
Box is equipped with the mechanism for preventing back cavity putty, and the feeding box lower part is equipped with vibrator, the vibrator and voltage modulator phase
Even, the sensor I, sensor II, sensor III, sensor IV, the mechanism for preventing back cavity putty, voltage modulator and control
Device is connected, and the controller is connected with system server.
Further, the sensor II of horizontal direction monitoring material position be located at back cavity horizontal direction distance bottom >=1cm
（It is preferred that 2-3 cm）Place.
Further, described to prevent the mechanism of back cavity putty include steering engine, and the steering engine is located at outside feeding box, and the steering engine is logical
It crosses steering engine connecting rod and is connected with steering engine plectrum, the steering engine plectrum is located in back cavity, and close to partition board and hopper.
Further, it is equipped with guide item between the two-way feeding mechanism and transport mechanism, prevents corn to be detected from two-way
The feeding trough of feeding mechanism comes out the center retrodeviated from transport mechanism, so as to the figure that two-sided machine visual mechanisms obtain up and down
As more complete.
Further, the transport mechanism includes transparent synchrome conveying belt and synchronous driving wheel, the synchronous driving wheel arrangement
On babinet, the synchronous driving wheel is equipped with synchronous gear I, and the edge of the transparent synchrome conveying belt is equipped with synchronous gear II,
The synchronous gear II of the transparent synchrome conveying belt and I assembly connection of synchronous gear of synchronous driving wheel, the transparent synchrome conveying belt
On partially pass through up and down two-sided machine visual mechanisms.
Further, the two-sided machine visual mechanisms up and down include upper machine vision mechanism, upper shadow-free light source, upper vision bottom
Plate, lower machine vision mechanism, lower shadow-free light source and lower vision bottom plate, the upper machine vision mechanism, upper shadow-free light source are located at saturating
Rear on the upside of bright synchrome conveying belt, the upper vision bottom plate are set on the downside of transparent synchrome conveying belt, and just positioned at upper shadow-free light source
Lower section, the lower machine vision mechanism, lower shadow-free light source are located at front on the downside of transparent conveyor belt, and the lower vision bottom plate is set to saturating
On the upside of bright synchrome conveying belt, and right over lower shadow-free light source.
Further, the two-way mechanism for sorting includes air valve, fixing bracket, limiting plate, air tube and double pulp-collecting box, the limit
Position plate is mounted on double pulp-collecting box, and the fixing bracket is located above double pulp-collecting box, and the air tube is mounted on fixing bracket, institute
Air valve is stated by pipeline to be connected with air tube.It is additionally provided with weighing sensor, the weighing sensor is located under two-way mechanism for sorting
Side, can directly weigh for statistical analysis to corn.
A method of quality inspection being carried out to corn using the artificial intelligence corn quality inspection robot, is included the following steps：
Corn measuring samples are reached into two-way feeding mechanism by the feeding mouth of artificial intelligence corn quality inspection robot body, simultaneously
Measuring samples in two-way feeding mechanism are detected by sensor and walk material state, and if there is putty situation, sensor is by putty
Information via controller sends system server to, controls voltage modulator by controller by system server, and then drive double
The vibrator of road feeding mechanism vibrates, and measuring samples is sent to transport mechanism for more than by two-way feeding mechanism, by transport mechanism
Corn measuring samples are sent to two-sided machine visual mechanisms up and down, is obtained by two-sided machine visual mechanisms up and down and is tested corn-like
Product original image, then it is tested to every beautiful by the artificial neural network system of the support graphics process built in system server
Rice sample original image carries out algorithm process, and the features such as the color of every tested corn sample, texture, profile, size are converted
It is characterized the value of information, artificial neural network system is inputted, is compared, obtains with the character pair value of information stored on neuron
The degree of membership of the character pair value of information, then differentiated according to the degree of membership of the character pair value of information with discriminant function, classification system
Meter is sorted unsound grain and impurity by two-way mechanism for sorting；Finally, the sample that detection is completed is output to by transport mechanism
Discharge port, entire quality check process are all automatically performed.
Further, the character pair value of information stored on the neuron obtains in the following manner：It will be sorted in advance
Corn sample sent to upper and lower Double-plate machine device visual mechanisms through two-way feeding mechanism, transport mechanism, upper and lower two-sided machine vision
Mechanism obtains every corn sample original image, by supporting the artificial neural network system of graphics process to every corn sample
Original image carries out algorithm process, converts the features such as the color of corn, texture, profile, size, transparency to characteristic information
Value, and be stored on the neuron of artificial neural network system, a corn characteristic information library is consequently formed.
In the present invention, the two-way feeding mechanism takes sensor to add the mode of intelligent control, passes through sensor senses
Information, system can decide whether putty, whether empty material, Flow of Goods and Materials whether smooth homogeneous and can be according to these information progress phase
It should handle to ensure that feeding is continuous, stablize, uniformly, be not in putty, material leakage, the discharging situations such as not to the utmost.Especially with two-way
Feeding is greatly improved quality inspection efficiency.
In the present invention, the transparent synchrome conveying belt of the transport mechanism is completed under the driving that synchronous driving wheel passes through motor
The transmission of material, transparent synchrome conveying belt are that middle section is in field of vision location transparency and edge can be complete with synchronous driving wheel
The synchronous belt of engagement.Field of vision is partially transparent to obtain enough clearly images convenient for two-sided machine visual mechanisms up and down, transparent same
Step conveyer belt is driven and uniform motion by motor under stable frequency in synchronous driving wheel, ensures image clearly, detected material
Raw information deviation will not occur.
In the present invention, the two-sided machine visual mechanisms up and down are staggered corresponding position completely so that two vision lens it
Between do not interfere with each other influence obtain original image accuracy and integrality so that do not interfered with each other between the light of two visions
Influence the reliability and stability of visual environment；Ensure that obtaining detected material measures the accurate, true, complete of spatial information with this
It is whole.
Research practice shows using the present invention from corn measuring samples information is obtained to detection judgement is completed, to each
The detection time of corn sample is no more than 20 milliseconds, and a 100 grams of standard sample of artificial intelligence detection robot detection only needs
Identification and data statistic analysis can be completed within 3-4 minutes, can precisely be completed by artificial intelligence corn quality inspection robot
The detection of corn unsound grain and impurity solves corn unsound grain and quickly detects this global problem.Whole process is not required to
Human intervention is wanted, can effectively solve manually organoleptic detection by human factor and external environment is influenced that Testing index is caused to drift about
The problem of, meanwhile, robot all detects each sample one by one, does not stay detection blind spot and dead angle.
The actually detected accuracy and repeatability index of the present invention：
Corn unsound grain detects（By taking 100 grams of every part of sample of national standard as an example）
Whole unsound grains, error≤0.5%, repetitive error≤0.3%；
Injured kernel, error≤0.5%, repetitive error≤0.3%；
Germinate grain, error≤0.5%, repetitive error≤0.3%；
Scab grain, error≤0.5%, repetitive error≤0.3%；
Broken kernel（It is broken）, error≤0.3%, repetitive error≤0.1%；
Moldy kernel, error≤0.3%, repetitive error≤0.2%.
Description of the drawings
Fig. 1 is the structure diagram of artificial intelligence corn quality inspection robotic embodiment of the present invention；
Fig. 2 is the structural schematic diagram of the artificial intelligence corn quality inspection robot body of embodiment illustrated in fig. 1；
Fig. 3 is the structural schematic diagram of the two-way feeding mechanism of embodiment illustrated in fig. 1；
Fig. 4 is artificial intelligence corn quality inspection robot controller annexation figure of the present invention；
Fig. 5 is the structural schematic diagram of the transport mechanism of embodiment illustrated in fig. 1；
Fig. 6 is the structural schematic diagram of the upper and lower two-sided machine visual mechanisms of embodiment illustrated in fig. 1；
Fig. 7 is the structural schematic diagram of the two-way mechanism for sorting of embodiment illustrated in fig. 1；
Fig. 8 is that artificial intelligence corn quality inspection machine hostage of the present invention examines process flow diagram flow chart.
Specific implementation mode
The invention will be further described with reference to the accompanying drawings and embodiments.
Embodiment
- Fig. 4 referring to Fig.1, a kind of artificial intelligence corn quality inspection robot, including artificial intelligence corn quality inspection robot body
1 and system server 2；The artificial intelligence corn quality inspection robot body 1 includes babinet, and the babinet is equipped with feeding mouth 1-
1 and discharge port, be equipped in the babinet two-way feeding mechanism 1-2, transport mechanism 1-3, upper and lower two-sided machine visual mechanisms 1-4 and
Two-way mechanism for sorting 1-5, the feeding mouth 1-1 are connected with two-way feeding mechanism 1-2, and the two-way feeding mechanism 1-2 passes through
Guide 1-6 is connected with transport mechanism 1-3, and the transport mechanism 1-3 passes through upper and lower two-sided machine visual mechanisms 1-4, described
Transport mechanism 1-3 is connected with discharge port, and the two-way mechanism for sorting 1-5 is located at the upper and lower two-sided rears machine visual mechanisms 1-4,
It is described that two-sided machine visual mechanisms 1-4, two-way mechanism for sorting 1-5 are connected with system server 2 up and down；
The two-way feeding mechanism 1-2 includes feeding box 1-2-1, and a partition board 1-2-2 is equipped in the feeding box 1-2-1, will be fed
The cavity of magazine 1-2-1 is divided into ante-chamber and back cavity, and the bottoms the feeding box 1-2-1 are equipped with two-way hopper 1-2-3, the two-way material
Slot 1-2-3 runs through ante-chamber and back cavity, and is divided into two-way all the way between partition board and ante-chamber, and the back cavity is on baffle material trough rim
Whether there is I 1-2-4 of sensor of material equipped with monitoring back cavity, it is horizontal to be equipped with one at the 2cm of back cavity horizontal direction distance bottom
Direction monitors that II 1-2-5 of sensor of material position, hopper center of the ante-chamber at partition board are equipped with whether monitoring back cavity discharges
III 1-2-6 of sensor, ante-chamber hopper exit upper limb be equipped with monitoring ante-chamber whether IV 1-2-7 of sensor of putty（Energy
The feeding situation of two-way hopper two-way part is sensed simultaneously）, the feeding box 1-2-1 is externally provided with steering engine 1-2-8, the steering engine 1-
2-8 is connected with the lower parts steering engine plectrum 1-2-9, the feeding box 1-2-1 by steering engine connecting rod and is equipped with vibrator 1-2-10, the vibration
Device 1-2-10 is connected with voltage modulator 4, I 1-2-4 of the sensor, II 1-2-5 of sensor, III 1-2-6 of sensor, sensor
IV 1-2-7, steering engine 1-2-8, voltage modulator 4 are connected with controller 3, and the controller 3 is connected with system server 2；
The course of work：
1）II 1-2-5 of sensor of horizontal direction monitoring material position is triggered, and controller 3 obtains information, sends information to system
Server 2, system server 2 will send out stopping sampling instruction, which is used for on-line checking（On-line automatic sampling）；
2）The ante-chamber putty of two-way feeding mechanism, whether IV 1-2-7 of sensor of putty is triggered monitoring ante-chamber, and controller 3 obtains
The information, sends information to system server 2, and system server 2 sends out stopping sampling instruction, then, system service first
Device 2 sends out instruction to controller 3, and controller 3 controls voltage modulator 4, will reinforce vibrator vibration frequency 2 seconds, then restores
Vibrator vibration frequency；If whether the sensor IV 1-2-7 triggerings of putty do not release monitoring ante-chamber, reinforce vibrator again
Vibration frequency 2 seconds, 3 times repeatedly, until ante-chamber putty sensor-triggered releases；
3）III 1-2-6 of sensor whether monitoring back cavity discharges is triggered, and whether monitoring back cavity has I 1-2-4 of sensor of material not
It is triggered, illustrates that the back cavity of two-way feeding mechanism putty, controller obtain heat transfer agent, start steering engine 1-2-8, steering engine is dialled
Piece 1-2-9 stirs rear chamber discharge port sample, releases back cavity putty state；Back cavity sample is all conveyed by two-way feeding mechanism
Afterwards, whether monitoring back cavity has I 1-2-4 of sensor of material to be triggered, and controller 2 sends out sample to system server 3 and all checks
Complete information.
The input of the controller 3 is connected with each sensor（Access transducing signal-putty transducing signal, full material sensing
Signal）, export and be connected with voltage modulator 4, voltage modulator 4 is connected with the vibrator 1-2-10 on two-way feeding mechanism
It connects, the voltage by modulating two-way feeding mechanism upper vibration generator 1-2-10 achievees the purpose that control vibrator 1-2-10 amplitudes.
The system server 2 is the command centre of corn quality inspection robot, is the brain of corn quality inspection robot, system
Server 2 is connected by RS232 communication ports with controller, and controller is connected with each sensor, and controller obtains the shape of each sensing
The information of each sensing is sent to system server by state, and system server refers to according to the heat transfer agent of acquisition to controller transmission
It enables, completes putty processing；The system server 2 is connected by RJ45 network interfaces with upper and lower two-sided machine visual mechanisms, is obtained
Take pictorial information, denoising then carried out to picture, analyzed, reasoning, judgement-differentiation, complete corn quality inspection robot
The orchestration of all steps.
With reference to Fig. 5, the transport mechanism 1-3 includes transparent synchrome conveying belt 1-3-1 and synchronous driving wheel 1-3-2, described
Synchronous driving wheel 1-3-2 is in rectangular layout on babinet 1-1, and the synchronous driving wheel 1-3-2 is equipped with synchronous gear I, described
The edge of bright synchrome conveying belt 1-3-1 is equipped with II 1-3-3 of synchronous gear, the synchronous gear II of the transparent synchrome conveying belt 1-3-1
I assembly connection of synchronous gear of 1-3-3 and synchronous driving wheel 1-3-2 partially pass through on the transparent synchrome conveying belt 1-3-1
Under two-sided machine visual mechanisms 1-4.
With reference to Fig. 6, the two-sided machine visual mechanisms 1-4 up and down includes upper machine vision mechanism 1-4-1, upper shadow-free light source
1-4-2, upper vision bottom plate 1-4-3, lower machine vision mechanism 1-4-4, lower shadow-free light source 1-4-5 and lower vision bottom plate 1-4-6, institute
Shu Shang machine vision mechanism 1-4-1, upper shadow-free light source 1-4-2 are located at rear on the upside of transparent synchrome conveying belt 1-3-1, it is described on regard
Feel that bottom plate 1-4-3 is set on the downside of transparent synchrome conveying belt 1-3-1, and immediately below upper shadow-free light source 1-4-2, the lower machine
Visual mechanisms 1-4-4, lower shadow-free light source 1-4-5 are located at front, the lower vision bottom plate 1-4-6 on the downside of transparent conveyor belt 1-3-1
On the upside of transparent synchrome conveying belt 1-3-1, and right over lower shadow-free light source 1-4-5.
With reference to Fig. 7, the two-way mechanism for sorting 1-5 includes air valve 1-5-1, fixing bracket 1-5-2, limiting plate 1-5-3, gas
Needle 1-5-4 and double pulp-collecting box 1-5-5, the limiting plate 1-5-3 are mounted on double pulp-collecting box 1-5-5, the fixing bracket 1-5-2
Above double pulp-collecting box 1-5-5, the air tube 1-5-4 is mounted on fixing bracket 1-5-2, and the air valve 1-5-1 passes through pipe
Road is connected with air tube 1-5-4.It is additionally provided with weighing sensor, the weighing sensor is located at below two-way mechanism for sorting.
Reference Fig. 8, a method of using the artificial intelligence corn quality inspection robot to corn progress quality inspection, including with
Lower step：
Corn measuring samples are reached into two-way feeding mechanism by the feeding mouth of artificial intelligence corn quality inspection robot body, simultaneously
Measuring samples in two-way feeding mechanism are detected by sensor and walk material state, and if there is putty situation, sensor is by putty
Information via controller sends system server to, controls voltage modulator by controller by system server, and then drive double
The vibrator of road feeding mechanism vibrates, and measuring samples is sent to transport mechanism for more than by two-way feeding mechanism, by transport mechanism
Corn measuring samples are sent to two-sided machine visual mechanisms up and down, is obtained by two-sided machine visual mechanisms up and down and is tested corn-like
Product original image, then by building the artificial neural network system of support graphics process in system server to every tested corn
Sample original image carries out algorithm process, converts the features such as the color of every tested corn sample, texture, profile, size to
Characteristic information value inputs artificial neural network system, is compared with the character pair value of information stored on neuron, obtained pair
The degree of membership of characteristic information value is answered, then is differentiated according to the degree of membership of the character pair value of information with S-shaped discriminant function, classification system
Meter is sorted unsound grain and impurity by two-way mechanism for sorting；Finally, the sample that detection is completed is output to by transport mechanism
Discharge port, entire quality check process are all automatically performed.
The character pair value of information stored on the neuron obtains in the following manner：By sorted in advance 20000
Corn sample（Including damaging by worms, going mouldy, embryo become, broken kernel）It is sent to upper and lower Double-plate machine device through two-way feeding mechanism, transport mechanism
Under visual mechanisms, upper and lower two-sided machine visual mechanisms obtain every corn sample original image, by the people for supporting graphics process
Artificial neural networks system carries out algorithm process to every corn sample original image, by the color of corn, texture, profile, size
Etc. features be converted into characteristic information value, and be stored on the neuron of artificial neural network system, a corn spy be consequently formed
Levy information bank.
Research practice shows using the present invention from corn measuring samples information is obtained to detection judgement is completed, to each
The detection time of corn sample is no more than 20 milliseconds, and a 100 grams of standard sample of artificial intelligence detection robot detection only needs
Identification and data statistic analysis can be completed within 3-4 minutes, can precisely be completed by artificial intelligence corn quality inspection robot
The detection of corn unsound grain and impurity solves corn unsound grain and quickly detects this global problem.Whole process is not required to
Human intervention is wanted, can effectively solve manually organoleptic detection by human factor and external environment is influenced that Testing index is caused to drift about
The problem of, meanwhile, robot all detects each sample one by one, does not stay detection blind spot and dead angle.
The actually detected accuracy and repeatability index of the present invention：
Corn unsound grain detects（By taking 100 grams of every part of sample of national standard as an example）
Whole unsound grains, error≤0.5%, repetitive error≤0.3%；
Injured kernel, error≤0.5%, repetitive error≤0.3%；
Germinate grain, error≤0.5%, repetitive error≤0.3%；
Scab grain, error≤0.5%, repetitive error≤0.3%；
Broken kernel（It is broken）, error≤0.3%, repetitive error≤0.1%；
Moldy kernel, error≤0.3%, repetitive error≤0.2%.
Claims (9)
1. artificial intelligence corn quality inspection robot, including artificial intelligence corn quality inspection robot body and system server；It is described
Artificial intelligence corn quality inspection robot body includes babinet, and the babinet is equipped with feeding mouth and discharge port, it is characterised in that：Institute
It states and is equipped with two-way feeding mechanism, transport mechanism, upper and lower two-sided machine visual mechanisms and two-way mechanism for sorting, the pan feeding in babinet
Mouth is connected with two-way feeding mechanism, and the two-way feeding mechanism is connected with transport mechanism, and the transport mechanism passes through up and down
Two-sided machine visual mechanisms, the transport mechanism are connected with discharge port, and the two-way mechanism for sorting is located at upper and lower two-sided machine
Visual mechanisms rear, two-sided machine visual mechanisms, the two-way mechanism for sorting up and down are connected with system server；The two-way is fed
Expect that mechanism includes feeding box, a partition board is equipped in the feeding box, the cavity of feeding box is divided into ante-chamber and back cavity, the feeding
Cassette bottom portion is equipped with two-way hopper, and the two-way hopper runs through ante-chamber and back cavity, and is divided into two-way all the way between partition board and ante-chamber,
The back cavity is equipped with whether monitoring back cavity has the sensor I of material, the back cavity to be equipped with a horizontal direction close to baffle material trough rim
Monitor the sensor II of material position, hopper center of the ante-chamber at partition board are equipped with the sensor whether monitoring back cavity discharges
III, ante-chamber hopper exit upper limb be equipped with monitoring ante-chamber whether the sensor IV of putty, the feeding box be equipped with prevent
The mechanism of back cavity putty, the feeding box lower part are equipped with vibrator, and the vibrator is connected with voltage modulator, the sensor
I, sensor II, sensor III, sensor IV, the mechanism of back cavity putty, voltage modulator is prevented to be connected with controller, the control
Device processed is connected with system server.
2. artificial intelligence corn quality inspection robot according to claim 1, it is characterised in that：The horizontal direction monitoring material
Position sensor II be located at back cavity horizontal direction distance bottom >=1cm at.
3. artificial intelligence corn quality inspection robot according to claim 1 or 2, it is characterised in that：It is described to prevent back cavity stifled
The mechanism of material includes steering engine, and the steering engine is located at outside feeding box, and the steering engine is connected with steering engine plectrum, the rudder by steering engine connecting rod
Machine plectrum is located in back cavity, and close to partition board and hopper.
4. artificial intelligence corn quality inspection robot according to claim 1 or 2, it is characterised in that：The two-way feeder
Guide item is equipped between structure and transport mechanism.
5. artificial intelligence corn quality inspection robot according to claim 1 or 2, it is characterised in that：The transport mechanism packet
Transparent synchrome conveying belt and synchronous driving wheel are included, the synchronous driving wheel is arranged on babinet, and the synchronous driving wheel is equipped with
Synchronous gear I, the edge of the transparent synchrome conveying belt are equipped with synchronous gear II, the synchronous gear II of the transparent synchrome conveying belt with
I assembly connection of synchronous gear of synchronous driving wheel partially passes through two-sided machine vision machine up and down on the transparent synchrome conveying belt
Structure.
6. artificial intelligence corn quality inspection robot according to claim 5, it is characterised in that：The two-sided machine up and down regards
Feel mechanism include upper machine vision mechanism, upper shadow-free light source, upper vision bottom plate, lower machine vision mechanism, lower shadow-free light source and under
Vision bottom plate, the upper machine vision mechanism, upper shadow-free light source are located at rear on the upside of transparent synchrome conveying belt, the upper vision bottom
Plate is set on the downside of transparent synchrome conveying belt, and immediately below upper shadow-free light source, the lower machine vision mechanism, lower shadow-free light source
The front on the downside of transparent conveyor belt, the lower vision bottom plate are set on the upside of transparent synchrome conveying belt, and are located at lower shadow-free light source
Surface.
7. artificial intelligence corn quality inspection robot according to claim 1 or 2, it is characterised in that：The two-way sorter
Structure includes air valve, fixing bracket, limiting plate, air tube and double pulp-collecting box, and the limiting plate is mounted on double pulp-collecting box, the fixation
Holder is located above double pulp-collecting box, and the air tube is mounted on fixing bracket, and the air valve is connected by pipeline with air tube.
8. a kind of method carrying out quality inspection to corn using artificial intelligence corn quality inspection robot described in claim 1, feature
It is, includes the following steps：
Corn measuring samples are reached into two-way feeding mechanism by the feeding mouth of artificial intelligence corn quality inspection robot body, simultaneously
Measuring samples in two-way feeding mechanism are detected by sensor and walk material state, and if there is putty situation, sensor is by putty
Information via controller sends system server to, controls voltage modulator by controller by system server, and then drive double
The vibrator of road feeding mechanism vibrates, and measuring samples is sent to transport mechanism for more than by two-way feeding mechanism, by transport mechanism
Corn measuring samples are sent to two-sided machine visual mechanisms up and down, is obtained by two-sided machine visual mechanisms up and down and is tested corn-like
Product original image, then it is tested to every beautiful by the artificial neural network system of the support graphics process built in system server
Rice sample original image carries out algorithm process, converts the feature of every tested corn sample to characteristic information value, input is artificial
Nerve network system is compared with the character pair value of information stored on neuron, obtains being subordinate to for the character pair value of information
Degree, then differentiated according to the degree of membership of the character pair value of information with discriminant function, statistic of classification, it will by two-way mechanism for sorting
Unsound grain and impurity sorting；Finally, the sample that detection is completed is output to discharge port by transport mechanism, entire quality check process is complete
Portion is automatically performed.
9. the method that artificial intelligence corn quality inspection robot according to claim 8 carries out quality inspection to corn, feature exist
In the character pair value of information stored on the neuron obtains in the following manner：By corn sample warp sorted in advance
Two-way feeding mechanism, transport mechanism are sent to upper and lower Double-plate machine device visual mechanisms, and upper and lower two-sided machine visual mechanisms obtain every
Corn sample original image, by supporting the artificial neural network system of graphics process to carry out every corn sample original image
Algorithm process converts corn feature to characteristic information value, and is stored on the neuron of artificial neural network system, thus shape
At a corn characteristic information library.
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| CN112487936A (en) * | 2020-11-26 | 2021-03-12 | 郑州数农通大数据科技有限公司 | Corn field management robot based on machine vision technology |
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