CN103760163A - Device for monitoring selection of soybean seeds in real time - Google Patents
Device for monitoring selection of soybean seeds in real time Download PDFInfo
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- CN103760163A CN103760163A CN201410037953.5A CN201410037953A CN103760163A CN 103760163 A CN103760163 A CN 103760163A CN 201410037953 A CN201410037953 A CN 201410037953A CN 103760163 A CN103760163 A CN 103760163A
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Abstract
The invention discloses a device for monitoring the selection of soybean seeds in real time, relates to the field of agricultural automation and aims to solve the problem that in the screening process of the soybean seeds, the screening process of the soybean seeds cannot be monitored in real time. The device adopts an intelligent camera to carry out whole-process real-time monitoring on the screening of the soybean seeds and utilizes a single chip microcomputer system to effectively control the screening of the soybean seeds so as to achieve the purpose of real-time monitoring. The device is suitable for the field of agricultural automation.
Description
Technical field
The present invention relates to agricultural automation field.
Background technology
Soybean is the main industrial crops of China, and the Northeast is the main producing region of China soybean, in recent years, implements under the drive of soybean development plan in the Ministry of Agriculture, and the cultivated area of our province soybean is surged year by year.Simultaneously also more and more stricter to the quality standard of the seed selection of soybean, outlet, processing.
The developed country such as Japan-US takes the lead in launching research in grain seed context of detection.Zayas etc. utilize computer image processing technology from wheat seed picture, to extract morphological feature parameter, apply kind and the non-wheat composition of these feature differentiation wheats.LiaoK. wait using corn kernel image with 34 characteristic parameters the input variable as neural network, Grain Morphology can be fallen into 5 types, the rate of accuracy reached 93% of complete seed being classified through the neural network of study.Nair M. etc. based on morphological parameters and colored parameter study the detection technique of wheat surface blot.When using morphological parameters separately, recognition accuracy is 89.4%; When using colored parameter separately, recognition accuracy is 71.4%; When combining form parameter and colored parameter, recognition accuracy is 93.2%.Cardarelli etc. have studied the detection technique of rice broken kernel, have proposed to using the average of R, G, B component as discriminant parameter, and the recognition accuracy of the damaged seeds of three kinds of rice is all reached more than 80%.Paliwal etc. have studied the recognition technology of different cultivars wheat, based on colored parameter and Fourier descriptors, utilize minimum distance classifier, and the recognition accuracy of five kinds of Canadian wheats is respectively to 100%, 94%, 93%, 99% and 95%.Steenhoek etc. have studied the detection technique of corn moldy kernel, broken kernel.Directly, using the R of original image, G, B pixel value as characteristic parameter, adopt probabilistic neural network sorter, recognition accuracy has reached 92%.Chtioui Y. etc. has proposed by computer vision technique, to evaluate as pattern classification instrument by Rough sets theory the method for broad bean quality.This is theoretical proposes to distinguish qualified, damaged, too small, foreign peoples's broad bean and stone with two kinds of different discrete methods.35 characteristic parameters that utilization is extracted from coloured image are classified, and classification results has been compared consistent degree preferably with discriminatory analysis statistical classification result.Tahir etc. have studied the relation of different in moisture content and color in three grow wheats, structural property, morphological characteristic based on machine vision, show that the relation that bulk grain compares color, structural property and moisture with the single cereal that shells is obvious.
The screening of soybean kernel is that the Ministry of Agriculture implements the calculated important indicator of soybean development, and above-mentioned detection method all can not realize Real-Time Monitoring, and staff can not carry out Real-Time Monitoring to the screening process of soybean kernel.
Summary of the invention
The present invention is in order to solve in the screening process of soybean kernel, can not carry out to the screening process of soybean kernel the problem of Real-Time Monitoring, and then provides a kind of Real-Time Monitoring soybean kernel selected device.
The device that Real-Time Monitoring soybean kernel is selected, it comprises frequency converter 9, asynchronous machine 10, enters kind of device 11, photoelectric sensor 1, single-chip microcomputer 2, intelligent video camera head 3, controllor for step-by-step motor 4, stepper motor 5, moving belt 6, camera bellows 7, first are blown a cylinder a, second blows a cylinder b, the first air pump and the second air pump;
The top that kind of mouth 8 is positioned at moving belt 6 that goes out of entering kind of device 11, described moving belt 6 is horizontally disposed with, and moving belt 6 is arranged in camera bellows 7; Be positioned on the camera bellows 7 of moving belt 6 ends and have out kind of mouth 8;
Intelligent video camera head 3 is suspended on camera bellows 7, and the shooting face of described intelligent video camera head 3 is towards travelling belt; The first air blowing cylinder a and a second air blowing cylinder b are arranged in parallel, and are all positioned at the side of moving belt 6;
The detection signal output terminal of photoelectric sensor 1 connects the detection signal input end of single-chip microcomputer 2; The control signal output terminal of intelligent video camera head 3 connects the control signal input end of single-chip microcomputer 2, the first air pump control signal output terminal of described single-chip microcomputer 2 connects the control signal input end of the first air pump, the second air pump control signal output terminal of single-chip microcomputer 2 connects the control signal input end of the second air pump, the step motor control signal output part of single-chip microcomputer 2 connects the control signal input end of controllor for step-by-step motor 4, and the control signal output terminal of described controllor for step-by-step motor 4 connects the control signal input end of stepper motor 5.
The invention has the beneficial effects as follows: the present invention adopts intelligent camera to carry out overall process to the screening of soybean kernel and monitors in real time, utilizes Single Chip Microcomputer (SCM) system effectively to control the screening of soybean kernel, thereby reach the object of Real-Time Monitoring.
Accompanying drawing explanation
Fig. 1 is the mechanical construction drawing of the selected device of Real-Time Monitoring soybean kernel;
Fig. 2 is the theory diagram of the electric part of the selected device of Real-Time Monitoring soybean kernel;
Fig. 3 enters kind of an electrical principle block diagram for device part in the selected device of Real-Time Monitoring soybean kernel.
Embodiment
Embodiment one: present embodiment is described below in conjunction with Fig. 1 and Fig. 2, the selected device of Real-Time Monitoring soybean kernel described in present embodiment, it comprises frequency converter 9, asynchronous machine 10, enters kind of device 11, photoelectric sensor 1, single-chip microcomputer 2, intelligent video camera head 3, controllor for step-by-step motor 4, stepper motor 5, moving belt 6, camera bellows 7, first are blown a cylinder a, second blows a cylinder b, the first air pump and the second air pump;
The top that kind of mouth 8 is positioned at moving belt 6 that goes out of entering kind of device 11, described moving belt 6 is horizontally disposed with, and moving belt 6 is arranged in camera bellows 7; Be positioned on the camera bellows 7 of moving belt 6 ends and have out kind of mouth 8;
Intelligent video camera head 3 is suspended on camera bellows 7, and the shooting face of described intelligent video camera head 3 is towards travelling belt; The first air blowing cylinder a and a second air blowing cylinder b are arranged in parallel, and are all positioned at the side of moving belt 6;
The detection signal output terminal of photoelectric sensor 1 connects the detection signal input end of single-chip microcomputer 2; The control signal output terminal of intelligent video camera head 3 connects the control signal input end of single-chip microcomputer 2, the first air pump control signal output terminal of described single-chip microcomputer 2 connects the control signal input end of the first air pump, the second air pump control signal output terminal of single-chip microcomputer 2 connects the control signal input end of the second air pump, the step motor control signal output part of single-chip microcomputer 2 connects the control signal input end of controllor for step-by-step motor 4, and the control signal output terminal of described controllor for step-by-step motor 4 connects the control signal input end of stepper motor 5.
Principle of work:
Single-chip microcomputer 2 receives the beans image information that intelligent video camera head 3 sends, according to beans image information, obtain the characteristic parameter of beans, the characteristic parameter of beans is carried out to analysis of neural network, according to the quality of the result judgement beans after analysis of neural network, control a first air blowing cylinder a beans of greyness or worm-eaten is blown off, control the second air blowing cylinder b the beans going mouldy is blown off.
Embodiment two: present embodiment is further qualified the selected device of Real-Time Monitoring soybean kernel described in embodiment one, in present embodiment, the model of intelligent video camera head 3 is VC2065/E.
In present embodiment, intelligent video camera head 3 can work alone by PC, the High Performance DSP that control able to programme is contained in inside, and integrated RS-232 hardware interface and single-chip microcomputer carry out serial data transmission.
Embodiment three: present embodiment is further qualified the selected device of Real-Time Monitoring soybean kernel described in embodiment one, in present embodiment, the transfer rate of moving belt 6 is 40cm/s.
Embodiment four: present embodiment is further qualified the selected device of Real-Time Monitoring soybean kernel described in embodiment two, in present embodiment, the thickness of moving belt 6 is 2mm.
Embodiment five: present embodiment is further qualified the selected device of Real-Time Monitoring soybean kernel described in embodiment one, in present embodiment, the model of entering kind of device 11 is 2QXP-1.
Claims (5)
1. the selected device of Real-Time Monitoring soybean kernel, is characterized in that: it comprises frequency converter (9), asynchronous machine (10), enters kind of a device (11), photoelectric sensor (1), single-chip microcomputer (2), intelligent video camera head (3), controllor for step-by-step motor (4), stepper motor (5), moving belt (6), camera bellows (7), first are blown cylinder (a), second blows cylinder (b), the first air pump and the second air pump;
Frequency converter (9) access three-phase supply, described frequency converter (9) power supply signal output terminal connects the power supply signal input end of asynchronous machine (10); Described asynchronous machine (10) drives into kind of a device (11) and works;
The top that kind of a mouth (8) is positioned at moving belt (6) that goes out of entering kind of a device (11), described moving belt (6) is horizontally disposed with, and moving belt (6) is arranged in camera bellows (7); Be positioned on the camera bellows (7) of moving belt (6) end and have out kind of a mouth (8);
It is upper that intelligent video camera head (3) is suspended on camera bellows (7), and the shooting face of described intelligent video camera head (3) is towards travelling belt; First blow cylinder (a) and second blow tin (b) be arranged in parallel, and be all the positioned at moving belt side of (6);
Stepper motor (5) access three-phase supply, for driving driving-belt (6) work; The first air pump is for providing gas to the first air blowing cylinder (a); The second air pump is for providing gas to the second air blowing cylinder (a);
The detection signal output terminal of photoelectric sensor (1) connects the detection signal input end of single-chip microcomputer (2); The control signal output terminal of intelligent video camera head (3) connects the control signal input end of single-chip microcomputer (2), the first air pump control signal output terminal of described single-chip microcomputer (2) connects the control signal input end of the first air pump, the second air pump control signal output terminal of single-chip microcomputer (2) connects the control signal input end of the second air pump, the step motor control signal output part of single-chip microcomputer (2) connects the control signal input end of controllor for step-by-step motor (4), and the control signal output terminal of described controllor for step-by-step motor (4) connects the control signal input end of stepper motor (5).
2. the selected device of Real-Time Monitoring soybean kernel according to claim 1, is characterized in that: the model of intelligent video camera head (3) is VC2065/E.
3. the selected device of Real-Time Monitoring soybean kernel according to claim 1, is characterized in that: the transfer rate of moving belt (6) is 40cm/s.
4. the selected device of Real-Time Monitoring soybean kernel according to claim 2, is characterized in that: the thickness of moving belt (6) is 2mm.
5. the selected device of Real-Time Monitoring soybean kernel according to claim 1, is characterized in that: the model of entering kind of a device (11) is 2QXP-1.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201410037953.5A CN103760163A (en) | 2014-01-26 | 2014-01-26 | Device for monitoring selection of soybean seeds in real time |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105092494A (en) * | 2015-07-17 | 2015-11-25 | 浙江大学 | Grain classification method based on multiband LED array and system |
| CN106185244A (en) * | 2016-08-30 | 2016-12-07 | 中电装备山东电子有限公司 | A kind of intelligence mistake proofing transmission system |
| CN106311629A (en) * | 2016-09-28 | 2017-01-11 | 东北农业大学 | Soybean seed grading device based on embedded machine vision |
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| JP5216977B2 (en) * | 2006-07-13 | 2013-06-19 | 秋田県 | Fruit discrimination structure |
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| JP5216977B2 (en) * | 2006-07-13 | 2013-06-19 | 秋田県 | Fruit discrimination structure |
| CN1943886A (en) * | 2006-10-13 | 2007-04-11 | 江苏大学 | Online detecting device and method based on computer vision for soft capsule quality |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105092494A (en) * | 2015-07-17 | 2015-11-25 | 浙江大学 | Grain classification method based on multiband LED array and system |
| CN105092494B (en) * | 2015-07-17 | 2018-02-06 | 浙江大学 | A kind of grain sorting technique and system based on multiband LED array |
| CN106185244A (en) * | 2016-08-30 | 2016-12-07 | 中电装备山东电子有限公司 | A kind of intelligence mistake proofing transmission system |
| CN106311629A (en) * | 2016-09-28 | 2017-01-11 | 东北农业大学 | Soybean seed grading device based on embedded machine vision |
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Application publication date: 20140430 |