CN112741069A - Orchard accurate physical prevention and control plant protection device and method based on machine vision - Google Patents
Orchard accurate physical prevention and control plant protection device and method based on machine vision Download PDFInfo
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- 230000002265 prevention Effects 0.000 title claims abstract description 94
- 239000002420 orchard Substances 0.000 title claims abstract description 48
- 238000000034 method Methods 0.000 title claims abstract description 12
- CBENFWSGALASAD-UHFFFAOYSA-N Ozone Chemical compound [O-][O+]=O CBENFWSGALASAD-UHFFFAOYSA-N 0.000 claims abstract description 159
- 230000007246 mechanism Effects 0.000 claims abstract description 86
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 58
- 241000607479 Yersinia pestis Species 0.000 claims abstract description 41
- 201000010099 disease Diseases 0.000 claims abstract description 35
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 35
- 239000003595 mist Substances 0.000 claims abstract description 17
- 241000238631 Hexapoda Species 0.000 claims abstract description 13
- 235000013399 edible fruits Nutrition 0.000 claims abstract description 7
- 238000004887 air purification Methods 0.000 claims description 11
- 238000004891 communication Methods 0.000 claims description 9
- 238000003860 storage Methods 0.000 claims description 9
- 238000013527 convolutional neural network Methods 0.000 claims description 7
- 238000013135 deep learning Methods 0.000 claims description 7
- 210000003462 vein Anatomy 0.000 claims description 7
- 239000000284 extract Substances 0.000 claims description 6
- 239000007921 spray Substances 0.000 claims 2
- 239000000575 pesticide Substances 0.000 abstract description 8
- 239000000447 pesticide residue Substances 0.000 abstract description 6
- 239000007789 gas Substances 0.000 description 12
- 238000012545 processing Methods 0.000 description 8
- 238000005507 spraying Methods 0.000 description 8
- 238000012271 agricultural production Methods 0.000 description 3
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 3
- 239000001301 oxygen Substances 0.000 description 3
- 229910052760 oxygen Inorganic materials 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 125000004430 oxygen atom Chemical group O* 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000000889 atomisation Methods 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005684 electric field Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 235000001968 nicotinic acid Nutrition 0.000 description 1
- 238000005096 rolling process Methods 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0003—Atomisers or mist blowers
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0089—Regulating or controlling systems
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- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Insects & Arthropods (AREA)
- Pest Control & Pesticides (AREA)
- Wood Science & Technology (AREA)
- Zoology (AREA)
- Environmental Sciences (AREA)
- Catching Or Destruction (AREA)
Abstract
本发明提供一种基于机器视觉的果园精准物理防控植保装置及方法，上述的基于机器视觉的果园精准物理防控植保装置，包括：图像采集机构、臭氧控制机构以及物理防控机构；所述物理防控机构用于通过臭氧与水雾结合生成羟基自由基，并喷洒到果树上；所述图像采集机构用于采集树体图像；所述臭氧控制机构用于基于所述树体图像获取与树冠大小、叶量多少和病虫害程度一一对应的臭氧浓度权重，从而得到臭氧浓度值，并根据所述臭氧浓度值控制所述物理防控机构的臭氧用量。本发明的基于机器视觉的果园精准物理防控植保装置，可以减少农药的使用，实现作物无农残物理防控；可以保证臭氧释放量的精准控制，有效减少臭氧损失、节约成本、防治病虫害。
The present invention provides a plant protection device and method for precise physical prevention and control of orchards based on machine vision. The above-mentioned precise physical prevention and control plant protection device for orchards based on machine vision includes: an image acquisition mechanism, an ozone control mechanism and a physical prevention and control mechanism; the The physical prevention and control mechanism is used to generate hydroxyl radicals through the combination of ozone and water mist, and sprayed on the fruit trees; the image acquisition mechanism is used to collect tree images; The size of the tree crown, the amount of leaves, and the degree of pest and disease damage are one-to-one corresponding to the ozone concentration weight, so as to obtain the ozone concentration value, and control the ozone dosage of the physical prevention and control mechanism according to the ozone concentration value. The machine vision-based precise physical prevention and control plant protection device for orchards of the present invention can reduce the use of pesticides, realize the physical prevention and control of crops without pesticide residues; can ensure the precise control of ozone emission, effectively reduce ozone loss, save costs, and prevent and control diseases and insect pests.
Description
Technical Field
The invention relates to the technical field of agricultural mechanical equipment, in particular to an orchard accurate physical prevention and control plant protection device and method based on machine vision.
Background
With the improvement of living standard of people, the demand of high-quality agricultural products is gradually increased, and the orchard operation scale in China is continuously enlarged. For fruit trees, although the pesticide can effectively prevent and treat plant diseases and insect pests, the quality safety of agricultural products can be directly influenced by unreasonable use of the pesticide, the produced threat is most direct, and the harm is most prominent. Therefore, in order to reduce agricultural pollution, ensure the quality of agricultural products and guarantee the life health and safety of people, the orchard pest control mode needs to be improved urgently.
Disclosure of Invention
The invention provides an orchard accurate physical prevention and control plant protection device and method based on machine vision, which are used for solving the problem that pesticides are unreasonably used in an orchard pest prevention and control mode in the prior art.
The invention provides an orchard accurate physical prevention and control plant protection device based on machine vision, which comprises: the device comprises an image acquisition mechanism, an ozone control mechanism and a physical prevention and control mechanism;
the physical prevention and control mechanism is used for generating hydroxyl radicals by combining ozone and water mist and spraying the hydroxyl radicals onto fruit trees;
the image acquisition mechanism is used for acquiring tree images;
the ozone control mechanism is used for acquiring ozone concentration weights corresponding to the size of a tree crown, the quantity of leaves and the pest and disease damage degree one by one on the basis of the tree body image so as to obtain an ozone concentration value, and controlling the ozone using amount of the physical prevention and control mechanism according to the ozone concentration value.
According to the orchard accurate physical prevention and control plant protection device based on the machine vision, the physical prevention and control mechanism comprises an air purification assembly, an ozone generation assembly, a water supply assembly and an atomizer, wherein the atomizer is provided with an atomization nozzle;
the air purification assembly is communicated with the ozone generation assembly and is used for providing pure air for the ozone generation assembly so that the ozone generation assembly can generate ozone;
the water supply assembly is communicated with the atomizer to form water mist through the atomizing nozzle;
the ozone generating assembly is communicated with the atomizer so that the ozone is combined with the water mist to generate hydroxyl radicals.
According to the orchard accurate physical prevention and control plant protection device based on the machine vision, the air purification assembly comprises an air filter element, an air pump, a triple filter and an air storage tank which are sequentially communicated;
the air filter is used for preliminarily filtering the outside air, the triple filter is used for removing water and oil from the preliminarily filtered air, and the treated pure air is conveyed to the air storage tank.
According to the orchard precise physical prevention and control plant protection device based on the machine vision, an air duct communicated with the ozone generating assembly is constructed in the atomizer, a flow guide cover is arranged in the air duct, a grid plate channel is communicated with the outlet of the air duct, and the outlet of the grid plate channel faces the spraying direction of the atomizing nozzle.
According to the orchard precise physical prevention and control plant protection device based on the machine vision, the water supply assembly comprises a water tank and a water pump, and the water pump is used for conveying water stored in the water tank to the atomizing nozzle to form water mist.
According to the orchard precise physical prevention and control plant protection device based on the machine vision, the image acquisition mechanism comprises a holder and a camera mounted on the holder.
According to the orchard precise physical prevention and control plant protection device based on the machine vision, the ozone control mechanism comprises an upper computer and a lower computer, the upper computer is in communication connection with the image acquisition mechanism and the lower computer, and the lower computer is in communication connection with the physical prevention and control mechanism.
According to the orchard accurate physical prevention and control plant protection device based on the machine vision, the orchard accurate physical prevention and control plant protection device based on the machine vision further comprises a travelling mechanism, and the travelling mechanism comprises a traction frame and an anti-sinking wheel arranged on the traction frame;
the image acquisition mechanism, the ozone control mechanism and the physical prevention and control mechanism are all installed on the traction frame.
The invention also provides an orchard accurate physical prevention and control plant protection method based on machine vision, which comprises the following steps:
preprocessing the collected tree body image, and determining the working range of the physical prevention and control mechanism;
extracting the outline of the crown, calculating the diameter of the crown, and determining the ozone concentration weight corresponding to the size of the crown;
extracting leaf contour and main vein skeleton, calculating area and quantity of leaves, and determining ozone concentration weight corresponding to the quantity of leaves;
performing pest and disease identification on the tree body image based on a convolutional neural network deep learning algorithm, calculating the types and the number of pests and diseases, and determining the ozone concentration weight corresponding to the pest and disease degree;
and obtaining an ozone concentration value according to ozone concentration weights corresponding to the size of the crown, the quantity of leaves and the pest and disease damage degree one by one, and controlling the ozone consumption of the physical prevention and control mechanism according to the ozone concentration value.
According to the orchard accurate physical prevention and control plant protection method based on the machine vision, the ozone using amount of the physical prevention and control mechanism controlled according to the ozone concentration value is specifically as follows:
the upper computer sends the ozone concentration value to the lower computer, and the lower computer controls the starting and stopping of the physical prevention and control mechanism according to the ozone concentration value.
The orchard accurate physical prevention and control plant protection device and method based on machine vision provided by the invention have the advantages that an ozone control mechanism preprocesses tree images acquired by an image acquisition mechanism to determine the working range of the physical prevention and control mechanism; performing crown part processing on the tree body image, extracting a crown outline, calculating the diameter of the crown, and determining the ozone concentration weight corresponding to the size of the crown; carrying out leaf part processing on the tree body image, extracting leaf outlines and main vein skeletons, calculating the area and the quantity of leaves, and determining the ozone concentration weight corresponding to the quantity of the leaves; performing pest and disease identification on the tree body image based on a convolutional neural network deep learning algorithm, calculating the types and the number of pests and diseases, and determining the ozone concentration weight corresponding to the pest and disease degree; and obtaining an ozone concentration value according to ozone concentration weights corresponding to the size of the crown, the quantity of leaves and the pest and disease damage degree one by one, and controlling the ozone consumption of the physical prevention and control mechanism according to the ozone concentration value. The orchard precise physical prevention and control plant protection device based on machine vision can reduce the use of pesticides and realize the physical prevention and control of crops without pesticide residues; can ensure the accurate control of the ozone release amount, effectively reduce the ozone loss, save the cost and prevent and treat the plant diseases and insect pests.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a top view of an orchard precise physical prevention and control plant protection device based on machine vision provided by the invention;
FIG. 2 is a front view of the orchard precise physical prevention and control plant protection device based on machine vision provided by the invention;
FIG. 3 is a partial schematic view of the orchard precise physical prevention and control plant protection device based on machine vision provided by the invention;
FIG. 4 is a view from the A-A direction of FIG. 3;
reference numerals:
1: a traction frame; 2: a camera; 3: a water tank;
4: a triple filter; 5: an ozone power supply; 6: a gas storage tank;
7: an air pump; 8: a fan; 9: an atomizer;
10: an ozone generator; 11: a motor; 12: an air filter element;
13: an anti-sinking wheel; 14: a lower computer; 15: an upper computer;
16: a water pump; 17: a pod; 18: an electric generator.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
China is developing from traditional agriculture to intelligent, precise and modern agriculture, and the rapid development of a machine vision technology and an automatic control technology provides a good development platform for the intellectualization and the precision of agricultural production. Machine vision is used for replacing human eyes, and orchard comprehensive management is carried out through automatic control, so that agricultural production is more accurate and efficient. The fruit tree body image is obtained based on machine vision, automatic target aiming and accurate prevention and control are realized, resource waste can be reduced, and agricultural production cost is saved; the ozone water is used for physical prevention and control, so that the use of pesticides can be reduced, and the orchard modernization is realized, and the environment is green and has no pesticide residues.
The orchard precise physical prevention and control plant protection device based on machine vision of the invention is described below with reference to fig. 1 to 4.
As shown in fig. 1 and fig. 2, the orchard precise physical prevention and control plant protection device based on machine vision according to the embodiment of the present invention includes: the device comprises an image acquisition mechanism, an ozone control mechanism and a physical prevention and control mechanism;
the physical prevention and control mechanism is used for generating hydroxyl radicals by combining ozone and water mist and spraying the hydroxyl radicals onto fruit trees; the image acquisition mechanism is used for acquiring tree images; the ozone control mechanism is used for acquiring ozone concentration weights corresponding to the size of the crown, the quantity of leaves and the pest and disease damage degree one by one on the basis of the tree body image so as to obtain an ozone concentration value, and controlling the ozone using amount of the physical prevention and control mechanism according to the ozone concentration value.
In the embodiment of the invention, the ozone control mechanism preprocesses the tree images acquired by the image acquisition mechanism and determines the working range of the physical prevention and control mechanism; performing crown part processing on the tree body image, extracting a crown outline, calculating the diameter of the crown, and determining the ozone concentration weight corresponding to the size of the crown; carrying out leaf part processing on the tree body image, extracting leaf outlines and main vein skeletons, calculating the area and the quantity of leaves, and determining the ozone concentration weight corresponding to the quantity of the leaves; performing pest and disease identification on the tree body image based on a convolutional neural network deep learning algorithm, calculating the types and the number of pests and diseases, and determining the ozone concentration weight corresponding to the pest and disease degree; and obtaining an ozone concentration value according to ozone concentration weights corresponding to the size of the crown, the quantity of leaves and the pest and disease damage degree one by one, and controlling the ozone consumption of the physical prevention and control mechanism according to the ozone concentration value. The orchard precise physical prevention and control plant protection device based on machine vision can reduce the use of pesticides and realize the physical prevention and control of crops without pesticide residues; can ensure the accurate control of the ozone release amount, effectively reduce the ozone loss, save the cost and prevent and treat the plant diseases and insect pests.
On the basis of the above embodiment, the physical prevention and control mechanism comprises an air purification assembly, an ozone generation assembly, a water supply assembly and an atomizer 9, wherein the atomizer 9 is provided with an atomizing nozzle;
the air purification assembly is communicated with the ozone generation assembly and is used for providing pure air for the ozone generation assembly so that the ozone generation assembly can generate ozone;
the water supply assembly is communicated with the atomizer 9 to form water mist through the atomizing nozzle;
the ozone generating assembly is communicated with the atomizer 9 so that the ozone is combined with the water mist to generate hydroxyl radicals.
It should be noted that the air purification assembly provides purified air for the ozone generation assembly, thereby prolonging the service life of the ozone generation assembly.
In the embodiment of the invention, the water supply assembly is communicated with the atomizer 9, and after water provided by the water supply assembly reaches the atomizing nozzle, the atomizing nozzle enables pressure water flow to form water mist; the air purification assembly is used for providing purified air for the ozone generation assembly, the ozone generation assembly generates ozone according to the purified air, ozone gas is conveyed to the atomizer 9 and then is combined with water mist to generate hydroxyl radicals, and the hydroxyl radicals are sprayed onto fruit trees.
On the basis of the above embodiment, the air purification assembly comprises an air filter element 12, an air pump 7, a triple filter 4 and an air storage tank 6 which are sequentially communicated;
the air filter element 12 is used for preliminarily filtering the outside air, and the triple filter 4 is used for removing water and oil from the preliminarily filtered air and conveying the treated pure air to the air storage tank 6.
It should be noted that, air filter element 12 filters the dust pollution, inhales comparatively clean gas, and air pump 7 carries triple filter 4 with the gas after air filter element 12 preliminary treatment through the air duct, removes oil through the dewatering of triple filter 4, obtains pure air to carry pure air to gas holder 6. Wherein, a certain amount of air pressure is stored in the air storage tank 6, which ensures that continuous pure air is provided for the ozone generating component and prolongs the service life of the ozone generating component.
On the basis of the above embodiment, the ozone generating assembly includes an ozone generator 10 in communication with the air tank 6, the ozone generator 10 being configured to generate ozone from the secondarily treated purified air provided by the triple filter 4 and deliver the ozone gas to the atomizer 9.
It should be noted that the ozone generating assembly further includes an ozone power supply 5, the ozone power supply 5 supplies power to the ozone generator 10, when the ozone generator 10 is powered on, an alternating high-voltage electric field is generated to generate corona discharge for the oxygen-containing gas, and high-energy electrons in the corona ionize oxygen molecules to form oxygen atoms, and combine the oxygen atoms with the oxygen molecules to form ozone molecules, so as to generate ozone. Wherein, the ozone generator 10 is respectively communicated with the gas storage tank 6 and the atomizer 9.
On the basis of the above-described embodiment, as shown in fig. 3 and 4, a plurality of atomizer heads are arranged symmetrically with respect to the axial direction of the atomizer 9, that is, the atomizer heads are arranged symmetrically at different angles on both sides of the atomizer 9.
It should be noted that when a plurality of atomizing nozzles are used simultaneously, the spraying angle can reach 270 degrees.
On the basis of the above embodiment, an air duct communicated with the ozone generating assembly is constructed in the atomizer 9, a flow guide cover 17 is arranged in the air duct, a grid plate channel is communicated with an outlet of the air duct, and the outlet direction of the grid plate channel faces the spraying direction of the atomizing nozzle.
It should be noted that the inlet of the air duct is connected to the ozone generator 10, the blower 8 is installed in the air duct, and the blower 8 is driven by the motor 11, so as to accelerate the flow speed of the ozone gas in the air duct.
It can be understood that the air guide sleeve 17 is arranged in the air duct, ozone gas is conveyed to two sides of the atomizer 9 through the air guide sleeve 17, outlets of the air duct are arranged on two sides of the atomizer 9, a grid plate channel is communicated with the outlets of the air duct, and the outlet direction of the grid plate channel faces the spraying direction of the atomizing nozzle, so that the ozone gas is combined with water mist sprayed by the atomizing nozzle after the ozone gas passes through the grid plate channel.
On the basis of the above embodiment, the water supply assembly includes the water tank 3 and the water pump 16, and the water pump 16 is used for delivering the water stored in the water tank 3 to the atomizer head to form the water mist.
The water pump 16 is connected to the atomizer 9 through a water conduit.
On the basis of the embodiment, the orchard precise physical prevention and control plant protection device based on machine vision further comprises a travelling mechanism, wherein the travelling mechanism comprises a traction frame 1 and an anti-sinking wheel 13 arranged on the traction frame;
the image acquisition mechanism, the ozone control mechanism and the physical prevention and control mechanism are all arranged on the traction vehicle frame 1.
It should be noted that the anti-trap wheels 13 are symmetrically arranged on both sides of the towing carriage 1. The tire surface of the anti-sinking wheel 13 is wider, the contact area with the ground is large, the pressure intensity is small, the stability is good, and the device can be prevented from sinking when soil is loose or muddy; and the device can be prevented from rolling over under the condition that the road is uneven. Furthermore, the contact surface of the anti-slip wheel 13 is rough, and the slip can be prevented by large friction force.
It will be appreciated that the towing carriage 1 may be towed by agricultural equipment such as a tractor to be towed thereby.
On the basis of the above embodiment, the image capturing mechanism includes a pan/tilt head and a camera 2 mounted on the pan/tilt head.
It should be noted that the camera 2 is a high-precision camera, the camera 2 and the pan-tilt are installed on the top of the water tank 3, the water tank 3 is located at the front end of the traction frame 1, and the two cameras 2 are symmetrically arranged on two sides of the traction frame 1.
It can be understood that the camera 2 has high precision and small delay, and can clearly reflect the tree conditions at the two sides of the road; the cloud platform utilizes bionics principle to carry out the anti-shake, can reduce the vibrations of pulling frame 1 and to camera 2's influence to guarantee camera 2's steady operation.
On the basis of the above embodiment, the ozone control mechanism includes an upper computer 15 and a lower computer 14, the upper computer 15 is in communication connection with the image acquisition mechanism and the lower computer 14, and the lower computer 14 is in communication connection with the physical prevention and control mechanism.
The image acquisition mechanism and the lower computer 14 are connected with the upper computer 15 through data transmission ports, tree images acquired by the image acquisition mechanism are uploaded to the upper computer 15 provided with image processing software through the data transmission ports, and the upper computer 15 judges whether physical prevention and control are needed or not and determines the ozone consumption of the physical prevention and control through the preprocessing of the image processing software and the identification of the tree images and plant diseases and insect pests. The upper computer 15 transmits the control instruction to the lower computer 14, so as to realize the control of the physical prevention and control mechanism and carry out physical prevention and control work.
Specifically, the camera 2 sends the collected tree body image to the upper computer 15, and the upper computer 15 preprocesses the tree body image collected by the image collection mechanism to determine the working range of the physical prevention and control mechanism; the upper computer 15 carries out crown part processing on the tree body image, extracts the crown outline, calculates the crown diameter and determines the ozone concentration weight corresponding to the size of the crown; the upper computer 15 carries out leaf part processing on the tree body image, extracts leaf outlines and main vein skeletons, calculates the area and the quantity of leaves, and determines the ozone concentration weight corresponding to the quantity of the leaves; the upper computer 15 identifies the plant diseases and insect pests of the tree body image based on a convolutional neural network deep learning algorithm, calculates the types and the number of the plant diseases and insect pests, and determines the ozone concentration weight corresponding to the plant disease and insect pest degree; the upper computer 15 obtains an ozone concentration value according to ozone concentration weights corresponding to the sizes of the crowns, the quantity of leaves and the pest and disease damage degree one by one; the upper computer 15 transmits a control instruction about the ozone concentration value to the lower computer 14, the camera 2, the cradle head, the water pump 16, the air pump 7, the ozone power supply 5 and the motor 11 are respectively connected with each control port of the lower computer 14, automatic control over the physical prevention and control mechanism and the image acquisition mechanism is achieved through the lower computer 14, and the effects of orchard pest control and green pesticide residue prevention and control are achieved.
The physical prevention and control mechanism further comprises a generator 18, and the generator 18 is connected with the upper computer 15 and the lower computer 14, and is used for supplying power to the upper computer 15 and the lower computer 14 and supplying power to power-requiring components of the physical prevention and control mechanism. For example, the water pump 16, the air pump 7 and the motor 11 are all electrically connected with the generator 18.
The embodiment of the invention also provides an orchard precise physical prevention and control plant protection method based on machine vision, which is based on the orchard precise physical prevention and control plant protection device based on machine vision and comprises the following steps:
s10, the upper computer 15 preprocesses the tree images collected by the camera to determine the working range of the physical prevention and control mechanism;
judging whether tree bodies are arranged on two sides, and determining the working range of the atomizing nozzle, namely bidirectional spraying or unidirectional spraying;
the upper computer 15 extracts the outline of the crown, calculates the diameter of the crown and determines the ozone concentration weight corresponding to the size of the crown;
performing crown part processing on the images collected by the cameras 2 at the two sides, extracting the contour of the crown, calculating the diameter of the crown, and determining the size of the crown and the corresponding ozone concentration weight;
the upper computer 15 extracts the leaf contour and the main vein skeleton, calculates the area and the quantity of the leaves, and determines the ozone concentration weight corresponding to the quantity of the leaves;
processing the leaves of the images collected by the cameras 2 at the two sides, extracting the leaf outline and the main vein skeleton, calculating the area and the quantity of the leaves, and determining the quantity of the leaves and the ozone concentration weight corresponding to the quantity of the leaves;
the upper computer 15 identifies the plant diseases and insect pests of the tree body image based on a convolutional neural network deep learning algorithm, calculates the types and the number of the plant diseases and insect pests, and determines the ozone concentration weight corresponding to the plant disease and insect pest degree;
and performing pest identification on the images collected by the cameras 2 on the two sides based on a convolutional neural network deep learning algorithm, calculating the types and the number of pests, and determining the pest degree and the ozone concentration weight corresponding to the pest degree.
And S20, obtaining an ozone concentration value according to the ozone concentration weights corresponding to the size of the tree crown, the leaf amount and the pest and disease damage degree one by one, and controlling the ozone dosage of the physical prevention and control mechanism according to the ozone concentration value.
And calculating an ozone concentration value according to the sizes of the tree crowns, the leaf quantity and different ozone concentration weights of the pest and disease damage degree.
On the basis of the above embodiment, the specific ozone dosage for controlling the physical prevention and control mechanism according to the ozone concentration value is as follows:
the upper computer 15 sends the ozone concentration value to the lower computer 14, and the lower computer 14 controls the start and stop of the physical prevention and control mechanism according to the ozone concentration value.
It should be noted that the upper computer 15 transmits a control instruction about the ozone concentration value to the lower computer 14, the camera 2, the cradle head, the water pump 16, the air pump 7, the ozone power supply 5 and the motor 11 are respectively connected with each control port of the lower computer 14, and the lower computer 14 controls the start and stop of the camera 2, the cradle head, the water pump 16, the air pump 7, the ozone power supply 5 and the motor 11.
The orchard precise physical prevention and control plant protection method based on machine vision can reduce the use of pesticides and realize the physical prevention and control of crops without pesticide residues; can ensure the accurate control of the ozone release amount, effectively prevent and treat plant diseases and insect pests, reduce the ozone loss and save the cost.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
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| Application Number | Priority Date | Filing Date | Title |
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| CN202110047715.2A CN112741069B (en) | 2021-01-14 | 2021-01-14 | Precise physical control plant protection devices and methods for orchards based on machine vision |
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| CN202110047715.2A CN112741069B (en) | 2021-01-14 | 2021-01-14 | Precise physical control plant protection devices and methods for orchards based on machine vision |
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| CN112741069A true CN112741069A (en) | 2021-05-04 |
| CN112741069B CN112741069B (en) | 2023-09-12 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113468964A (en) * | 2021-05-31 | 2021-10-01 | 山东省邮电工程有限公司 | Hyperspectrum-based agricultural disease and pest monitoring method and device |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5816498A (en) * | 1996-12-04 | 1998-10-06 | Ozone Technologies, Inc. | Ozonation system for agricultural crop and field sprayer |
| US6499671B1 (en) * | 2000-09-01 | 2002-12-31 | Del Industries, Inc. | Ozone systems and methods for agricultural applications |
| JP2003092970A (en) * | 2001-09-25 | 2003-04-02 | Fuji Robin Ind Ltd | Pest control machine |
| CN203539735U (en) * | 2013-11-08 | 2014-04-16 | 中国农业大学 | Ozone water spraying device |
| CN204994369U (en) * | 2015-04-13 | 2016-01-27 | 陈良忠 | Water atomization of agricultural disease ozone is irrigated intelligence and is prevented and treated system |
| CN106070155A (en) * | 2016-07-30 | 2016-11-09 | 重庆科技学院 | Automatic target detection variable rate spray system based on PLC and control method thereof |
| CN109819957A (en) * | 2019-02-21 | 2019-05-31 | 山东理工大学 | A high-voltage ionized air-delivered plant protection tractor that only adds water and no pesticides |
| CN110140703A (en) * | 2019-04-22 | 2019-08-20 | 许祥洪 | A kind of intelligence physical sterilization deinsectization device and method |
| CN110235882A (en) * | 2019-06-28 | 2019-09-17 | 南京农业大学 | A multi-sensor based precision variable fruit tree pesticide application robot |
| CN214853837U (en) * | 2021-01-14 | 2021-11-26 | 农芯科技（北京）有限责任公司 | Precise physical control plant protection device for orchard based on machine vision |
-
2021
- 2021-01-14 CN CN202110047715.2A patent/CN112741069B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5816498A (en) * | 1996-12-04 | 1998-10-06 | Ozone Technologies, Inc. | Ozonation system for agricultural crop and field sprayer |
| US6499671B1 (en) * | 2000-09-01 | 2002-12-31 | Del Industries, Inc. | Ozone systems and methods for agricultural applications |
| JP2003092970A (en) * | 2001-09-25 | 2003-04-02 | Fuji Robin Ind Ltd | Pest control machine |
| CN203539735U (en) * | 2013-11-08 | 2014-04-16 | 中国农业大学 | Ozone water spraying device |
| CN204994369U (en) * | 2015-04-13 | 2016-01-27 | 陈良忠 | Water atomization of agricultural disease ozone is irrigated intelligence and is prevented and treated system |
| CN106070155A (en) * | 2016-07-30 | 2016-11-09 | 重庆科技学院 | Automatic target detection variable rate spray system based on PLC and control method thereof |
| CN109819957A (en) * | 2019-02-21 | 2019-05-31 | 山东理工大学 | A high-voltage ionized air-delivered plant protection tractor that only adds water and no pesticides |
| CN110140703A (en) * | 2019-04-22 | 2019-08-20 | 许祥洪 | A kind of intelligence physical sterilization deinsectization device and method |
| CN110235882A (en) * | 2019-06-28 | 2019-09-17 | 南京农业大学 | A multi-sensor based precision variable fruit tree pesticide application robot |
| CN214853837U (en) * | 2021-01-14 | 2021-11-26 | 农芯科技（北京）有限责任公司 | Precise physical control plant protection device for orchard based on machine vision |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113468964A (en) * | 2021-05-31 | 2021-10-01 | 山东省邮电工程有限公司 | Hyperspectrum-based agricultural disease and pest monitoring method and device |
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