CN113895629A - Vegetable growth monitoring and pesticide spraying system based on unmanned aerial vehicle - Google Patents
Vegetable growth monitoring and pesticide spraying system based on unmanned aerial vehicle Download PDFInfo
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- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64D—EQUIPMENT FOR FITTING IN OR TO AIRCRAFT; FLIGHT SUITS; PARACHUTES; ARRANGEMENT OR MOUNTING OF POWER PLANTS OR PROPULSION TRANSMISSIONS IN AIRCRAFT
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- B64D1/16—Dropping or releasing powdered, liquid, or gaseous matter, e.g. for fire-fighting
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- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0003—Atomisers or mist blowers
- A01M7/0014—Field atomisers, e.g. orchard atomisers, self-propelled, drawn or tractor-mounted
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- A—HUMAN NECESSITIES
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- 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
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- A—HUMAN NECESSITIES
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Abstract
The invention discloses a vegetable growth monitoring and pesticide spraying system based on an unmanned aerial vehicle, which comprises the unmanned aerial vehicle, a power supply, a control unit, a navigation unit, a monitoring unit and a pesticide spraying unit, wherein the power supply, the control unit, the navigation unit, the monitoring unit and the pesticide spraying unit are carried on the unmanned aerial vehicle, the monitoring unit comprises a camera and a light source generator, one end of the light source generator is electrically connected with the power supply, the other end of the light source generator is connected with a condensing lens, the light source generator is arranged on the camera, the power supply is electrically connected with the control unit, the navigation unit and the pesticide spraying unit, the navigation unit outputs position information data to the control unit, the control unit outputs control signals to the pesticide spraying unit and the monitoring unit, crops are monitored and fed back crop growth state information through the monitoring unit, and the control unit can control the pesticide spraying unit to carry out quantitative pesticide spraying on the crops according to the crop growth state information fed back by the monitoring unit, And spraying the pesticide at fixed time and position.
Description
Field of application
The invention relates to the field of agricultural detection, in particular to a vegetable growth monitoring and pesticide spraying system based on an unmanned aerial vehicle.
Background
In the crop planting process, disease observation needs to be carried out on the growth condition of crops, and timely diagnosis and treatment needs to be carried out on diseases and pests, particularly large-area farmlands, the diseases and pests need to be detected manually, and planting areas need to be marked in a dividing mode, so that time is wasted, and errors can occur.
Along with the development of unmanned aerial vehicle technique, it becomes possible that unmanned aerial vehicle carries out the pesticide and sprays in order to replace artifical spraying work. Carry out the pesticide through unmanned aerial vehicle and spray and have that prevention and cure is effectual, remote control operation, spray the danger that the operation personnel had avoided exposing in the pesticide, improved a great deal of advantages such as spraying operation security. However, the current plant protection unmanned aerial vehicle generally carries out spraying and pesticide applying operation on a large-area farmland after the plant diseases are manually detected, and the mode has two disadvantages: firstly, the detection is inaccurate and takes long time; secondly, a single unmanned aerial vehicle is often used for large-area pesticide application treatment on crops with the same diseases, and simultaneous treatment on multiple diseases cannot be achieved; however, the conditions of the pests of crops in each area are different, so the application condition should be adjusted according to the local conditions.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides a vegetable growth monitoring and pesticide spraying system based on an unmanned aerial vehicle.
In order to achieve the aim, the invention adopts the technical scheme that: a vegetable growth monitoring and pesticide spraying system based on an unmanned aerial vehicle comprises the unmanned aerial vehicle, and a power supply, a control unit, a navigation unit, a monitoring unit and a pesticide spraying unit which are carried on the unmanned aerial vehicle;
the monitoring unit comprises a camera and a light source generator, one end of the light source generator is electrically connected with the power supply, the other end of the light source generator is connected with a condensing lens, the light source generator is arranged on the camera, the power supply is electrically connected with the control unit, the navigation unit and the pesticide spraying unit, the navigation unit outputs position information data to the control unit, and the control unit outputs control signals to the pesticide spraying unit and the monitoring unit;
the pesticide spraying unit comprises a pesticide box and a spray head communicated with the pesticide box, a flow regulating valve is arranged between a pesticide outlet of the pesticide box and a pesticide inlet of the spray head, and the monitoring unit is used for monitoring crop growth state information; during the monitoring process of the unmanned aerial vehicle along the preset air route, according to the position information data, the unmanned aerial vehicle traverses all hovering positions on the preset air route, monitors crops and feeds back crop growth state information through the monitoring unit, and the control unit can control the pesticide spraying unit to spray pesticide quantitatively, regularly and in a positioning mode on the crops according to the crop growth state information fed back by the monitoring unit.
Further, in a preferred embodiment of the present invention, a bearing mechanism is disposed at the bottom of the unmanned aerial vehicle, the medicine box is placed on the bearing mechanism, the bearing mechanism includes a fixing plate and a clamping mechanism, the clamping mechanism includes a first clamping arm and a second clamping arm, the first clamping arm and the second clamping arm are rotatably connected to two sides of the fixing plate through a first rotating shaft, the first clamping arm and the second clamping arm have the same structure and include a first clamping joint and a second clamping joint, the first clamping joint and the second clamping joint are rotatably connected together through a second rotating shaft, the second joint is rotatably connected to a clamping rod through a third rotating shaft, and a supporting seat is cooperatively connected to the bottom of the clamping rod.
Further, in a preferred embodiment of the present invention, a first gear is cooperatively connected to the first rotating shaft, a second gear is cooperatively connected to the second rotating shaft, a third gear is cooperatively connected to the third rotating shaft, the first gear and the second gear can be in meshing transmission, and the second gear and the third gear can be in meshing transmission.
Further, in a preferred embodiment of the present invention, a first rotating mechanism is fixedly installed at the bottom of the unmanned aerial vehicle, a fixed frame is cooperatively connected to the first rotating mechanism, the camera is rotatably connected to the fixed frame through a second rotating mechanism, and a position finder is disposed at the top of the unmanned aerial vehicle and is used for recording position information of the unmanned aerial vehicle.
Further, in a preferred embodiment of the present invention, the light source generator is provided with a plurality of light emitting holes, the light emitting holes are used for emitting light with one or more different wavelengths, the light source generator is used for adjusting brightness according to the illumination condition of the environment, and the light emitted from the light emitting holes is corrected in the light emitting direction by the condenser lens.
The invention provides a detection method of a vegetable growth monitoring and pesticide spraying system based on an unmanned aerial vehicle, which is applied to any one vegetable growth monitoring and pesticide spraying system based on the unmanned aerial vehicle, and comprises the following steps:
acquiring target object information and detection area position information, wherein the target object information comprises target object characteristics and target object types, and defining the detection area position information as a detection node;
executing an ant colony algorithm, wherein the ant colony algorithm is a process of simulating ants to search for food, and the unmanned aerial vehicle can calculate the shortest path starting from the original point and finally returning to the original point after passing through a plurality of nodes through the algorithm;
when no one reaches a preset node, starting a camera and entering a detection stage;
detecting the target object in the node to generate a detection result, and judging the growth condition of the target object according to the detection result;
if the growth condition is abnormal, generating a treatment scheme and spraying the treatment scheme;
if the growth condition is normal, the unmanned aerial vehicle moves to the next node for detection.
Further, in a preferred embodiment of the present invention, the detecting the target object in the node to generate a detection result further includes the following steps:
acquiring image information of crops in each normal growth period, and storing the acquired image information in a standard database;
acquiring an initial video of a crop to be detected through a camera, and processing the initial video according to a preset video processing method to obtain a target video with an amplification effect; wherein the amplification effect means that the region to be detected is amplified in the target video;
acquiring growth information of crops to be detected through the target video; the growth information comprises crop leaf tip information, dry leaf information and crop stem information;
comparing the crop growth information with a standard database, and analyzing the current crop growth condition;
if the crop growth condition is larger than a preset threshold value, indicating that the crop growth condition is normal;
if the crop growth condition is smaller than a preset threshold value, the growth condition is abnormal, and a pest development early warning model is adopted for prediction to obtain a pest risk prediction result;
and sending the crop pest risk prediction result to the control unit according to the prediction result.
Further, in a preferred embodiment of the present invention, processing the initial video according to a predetermined video processing method to obtain a target video with an amplification effect further includes:
processing an initial video of the crop to be detected, which is acquired by a camera according to the preset video processing method, to obtain a brightness Y channel image of the initial video corresponding to a motion amplification effect;
determining a weight coefficient corresponding to the brightness Y-channel image according to the preset video processing method;
and according to the weight coefficient corresponding to the brightness Y-channel image and the brightness Y-channel corresponding to the initial video.
Further, in a preferred embodiment of the present invention, the processing, according to the preset video processing method, of the initial video of the crop to be detected, acquired by the camera, to obtain a luminance Y channel image with an amplification effect corresponding to the initial video, further includes:
determining the position parameters of the camera relative to the crops to be detected; wherein the position parameters comprise a distance parameter and an angle parameter;
determining the definition grade of the Y image of the brightness channel according to the position parameter;
when the definition level is greater than or equal to a preset definition level, acquiring the brightness Y-channel image through a first amplification algorithm;
when the definition level is smaller than a preset definition level, acquiring the brightness Y-channel image through a second amplification algorithm;
the first amplification algorithm is a motion amplification algorithm based on an Euler visual angle, and the second amplification algorithm is a motion amplification algorithm based on a Laplace visual angle.
Further, in a preferred embodiment of the present invention, if the growth status is abnormal, a processing scheme is generated, and the spraying process is performed on the growth status, specifically: according to the generated processing scheme, the control unit controls the pesticide spraying unit to spray pesticide on abnormally-growing crops in a timing, quantitative and positioning mode.
The invention discloses a vegetable growth monitoring and pesticide spraying system based on an unmanned aerial vehicle, which monitors crops and feeds back crop growth state information through a monitoring unit, and a control unit can control a pesticide spraying unit to spray pesticide quantitatively, regularly and positionally to the crops according to the crop growth state information fed back by the monitoring unit; through control gear motor rotation, first gear is along with rotating, then second gear and third gear are also along with rotating, drive first centre gripping joint and the joint clamp of second centre gripping or relax through second gear and second gear to can the not medical kit of equidimension of centre gripping.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings of the embodiments can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic perspective view of the present invention;
FIG. 2 is a schematic perspective view of another embodiment of the present invention;
FIG. 3 is a schematic structural diagram of the carrying mechanism of the present invention;
FIG. 4 is a schematic structural view of a clamping mechanism according to the present invention;
fig. 5 is a flow chart of a detection method of the drone;
FIG. 6 is a flow chart of a method for detecting a target within a node;
FIG. 7 is a flow chart of a method of processing an initial video;
FIG. 8 is a flow chart of a method of obtaining a luminance Y channel image;
the reference numerals are explained below: 101. an unmanned aerial vehicle; 102. a camera; 103. a light source generator; 104. a medicine chest; 105. a spray head; 106. a flow regulating valve; 107. a carrying mechanism; 108. a fixing plate; 109. a clamping mechanism; 201. a first clamp arm; 202. a second clamp arm; 203. a first rotating shaft; 204. a first clamping joint; 205. a second clamping joint; 206. a second rotating shaft; 207. a clamping lever; 208. a supporting seat; 209. a first gear; 301. a second gear; 302. a third gear; 303. a first rotating mechanism; 304. a fixed mount; 305. a second rotating mechanism; 306. a positioning instrument; 307. a third rotation axis.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, the present invention will be further described in detail with reference to the accompanying drawings and the detailed description, wherein the drawings are simplified schematic drawings and only the basic structure of the present invention is illustrated schematically, so that only the structure related to the present invention is shown, and it is to be noted that the embodiments and features of the embodiments in the present application can be combined with each other without conflict.
In the description of the present application, it is to be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in the orientation or positional relationship indicated in the drawings for convenience in describing the present application and for simplicity in description, and are not intended to indicate or imply that the referenced devices or elements must have a particular orientation, be constructed in a particular orientation, and be operated in a particular manner, and are not to be considered limiting of the scope of the present application. Furthermore, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the invention, the meaning of "a plurality" is two or more unless otherwise specified.
In the description of the present application, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art through specific situations.
To facilitate an understanding of the invention, the invention will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
The first embodiment is as follows:
the invention provides a vegetable growth monitoring and pesticide spraying system based on an unmanned aerial vehicle, which comprises the unmanned aerial vehicle 101, and a power supply, a control unit, a navigation unit, a monitoring unit and a pesticide spraying unit which are carried on the unmanned aerial vehicle 101;
as shown in fig. 1 and 2, the monitoring unit includes a camera 102 and a light source generator 103, one end of the light source generator 103 is electrically connected to the power supply, the other end is connected to a collecting mirror, the light source generator 103 is disposed on the camera 102, the power supply is electrically connected to the control unit, the navigation unit and the spraying unit, the navigation unit outputs position information data to the control unit, and the control unit outputs control signals to the spraying unit and the monitoring unit;
the pesticide spraying unit comprises a pesticide box 104 and a spray head 105 communicated with the pesticide box 104, a flow regulating valve 106 is arranged between a pesticide outlet of the pesticide box 104 and a pesticide inlet of the spray head 105, and the monitoring unit is used for monitoring crop growth state information; in the monitoring process of the unmanned aerial vehicle 101 along the preset air route, according to the position information data, the unmanned aerial vehicle 101 traverses all hovering positions on the preset air route, the crops are monitored and fed back by the monitoring unit, the growth state information of the crops is fed back, and the control unit can control the pesticide spraying unit to spray pesticide quantitatively, regularly and in a positioning mode on the crops according to the growth state information of the crops fed back by the monitoring unit.
It should be noted that, by additionally arranging the flow control valve 106, the control of the spraying amount of the spraying unit in the unit time is facilitated, the growth condition of crops is monitored by the monitoring unit, then the position of the spraying agent, the spraying amount, the spraying time and the like are made according to the growth condition of the crops, in the spraying process, the control unit controls the spraying unit to spray the spraying agent in the preset time when the unmanned aerial vehicle 101 is in a hovering state, so as to solve the problem that the unmanned aerial vehicle 101 in the prior art has uncertain speed and posture in the flying process and has influence on actual dosage received in different areas, so as to balance the spraying amount at different positions in the area to be sprayed with the spraying agent, improve the spraying effect and avoid pesticide waste. In addition, control in order to spout it with the medicine rate through adjusting flow control valve 106 to can carry out more accurate regulation and control to unmanned aerial vehicle 101 hover time, further improve and spout the medicine quality, possess the accurate function of spouting the medicine.
As shown in fig. 3 and 4, a carrying mechanism 107 is arranged at the bottom of the unmanned aerial vehicle 101, the medicine box 104 is placed on the carrying mechanism 107, the carrying mechanism 107 includes a fixing plate 108 and a clamping mechanism 109, the clamping mechanism 109 includes a first clamping arm 201 and a second clamping arm 202, the first clamping arm 201 and the second clamping arm 202 are rotatably connected to two sides of the fixing plate 108 through a first rotating shaft 203, the first clamping arm 201 and the second clamping arm 202 have the same structure and include a first clamping joint 204 and a second clamping joint 205, the first clamping joint 204 and the second clamping joint 205 are rotatably connected together through a second rotating shaft 206, the second joint is rotatably connected to a clamping rod 207 through a third rotating shaft 307, and a supporting seat 208 is cooperatively connected to the bottom of the clamping rod 207.
The first rotating shaft 203 is connected with a first gear 209 in a matching manner, the second rotating shaft 206 is connected with a second gear 301 in a matching manner, the third rotating shaft 307 is connected with a third gear 302 in a matching manner, the first gear 209 and the second gear 301 can be in meshing transmission, and the second gear 301 and the third gear 302 can be in meshing transmission.
It should be noted that the medicine boxes 104 are placed on the bearing mechanism 107, and the bearing mechanism 107 can clamp the medicine boxes 104 with different sizes through the first clamping arm 201 and the second clamping arm 202 to meet different medicine spraying requirements, for example, when the unmanned aerial vehicle 101 needs to be monitored in a wider range and in a shorter distance, the unmanned aerial vehicle 101 can carry the medicine boxes 104 with a larger volume, so as to ensure that the work can be completed by a single time of going out of the air, and pesticide supplementation is not required to be performed back and forth; when the range of monitoring is small and the distance is long, the medicine boxes 104 with small volumes can be used to ensure sufficient cruising ability. The specific working principle of the bearing mechanism 107 is as follows: the gear motor is connected to one end of the first gear 209 in a matching mode, the gear motor can drive the first gear 209 to rotate, when the medicine boxes 104 with different sizes are clamped, the gear motor is controlled to rotate, the first gear 209 rotates, then the second gear 301 and the third gear 302 also rotate, the second gear 301 and the second gear 301 drive the first clamping joint 204 and the second clamping joint 205 to clamp or loosen the medicine boxes 104 with different sizes, and accordingly the medicine boxes 104 with different sizes can be clamped.
As shown in fig. 1 and 2, a first rotating mechanism 303 is fixedly mounted at the bottom of the unmanned aerial vehicle 101, a fixing frame 304 is connected to the first rotating mechanism 303 in a matching manner, the camera 102 is rotatably connected to the fixing frame 304 through a second rotating mechanism 305, a positioning instrument 306 is arranged at the top of the unmanned aerial vehicle 101, and the positioning instrument 306 is used for recording position information of the unmanned aerial vehicle 101.
The light source generator 103 is provided with a plurality of light emitting holes, the light emitting holes are used for emitting light with one or more different wavelengths, the light source generator 103 is used for adjusting the brightness according to the illumination condition of the environment, and the light emitted from the light emitting holes is corrected in the light emitting direction through the condenser lens.
It should be noted that the number of the emitted light rays is changed through the light outlet holes, so that the illumination intensity emitted by the condenser lens is changed, after the leaves of the crops are irradiated by light, if pests are hidden at the back of the leaves, shadows with different outlines can be presented on the leaves, the image information of the leaves is obtained through shooting by the camera 102, the types of the pests can be identified according to the shapes of the outlines, and the insect pest monitoring function is provided, so that a user can take medicines according to the symptoms later.
Example two:
the invention provides a detection method of a vegetable growth monitoring and pesticide spraying system based on an unmanned aerial vehicle 101, which is applied to any one of the vegetable growth monitoring and pesticide spraying systems based on the unmanned aerial vehicle, as shown in fig. 5, and comprises the following steps:
s102: acquiring target object information and detection area position information, wherein the target object information comprises target object characteristics and target object types, and defining the detection area position information as a detection node;
s104: executing an ant colony algorithm, wherein the ant colony algorithm is a process of simulating ants to search for food, and the unmanned aerial vehicle 101 can calculate the shortest path starting from the original point and finally returning to the original point after passing through a plurality of nodes through the algorithm;
s106: when no one reaches a preset node, starting a camera and entering a detection stage;
s108: detecting the target object in the node to generate a detection result, and judging the growth condition of the target object according to the detection result;
s110: if the growth condition is abnormal, generating a treatment scheme and spraying the treatment scheme;
s112: if the growth condition is normal, the unmanned aerial vehicle moves to the next node for detection.
It should be noted that in a certain area, the growth of crops is affected by various factors, such as plant diseases and insect pests, excessive weeds, lack of certain fertilizers, and the like. In the invention, the video information of crops is shot by the camera 102, the information such as the shape outline, the color and the like of the crops can be detected, then the detection result is identified according to the detected information, and different schemes are formulated according to the detection result. For example, in a region where the crop is lack of a certain fertilizer and the pest and disease damage causes the crop to grow slowly, the control unit marks the region and marks the region with multiple colors, the area of the pest and disease damage region is calculated, and the application amount is calculated according to the area of the pest and disease damage, so that in the case of the region, the pesticide spraying is reduced, and the pesticide spraying is prevented from being too much and remaining in the environment to cause pollution. In addition, some crops with slow growth often show dark yellow leaves, withered leaves and the like, and some insect-infested leaves also show dark yellow leaves, withered leaves and the like, and in the same way, in the process of image recognition, the illumination intensity is increased, the thickness of each leaf is not thick, and under the condition of certain illumination intensity, the insect-infested leaves often show a shadow outline of a concave part. Therefore, the method is used for distinguishing the plant diseases and insect pests, the natural growth condition and the condition of insufficient fertilizer, and the growth condition of crops can be accurately, efficiently and reliably identified.
As shown in fig. 6, the method for detecting a target object in the node to generate a detection result further includes the following steps:
s202: acquiring image information of crops in each normal growth period, and storing the acquired image information in a standard database;
s204: acquiring an initial video of a crop to be detected through a camera, and processing the initial video according to a preset video processing method to obtain a target video with an amplification effect; wherein the amplification effect means that the region to be detected is amplified in the target video;
s206: acquiring growth information of crops to be detected through the target video; the growth information comprises crop leaf tip information, dry leaf information and crop stem information;
it should be noted that if the area of the canopy of the crop decreases and even the leaves shrink, it indicates that the pest may have occurred, and the number and scale of pest occurrence can be monitored. After the pest happens, the pest can get the blade of eating the crop, sees from the canopy characteristic of crop, can cause the blade of crop to curl the deformity, leads to the reduction of crop blade area, and then causes the blade atrophy of crop and rot even, sees from the colour characteristic of crop, and the stripe appears in the blade surface, and then presents brown or blackens, and blade withering is black when serious. Therefore, the index histograms of the images shot by the camera 102 are respectively calculated through R, G, B components in the images, the average value of the index histograms is compared, and if the average value of the G component is larger than the average value of the other two components, the condition of the growth of the crops is preliminarily judged to be good; if the average value of the G component is far lower than one component, warning information is sent out, and insect pests may occur.
S208: comparing the crop growth information with a standard database, and analyzing the current crop growth condition;
s210: if the crop growth condition is larger than a preset threshold value, indicating that the crop growth condition is normal;
s212: if the crop growth condition is smaller than a preset threshold value, the growth condition is abnormal, and a pest development early warning model is adopted for prediction to obtain a pest risk prediction result;
s214: and sending the crop pest risk prediction result to the control unit according to the prediction result.
It should be noted that the initial video includes a plurality of frames of images composed of RGB color spaces of three primary colors, and luminance Y information of the plurality of frames of images is obtained by converting the RGB color spaces of the plurality of frames of images into YIQ color spaces, where YIQ refers to a television system standard, Y is a luminance signal providing a black-and-white television and a color television, I is luminance, I is In-phase, colors are from orange to cyan, Q is quadrate-phase, and colors are from violet to yellow-green.
The specific implementation manner of obtaining the brightness Y-channel image with the motion amplification effect corresponding to the initial video is as follows: and starting a plurality of threads of the processor, simultaneously executing a video motion amplification algorithm on the Y-channel image by the plurality of threads, wherein each thread can be responsible for one or more initial videos to obtain an amplified Y-channel image, then adding the amplified Y-channel image and the converted I, Q-channel image, and reversely converting the image into an RGB color space to obtain a target video.
It should be noted that the memory on the test system stores the mapping relationship between the video motion amplification algorithm and the weight coefficient, and the processor on the test system can query the mapping relationship according to another video motion amplification algorithm and then determine the corresponding weight coefficient.
The specific implementation manner of synthesizing the target video with the motion amplification effect of the motor to be detected according to the weight coefficient corresponding to the brightness Y-channel image and the brightness Y-channel image corresponding to the initial video is as follows: and calculating the amplified brightness Y-channel image corresponding to the initial video according to the corresponding weight coefficient to obtain the amplified brightness Y-channel image of the target video file, adding the amplified brightness Y-channel image and the I, Q channel image after color space conversion, and reversely converting the amplified brightness Y-channel image into an RGB color space to obtain the target video.
As shown in fig. 7, the method for processing an initial video according to a preset video processing method to obtain a target video with an amplification effect further includes:
s302: processing an initial video of the crop to be detected, which is acquired by a camera according to the preset video processing method, to obtain a brightness Y channel image of the initial video corresponding to a motion amplification effect;
s304: determining a weight coefficient corresponding to the brightness Y-channel image according to the preset video processing method;
s306: and according to the weight coefficient corresponding to the brightness Y-channel image and the brightness Y-channel corresponding to the initial video.
The processing method includes acquiring an initial video of a crop to be detected by the camera 102 according to the preset video processing method, and obtaining a brightness Y channel image with an amplification effect corresponding to the initial video, as shown in fig. 8, further including:
s402: determining the position parameters of the camera relative to the crops to be detected; wherein the position parameters comprise a distance parameter and an angle parameter;
s404: determining the definition grade of the Y image of the brightness channel according to the position parameter;
s406: when the definition level is greater than or equal to a preset definition level, acquiring the brightness Y-channel image through a first amplification algorithm;
s408: when the definition level is smaller than a preset definition level, acquiring the brightness Y-channel image through a second amplification algorithm;
the first amplification algorithm is a motion amplification algorithm based on an Euler visual angle, and the second amplification algorithm is a motion amplification algorithm based on a Laplace visual angle.
It should be noted that the amplification algorithm in the preset video processing method may be determined according to a distance parameter in the position parameters, or the amplification algorithm in the preset video processing method may be determined according to an angle parameter in the position parameters. For example, when the distance parameter between the crop to be detected and the camera 102 is less than or equal to the preset distance threshold, an initial video with relatively clear image and relatively high resolution can be shot, so that a first amplification algorithm with relatively high operation speed and relatively low accuracy can be used; when the distance parameter between the crop to be detected and the camera 102 is greater than the preset distance threshold, the definition of the shot initial video is not high, and therefore the second amplification algorithm with relatively high use accuracy is determined.
It should be noted that the euler visual angle-based motion amplification algorithm does not need to track motion points, is convenient for operation, has a high operation speed, and can be used for an initial video with high definition and a large data volume; the motion amplification algorithm based on the Laplace visual angle needs to accurately track and estimate the motion tracks of the feature points in the multi-frame images, has large calculation amount, and can be used for initial videos with poor definition and small data amount.
Wherein, if the growth situation is abnormal, a processing scheme is generated, and the spraying treatment is carried out on the growth situation, which specifically comprises the following steps: according to the generated processing scheme, the control unit controls the pesticide spraying unit to spray pesticide on abnormally-growing crops in a timing, quantitative and positioning mode.
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. The utility model provides a vegetables growth monitoring and spout medicine system based on unmanned aerial vehicle, includes unmanned aerial vehicle and carries on power, the control unit, the navigation unit, the monitoring unit on unmanned aerial vehicle, spouts the medicine unit, its characterized in that:
the monitoring unit comprises a camera and a light source generator, one end of the light source generator is electrically connected with the power supply, the other end of the light source generator is connected with a condensing lens, the light source generator is arranged on the camera, the power supply is electrically connected with the control unit, the navigation unit and the pesticide spraying unit, the navigation unit outputs position information data to the control unit, and the control unit outputs control signals to the pesticide spraying unit and the monitoring unit;
the pesticide spraying unit comprises a pesticide box and a spray head communicated with the pesticide box, a flow regulating valve is arranged between a pesticide outlet of the pesticide box and a pesticide inlet of the spray head, and the monitoring unit is used for monitoring crop growth state information; during the monitoring process of the unmanned aerial vehicle along the preset air route, according to the position information data, the unmanned aerial vehicle traverses all hovering positions on the preset air route, monitors crops and feeds back crop growth state information through the monitoring unit, and the control unit can control the pesticide spraying unit to spray pesticide quantitatively, regularly and in a positioning mode on the crops according to the crop growth state information fed back by the monitoring unit.
2. The vegetable growth monitoring and pesticide spraying system based on the unmanned aerial vehicle as claimed in claim 1, wherein: the unmanned aerial vehicle bottom is provided with bears the weight of the mechanism, the medical kit is placed bear on the mechanism, bear the weight of the mechanism and include fixed plate and fixture, fixture includes first centre gripping arm and second centre gripping arm, first centre gripping arm with the second centre gripping arm rotates through first axis of rotation to be connected the both sides of fixed plate, first centre gripping arm is the same with second centre gripping arm structure, including first centre gripping joint and second centre gripping joint, first centre gripping joint with the second centre gripping joint rotates through the second axis of rotation to be connected together, be connected with the clamping bar through the rotation of third axis of rotation on the second joint, the bottom cooperation of clamping bar is connected with the supporting seat.
3. The vegetable growth monitoring and pesticide spraying system based on the unmanned aerial vehicle as claimed in claim 2, wherein: the first rotating shaft is connected with a first gear in a matched mode, the second rotating shaft is connected with a second gear in a matched mode, the third rotating shaft is connected with a third gear in a matched mode, the first gear and the second gear can be in meshed transmission, and the second gear and the third gear can be in meshed transmission.
4. The vegetable growth monitoring and pesticide spraying system based on the unmanned aerial vehicle as claimed in claim 1, wherein: unmanned aerial vehicle bottom fixed mounting has first slewing mechanism, the cooperation is connected with the mount on the first slewing mechanism, the camera rotates through the second slewing mechanism and connects on the mount, the unmanned aerial vehicle top is provided with the locater, the locater is used for taking notes unmanned aerial vehicle's positional information.
5. The vegetable growth monitoring and pesticide spraying system based on the unmanned aerial vehicle as claimed in claim 1, wherein: the light source generator is provided with a plurality of light-emitting holes, the light-emitting holes are used for emitting light with one or more different wavelengths, the light source generator is used for adjusting the brightness according to the illumination condition of the environment, and the light emitted from the light-emitting holes is corrected in the light-emitting direction through the condenser lens.
6. A detection method of a vegetable growth monitoring and pesticide spraying system based on an unmanned aerial vehicle is applied to the vegetable growth monitoring and pesticide spraying system based on the unmanned aerial vehicle according to any one of claims 1 to 5, and is characterized by comprising the following steps:
acquiring target object information and detection area position information, wherein the target object information comprises target object characteristics and target object types, and defining the detection area position information as a detection node;
executing an ant colony algorithm, wherein the ant colony algorithm is a process of simulating ants to search for food, and the unmanned aerial vehicle can calculate the shortest path starting from the original point and finally returning to the original point after passing through a plurality of nodes through the algorithm;
when no one reaches a preset node, starting a camera and entering a detection stage;
detecting the target object in the node to generate a detection result, and judging the growth condition of the target object according to the detection result;
if the growth condition is abnormal, generating a treatment scheme and spraying the treatment scheme;
if the growth condition is normal, the unmanned aerial vehicle moves to the next node for detection.
7. The detection method of the unmanned aerial vehicle-based vegetable growth monitoring and pesticide spraying system as claimed in claim 6, wherein the target object in the node is detected to generate a detection result, and further comprising the following steps:
acquiring image information of crops in each normal growth period, and storing the acquired image information in a standard database;
acquiring an initial video of a crop to be detected through a camera, and processing the initial video according to a preset video processing method to obtain a target video with an amplification effect; wherein the amplification effect means that the region to be detected is amplified in the target video;
acquiring growth information of crops to be detected through the target video; the growth information comprises crop leaf tip information, dry leaf information and crop stem information;
comparing the crop growth information with a standard database, and analyzing the current crop growth condition;
if the crop growth condition is larger than a preset threshold value, indicating that the crop growth condition is normal;
if the crop growth condition is smaller than a preset threshold value, the growth condition is abnormal, and a pest development early warning model is adopted for prediction to obtain a pest risk prediction result;
and sending the crop pest risk prediction result to the control unit according to the prediction result.
8. The method for detecting the vegetable growth monitoring and pesticide spraying system based on the unmanned aerial vehicle as claimed in claim 7, wherein the initial video is processed according to a preset video processing method to obtain a target video with an amplification effect, further comprising:
processing an initial video of the crop to be detected, which is acquired by a camera according to the preset video processing method, to obtain a brightness Y channel image of the initial video corresponding to a motion amplification effect;
determining a weight coefficient corresponding to the brightness Y-channel image according to the preset video processing method;
and synthesizing the target video with the amplification effect of the crop to be detected according to the weight coefficient corresponding to the brightness Y channel image and the brightness Y channel image corresponding to the initial video.
9. The method for detecting the vegetable growth monitoring and pesticide spraying system based on the unmanned aerial vehicle as claimed in claim 8, wherein the method comprises the steps of processing an initial video of a crop to be detected by a camera according to the preset video processing method to obtain a brightness Y-channel image with an amplification effect corresponding to the initial video, and further comprising:
determining the position parameters of the camera relative to the crops to be detected; wherein the position parameters comprise a distance parameter and an angle parameter;
determining the definition grade of the Y image of the brightness channel according to the position parameter;
when the definition level is greater than or equal to a preset definition level, acquiring the brightness Y-channel image through a first amplification algorithm;
when the definition level is smaller than a preset definition level, acquiring the brightness Y-channel image through a second amplification algorithm;
the first amplification algorithm is a motion amplification algorithm based on an Euler visual angle, and the second amplification algorithm is a motion amplification algorithm based on a Laplace visual angle.
10. The detection method of the unmanned aerial vehicle-based vegetable growth monitoring and pesticide spraying system according to claim 6, wherein if the growth condition is abnormal, a processing scheme is generated, and pesticide spraying is performed on the processing scheme, specifically: according to the generated processing scheme, the control unit controls the pesticide spraying unit to spray pesticide on abnormally-growing crops in a timing, quantitative and positioning mode.
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