CN110006614B - System and method for monitoring drift trend of aerial pesticide application liquid medicine fogdrop cloud cluster - Google Patents
System and method for monitoring drift trend of aerial pesticide application liquid medicine fogdrop cloud cluster Download PDFInfo
- Publication number
- CN110006614B CN110006614B CN201910104804.9A CN201910104804A CN110006614B CN 110006614 B CN110006614 B CN 110006614B CN 201910104804 A CN201910104804 A CN 201910104804A CN 110006614 B CN110006614 B CN 110006614B
- Authority
- CN
- China
- Prior art keywords
- cloud
- cloud cluster
- cluster
- droplet
- fogdrop
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M9/00—Aerodynamic testing; Arrangements in or on wind tunnels
Landscapes
- Physics & Mathematics (AREA)
- Fluid Mechanics (AREA)
- General Physics & Mathematics (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The embodiment of the invention provides a system and a method for monitoring the drift trend of aerial pesticide application liquid medicine fogdrop cloud clusters, which comprises a laser detection device and a data processing device which are connected with each other; the laser detection device is used for emitting laser beams and recovering the laser beams reflected by the fog drop cloud cluster; the data processing device is used for monitoring the drift trend of the mist cloud cluster in real time according to the emitted laser beam and the information of the laser beam reflected by the mist cloud cluster.
Description
Technical Field
The embodiment of the invention relates to the technical field of aerial pesticide application, in particular to a system and a method for monitoring the drifting trend of aerial pesticide application liquid medicine fogdrop cloud clusters.
Background
In the aerial pesticide application process, the pesticide atomization degree directly influences the pesticide application operation effect and the drift condition of a fog drop cloud cluster, and the spray drift is the phenomenon that the spray exceeds a spraying area due to the action of air flow in the spraying process. The drift condition of the fog drop cloud directly influences the pesticide pollution condition of the surrounding environment of the pesticide application area. The fogdrop cloud cluster is very easily influenced by environmental factors such as crosswind and the like to cause drift in the aerial pesticide application process, becomes a potential environment pollution way, destroys water resources and an ecological system and poses certain threat to the health of adjacent personnel.
In the process of aerial pesticide application, aiming at monitoring the dispersion and drift trends of the liquid medicine cloud cluster, the method mostly focuses on a pre-experiment stage and a data acquisition and processing stage after spraying, the dispersion condition of the liquid medicine cloud cluster on site cannot be obtained in real time in the pesticide application stage, and the drift trends of the liquid medicine cloud cluster are monitored and analyzed. The method mainly comprises two methods: one is to monitor the spray drift longitudinal section by using related equipment under the laboratory condition and monitor the drift motion trend in a model mode; and the other method is to collect the fog drop cloud cluster by using traditional fog drop cloud cluster collecting devices such as water-sensitive paper, nylon ropes and the like in the field pesticide application process and obtain data such as the drift distance of the fog drop cloud cluster through post-treatment. However, both of the two modes have time and space limitations, and cannot reflect the change of the cloud of droplets influenced by the environment in the aerial pesticide application process in real time.
At present, a design of a fog drop cloud deposition sensor or a design of a remote measuring system for spray distribution and drift by using infrared light radiation is proposed, and the two methods provide an effective improvement idea for aerial pesticide application fog drop cloud real-time monitoring. The design of the fogdrop cloud cluster deposition sensor enables the fogdrop cloud cluster deposition amount to be rapidly obtained in the pesticide application process, compared with the traditional mode of using water-sensitive paper, the method can greatly reduce manpower and material resources, but the integral drift condition of the fogdrop cloud cluster in the pesticide application process cannot be reflected only through deposition detection; the infrared light radiation is utilized to carry out spray distribution and drift remote measurement, so that the remote space monitoring can be realized, and the whole drift condition of the fogdrop cloud cluster can be reflected.
Therefore, the problem that the whole drifting condition of a fogdrop cloud group in the pesticide application process cannot be reflected in real time or the equipment operation is relatively complex and has high requirements on the environment exists in the current process of monitoring the drifting diffusion of the aerial pesticide application liquid medicine in real time.
Disclosure of Invention
In order to solve the above problems, embodiments of the present invention provide a system and a method for monitoring a drift tendency of aerial pesticide spray cloud.
According to a first aspect of the embodiments of the present invention, there is provided a system for monitoring a drift tendency of a cloud of airborne drug delivery droplets, the system including: the laser detection device and the data processing device are connected with each other; the laser detection device is used for emitting laser beams and recovering the laser beams reflected by the fog drop cloud cluster; the data processing device is used for monitoring the drift trend of the cloud cluster of the droplets in real time according to the emitted laser beams and the information of the laser beams reflected by the cloud cluster of the droplets; the drift tendency of the cloud of droplets includes the drift direction, drift rate, cross-sectional distribution and density of the cloud of droplets.
According to a second aspect of the embodiments of the present invention, there is provided a method for monitoring a drift tendency of a cloud of airborne pesticide application droplets, the method including: emitting laser beams to the cloud cluster of droplets and recovering the laser beams reflected by the cloud cluster of droplets; and monitoring the drift trend of the cloud cluster of the fog drops in real time according to the information of the emitted laser beams and the laser beams reflected by the cloud cluster of the fog drops, wherein the drift trend of the cloud cluster of the fog drops comprises the drift direction, the drift rate, the cross section distribution and the density of the cloud cluster of the fog drops.
The embodiment of the invention emits laser beams to the pesticide liquid mist cloud cluster, and the position, the moving direction, the moving speed, the density and the like of the mist cloud cluster are determined by the laser beams reflected by the mist cloud cluster, so that the drifting trend of the mist cloud cluster is monitored. The invention can realize three-dimensional monitoring of the cloud cluster of the fogdrop, provides more comprehensive data for researching the drift and diffusion of the liquid medicine cloud cluster and the influence of environmental factors on the drift of the cloud cluster of the fogdrop, and provides a more perfect data support basis for the follow-up prediction of the drift trend of the cloud cluster of the fogdrop.
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 invention, and that for a person skilled in the art, other drawings can be derived from these without inventive effort.
Fig. 1 is a schematic structural diagram of a system for monitoring a drift tendency of aerial pesticide spray cloud droplets according to an embodiment of the invention;
fig. 2 is a schematic structural diagram of a data processing device of a system for monitoring a cloud drift tendency of aerial pesticide application liquid droplets according to an embodiment of the invention;
fig. 3 is a schematic structural diagram of a droplet cloud trajectory processing unit of the data processing device for aviation pesticide spray droplet cloud drift tendency according to the embodiment of the present invention;
FIG. 4 is a schematic diagram of polar coordinate to spatial three-dimensional coordinate conversion of a cloud of droplets according to an embodiment of the present invention;
FIG. 5 is a schematic illustration of the location of a cloud density calculation for a droplet in accordance with an embodiment of the present invention;
FIG. 6 is a schematic flow chart of cloud density calculation of the droplets according to the embodiment of the present invention;
FIG. 7 is a schematic illustration of a cloud boundary of droplets according to an embodiment of the present invention;
FIG. 8 is a schematic illustration of a cloud projection of droplets according to an embodiment of the present invention;
fig. 9 is a schematic flow chart of a method for monitoring a drift tendency of aerial pesticide spray mist cloud according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments, 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.
At present, the problem that the whole drifting condition of a fogdrop cloud cluster in the pesticide application process cannot be reflected in real time or the equipment operation is relatively complex and has high requirements on the environment exists in the process of monitoring the drifting diffusion of the aerial pesticide application liquid medicine in real time.
Fig. 1 is a schematic structural diagram of a system for monitoring a drift tendency of a cloud of aerial pesticide application liquid droplets according to an embodiment of the present invention, and as shown in fig. 1, the embodiment of the present invention provides a system for monitoring a drift tendency of a cloud of aerial pesticide application liquid droplets, where the system includes: the laser detection device and the data processing device are connected with each other; the laser detection device is used for emitting laser beams and recovering the laser beams reflected by the fog drop cloud cluster; the data processing device is used for monitoring the drift trend of the cloud cluster of the droplets in real time according to the emitted laser beams and the information of the laser beams reflected by the cloud cluster of the droplets; the drift tendency of the cloud of droplets includes the drift direction, drift rate, cross-sectional distribution and density of the cloud of droplets.
Specifically, in order to determine the position of the cloud cluster of the pesticide application liquid, a laser detection device is used for emitting laser beams to the cloud cluster of the pesticide application liquid, the emitted laser beams are emitted to a data processing device through the cloud cluster of the pesticide application liquid, and the data processing device judges the position, the moving direction, the moving speed and the like of the cloud cluster of the pesticide application liquid according to the emitted laser beams and information of the laser beams reflected by the cloud cluster of the pesticide application liquid, so that the drifting trend of the cloud cluster of the pesticide application liquid, including the drifting direction, the drifting speed, the cross section distribution and the density of the cloud cluster of the pesticide application liquid, is monitored in real time.
The embodiment of the invention starts from the whole process of pesticide application, and realizes real-time dynamic monitoring of the liquid medicine cloud cluster by changing the traditional spray monitoring mode, namely, the measurement of key parameters of the liquid medicine cloud cluster is realized based on a laser scanning method, so that the drift trend of the liquid medicine cloud cluster is monitored, and the defects of the traditional liquid medicine cloud cluster drift monitoring mode are overcome.
Based on the above embodiment, the laser detection device comprises a laser generation and emission unit and a laser echo receiving and processing unit which are connected with each other; the laser generating and emitting unit consists of a laser generating and emitting dot matrix unit and is used for emitting laser beams according to a preset angle; the laser echo receiving and processing unit is used for receiving the reflected laser beam and storing the information of the reflected laser beam, wherein the information of the reflected laser beam comprises echo time, the number of the laser transmitter, the deflection angle of the laser transmitter, the scanning frequency of the laser transmitter, echo distance, echo width and echo intensity.
Specifically, the laser generating and emitting unit is composed of a plurality of lattice-arranged laser emitters. The laser emitters are distributed at equal intervals. A driving module is arranged in the laser generating and emitting unit, and the emitting angle and the running state of the laser generating and emitting unit can be adjusted through the driving module, so that the laser generating and emitting unit can emit laser beams meeting the requirements according to a preset angle. The laser beam is continuously scanned during a specific time interval at the scanning frequency.
Meanwhile, the laser emitted by the laser generating and emitting unit is reflected back after encountering the fogdrop cloud cluster and is received by the laser echo receiving and processing unit. And after the laser echo receiving and processing unit receives the laser beam reflected by the cloud cluster of the fogdrops, the spatial position of the fogdrops is determined according to the time difference between the emission time and the receiving time of the laser beam and the preset angle emitted by the laser beam. It should be noted that, because the reflectivity and the transmissivity of each droplet are different, the reflectivity of each droplet to the laser is different, and the transmitted laser can be further propagated in the space until encountering the next droplet to continue to generate reflection and transmission, so that one laser can realize multiple echoes, thereby realizing the extension of the scanning area space in the depth direction.
Further, the laser echo receiving and processing unit converts the echo intensity into a voltage value by the receiver. The system noise is distinguished from the object echo by the threshold voltage value. When the voltage value is smaller than the threshold value, the system does not record the echo information, so that the filtering of the echo with the intensity smaller than the specific intensity is realized, and the influence of clutter on the echo information is reduced. I.e. if the intensity of the reflected laser beam is less than the sensitivity of the laser echo reception processing unit, the data will not be stored.
Based on the above embodiment, fig. 2 is a schematic structural diagram of a data processing device of a system for monitoring a drift tendency of a cloud cluster of aerial pesticide application liquid medicine droplets according to an embodiment of the present invention, and as shown in fig. 2, the data processing device includes a cloud cluster space positioning unit, a cloud cluster drawing unit, a cloud cluster space distribution density analysis unit, a cloud cluster trajectory processing unit, and a cloud cluster settling velocity analysis unit; the fog drop cloud cluster space positioning unit is used for converting the fog drop cloud cluster from a polar coordinate to a space three-dimensional coordinate so as to determine the position of the fog drop cloud cluster point; the droplet cloud cluster drawing unit is used for drawing coordinate points at corresponding positions of a space coordinate system according to the obtained space three-dimensional coordinate to represent the droplets scanned by the laser; the mist cloud cluster space distribution density analysis unit is used for calculating the density of the liquid medicine mist cloud clusters in the scanning cloud cluster area range and performing coloring visual display so as to realize that the whole cluster drawing unit is used for drawing coordinate points at corresponding positions of a space coordinate system according to a space three-dimensional coordinate to represent the mist cloud clusters scanned by the laser; analyzing the spatial distribution density of the fogdrop cloud cluster, automatically estimating the density of the fogdrop cloud cluster, and counting the number of fogdrop in a preset area and calculating the density of the fogdrop; the cloud cluster trajectory processing unit is used for extracting and storing the cloud cluster boundary coordinates at specific time in a coordinate point set mode, calculating projection sections of the cloud cluster at different planes of a coordinate system at the specific time and displaying the change condition of the boundary of the cloud cluster at different moments; and the fog drop cloud cluster sedimentation velocity analysis unit is used for completing the analysis work of the sedimentation related data values of the obtained fog drop cloud clusters.
Specifically, the data processing apparatus is a core part of the embodiment of the present invention, and the operation process of the data processing apparatus specifically includes:
firstly, the reflected laser beam can be received by a laser echo receiving processing unit through a filter lens, the spatial position of the fog drop is determined according to the emission-return time difference of the laser beam and the spatial angle of the laser beam, then the position of the fog drop is converted into a spatial three-dimensional coordinate from a polar coordinate taking the emission starting point of the laser beam as the origin point by a fog drop cloud cluster spatial positioning unit according to the relation between the emission starting point of the laser beam and the position reflected by the fog drop, and the spatial relative position of the fog drop is determined according to the spatial three-dimensional coordinate obtained by calculation.
And then, drawing coordinate points at corresponding positions of a space coordinate system by a fogdrop cloud cluster drawing unit according to the space three-dimensional coordinates of the fogdrop so as to represent the fogdrop scanned by the emitted laser beam.
Then, the fog drop density in the fog drop cloud cluster area is calculated and is visually displayed in a coloring mode by the fog drop cloud cluster spatial distribution density analysis unit according to the fog drops drawn by the fog drop cloud cluster drawing unit in the spatial coordinate system, for example, a dark area represents an area with a high fog drop concentration, a light area represents an area with a low fog drop concentration, or different colors represent areas with different fog drop concentrations, so that the automatic estimation of the whole fog drop cloud cluster density, the statistics of the fog drop number in a preset area and the calculation of the fog drop density are realized.
And the droplet cloud cluster track processing unit extracts and stores the boundary coordinates of the droplet cloud clusters at the specific time in a coordinate point set mode, calculates projection sections of the droplet cloud clusters at the specific time on different planes of a coordinate system, and displays the change condition of the changing boundary of the droplet cloud clusters at different moments.
And the fog drop cloud settling velocity analysis unit mainly completes the analysis work of the obtained settling related data values of the obtained fog drop cloud.
The embodiment of the invention utilizes a fog drop cloud cluster space positioning unit, a fog drop cloud cluster drawing unit, a fog drop cloud cluster space distribution density analysis unit, a fog drop cloud cluster track processing unit and a fog drop cloud cluster settling velocity analysis unit to monitor the drift trend of the fog drop cloud cluster including the drift direction, drift rate, cross section distribution and density of the fog drop cloud cluster.
Based on the above embodiment, the converting of the cloud cluster of droplets from the polar coordinate to the spatial three-dimensional coordinate to determine the position of the cloud cluster of droplets includes: and establishing a spatial function conversion relation between the pole of any laser beam and the place where the laser beam is reflected by the fog drop cloud cluster so as to determine the spatial relative position of the fog drop cloud cluster.
Specifically, fig. 4 is a schematic diagram of polar coordinate to spatial three-dimensional coordinate conversion of a cloud of droplets according to an embodiment of the present invention, and as shown in fig. 4, with O as a coordinate origin, assuming that laser beams are all emitted from this point, and with a positive direction of a z-axis of a three-dimensional spatial coordinate system as a laser detection direction. Assume that there is a point P in space and that there is a reflection of the laser beam at that point. The echo information stores the distance R of the point from the origin, the vertical angle offset gamma, and the horizontal angle offsets alpha, beta. Then there is a functional transfer relationship P (x, y, z) ═ F (R, α, β, γ) between the two coordinate systems.
Take point P as an example. According to the method requirements, a vertical elevation angle gamma, an x-axis forward included angle alpha and a y-axis forward included angle beta are analyzed from scanning data. And the distance R from the laser generating and transmitting unit, the following relationship exists between the coordinate and the three-dimensional space coordinate:
x＝R·cosγ·sinα y＝R cosγ·sinβ z＝R·sinγ
and determining the space relative position of the fog drop according to the calculated space coordinate point data, and recording the coordinates of the fog drop as (T, x, y, z), wherein T is a time value when the system receives the echo data of the point.
Based on the above embodiment, the automatic estimation of the density of the whole cloud of droplets specifically includes: randomly selecting a cube with a preset side length in a laser scanning cloud cluster range as a standard sample, and determining the volume of the standard sample; and acquiring the number of the cloud clusters of the fog drops in the standard sample prescription, and acquiring the density of the cloud clusters of the fog drops in the standard sample prescription according to the number of the cloud clusters of the fog drops in the standard sample prescription and the volume of the standard sample prescription.
Further, the counting of the number of the fog drops in the preset area and the calculation of the density of the fog drops specifically comprise: judging whether any droplet cloud cluster point falls into a preset region or not, so as to obtain the number of the droplet cloud clusters in the preset region; and calculating the volume of the preset area, and acquiring the density of the fog drop cloud cluster in the preset area according to the quantity of the fog drop cloud cluster in the preset area and the volume of the preset area.
The cloud cluster density of the fog drops is divided into two types, namely the cloud cluster space distribution density and the cloud cluster cross section distribution density, wherein the former is used for calculating the quantity of the fog drops in the space standard cube, and the latter is used for calculating the quantity of the fog drops in the projection cross section. Therefore, the calculation of the distribution density of the cross section of the cloud cluster of the fog drops is similar to the calculation of the spatial distribution density of the cloud cluster of the fog drops, the cloud cluster of the fog drops is projected to a plane from the space, the cloud cluster of the fog drops is converted into a two-dimensional coordinate from a three-dimensional coordinate, and the distribution density of the cross section of the cloud cluster of the fog drops on the plane is calculated through the two-dimensional coordinate.
It should be noted that, with the laser detection device as the origin of the overall three-dimensional detection area, the flight direction of the aircraft is the x-axis forward direction, the direction perpendicular to the ground is the z-axis, the upward direction is the positive direction, the flight direction of the aircraft is the y-axis horizontally and perpendicularly, and the laser beam emission point is used as the origin O of the coordinate system to establish the coordinate system as shown in the figure.
Specifically, fig. 5 is a schematic position diagram of droplet cloud cluster density calculation according to an embodiment of the present invention, fig. 6 is a schematic flow diagram of droplet cloud cluster density calculation according to an embodiment of the present invention, and as shown in fig. 5 and fig. 6, in order to achieve automatic estimation of the overall cloud cluster density, a cube with a side length of a preset length is continuously selected as a unit sample in a laser scanning cloud cluster range area, and the volume is denoted as V.
At any one time, the number of droplets in a unit square area is referred to as the cloud spatial distribution. The unit square space region position is determined by the vertex coordinate value. The coordinate values of five vertexes of the unit sample are respectively P1(x1，y1，z1)，P2(x2，y2，z2)，P3(x3，y3，z3)，P4(x4，y4，z4)，P1'(x′1,y′1,z′1) Wherein P is1、P2、P3、P4Is the four vertices of the lower surface of the unit square, P1' is a vertex on the upper right of the upper surface in the unit sample. According to the x, y and z coordinate values of any fog drop point, whether the point is in a unit square is determined, namely x1＜x≤x2，y4＜y≤y1，z1＜z≤z′1And determining that the fog drop points are in the unit sample, thereby obtaining that the number of the fog drop points in the unit sample is N, and determining that the density of the fog drops in the unit sample is rho N/V.
And dividing the density of the sample into different grades according to the density value of the fog drops, and marking the different grades with different colors according to the grading color card. And displaying the space color of the sample by contrasting with the corresponding color card grade so as to visually show the density conditions of the droplets at different positions of the cloud cluster and the change trend of the density of the whole droplets in the cloud cluster. Areas with different droplet concentrations are represented by different colors, or areas with different droplet concentrations are represented by the same color but different depths, e.g., areas with darker droplet concentrations are represented by darker colors and areas with lighter droplet concentrations are represented by lighter colors.
Further, in order to support the statistics of the number of the fogdrops in the preset area and the calculation of the density of the fogdrops, namely, the calculation of the density of the fogdrops in any two-dimensional plane and any three-dimensional area in the preset area framed by the user is also supported, the method includes the steps of predicting the density of the fogdrops in a unit sample, firstly obtaining the boundary point coordinates of the preset area selected by the user, storing the boundary point coordinates as a boundary point set, comparing the coordinates of the fogdrops with the boundary coordinates, judging that the fogdrops fall in the preset area when the x, y and z coordinate values of any fogdrops fall in the boundary coordinates of the preset area, and circularly comparing the coordinates until the judgment of all the points is completed until the total number of the fogdrops in. Secondly, dividing the preset area into unit rectangles or unit cubes in a threshold dividing mode by using the boundary coordinate point set, and acquiring an area value or a volume value of the irregular area through cyclic accumulation, wherein the area value or the volume value is recorded as S. The concentration ρ of the fog droplets in the preset regions＝M/S。
Based on the above embodiment, fig. 3 is a schematic structural diagram of a droplet cloud cluster trajectory processing unit of a data processing device for aviation pesticide application droplet cloud cluster drift tendency according to an embodiment of the present invention, and as shown in fig. 3, the droplet cloud cluster trajectory processing unit includes a droplet cloud cluster boundary identifying subunit, a droplet cloud cluster projection processing subunit, and a droplet cloud cluster trajectory describing subunit; the cloud cluster boundary identification subunit is used for extracting cloud cluster boundary coordinates of the droplets at a specific time and acquiring coordinates of a cloud cluster coordinate point set; the droplet cloud cluster projection processing subunit is used for calculating projection sections of the droplet cloud clusters in different planes of a coordinate system at specific time to obtain the droplet cloud cluster section, the droplet cloud cluster deposition section and the droplet cloud cluster depth; and the droplet cloud cluster track description subunit is used for obtaining the profile change and the position movement of the droplet cloud cluster at any moment according to the change and the position movement of the droplet cloud cluster section, the droplet cloud cluster deposition section and the droplet cloud cluster depth at any moment.
At any moment, the projection area of the cloud of fog drops on the Y-Z plane in the space area detected by the laser detection device is called the cross section of the cloud of fog drops at the moment. At any moment, the projection area of the fog drop cloud cluster in the X-Z plane in the space area detected by the laser detection device is called the deposition section of the fog drop cloud cluster at the moment. At any one time, the distribution length of the cloud of droplets on the z-axis is called the cloud depth of the droplets at that time. The change and the position movement of the section of the cloud of droplets at different moments are called the section track of the cloud of droplets. The change and position movement of the cloud depth of the droplets at different times is called the cloud depth trajectory of the droplets. At any one time, the number of droplets in a unit space region is referred to as the cloud spatial distribution. At any moment, the density of the droplets projected in the cross section of the cloud of droplets is called the distribution of the droplets in the cloud of droplets at the moment. The distribution and diffusion of the sprayed liquid medicine are described through the section, the depth, the section track, the depth track, the spatial distribution and the interface distribution of fogdrop and fogdrop.
Specifically, the cloud cluster boundary identification subunit is used for extracting cloud cluster boundary coordinates at a specific time and storing the cloud cluster boundary coordinates in a coordinate point set mode. And the droplet cloud cluster projection processing subunit is used for calculating projection cross sections of the droplet cloud clusters in different planes of the coordinate system at specific time. The droplet cloud cluster trajectory description subunit is used for displaying the change condition of the boundary of the droplet cloud cluster at different moments.
Fig. 7 is a schematic diagram of a cloud cluster boundary according to an embodiment of the present invention, and as shown in fig. 7, to obtain a coordinate point set of the cloud cluster boundary at a certain time, first, a z value is determined by using Δ h as a threshold, and points with the same z value are taken to form a plane, so as to divide a scanning cloud cluster into two-dimensional planes with infinite proximity in a vertical direction. Secondly, the y value is judged by taking the delta s as a threshold value, points with the same y value are taken to form a line, and the plane is divided into lines which are infinitely close. And finally, circularly comparing the x coordinates of all the points on the line to obtain the maximum value and the minimum value. The x, y, z point coordinate values at this time are recorded in the point set.
And at any moment, projecting the detected fogdrop cloud cluster in a space coordinate system by using a fogdrop cloud cluster projection processing subunit. The area projected on the Y-Z plane is called the mist cloud section at the moment, the area projected on the X-Z plane is called the mist cloud deposition section at the moment, and the projection length in the Z-axis direction is called the mist cloud depth at the moment. And obtaining the cloud cluster projection, namely obtaining the cloud cluster boundary maximum value in the projection direction.
Fig. 8 is a schematic diagram of cloud projection of droplets according to an embodiment of the present invention, and as shown in fig. 8, in order to obtain cloud projection of Y-Z plane, a boundary data point set obtained by a boundary identification unit is required. In order to not influence the storage of the boundary point set data, the point set data is backed up and stored, and the fogdrop cloud cluster projection processing subunit calls the point set data. Firstly, all the x coordinates of the points stored in the point set are set to 0, and the coordinate points are unified in one plane. And secondly, starting from the minimum value of the Y value, gradually increasing the Y value by taking delta Y as a threshold value, dividing the plane into wireless approximate lines, circularly comparing Z coordinate values of all points on the lines to obtain the maximum value and the minimum value of the Z coordinate, and recording the coordinates in a new point set at the moment, wherein the point set represents the cross section of the cloud cluster of the fog drops on the Y-Z plane.
It should be noted that the cross section of the cloud of droplets and the deposition cross section of the cloud of droplets have three important parameters, namely cross section area, maximum horizontal width and moving speed. In order to obtain the cross-sectional area, a mode of circularly intercepting the maximum inscribed rectangle is adopted, the maximum inscribed rectangle is fitted in an area which is not calculated, circulation is continuously carried out, and the boundary value of the minimum rectangle is 10 cm. The sectional area value S of the fogdrop cloud cluster is obtained by accumulating the areas of all rectanglesa。
In order to obtain the maximum horizontal width of the cross section, the width values of the 2 cross sections along the y-axis direction are obtained, and the values of the 2 cross sections are the same at the same time. Circularly comparing Y-axis coordinate values of the same z-axis coordinate values of the cross sections of the fogdrop cloud cluster, and recording the maximum Y-axis coordinate valuemaxAnd minimum value YminAnd calculating the horizontal width m at the moment, and taking the maximum value of m as the maximum horizontal width value of the section after all the coordinate values of the z axis are cycled.
In order to obtain the fog drop cloud cluster depth data, the boundary data stored by the fog drop cloud cluster projection processing subunit is utilized to circularly compare the coordinate values of the Z axes of all coordinate points of the boundary, and the maximum value Z of the Z coordinate in the set of the boundary points is takenmaxAnd minimum value ZminAnd the calculated absolute value H of the difference between the two is the depth value of the fogdrop cloud cluster at the moment.
To obtain the value of the cross-section moving speed, Z obtained in the depth calculation of the cloud cluster of the fogdrops is firstly utilizedmax、ZminThe value of Z coordinate at the position of calculating the median of the two is recorded as ZmAt each time ZmThe degree of change in value reflects the rate of movement of the cloud of droplets in the direction perpendicular to the cross-section. Secondly, the Y obtained in the maximum horizontal width calculation is utilizedmaxAnd YminThe value of Y coordinate value at the position of calculating the median of the two is recorded as YmAt each time YmThe degree of change in value reflects the rate of horizontal movement of the cloud deposition cross-section. Respectively calculate Zm、YmAnd dividing the minimum time interval variation by the time interval, and calculating the moving speed of the fog drop cloud cluster in the vertical and horizontal directions at different moments.
The fog drop interface distribution is the fog drop density projected in the cross section of the fog drop cloud at any moment. The sectional area of the fog drop cloud cluster and the quantity value of the fog drop points in the projection section need to be obtained respectively. The cross section area value S of the fogdrop cloud clusteraDividing the value by the number value Q of the fog drop points in the projection section to obtain the distribution value Q/S of the fog drop sectiona。
In order to count the number of fog drops in the projection section, the stored coordinates x of the fog drops are stored again after being set to zero, and the number Q of the fog drops is counted. And carrying out cyclic comparison in the point set, only keeping one effective numerical value for the same coordinate value, and correspondingly reducing the Q value.
And the droplet cloud cluster track description subunit reflects the profile change and position movement conditions of the droplet cloud cluster at different moments. The change and the position movement of the section of the cloud of droplets at different moments are called the section track of the cloud of droplets. The change and position movement of the cloud depth of the droplets at different times is called the cloud depth trajectory of the droplets.
In order to reflect the overall change condition of the cloud cluster, a point set stored in the cloud cluster boundary identification subunit is used for drawing and fitting the overall boundary points of the cloud cluster into a curved surface by using an algorithm in a three-dimensional coordinate system.
Two different representation modes are provided for reflecting the section track of the fogdrop cloud cluster, namely feature point fitting and integral boundary representation. When the characteristic points are used for fitting, the maximum values and the minimum values of the directions of the y axis and the z axis of the section of the fogdrop cloud cluster are selected, and the 4 point coordinate values are used for fitting the ellipse to reflect the overall change condition of the fogdrop cloud cluster. When the overall boundary is used for representation, the cross section contour is represented by all coordinate points of the cross section of the cloud cluster of the fogdrop. And drawing the coordinates of the stored points in a specific space by using the point set data stored by the fogdrop cloud cluster projection processing subunit, and displaying the spatial position information of the cloud cluster projection section.
In order to reflect the fog drop cloud cluster depth track, a fog drop cloud cluster depth value H data set and fog drop cloud cluster section moving speed representation values Zm and Ym data sets obtained by a fog drop cloud cluster projection processing subunit are utilized, and the depth value H is represented in a space coordinate system in a line segment mode according to a position point corresponding to a section moving speed coordinate data set.
The displayed outline images are continuously refreshed at specific time intervals in the above representation modes, the new image and the original image are displayed in the same coordinate system, the color of the original image gradually becomes lighter along with the change of time, the color of the new image keeps the highest saturation, and the cloud cluster diffusion condition along with the change of the color is intuitively reflected.
Based on the above embodiment, the droplet cloud sedimentation velocity analysis unit is configured to complete the analysis of the obtained sedimentation related data values of the obtained droplet cloud, and specifically includes: calculating the integral settling rate and the offset angle of the fogdrop cloud cluster at each time point according to the moving speed values of the fogdrop cloud cluster in the vertical direction or the horizontal direction at different moments of the cross section of the fogdrop cloud cluster, thereby obtaining the integral settling rate of the fogdrop cloud cluster; through obtaining conditions such as ambient wind speed in the test and carrying out correlation analysis on the integral sedimentation speed of the fogdrop cloud cluster, the influence degree of the ambient wind speed on the sedimentation speed of the fogdrop cloud cluster is obtained, and the deposition condition and the drift trend of the fogdrop cloud cluster are monitored.
Specifically, the droplet cloud sedimentation velocity analysis unit mainly performs the analysis of the obtained sedimentation-related data values of the obtained droplet cloud. The vertical and horizontal moving speed values of the cross section of the fog drop cloud cluster at different moments can be obtained in the spray drop cloud cluster track processing unit, the integral settling rate and the offset angle of the fog drop cloud cluster at each time point can be calculated through the two values, and the integral settling rate of the fog drop cloud cluster is obtained. Through obtaining conditions such as ambient wind speed and the like in the test and carrying out correlation analysis on the integral settling velocity of the fogdrop cloud cluster, the influence degree of the ambient wind speed on the settling velocity of the fogdrop cloud cluster is obtained, and the deposition condition and the drift trend of fogdrop cloud clusters are predicted.
On the other hand, based on the above embodiment, fig. 9 is a schematic flow chart of a method for monitoring a drift tendency of a cloud cluster of aerial pesticide application liquid droplets according to an embodiment of the present invention, and as shown in fig. 9, an embodiment of the present invention further provides a method for monitoring a drift tendency of a cloud cluster of aerial pesticide application liquid droplets in real time, where the method includes: emitting laser beams to the cloud cluster of droplets and recovering the laser beams reflected by the cloud cluster of droplets; and monitoring the drift trend of the cloud cluster of the fog drops in real time according to the information of the emitted laser beams and the laser beams reflected by the cloud cluster of the fog drops, wherein the drift trend of the cloud cluster of the fog drops comprises the drift direction, the drift rate, the cross section distribution and the density of the cloud cluster of the fog drops.
Specifically, in order to determine the position of the mist cloud cluster of the pesticide application liquid, a laser beam is emitted to the mist cloud cluster, the laser beam is emitted and transmitted after encountering the mist cloud cluster, the transmitted laser beam is further transmitted in the space, and is reflected and transmitted after encountering the mist cloud cluster again, so that multiple echoes can be realized by one laser beam, and the laser beam extends to the depth direction of the space of a scanning area. Therefore, the drift trend of the cloud cluster of the fog drops is monitored in real time according to the information of the emitted laser beams and the laser beams reflected by the cloud cluster of the fog drops, and the drift trend comprises the drift direction, the drift speed, the cross section distribution and the density of the cloud cluster of the fog drops.
The embodiment of the invention starts from the whole process of pesticide application, and realizes real-time dynamic monitoring of the liquid medicine cloud cluster by changing the traditional spray monitoring mode, namely, the measurement of key parameters of the liquid medicine cloud cluster is realized based on a laser scanning method, so that the drift trend of the liquid medicine cloud cluster is monitored, and the defects of the traditional liquid medicine cloud cluster drift monitoring mode are overcome.
Based on the above embodiment, the method for monitoring the drift tendency of the cloud cluster of droplets in real time according to the emitted laser beam and the information of the laser beam reflected by the cloud cluster of droplets specifically includes: recording information of laser beams reflected by the emitted laser beams by the cloud cluster of the fogdrops to obtain a coordinate point set of the cloud cluster of the fogdrops; storing boundary point coordinates of a preset area as a boundary point set, and comparing the boundary point set with a cloud cluster coordinate point set to obtain the cloud cluster density of the fog drops in the preset area; and fitting according to the cloud cluster coordinate point set to obtain the cross section of the cloud cluster, the deposition cross section of the cloud cluster and the track of the depth of the cloud cluster so as to monitor the drift trend of the cloud cluster in real time.
Specifically, the spatial position of the cloud cluster of the droplets is determined according to the emission-return time difference of the laser beam reflected by the cloud cluster of the droplets and the emission angle of the laser beam, and a coordinate point set of the cloud cluster of the droplets is obtained; the method comprises the steps of defining a preset area, storing boundary point coordinates of the preset area as a boundary point set, comparing the boundary point sets of the cloud cluster coordinate point sets of the fogdrops, determining that the cloud clusters of the fogdrops fall into the preset area when the cloud cluster coordinate point set of the fogdrops is determined to fall into the boundary point set, and determining the density of the cloud clusters of the fogdrops in the preset area according to the number of the cloud clusters of the fogdrops in the preset area and the area of the preset area; meanwhile, the cross section of the fog drop cloud cluster, the deposition cross section of the fog drop cloud cluster and the depth track of the fog drop cloud cluster are obtained according to the matching of the coordinate point set of the fog drop cloud cluster, so that the motion track of the fog drop cloud cluster is obtained, and the effect of monitoring the drift trend of the fog drop cloud cluster in real time is realized.
The embodiment of the invention emits laser beams to the pesticide liquid mist cloud cluster, and the position, the moving direction, the moving speed, the density and the like of the mist cloud cluster are determined by the laser beams reflected by the mist cloud cluster, so that the drifting trend of the mist cloud cluster is monitored. The invention can realize three-dimensional monitoring of the cloud cluster of the fogdrop, provides more comprehensive data for researching the drift and diffusion of the liquid medicine cloud cluster and the influence of environmental factors on the drift of the cloud cluster of the fogdrop, and provides a more perfect data support basis for the follow-up prediction of the drift trend of the cloud cluster of the fogdrop.
The above-described embodiments of the apparatuses and devices are merely illustrative, and 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 multiple 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 (8)
1. A monitoring system for aerial pesticide application liquid medicine cloud cluster drifting trend is characterized by comprising: the laser detection device and the data processing device are connected with each other;
the laser detection device is used for emitting laser beams and recovering the laser beams reflected by the fog drop cloud cluster;
the data processing device is used for monitoring the drift trend of the fog drop cloud cluster in real time according to the emitted laser beam and the information of the laser beam reflected by the fog drop cloud cluster; the drift tendency of the fog drop cloud cluster comprises the drift direction, the drift speed, the cross section distribution and the density of the fog drop cloud cluster;
the laser detection device comprises a laser generation and emission unit and a laser echo receiving and processing unit which are connected with each other;
the laser generating and emitting unit consists of a laser generating and emitting dot matrix unit and is used for emitting laser beams according to a preset angle;
the laser echo receiving and processing unit is used for receiving a reflected laser beam and storing information of the reflected laser beam, wherein the information of the reflected laser beam comprises echo time, a laser transmitter number, a laser transmitter deflection angle, a laser transmitter scanning frequency, an echo distance, echo width and echo intensity;
the data processing device comprises a fogdrop cloud cluster space positioning unit, a fogdrop cloud cluster drawing unit, a fogdrop cloud cluster space distribution density analysis unit, a fogdrop cloud cluster track processing unit and a fogdrop cloud cluster settling velocity analysis unit;
the droplet cloud cluster space positioning unit is used for converting a droplet cloud cluster from a polar coordinate to a space three-dimensional coordinate so as to determine the position of the droplet cloud cluster point;
the droplet cloud cluster drawing unit is used for drawing coordinate points at corresponding positions of a space coordinate system according to the space three-dimensional coordinate to represent the droplet cloud clusters scanned by the laser;
the mist drop cloud cluster space distribution density analysis unit is used for calculating the density of the liquid medicine mist drop cloud clusters in the mist drop cloud cluster area scanned by the laser and performing coloring visual display so as to realize automatic estimation of the density of the whole mist drop cloud clusters, statistics of the number of the mist drop cloud clusters in a preset area and calculation of the density of the mist drop cloud clusters;
the cloud droplet cloud cluster track processing unit is used for extracting and storing the boundary coordinates of the cloud droplet cloud cluster at a specific time in a coordinate point set mode, calculating projection sections of the cloud droplet cloud cluster at the specific time on different planes of a coordinate system, and displaying the change condition of the boundary of the cloud droplet cloud cluster at different moments;
and the fogdrop cloud group sedimentation velocity analysis unit is used for completing the analysis work of the obtained sedimentation related data value of the fogdrop cloud group.
2. The system for monitoring the drift tendency of a cloud of aerial pesticide application liquid droplets according to claim 1, wherein the conversion of the cloud of aerial pesticide application liquid droplets from polar coordinates to three-dimensional spatial coordinates is performed to determine the position of the cloud of aerial pesticide application liquid droplets, and specifically comprises: and establishing a spatial function conversion relation between the pole of any laser beam and the position where the laser beam is reflected by the fog drop cloud cluster so as to determine the spatial relative position of the fog drop cloud cluster.
3. The system for monitoring the drift tendency of aerial pesticide spray cloud, as claimed in claim 1, wherein the automatic estimation of the overall cloud density comprises:
randomly selecting a cube with a preset side length in a fog drop cloud cluster area scanned by laser as a standard sample, and determining the volume of the standard sample;
and acquiring the number of the cloud droplets in the standard sample, and acquiring the density of the cloud droplets in the standard sample according to the number of the cloud droplets in the standard sample and the volume of the standard sample.
4. The system for monitoring the drift tendency of aerial pesticide spray liquid mist cloud clusters as claimed in claim 1, wherein the statistics of the number of the mist cloud clusters in the preset area and the calculation of the density of the mist cloud clusters specifically comprise:
judging whether any droplet cloud cluster point falls into the preset area or not, so as to obtain the number of the droplet cloud clusters in the preset area;
and calculating the volume of the preset area, and acquiring the density of the fog drop cloud cluster in the preset area according to the quantity of the fog drop cloud cluster in the preset area and the volume of the preset area.
5. The system for monitoring the drift tendency of aerial pesticide application liquid medicine fogdrop clouds according to claim 1, wherein the fogdrop cloud trajectory processing unit comprises a fogdrop cloud boundary identification subunit, a fogdrop cloud projection processing subunit and a fogdrop cloud trajectory description subunit;
the cloud droplet cloud cluster boundary identification subunit is used for extracting cloud droplet cloud cluster boundary coordinates at a specific time and acquiring cloud droplet cloud cluster coordinate point set coordinates;
the droplet cloud cluster projection processing subunit is used for calculating projection sections of the droplet cloud clusters in different planes of a coordinate system at specific time to obtain the droplet cloud cluster section, the droplet cloud cluster deposition section and the droplet cloud cluster depth;
the droplet cloud cluster trajectory description subunit is used for obtaining the profile change and the position movement of the droplet cloud cluster at any moment according to the change and the position movement of the droplet cloud cluster cross section, the droplet cloud cluster deposition cross section and the droplet cloud cluster depth at any moment.
6. The system for monitoring the drift tendency of the cloud cluster of aerial pesticide application liquid droplets according to claim 5, wherein the cloud cluster settling velocity analysis unit is configured to perform an analysis operation on the obtained data values related to the settling of the cloud cluster of droplets, and specifically comprises:
calculating the integral settling rate and the offset angle of the fogdrop cloud cluster at each time point according to the moving speed values of the fogdrop cloud cluster in the vertical direction or the horizontal direction at different moments of the cross section of the fogdrop cloud cluster, thereby obtaining the integral settling rate of the fogdrop cloud cluster;
through obtaining the environmental wind speed in the test and carrying out correlation analysis on the integral sedimentation speed of the fogdrop cloud cluster, the influence degree of the environmental wind speed on the integral sedimentation speed of the fogdrop cloud cluster is obtained, and the deposition condition and the drift trend of the fogdrop cloud cluster are monitored.
7. The real-time monitoring method of the aerial pesticide spray liquid droplet cloud drift tendency monitoring system based on the claim 1 is characterized by comprising the following steps:
emitting a laser beam to the cloud of droplets and recovering the laser beam reflected by the emitted laser beam by the cloud of droplets;
monitoring the drift trend of the cloud cluster of the droplets in real time according to the information of the emitted laser beams and the laser beams reflected by the cloud cluster of the droplets, wherein the drift trend of the cloud cluster of the droplets comprises the drift direction, the drift rate, the cross section distribution and the density of the cloud cluster of the droplets;
the laser detection device comprises a laser generation and emission unit and a laser echo receiving and processing unit which are connected with each other;
the laser generating and emitting unit consists of a laser generating and emitting dot matrix unit and is used for emitting laser beams according to a preset angle;
the laser echo receiving and processing unit is used for receiving a reflected laser beam and storing information of the reflected laser beam, wherein the information of the reflected laser beam comprises echo time, a laser transmitter number, a laser transmitter deflection angle, a laser transmitter scanning frequency, an echo distance, echo width and echo intensity;
the data processing device comprises a fogdrop cloud cluster space positioning unit, a fogdrop cloud cluster drawing unit, a fogdrop cloud cluster space distribution density analysis unit, a fogdrop cloud cluster track processing unit and a fogdrop cloud cluster settling velocity analysis unit;
the droplet cloud cluster space positioning unit is used for converting a droplet cloud cluster from a polar coordinate to a space three-dimensional coordinate so as to determine the position of the droplet cloud cluster point;
the droplet cloud cluster drawing unit is used for drawing coordinate points at corresponding positions of a space coordinate system according to the space three-dimensional coordinate to represent the droplet cloud clusters scanned by the laser;
the device comprises a cloud droplet cloud cluster space distribution density analysis unit, a cloud droplet cloud cluster density analysis unit and a cloud droplet cloud cluster density analysis unit, wherein the cloud droplet cloud cluster space distribution density analysis unit is used for calculating the density of liquid medicine cloud droplets in a scanned cloud droplet cloud cluster region range and performing coloring visual display so as to realize automatic estimation of the density of the whole cloud droplet cloud cluster, statistics of the number of the cloud droplet cloud clusters in a preset region and calculation of the;
the cloud droplet cloud cluster track processing unit is used for extracting and storing the boundary coordinates of the cloud droplet cloud cluster at a specific time in a coordinate point set mode, calculating projection sections of the cloud droplet cloud cluster at the specific time on different planes of a coordinate system, and displaying the change condition of the boundary of the cloud droplet cloud cluster at different moments;
and the fogdrop cloud group sedimentation velocity analysis unit is used for completing the analysis work of the obtained sedimentation related data value of the fogdrop cloud group.
8. The real-time monitoring method according to claim 7, wherein the real-time monitoring of the drift tendency of the cloud of droplets according to the information of the emitted laser beam and the laser beam reflected by the cloud of droplets comprises:
recording information of laser beams reflected by the emitted laser beams by the fogdrop cloud cluster to obtain a fogdrop cloud cluster coordinate point set;
storing boundary point coordinates of a preset area as a boundary point set, and comparing the boundary point set with the cloud cluster coordinate point set to obtain the cloud cluster density of the fog drops in the preset area;
and fitting according to the cloud cluster coordinate point set to obtain the cross section of the cloud cluster, the deposition cross section of the cloud cluster and the track of the depth of the cloud cluster so as to monitor the drift trend of the cloud cluster in real time.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910104804.9A CN110006614B (en) | 2019-02-01 | 2019-02-01 | System and method for monitoring drift trend of aerial pesticide application liquid medicine fogdrop cloud cluster |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910104804.9A CN110006614B (en) | 2019-02-01 | 2019-02-01 | System and method for monitoring drift trend of aerial pesticide application liquid medicine fogdrop cloud cluster |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110006614A CN110006614A (en) | 2019-07-12 |
| CN110006614B true CN110006614B (en) | 2021-01-05 |
Family
ID=67165627
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910104804.9A Active CN110006614B (en) | 2019-02-01 | 2019-02-01 | System and method for monitoring drift trend of aerial pesticide application liquid medicine fogdrop cloud cluster |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110006614B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115053882B (en) * | 2022-08-05 | 2023-01-31 | 北京市农林科学院智能装备技术研究中心 | Aerial pesticide application method and device, electronic equipment and storage medium |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7388662B2 (en) * | 2005-09-30 | 2008-06-17 | Institut National D'optique | Real-time measuring of the spatial distribution of sprayed aerosol particles |
| CN103424276B (en) * | 2013-08-09 | 2016-04-27 | 北京农业信息技术研究中心 | A kind of telecontrolled aircraft variable pesticide spraying test platform device and method |
| CN105300851B (en) * | 2015-11-11 | 2017-08-25 | 中国农业大学 | A kind of detection method of the spraying droplet three-dimensional spatial distribution based on laser technology |
| CN105842132A (en) * | 2016-04-28 | 2016-08-10 | 北京农业智能装备技术研究中心 | Aerial pesticide application spray automatic test system |
| CN106124156B (en) * | 2016-06-20 | 2019-08-13 | 北京农业智能装备技术研究中心 | For studying the testing equipment of droplet drift and for the processing method of the equipment |
| CN109116373B (en) * | 2018-07-17 | 2022-12-09 | 江苏省农业科学院 | Droplet drift detection system based on two-dimensional laser radar scanning sensor |
| CN109187292B (en) * | 2018-09-18 | 2022-04-05 | 江苏擎宇化工科技有限公司 | Device for testing droplet transfer behavior |
-
2019
- 2019-02-01 CN CN201910104804.9A patent/CN110006614B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN110006614A (en) | 2019-07-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107561547B (en) | Method, device and system for measuring distance from power transmission line to target object | |
| US20220383484A1 (en) | Tunnel defect detecting method and system using unmanned aerial vehicle | |
| CN105812733B (en) | A kind of scene monitoring guiding system of air traffic control | |
| AU2013245476B2 (en) | Tree metrology system | |
| CN115597659B (en) | Intelligent safety management and control method for transformer substation | |
| Takahashi et al. | Estimating individual tree heights of sugi (Cryptomeria japonica D. Don) plantations in mountainous areas using small-footprint airborne LiDAR | |
| CN104808216B (en) | A kind of vehicle collision avoidance early warning system based on laser radar range | |
| CN110688904A (en) | Base station antenna parameter surveying method and device based on 5G unmanned aerial vehicle | |
| JP2011123060A (en) | Identification-only optronic system and method for forming three-dimensional image | |
| CN113532293B (en) | Structure dynamic displacement measuring method and system based on unmanned aerial vehicle | |
| CN108535789A (en) | A kind of foreign matter identifying system based on airfield runway | |
| CN107941170A (en) | Road detection apparatus and system | |
| CN114743021A (en) | Fusion method and system of power transmission line image and point cloud data | |
| CN108710818A (en) | A kind of real-time monitoring and statistics system and method for number based on three-dimensional laser radar | |
| CN107221006A (en) | A kind of communication single pipe tower slant detection method based on unmanned plane imaging platform | |
| CN108596117A (en) | A kind of scene monitoring method based on scanning laser range finder array | |
| CN110006614B (en) | System and method for monitoring drift trend of aerial pesticide application liquid medicine fogdrop cloud cluster | |
| CN115825067A (en) | Geological information acquisition method and system based on unmanned aerial vehicle and electronic equipment | |
| CN104464055A (en) | PSD linear array and ultrasonic linear array combined passenger flow volume calculation system | |
| CN108803620A (en) | A kind of UWB positioning systems for robot | |
| Gangadharan et al. | A comparison of approaches for citrus canopy profile generation using ultrasonic and Leddar® sensors | |
| US20240103537A1 (en) | Methods, systems, and devices for inspecting structures and objects | |
| Mor | Generating photo-realistic images from LiDAR point clouds with generative adversarial networks | |
| Jacob et al. | Assessment of Lockheed Martin's aircraft wake vortex circulation estimation algorithms using simulated lidar data | |
| CN114049580A (en) | Airport apron aircraft positioning system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |