WO2019137135A1 - Plant protection unmanned aerial vehicle operation effect evaluation method - Google Patents

Plant protection unmanned aerial vehicle operation effect evaluation method Download PDF

Info

Publication number
WO2019137135A1
WO2019137135A1 PCT/CN2018/120307 CN2018120307W WO2019137135A1 WO 2019137135 A1 WO2019137135 A1 WO 2019137135A1 CN 2018120307 W CN2018120307 W CN 2018120307W WO 2019137135 A1 WO2019137135 A1 WO 2019137135A1
Authority
WO
WIPO (PCT)
Prior art keywords
spray
plant protection
time
protection drone
coordinates
Prior art date
Application number
PCT/CN2018/120307
Other languages
French (fr)
Chinese (zh)
Inventor
薛新宇
顾伟
孙竹
丁素明
秦维彩
陈晨
杨风波
蔡晨
张宋超
周良富
周立新
Original Assignee
农业部南京农业机械化研究所
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by 农业部南京农业机械化研究所 filed Critical 农业部南京农业机械化研究所
Priority to AU2018402493A priority Critical patent/AU2018402493A1/en
Publication of WO2019137135A1 publication Critical patent/WO2019137135A1/en

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/18502—Airborne stations
    • H04B7/18506—Communications with or from aircraft, i.e. aeronautical mobile service
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/029—Location-based management or tracking services

Definitions

  • the invention belongs to the technical field of plant protection drones, and particularly relates to an evaluation method for the operation effect of a planting maintenance drone.
  • the technical problem to be solved by the present invention is to provide an evaluation method for the operation effect of the planting protection drone for the above-mentioned deficiencies of the prior art, and the method for evaluating the operation effect of the plant protection drone can accurately calculate the effective spraying rate and leakage of the plant protection drone.
  • the spraying efficiency parameters of the plant protection drone are evaluated by the spraying effect parameters such as the spray rate, the re-spray rate, the hourly productivity of the shift, the hourly productivity of the pure spray, the time utilization rate, the use reliability coefficient, and the labor productivity.
  • the technical solution adopted by the present invention is:
  • a planting protection drone operation effect evaluation method comprising an operation effect evaluation system, the work effect evaluation system includes an onboard operation information collection device, a cloud server, and an intelligent terminal; and the onboard operation information collection device is installed in the plant protection On-board and used to measure the flight status information of the plant protection drone and send the flight status information to the cloud server through the 4G wireless network.
  • the cloud server is used to calculate the spray effect parameter according to the flight state information
  • the smart terminal is used to log in to the cloud server to view the spray effect.
  • the flight status information includes coordinate information of a flight path point of the plant protection drone, and the spray effect parameter includes an effective spray rate, a leak rate, a re-spray rate, a shift time hourly productivity, a pure spray time hourly productivity, Time utilization, use reliability factor and labor productivity;
  • the on-board operation information collection device records the operation width of the plant protection drone, the coordinates of the flight path point of the plant protection drone, and the working shift time of the plant protection drone, and the operation width of the plant protection drone The width, the coordinates of the flight path point, and the job shift time are sent to the cloud server;
  • the cloud server calculates the spray area between the two track points corresponding to the adjacent work time in the work shift time according to the operation width of the plant protection drone, the coordinates of the flight track point, and the work shift time;
  • the cloud server counts the total spray area during the shift time according to the result calculated in step (2), and calculates the effective spray rate, leak rate and re-spray rate of the plant protection drone according to the total spray area of the plant protection drone. , shift time hourly productivity, pure spray time hourly productivity, time utilization, use reliability factor and labor productivity.
  • the step (3) includes:
  • the effective spraying rate ⁇ v , the leakage rate ⁇ m and the re-injection rate ⁇ o are respectively:
  • W b is the hourly productivity of the shift
  • T b is the shift time of the shift
  • the pure spray time hourly productivity is:
  • W s is the pure spray hourly productivity and T s is the pure spray time
  • ⁇ k is the reliability factor used
  • T g is the fault time
  • the labor productivity is:
  • G j labor productivity and A j is the number of crew operations.
  • the step (1) includes:
  • the on-board operation information collecting device comprises a positioning antenna, a positioning module and a main control unit; the positioning module separately collects coordinates of two ends of the spray bar of the plant protection drone through two positioning antennas and sends the coordinates to the main control module
  • the main control unit calculates the coordinates of the flight path point of the plant protection drone according to the coordinates of the two ends of the spray bar of the plant protection drone, and the coordinates of the flight path point are the two coordinate points detected by the two positioning antennas.
  • the main control unit of the onboard operation information collecting device collects the working state of the internal liquid pump of the plant protection drone to calculate the working shift time of the plant protection drone;
  • the onboard operation information collecting device records the working width of the plant protection drone and transmits the working width of the plant protection drone, the coordinates of the flight path point, and the work shift time to the cloud server.
  • the step (2) includes:
  • the invention has the beneficial effects that the invention can effectively and accurately calculate the effective spraying rate, the leakage rate, the re-spray rate, the shift time, the hourly productivity, and the pure spraying of the plant protection drone by the planting protection drone operation effect evaluation method.
  • Time-hour productivity, time utilization, reliability factor and labor productivity are used to evaluate the efficiency and effectiveness of plant protection drones, laying the foundation for the subsequent improvement of plant protection drones.
  • Figure 1 is a schematic view of the structure of the present invention.
  • Figure 2 is a flow chart of the operation of the present invention.
  • the method for evaluating the operation effect of the planting maintenance drone includes the operation effect evaluation system.
  • the operation effect evaluation system includes an onboard operation information collection device, a cloud server, and an intelligent terminal;
  • the operation information collecting device is installed on the plant protection drone and is used for measuring the flight state information of the plant protection drone and transmitting the flight state information to the cloud server through the 4G wireless network, and the cloud server calculates the spraying effect parameter according to the flight state information, and the smart terminal is used for Logging in to the cloud server to view the spray effect parameter;
  • the flight state information includes a flight path point of the plant protection drone, and the spray effect parameters include an effective spray rate, a leak rate, a re-spray rate, a shift time hourly productivity, and a pure spray Time-hour productivity, time utilization, use reliability factor, and labor productivity.
  • the onboard operation information collection device accurately records the aircraft state data of the plant protection drone, and transmits the aircraft state data collected in real time to the cloud server through the 4G wireless network.
  • the cloud server aggregates the data and calculates the spray effect parameters, including spray coverage, re-spray leakage rate, drone efficiency, and reliability. Users can view the spray directly through a smart terminal such as a computer or mobile phone.
  • the method for evaluating the effect of the plant protection drone includes the following steps:
  • the on-board operation information collection device inserting the SIM card into the cover of the on-board operation information collection device, and the on-board operation information collection device is internally provided with a 4G communication module and a 4G antenna, through the 4G communication module, the 4G antenna and the SIM
  • the card is connected to the cloud server;
  • the onboard operation information collection device further includes two GPS positioning antennas, a positioning module and a main control unit;
  • the cloud server calculates the spray area between the two track points corresponding to the adjacent work time in the work shift time according to the operation width of the plant protection drone, the coordinates of the flight track point and the work shift time;
  • the cloud server counts the total spray area during the shift time according to the result calculated in step (4), and calculates the effective spray rate, leak rate and re-spray rate of the plant protection drone according to the total spray area of the plant protection drone.
  • the step (5) includes:
  • the effective spraying rate ⁇ v , the leakage rate ⁇ m and the re-injection rate ⁇ o are respectively:
  • W b is the hourly productivity of the shift
  • T b is the shift time of the shift
  • the pure spray time hourly productivity is:
  • T s is pure spray time
  • ⁇ k is the reliability factor used
  • T g is the fault time
  • the labor productivity is:
  • G j labor productivity and A j is the number of crew operations.
  • the step (3) described includes:
  • the positioning module separately collects the coordinates of the two ends of the spray bar of the plant protection drone corresponding to each work time in the work shift time through two positioning antennas and sends the coordinates to the main control module according to the plant protection drone
  • the coordinates of the two ends of the spray bar are used to calculate the coordinates of the flight path point of the plant protection drone, and the coordinates of the flight track point are the midpoint coordinates of the two coordinate points detected by the two positioning antennas;
  • the Hall element detects the working current of the liquid pump in real time to detect whether the liquid pump operates, and the Hall element transmits the detected signal to the main control unit of the onboard operation information collecting device. Further realizing the real-time detection of the working state of the liquid pump by the main control unit, and counting the working shift time of the plant protection drone;
  • the onboard operation information collecting device records the working width of the plant protection drone and transmits the working width of the plant protection drone, the coordinates of the flight path point, and the work shift time to the cloud server.
  • the step (4) described includes:
  • the cloud server filters the coordinates of the flight path point by an adaptive Gaussian filtering algorithm
  • w i is the working width of the plant protection drone
  • ⁇ i is the angle between the extending direction of the spray bar and the flight trajectory at time t i ; the flight trajectory is the line connecting each track point;
  • the spray area of the adjacent two track points P i , P i+1 is:

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Strategic Management (AREA)
  • Signal Processing (AREA)
  • Development Economics (AREA)
  • Educational Administration (AREA)
  • Economics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Game Theory and Decision Science (AREA)
  • Theoretical Computer Science (AREA)
  • Astronomy & Astrophysics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Catching Or Destruction (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

A plant protection unmanned aerial vehicle operation effect evaluation method, comprising an on-board operation information collection apparatus, a cloud server and a smart terminal. The on-board operation information collection apparatus is mounted on a plant protection unmanned aerial vehicle, and is used for measuring flight status information of the plant protection unmanned aerial vehicle and sending the flight status information to the cloud server. The cloud server is used for calculating spray effect parameters according to the flight status information. The smart terminal is used for logging in to the cloud server in order to view the spray effect parameters. The flight status information comprises coordinate information of flight path points of the plant protection unmanned aerial vehicle. The spray effect parameters comprise an effective spray rate, a mis-spray rate, a re-spray rate, a flight time hourly productivity, a pure spray time hourly productivity, a time utilisation rate, a usage reliability factor and a labour productivity. The evaluation method can accurately calculate the spray effect parameters such as the effective spray rate, the mis-spray rate, the re-spray rate and the flight time hourly productivity of the plant protection unmanned aerial vehicle, and thereby evaluate the operation efficiency and effect of the plant protection unmanned aerial vehicle.

Description

植保无人机作业效果评价方法Plant protection drone operation effect evaluation method 技术领域Technical field
本发明属于植保无人机技术领域，具体涉及一种植保无人机作业效果评价方法。The invention belongs to the technical field of plant protection drones, and particularly relates to an evaluation method for the operation effect of a planting maintenance drone.
背景技术Background technique
近年来，随着农业无人机(unmanned aerial vehicle,UAV)的出现，航空植保领域的研究与应用越来越广泛。当前，植保无人飞机发展迅速，尤其是在中国、日本、韩国等东亚地区。无人飞机在植保作业时，机具的作业效果和效率关系到生产成本和农田增收，直接影响农民使用无人机的积极性。In recent years, with the emergence of unmanned aerial vehicles (UAVs), research and application in the field of aviation plant protection has become more widespread. At present, plant protection unmanned aircraft is developing rapidly, especially in East Asia such as China, Japan and South Korea. When the unmanned aircraft is in plant protection operation, the operation effect and efficiency of the machine are related to the production cost and the increase of farmland, which directly affects the enthusiasm of farmers to use the drone.
因此急需发明一种植保无人机作业效果评价方法来计算有效喷洒率、漏喷率、重喷率、班次时间小时生产率等喷洒效果参数从而来评价植保无人机的作业效率和效果，从而为植保无人机的后续改进工作的开展奠定基础。Therefore, it is urgent to invent a planting protection drone operation evaluation method to calculate the effective spraying rate, leakage rate, re-spray rate, shift time hourly productivity and other spray effect parameters to evaluate the efficiency and effect of plant protection drones. The foundation for the follow-up improvement work of the plant protection drone.
发明内容Summary of the invention
本发明所要解决的技术问题是针对上述现有技术的不足提供一种植保无人机作业效果评价方法，本植保无人机作业效果评价方法能准确计算出植保无人机的有效喷洒率、漏喷率、重喷率、班次时间小时生产率、纯喷药时间小时生产率、时间利用率、使用可靠性系数和劳动生产率等喷洒效果参数，从而评价植保无人机的作业效率和效果。The technical problem to be solved by the present invention is to provide an evaluation method for the operation effect of the planting protection drone for the above-mentioned deficiencies of the prior art, and the method for evaluating the operation effect of the plant protection drone can accurately calculate the effective spraying rate and leakage of the plant protection drone. The spraying efficiency parameters of the plant protection drone are evaluated by the spraying effect parameters such as the spray rate, the re-spray rate, the hourly productivity of the shift, the hourly productivity of the pure spray, the time utilization rate, the use reliability coefficient, and the labor productivity.
为实现上述技术目的，本发明采取的技术方案为：To achieve the above technical purpose, the technical solution adopted by the present invention is:
一种植保无人机作业效果评价方法，包括作业效果评价系统，所述作业效果评价系统包括机载作业信息采集装置、云服务器和智能终端；所述机载作业信息采集装置安装在植保无人机上并用于测量植保无人机的飞行状态信息并将飞行状态信息通过4G无线网络发送到云服务器，云服务器用于根据飞行状态信息计算喷洒效果参数，智能终端用于登录云服务器从而查看喷洒效果参数；所述飞行状态信息包括植保无人机的飞行轨迹点的坐标信息，所述喷洒效果参数包括有效喷洒率、漏喷率、重喷率、班次时间小时生产率、纯喷药时间小时生产率、时间利用率、使用可靠性系数和劳动生产率；A planting protection drone operation effect evaluation method, comprising an operation effect evaluation system, the work effect evaluation system includes an onboard operation information collection device, a cloud server, and an intelligent terminal; and the onboard operation information collection device is installed in the plant protection On-board and used to measure the flight status information of the plant protection drone and send the flight status information to the cloud server through the 4G wireless network. The cloud server is used to calculate the spray effect parameter according to the flight state information, and the smart terminal is used to log in to the cloud server to view the spray effect. The flight status information includes coordinate information of a flight path point of the plant protection drone, and the spray effect parameter includes an effective spray rate, a leak rate, a re-spray rate, a shift time hourly productivity, a pure spray time hourly productivity, Time utilization, use reliability factor and labor productivity;
具体包括以下步骤：Specifically, the following steps are included:
(1)机载作业信息采集装置记录植保无人机的作业幅宽、采集植保无人机的飞行轨迹点的坐标以及统计植保无人机的作业班次时间，并将植保无人机的作业幅宽、飞行轨迹点的坐标和作业班次时间发送到云服务器；(1) The on-board operation information collection device records the operation width of the plant protection drone, the coordinates of the flight path point of the plant protection drone, and the working shift time of the plant protection drone, and the operation width of the plant protection drone The width, the coordinates of the flight path point, and the job shift time are sent to the cloud server;
(2)云服务器根据植保无人机的作业幅宽、飞行轨迹点的坐标和作业班次时间计算作业班次时间内相邻作业时刻对应的两个轨迹点之间的喷洒面积；(2) The cloud server calculates the spray area between the two track points corresponding to the adjacent work time in the work shift time according to the operation width of the plant protection drone, the coordinates of the flight track point, and the work shift time;
(3)云服务器根据步骤(2)计算的结果统计作业班次时间内的总喷洒面积，并根据植保无人机的总喷洒面积计算植保无人机的有效喷洒率、漏喷率、重喷率、班次时间小时生产率、纯喷药时间小时生产率、时间利用率、使用可靠性系数和劳动生产率。(3) The cloud server counts the total spray area during the shift time according to the result calculated in step (2), and calculates the effective spray rate, leak rate and re-spray rate of the plant protection drone according to the total spray area of the plant protection drone. , shift time hourly productivity, pure spray time hourly productivity, time utilization, use reliability factor and labor productivity.
作为本发明进一步改进的技术方案，所述步骤(3)包括：As a further improved technical solution of the present invention, the step (3) includes:
(a)作业班次时间内相邻作业时刻对应的两个轨迹点之间的喷洒面积依次为S 1,S 2,…,S N，通过布尔运算，得到喷洒作业班次时间内的总喷洒面积S A: (a) The spraying area between the two track points corresponding to the adjacent working time in the working shift time is S 1 , S 2 ,..., S N , and the total spraying area S in the spraying operation time is obtained by Boolean operation. A :
S A＝S 1∪S 2∪S 3∪…∪S N, S A =S 1 ∪S 2 ∪S 3 ∪...∪S N ,
(b)顺序连接植保无人机需要喷洒的作业面的每个顶点从而得到需要喷洒的作业面的几何面积S F，则喷洒作业的有效面积为： (b) sequentially connecting each vertex of the working surface of the plant protection drone that needs to be sprayed to obtain the geometrical area S F of the working surface to be sprayed, and the effective area of the spraying operation is:
S v＝S F∩S A, S v =S F ∩S A ,
则漏喷面积S m和重喷面积S o分别为： Then, the leakage spray area S m and the heavy spray area S o are respectively:
S m＝S F-S V,S o＝(S 1∩S A)∪(S 2∩S A)∪…∪(S N∩S A), S m =S F -S V , S o =(S 1 ∩S A )∪(S 2 ∩S A )∪...∪(S N ∩S A ),
则有效喷洒率η v、漏喷率η m和重喷率η o分别为： The effective spraying rate η v , the leakage rate η m and the re-injection rate η o are respectively:
Figure PCTCN2018120307-appb-000001
Figure PCTCN2018120307-appb-000001
则班次时间小时生产率为：Then the hourly productivity of the shift is:
Figure PCTCN2018120307-appb-000002
Figure PCTCN2018120307-appb-000002
其中W b为班次时间小时生产率，T b为作业班次时间； Where W b is the hourly productivity of the shift, and T b is the shift time of the shift;
则纯喷药时间小时生产率为：The pure spray time hourly productivity is:
Figure PCTCN2018120307-appb-000003
Figure PCTCN2018120307-appb-000003
其中W s为纯喷药小时生产率，T s为纯喷药时间； Where W s is the pure spray hourly productivity and T s is the pure spray time;
则时间利用率为：Then the time utilization is:
Figure PCTCN2018120307-appb-000004
Figure PCTCN2018120307-appb-000004
其中η T为时间利用率； Where η T is time utilization;
则使用可靠性系数为：Then use the reliability factor:
Figure PCTCN2018120307-appb-000005
Figure PCTCN2018120307-appb-000005
其中τ k为使用可靠性系数；T g为故障时间； Where τ k is the reliability factor used; T g is the fault time;
则劳动生产率为：The labor productivity is:
Figure PCTCN2018120307-appb-000006
Figure PCTCN2018120307-appb-000006
其中G j为劳动生产率，A j为机组作业人数。 Where G j is labor productivity and A j is the number of crew operations.
作为本发明进一步改进的技术方案，所述的步骤(1)包括：As a further improvement of the technical solution of the present invention, the step (1) includes:
(a)所述机载作业信息采集装置包括定位天线、定位模块和主控单元；所述定位模块通过两个定位天线分别采集植保无人机的喷杆的两端的坐标并发送到主控模块，主控单元根据植保无人机的喷杆的两端的坐标计算植保无人机的飞行轨迹点的坐标，所述飞行轨迹点的坐标为两个定位天线检测的两个坐标点连线的中点坐标；(a) The on-board operation information collecting device comprises a positioning antenna, a positioning module and a main control unit; the positioning module separately collects coordinates of two ends of the spray bar of the plant protection drone through two positioning antennas and sends the coordinates to the main control module The main control unit calculates the coordinates of the flight path point of the plant protection drone according to the coordinates of the two ends of the spray bar of the plant protection drone, and the coordinates of the flight path point are the two coordinate points detected by the two positioning antennas. Point coordinates
(b)所述机载作业信息采集装置的主控单元采集植保无人机内部液泵的工作状态从而统计植保无人机的作业班次时间；(b) The main control unit of the onboard operation information collecting device collects the working state of the internal liquid pump of the plant protection drone to calculate the working shift time of the plant protection drone;
(c)所述机载作业信息采集装置记录植保无人机的作业幅宽并将植保无人机的作业幅宽、飞行轨迹点的坐标和作业班次时间发送到云服务器。(c) The onboard operation information collecting device records the working width of the plant protection drone and transmits the working width of the plant protection drone, the coordinates of the flight path point, and the work shift time to the cloud server.
作为本发明进一步改进的技术方案，所述的步骤(2)包括：As a further improvement of the technical solution of the present invention, the step (2) includes:
(a)根据作业班次时间内每一个作业时刻植保无人机的喷杆的延伸方向与飞行轨迹线的夹角、作业幅宽和飞行轨迹点的坐标计算作业班次时间内每一个作业时刻的轨迹点对应的两个喷洒端点的坐标；(a) Calculate the trajectory of each working time in the working shift time according to the angle between the extending direction of the spray bar of the plant protection drone and the flight trajectory, the working width and the coordinates of the flight path at each working time. The coordinates of the two spray endpoints corresponding to the points;
(b)连接作业班次时间内相邻作业时刻对应的两个轨迹点的喷洒端点，得到四边形的喷洒形状，计算四边形的喷洒形状的面积从而得到班次作业时间内相邻作业时刻对应的两个轨迹点之间的喷洒面积。(b) Connect the spray end points of the two track points corresponding to the adjacent work time in the work shift time to obtain the spray shape of the quadrilateral, calculate the area of the spray shape of the quadrilateral to obtain the two tracks corresponding to the adjacent work time in the shift operation time. The area of the spray between the points.
本发明的有益效果为：本发明通过植保无人机作业效果评价方法能有效并准确的计算出植保无人机的有效喷洒率、漏喷率、重喷率、班次时间小时生产率、纯喷药时间小时生产率、时间利用率、使用可靠性系数和劳动生产率等喷洒效果参数，从而实现对植保无人机的作业效率和效果的评价，为植保无人机的后续改进工作的开展奠定基础。The invention has the beneficial effects that the invention can effectively and accurately calculate the effective spraying rate, the leakage rate, the re-spray rate, the shift time, the hourly productivity, and the pure spraying of the plant protection drone by the planting protection drone operation effect evaluation method. Time-hour productivity, time utilization, reliability factor and labor productivity are used to evaluate the efficiency and effectiveness of plant protection drones, laying the foundation for the subsequent improvement of plant protection drones.
附图说明DRAWINGS
图1为本发明的结构示意图。Figure 1 is a schematic view of the structure of the present invention.
图2为本发明的工作流程图。Figure 2 is a flow chart of the operation of the present invention.
具体实施方式Detailed ways
下面根据图1和图2对本发明的具体实施方式作出进一步说明：The specific embodiments of the present invention are further described below with reference to FIGS. 1 and 2.
本实施例提供的一种植保无人机作业效果评价方法，包括作业效果评价系统，参见图1，所述作业效果评价系统包括机载作业信息采集装置、云服务器和智能终端；所述机载作业信息采集装置安装在植保无人机上并用于测量植保无人机的飞行状态信息并将飞行状态信息通过4G无线网络发送到云服务器，云服务器根据飞行状态信息计算喷洒效果参数，智能终端用于登录云服务器从而查看喷洒效果参数；所述飞行状态信息包括植保无人机的飞行轨迹点，所述喷洒效果参数包括有效喷洒率、漏喷率、重喷率、班次时间小时生产率、纯喷药时间小时生产率、时间利用率、使用可靠性系数和劳动生产率。The method for evaluating the operation effect of the planting maintenance drone provided by the embodiment includes the operation effect evaluation system. Referring to FIG. 1, the operation effect evaluation system includes an onboard operation information collection device, a cloud server, and an intelligent terminal; The operation information collecting device is installed on the plant protection drone and is used for measuring the flight state information of the plant protection drone and transmitting the flight state information to the cloud server through the 4G wireless network, and the cloud server calculates the spraying effect parameter according to the flight state information, and the smart terminal is used for Logging in to the cloud server to view the spray effect parameter; the flight state information includes a flight path point of the plant protection drone, and the spray effect parameters include an effective spray rate, a leak rate, a re-spray rate, a shift time hourly productivity, and a pure spray Time-hour productivity, time utilization, use reliability factor, and labor productivity.
机载作业信息采集装置精确记录植保无人机的飞机状态数据，将实时采集到的飞机状态数据，通过4G无线网络发送给云服务器。当一个飞行架次结束后，云服务器将数据汇总，并计算出喷洒效果参数，包括喷洒覆盖率、重喷漏喷率、无人机工作效率、使用可靠性等指标。用户可以通过智能终端，例如电脑或手机来直接查看喷洒情况。The onboard operation information collection device accurately records the aircraft state data of the plant protection drone, and transmits the aircraft state data collected in real time to the cloud server through the 4G wireless network. When a flight is over, the cloud server aggregates the data and calculates the spray effect parameters, including spray coverage, re-spray leakage rate, drone efficiency, and reliability. Users can view the spray directly through a smart terminal such as a computer or mobile phone.
参见图2，植保无人机作业效果评价方法具体包括以下步骤：Referring to FIG. 2, the method for evaluating the effect of the plant protection drone includes the following steps:
(1)注册机载作业信息采集装置，将SIM卡插入机载作业信息采集装置机盖内，机载作业信息采集装置内部设有4G通信模块和4G天线，通过4G通信模块、4G天线和SIM卡与云服务器通信连接；所述机载作业信息采集装置内部还包括两个GPS定位天线、定位模块和主控单元；(1) Registering the on-board operation information collection device, inserting the SIM card into the cover of the on-board operation information collection device, and the on-board operation information collection device is internally provided with a 4G communication module and a 4G antenna, through the 4G communication module, the 4G antenna and the SIM The card is connected to the cloud server; the onboard operation information collection device further includes two GPS positioning antennas, a positioning module and a main control unit;
(2)将机载作业信息采集装置安装在植保无人机上，安装步骤如下：(2) Install the onboard operation information collection device on the plant protection drone. The installation steps are as follows:
a、将两个GPS定位天线固定到植保无人机上，即喷杆的两端且卫星信号不受遮挡的合适位置；a. Fix two GPS positioning antennas to the plant protection drone, that is, the two ends of the boom and the satellite signal is not blocked at a suitable position;
b、将机载作业信息采集装置的壳体固定到植保无人机上。b. Fix the housing of the onboard operation information collection device to the plant protection drone.
c、确保4G天线已旋好连接到机载作业信息采集装置上。c. Ensure that the 4G antenna is screwed up to the onboard operation information collection device.
(3)在机载作业信息采集装置上记录植保无人机的作业幅宽，植保无人机的作业幅宽可以根据植保无人机的使用说明书得到，是已知值，机载作业信息采集装置通过定位天线采集植保无人机的飞行轨迹点的坐标以及通过主控单元统计植保无人机的作业班次 时间，并将植保无人机的作业幅宽、飞行轨迹点的坐标和作业班次时间发送到云服务器；(3) Record the working width of the plant protection drone on the airborne operation information collecting device, and the working width of the plant protection drone can be obtained according to the instruction manual of the plant protection drone, which is a known value, and the onboard operation information is collected. The device collects the coordinates of the flight path point of the plant protection drone through the positioning antenna and counts the operation shift time of the plant protection drone through the main control unit, and the operation width of the plant protection drone, the coordinates of the flight track point and the work shift time. Send to the cloud server;
(4)云服务器根据植保无人机的作业幅宽、飞行轨迹点的坐标和作业班次时间计算作业班次时间内相邻作业时刻对应的两个轨迹点之间的喷洒面积；(4) The cloud server calculates the spray area between the two track points corresponding to the adjacent work time in the work shift time according to the operation width of the plant protection drone, the coordinates of the flight track point and the work shift time;
(5)云服务器根据步骤(4)计算的结果统计作业班次时间内的总喷洒面积，并根据植保无人机的总喷洒面积计算植保无人机的有效喷洒率、漏喷率、重喷率、班次时间小时生产率、纯喷药时间小时生产率、时间利用率、使用可靠性系数和劳动生产率；(5) The cloud server counts the total spray area during the shift time according to the result calculated in step (4), and calculates the effective spray rate, leak rate and re-spray rate of the plant protection drone according to the total spray area of the plant protection drone. Time, hourly productivity, pure spray time, hourly productivity, time utilization, use reliability factor, and labor productivity;
所述步骤(5)包括：The step (5) includes:
(a)作业班次时间内相邻作业时刻对应的两个轨迹点之间的喷洒面积依次为S 1,S 2,…,S N，通过布尔运算，得到喷洒作业班次时间内的总喷洒面积S A: (a) The spraying area between the two track points corresponding to the adjacent working time in the working shift time is S 1 , S 2 ,..., S N , and the total spraying area S in the spraying operation time is obtained by Boolean operation. A :
S A＝S 1∪S 2∪S 3∪…∪S N, S A =S 1 ∪S 2 ∪S 3 ∪...∪S N ,
(b)顺序连接植保无人机需要喷洒的作业面的每个顶点从而得到需要喷洒的作业面的几何面积S F，则喷洒作业的有效面积为： (b) sequentially connecting each vertex of the working surface of the plant protection drone that needs to be sprayed to obtain the geometrical area S F of the working surface to be sprayed, and the effective area of the spraying operation is:
S v＝S F∩S A, S v =S F ∩S A ,
则漏喷面积S m和重喷面积S o分别为： Then, the leakage spray area S m and the heavy spray area S o are respectively:
S m＝S F-S V,S o＝(S 1∩S A)∪(S 2∩S A)∪…∪(S N∩S A), S m =S F -S V , S o =(S 1 ∩S A )∪(S 2 ∩S A )∪...∪(S N ∩S A ),
则有效喷洒率η v、漏喷率η m和重喷率η o分别为： The effective spraying rate η v , the leakage rate η m and the re-injection rate η o are respectively:
Figure PCTCN2018120307-appb-000007
Figure PCTCN2018120307-appb-000007
则班次时间小时生产率为：Then the hourly productivity of the shift is:
Figure PCTCN2018120307-appb-000008
Figure PCTCN2018120307-appb-000008
其中W b为班次时间小时生产率，T b为作业班次时间； Where W b is the hourly productivity of the shift, and T b is the shift time of the shift;
则纯喷药时间小时生产率为：The pure spray time hourly productivity is:
Figure PCTCN2018120307-appb-000009
Figure PCTCN2018120307-appb-000009
其中W s纯喷药小时生产率，T s为纯喷药时间； Where W s pure spray hourly productivity, T s is pure spray time;
则时间利用率为：Then the time utilization is:
Figure PCTCN2018120307-appb-000010
Figure PCTCN2018120307-appb-000010
其中η T为时间利用率； Where η T is time utilization;
则使用可靠性系数为：Then use the reliability factor:
Figure PCTCN2018120307-appb-000011
Figure PCTCN2018120307-appb-000011
其中τ k为使用可靠性系数；T g为故障时间； Where τ k is the reliability factor used; T g is the fault time;
则劳动生产率为：The labor productivity is:
Figure PCTCN2018120307-appb-000012
Figure PCTCN2018120307-appb-000012
其中G j为劳动生产率，A j为机组作业人数。 Where G j is labor productivity and A j is the number of crew operations.
所述的步骤(3)包括：The step (3) described includes:
(a)所述定位模块通过两个定位天线分别采集作业班次时间内每一个作业时刻对应的植保无人机的喷杆的两端的坐标并发送到主控模块，主控单元根据植保无人机的喷杆的两端的坐标计算植保无人机的飞行轨迹点的坐标，所述飞行轨迹点的坐标为两个定位天线检测的两个坐标点连线的中点坐标；(a) The positioning module separately collects the coordinates of the two ends of the spray bar of the plant protection drone corresponding to each work time in the work shift time through two positioning antennas and sends the coordinates to the main control module according to the plant protection drone The coordinates of the two ends of the spray bar are used to calculate the coordinates of the flight path point of the plant protection drone, and the coordinates of the flight track point are the midpoint coordinates of the two coordinate points detected by the two positioning antennas;
(b)采用基于直流互感原理的非接触式测量方法，检测植保无人飞机内部液泵的当前工作状态。具体为：霍尔元件(磁芯线圈的非接触方法)实时检测液泵的工作电流从而检测液泵是否工作，霍尔元件将检测的信号发送到机载作业信息采集装置的主控单元内，进而实现主控单元对液泵工作状态的实时检测，统计植保无人机的作业班次时间；(b) Using the non-contact measurement method based on the DC mutual inductance principle to detect the current working state of the internal liquid pump of the plant protection unmanned aerial vehicle. Specifically, the Hall element (non-contact method of the magnetic core coil) detects the working current of the liquid pump in real time to detect whether the liquid pump operates, and the Hall element transmits the detected signal to the main control unit of the onboard operation information collecting device. Further realizing the real-time detection of the working state of the liquid pump by the main control unit, and counting the working shift time of the plant protection drone;
(c)所述机载作业信息采集装置记录植保无人机的作业幅宽并将植保无人机的作业幅宽、飞行轨迹点的坐标和作业班次时间发送到云服务器。(c) The onboard operation information collecting device records the working width of the plant protection drone and transmits the working width of the plant protection drone, the coordinates of the flight path point, and the work shift time to the cloud server.
所述的步骤(4)包括：The step (4) described includes:
(a)云服务器通过自适应高斯滤波算法对飞行轨迹点的坐标进行滤波；(a) The cloud server filters the coordinates of the flight path point by an adaptive Gaussian filtering algorithm;
t i时刻对应的轨迹点P i的坐标x,y滤波后的值为： The coordinates x, y of the track point P i corresponding to the time t i are filtered:
Figure PCTCN2018120307-appb-000013
Figure PCTCN2018120307-appb-000013
Figure PCTCN2018120307-appb-000014
Figure PCTCN2018120307-appb-000014
其中x(t i),y(t i)分别为t i时刻的轨迹点P i滤波前的x,y坐标，i＝0,1,2,…；σ为滤波核函数的宽带参数，根据采样频率确定； Where x (t i), y ( t i) are x front track point in time t i P i of the filter, y coordinates, i = 0,1,2, ...; σ is the broadband filter kernel function parameters, in accordance with The sampling frequency is determined;
(b)根据每一个作业时刻植保无人机的喷杆的延伸方向与飞行轨迹线的夹角、作业幅宽和飞行轨迹点的坐标计算作业班次时间内每一个作业时刻的轨迹点对应的两个喷洒端点的坐标；(b) Calculate the two points corresponding to the trajectory points of each working time in the working shift time according to the angle between the extending direction of the spray bar of the plant protection drone and the flight trajectory, the working width and the coordinates of the flight path point. The coordinates of the spray endpoints;
定义轨迹点P i对应的两个喷洒端点的坐标分别为
Figure PCTCN2018120307-appb-000015
其中： The coordinates of the two spray end points corresponding to the defined track point P i are respectively
Figure PCTCN2018120307-appb-000015
among them:
Figure PCTCN2018120307-appb-000016
Figure PCTCN2018120307-appb-000016
Figure PCTCN2018120307-appb-000017
Figure PCTCN2018120307-appb-000017
其中
Figure PCTCN2018120307-appb-000018
w i为植保无人机的作业幅宽，θ i为t i时刻喷杆的延伸方向与飞行轨迹线的夹角；飞行轨迹线为每一个轨迹点的连线； among them
Figure PCTCN2018120307-appb-000018
w i is the working width of the plant protection drone, θ i is the angle between the extending direction of the spray bar and the flight trajectory at time t i ; the flight trajectory is the line connecting each track point;
(c)连接作业班次时间内相邻作业时刻对应的两个轨迹点P i,P i+1的喷洒端点，得到四边形的喷洒形状P i1P i2P i+11P i+12，计算四边形的喷洒形状的面积从而得到班次作业时间内相邻作业时刻对应的两个轨迹点之间的喷洒面积；其中
Figure PCTCN2018120307-appb-000019
为轨迹点P i的坐标滤波后的值，
Figure PCTCN2018120307-appb-000020
为轨迹点P i+1的坐标滤波后的值，
Figure PCTCN2018120307-appb-000021
为轨迹点P i对应的两个喷洒端点的坐标值，
Figure PCTCN2018120307-appb-000022
为轨迹点P i+1对应的两个喷洒端点的坐标值；轨迹点P i+1对应的两个喷洒端点的坐标值可用步骤(b)的公式得到； (c) connecting the spray end points of the two track points P i , P i+1 corresponding to the adjacent work time in the work shift time to obtain the quadrilateral spray shape P i1 P i2 P i+11 P i+12 , calculating the quadrilateral shape Spraying the area of the shape to obtain the spray area between the two track points corresponding to the adjacent work time during the shift operation time;
Figure PCTCN2018120307-appb-000019
The value filtered for the coordinates of the track point P i ,
Figure PCTCN2018120307-appb-000020
The filtered value of the coordinates of the track point P i+1 ,
Figure PCTCN2018120307-appb-000021
The coordinate values of the two spray end points corresponding to the track point P i ,
Figure PCTCN2018120307-appb-000022
The coordinate values of the two spray end points corresponding to the track point P i+1 ; the coordinate values of the two spray end points corresponding to the track point P i+1 can be obtained by the formula of the step (b);
则相邻的两个轨迹点P i,P i+1的喷洒面积为： The spray area of the adjacent two track points P i , P i+1 is:
Figure PCTCN2018120307-appb-000023
Figure PCTCN2018120307-appb-000023
本发明的保护范围包括但不限于以上实施方式，本发明的保护范围以权利要求书为准，任何对本技术做出的本领域的技术人员容易想到的替换、变形、改进均落入本发明 的保护范围。The scope of the present invention includes, but is not limited to, the above embodiments, and the scope of the present invention is defined by the claims, and any substitutions, modifications, and improvements which are obvious to those skilled in the art to which the present invention is made fall within the scope of the present invention. protected range.

Claims (4)

  1. 一种植保无人机作业效果评价方法，其特征在于：包括作业效果评价系统，所述作业效果评价系统包括机载作业信息采集装置、云服务器和智能终端；所述机载作业信息采集装置安装在植保无人机上并用于测量植保无人机的飞行状态信息并将飞行状态信息通过4G无线网络发送到云服务器，云服务器用于根据飞行状态信息计算喷洒效果参数，智能终端用于登录云服务器从而查看喷洒效果参数；所述飞行状态信息包括植保无人机的飞行轨迹点的坐标信息，所述喷洒效果参数包括有效喷洒率、漏喷率、重喷率、班次时间小时生产率、纯喷药时间小时生产率、时间利用率、使用可靠性系数和劳动生产率；A planting maintenance drone operation effect evaluation method, comprising: an operation effect evaluation system, wherein the work effect evaluation system includes an onboard operation information collection device, a cloud server, and an intelligent terminal; and the onboard operation information collection device is installed On the plant protection drone, and used to measure the flight state information of the plant protection drone and send the flight state information to the cloud server through the 4G wireless network, the cloud server is configured to calculate the spray effect parameter according to the flight state information, and the smart terminal is used to log in to the cloud server. Thereby viewing the spray effect parameter; the flight state information includes coordinate information of a flight path point of the plant protection drone, the spray effect parameter includes an effective spray rate, a leak spray rate, a re-spray rate, a shift time hourly productivity, and a pure spray Time-hour productivity, time utilization, use reliability factor, and labor productivity;
    具体包括以下步骤：Specifically, the following steps are included:
    (1)机载作业信息采集装置记录植保无人机的作业幅宽、采集植保无人机的飞行轨迹点的坐标以及统计植保无人机的作业班次时间，并将植保无人机的作业幅宽、飞行轨迹点的坐标和作业班次时间发送到云服务器；(1) The on-board operation information collection device records the operation width of the plant protection drone, the coordinates of the flight path point of the plant protection drone, and the working shift time of the plant protection drone, and the operation width of the plant protection drone The width, the coordinates of the flight path point, and the job shift time are sent to the cloud server;
    (2)云服务器根据植保无人机的作业幅宽、飞行轨迹点的坐标和作业班次时间计算作业班次时间内相邻作业时刻对应的两个轨迹点之间的喷洒面积；(2) The cloud server calculates the spray area between the two track points corresponding to the adjacent work time in the work shift time according to the operation width of the plant protection drone, the coordinates of the flight track point, and the work shift time;
    (3)云服务器根据步骤(2)计算的结果统计作业班次时间内的总喷洒面积，并根据植保无人机的总喷洒面积计算植保无人机的有效喷洒率、漏喷率、重喷率、班次时间小时生产率、纯喷药时间小时生产率、时间利用率、使用可靠性系数和劳动生产率。(3) The cloud server counts the total spray area during the shift time according to the result calculated in step (2), and calculates the effective spray rate, leak rate and re-spray rate of the plant protection drone according to the total spray area of the plant protection drone. , shift time hourly productivity, pure spray time hourly productivity, time utilization, use reliability factor and labor productivity.
  2. 根据权利要求1所述的植保无人机作业效果评价方法，其特征在于：The method for evaluating the operation effect of a plant protection drone according to claim 1, wherein:
    所述步骤(3)包括：The step (3) includes:
    (a)作业班次时间内相邻作业时刻对应的两个轨迹点之间的喷洒面积依次为S 1,S 2,…,S N，通过布尔运算，得到喷洒作业班次时间内的总喷洒面积S A: (a) The spraying area between the two track points corresponding to the adjacent working time in the working shift time is S 1 , S 2 ,..., S N , and the total spraying area S in the spraying operation time is obtained by Boolean operation. A :
    S A＝S 1∪S 2∪S 3∪…∪S N, S A =S 1 ∪S 2 ∪S 3 ∪...∪S N ,
    (b)顺序连接植保无人机需要喷洒的作业面的每个顶点从而得到需要喷洒的作业面的几何面积S F，则喷洒作业的有效面积为： (b) sequentially connecting each vertex of the working surface of the plant protection drone that needs to be sprayed to obtain the geometrical area S F of the working surface to be sprayed, and the effective area of the spraying operation is:
    S v＝S F∩S A, S v =S F ∩S A ,
    则漏喷面积S m和重喷面积S o分别为： Then, the leakage spray area S m and the heavy spray area S o are respectively:
    S m＝S F-S V,S o＝(S 1∩S A)∪(S 2∩S A)∪…∪(S N∩S A), S m =S F -S V , S o =(S 1 ∩S A )∪(S 2 ∩S A )∪...∪(S N ∩S A ),
    则有效喷洒率η v、漏喷率η m和重喷率η o分别为： The effective spraying rate η v , the leakage rate η m and the re-injection rate η o are respectively:
    Figure PCTCN2018120307-appb-100001
    Figure PCTCN2018120307-appb-100001
    则班次时间小时生产率为：Then the hourly productivity of the shift is:
    Figure PCTCN2018120307-appb-100002
    Figure PCTCN2018120307-appb-100002
    其中W b为班次时间小时生产率，T b为作业班次时间； Where W b is the hourly productivity of the shift, and T b is the shift time of the shift;
    则纯喷药时间小时生产率为：The pure spray time hourly productivity is:
    Figure PCTCN2018120307-appb-100003
    Figure PCTCN2018120307-appb-100003
    其中W s纯喷药小时生产率，T s为纯喷药时间； Where W s pure spray hourly productivity, T s is pure spray time;
    则时间利用率为：Then the time utilization is:
    Figure PCTCN2018120307-appb-100004
    Figure PCTCN2018120307-appb-100004
    其中η T为时间利用率； Where η T is time utilization;
    则使用可靠性系数为：Then use the reliability factor:
    Figure PCTCN2018120307-appb-100005
    Figure PCTCN2018120307-appb-100005
    其中τ k为使用可靠性系数；T g为故障时间； Where τ k is the reliability factor used; T g is the fault time;
    则劳动生产率为：The labor productivity is:
    Figure PCTCN2018120307-appb-100006
    Figure PCTCN2018120307-appb-100006
    其中G j为劳动生产率，A j为机组作业人数。 Where G j is labor productivity and A j is the number of crew operations.
  3. 根据权利要求2所述的植保无人机作业效果评价方法，其特征在于：所述的步骤(1)包括：The method for evaluating the effect of the plant protection drone according to claim 2, wherein the step (1) comprises:
    (a)所述机载作业信息采集装置包括定位天线、定位模块和主控单元；所述定位模块通过两个定位天线分别采集植保无人机的喷杆的两端的坐标并发送到主控模块，主控单元根据植保无人机的喷杆的两端的坐标计算植保无人机的飞行轨迹点的坐标，所述飞行轨迹点的坐标为两个定位天线检测的两个坐标点连线的中点坐标；(a) The on-board operation information collecting device comprises a positioning antenna, a positioning module and a main control unit; the positioning module separately collects coordinates of two ends of the spray bar of the plant protection drone through two positioning antennas and sends the coordinates to the main control module The main control unit calculates the coordinates of the flight path point of the plant protection drone according to the coordinates of the two ends of the spray bar of the plant protection drone, and the coordinates of the flight path point are the two coordinate points detected by the two positioning antennas. Point coordinates
    (b)所述机载作业信息采集装置的主控单元采集植保无人机内部液泵的工作状态 从而统计植保无人机的作业班次时间；(b) The main control unit of the onboard operation information collecting device collects the working state of the internal liquid pump of the plant protection drone to calculate the working shift time of the plant protection drone;
    (c)所述机载作业信息采集装置记录植保无人机的作业幅宽并将植保无人机的作业幅宽、飞行轨迹点的坐标和作业班次时间发送到云服务器。(c) The onboard operation information collecting device records the working width of the plant protection drone and transmits the working width of the plant protection drone, the coordinates of the flight path point, and the work shift time to the cloud server.
  4. 根据权利要求3所述的植保无人机作业效果评价方法，其特征在于：所述的步骤(2)包括：The method for evaluating the effect of the plant protection drone according to claim 3, wherein the step (2) comprises:
    (a)根据作业班次时间内每一个作业时刻植保无人机的喷杆的延伸方向与飞行轨迹线的夹角、作业幅宽和飞行轨迹点的坐标计算作业班次时间内每一个作业时刻的轨迹点对应的两个喷洒端点的坐标；(a) Calculate the trajectory of each working time in the working shift time according to the angle between the extending direction of the spray bar of the plant protection drone and the flight trajectory, the working width and the coordinates of the flight path at each working time. The coordinates of the two spray endpoints corresponding to the points;
    (b)连接作业班次时间内相邻作业时刻对应的两个轨迹点的喷洒端点，得到四边形的喷洒形状，计算四边形的喷洒形状的面积从而得到班次作业时间内相邻作业时刻对应的两个轨迹点之间的喷洒面积。(b) Connect the spray end points of the two track points corresponding to the adjacent work time in the work shift time to obtain the spray shape of the quadrilateral, calculate the area of the spray shape of the quadrilateral to obtain the two tracks corresponding to the adjacent work time in the shift operation time. The area of the spray between the points.
PCT/CN2018/120307 2018-05-11 2018-12-11 Plant protection unmanned aerial vehicle operation effect evaluation method WO2019137135A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2018402493A AU2018402493A1 (en) 2018-05-11 2018-12-11 Plant protection unmanned aerial vehicle operation effect evaluation method

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201810449507.3A CN108805410B (en) 2018-05-11 2018-05-11 Method for evaluating operation effect of plant protection unmanned aerial vehicle
CN201810449507.3 2018-05-11

Publications (1)

Publication Number Publication Date
WO2019137135A1 true WO2019137135A1 (en) 2019-07-18

Family

ID=64092237

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/120307 WO2019137135A1 (en) 2018-05-11 2018-12-11 Plant protection unmanned aerial vehicle operation effect evaluation method

Country Status (3)

Country Link
CN (1) CN108805410B (en)
AU (1) AU2018402493A1 (en)
WO (1) WO2019137135A1 (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113091755A (en) * 2019-12-19 2021-07-09 广州极飞科技股份有限公司 Method, device and equipment for tracking motion trail and storage medium
CN117837366B (en) * 2024-03-04 2024-06-07 湖南惠农科技有限公司 Agricultural supervision platform based on agricultural Internet of things

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108805410B (en) * 2018-05-11 2022-05-27 农业农村部南京农业机械化研究所 Method for evaluating operation effect of plant protection unmanned aerial vehicle
CN109709971A (en) * 2018-12-10 2019-05-03 北京云无忧大数据科技有限公司 For the method and apparatus of plant protection, storage medium and electronic equipment
CN110297501B (en) * 2019-07-31 2022-05-24 朱彬 Unmanned aerial vehicle control method, device and equipment
CN111557642B (en) * 2020-03-31 2021-05-11 广东省国土资源测绘院 Method and system for evaluating field operation effect based on track
CN112631327A (en) * 2020-12-10 2021-04-09 许昌雷鸣电子科技有限公司 Pesticide spraying detection method and device for plant protection unmanned aerial vehicle, electronic equipment and storage medium
CN115630770B (en) * 2022-12-07 2023-03-10 广东省农业科学院植物保护研究所 Operation effect evaluation method, system and medium based on plant protection unmanned aerial vehicle
CN116797106B (en) * 2023-08-29 2023-11-14 山东孟子居生态农业股份有限公司 Plant protection unmanned aerial vehicle operation effect evaluation system

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20100092199A (en) * 2009-02-12 2010-08-20 주식회사 무성항공 A cost estimating system about spraying chemicals, seeds or fertilizer of unmaned aerial vehicles
CN106094532A (en) * 2016-08-16 2016-11-09 华南农业大学 A kind of agricultural unmanned plane spraying system self-checking device and control method
CN106200674A (en) * 2016-08-16 2016-12-07 吉林农业大学 A kind of method of unmanned plane self adaptation accuracy pesticide applying
CN106530103A (en) * 2016-10-11 2017-03-22 北京农业智能装备技术研究中心 Aviation plant protection operation real-time supervision system
CN106528513A (en) * 2016-10-18 2017-03-22 广州极飞科技有限公司 An unmanned aerial vehicle work-based work report generating method and device
CN107437250A (en) * 2017-06-30 2017-12-05 上海拓攻机器人有限公司 A kind of charge book generation method and device based on unmanned machine operation
CN107453798A (en) * 2017-03-28 2017-12-08 亿航智能设备（广州）有限公司 The device and method of remote information exchange is carried out by 4G networks and unmanned plane
US20180129879A1 (en) * 2016-11-04 2018-05-10 Intel Corporation Unmanned aerial vehicle-based systems and methods for agricultural landscape modeling
CN108805410A (en) * 2018-05-11 2018-11-13 农业部南京农业机械化研究所 Plant protection drone operation effectiveness evaluation method

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101372351B1 (en) * 2012-02-22 2014-03-13 전북대학교산학협력단 Flight simulation system for evaluation of unmanned aerial vehicle based on solar energy
CN107272726A (en) * 2017-08-11 2017-10-20 上海拓攻机器人有限公司 Operating area based on unmanned plane plant protection operation determines method and device

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20100092199A (en) * 2009-02-12 2010-08-20 주식회사 무성항공 A cost estimating system about spraying chemicals, seeds or fertilizer of unmaned aerial vehicles
CN106094532A (en) * 2016-08-16 2016-11-09 华南农业大学 A kind of agricultural unmanned plane spraying system self-checking device and control method
CN106200674A (en) * 2016-08-16 2016-12-07 吉林农业大学 A kind of method of unmanned plane self adaptation accuracy pesticide applying
CN106530103A (en) * 2016-10-11 2017-03-22 北京农业智能装备技术研究中心 Aviation plant protection operation real-time supervision system
CN106528513A (en) * 2016-10-18 2017-03-22 广州极飞科技有限公司 An unmanned aerial vehicle work-based work report generating method and device
US20180129879A1 (en) * 2016-11-04 2018-05-10 Intel Corporation Unmanned aerial vehicle-based systems and methods for agricultural landscape modeling
CN107453798A (en) * 2017-03-28 2017-12-08 亿航智能设备（广州）有限公司 The device and method of remote information exchange is carried out by 4G networks and unmanned plane
CN107437250A (en) * 2017-06-30 2017-12-05 上海拓攻机器人有限公司 A kind of charge book generation method and device based on unmanned machine operation
CN108805410A (en) * 2018-05-11 2018-11-13 农业部南京农业机械化研究所 Plant protection drone operation effectiveness evaluation method

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113091755A (en) * 2019-12-19 2021-07-09 广州极飞科技股份有限公司 Method, device and equipment for tracking motion trail and storage medium
CN113091755B (en) * 2019-12-19 2024-04-09 广州极飞科技股份有限公司 Method, device, equipment and storage medium for tracking motion trail
CN117837366B (en) * 2024-03-04 2024-06-07 湖南惠农科技有限公司 Agricultural supervision platform based on agricultural Internet of things

Also Published As

Publication number Publication date
AU2018402493A1 (en) 2020-06-25
CN108805410B (en) 2022-05-27
CN108805410A (en) 2018-11-13

Similar Documents

Publication Publication Date Title
WO2019137135A1 (en) Plant protection unmanned aerial vehicle operation effect evaluation method
WO2019137136A1 (en) Plant protection unmanned aerial vehicle operation quality detection apparatus and detection method therefor
CN106932753B (en) Anti- unmanned plane passive detection and direction detecting positioning system
CN104035091B (en) Indoor unmanned plane alignment system
CN106296871B (en) Unmanned plane monitoring and managing method and system
CN205121341U (en) Unmanned aerial vehicle ground command system
CN104268685A (en) Airport ground vehicle tracking management system
CN106597369B (en) A kind of control method of unmanned plane, control platform, control system
CN206922767U (en) A kind of intelligent coordinated radio detection system based on unmanned plane
CN110488873A (en) A kind of plant protection drone operation flight course planning method and system
CN201918664U (en) Line-walking real-time system of unmanned aerial vehicle
CN107608386A (en) A kind of UAV Navigation System and method based on the distribution of high-voltage line electromagnetism fingerprint
CN209281618U (en) A kind of Vehicle Detection device based on millimetre-wave radar and video
CN203480030U (en) Unmanned aerial vehicle positioning system based on mobile phone base station signal
CN213661639U (en) Full-frequency-band detection and counter-control automatic management and control system of unmanned aerial vehicle
CN104730988A (en) Intelligent management system of aircraft pipeline fuelling vehicle
CN104777763A (en) Intelligent system for agricultural planting
Xu et al. Online spraying quality assessment system of plant protection unmanned aerial vehicle based on Android client
CN207439401U (en) A kind of electric power line pole tower construction work monitors system
CN104735423A (en) Transmission equipment recognition platform located on unmanned aerial vehicle
CN103940823A (en) Iron tower defect detection system based on aircraft and aircraft positioning method
CN105333900A (en) Flue gas monitoring system and method based on multi-rotor platform
CN202871010U (en) A double-waveband wireless forest fire early warning system based on an unmanned aerial vehicle
CN209417014U (en) A kind of atmosphere pollution on-line monitoring system of UAV flight
CN110986871A (en) Cross spanning line spacing image measuring method based on RTK (real time kinematic) precise positioning

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18899740

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2018402493

Country of ref document: AU

Date of ref document: 20181211

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 18899740

Country of ref document: EP

Kind code of ref document: A1