CN112114383A - High-spatial-temporal-resolution wind measurement system and wind measurement method based on multi-rotor unmanned aerial vehicle - Google Patents
High-spatial-temporal-resolution wind measurement system and wind measurement method based on multi-rotor unmanned aerial vehicle Download PDFInfo
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- CN112114383A CN112114383A CN202011190728.7A CN202011190728A CN112114383A CN 112114383 A CN112114383 A CN 112114383A CN 202011190728 A CN202011190728 A CN 202011190728A CN 112114383 A CN112114383 A CN 112114383A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/08—Adaptations of balloons, missiles, or aircraft for meteorological purposes; Radiosondes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P13/00—Indicating or recording presence, absence, or direction, of movement
- G01P13/02—Indicating direction only, e.g. by weather vane
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P5/00—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft
- G01P5/14—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft by measuring differences of pressure in the fluid
Abstract
The invention discloses a high-spatial-temporal-resolution wind measurement system and a wind measurement method based on a multi-rotor unmanned aerial vehicle. The invention uses the multi-rotor unmanned aerial vehicle as a wind measuring carrier, and has small volume, easy deployment, convenience and high efficiency; when detecting the wind pressure through the pressure sensing unit, through flight gesture collection unit collection testing in-process unmanned aerial vehicle's attitude information to provide a anemometry algorithm according to attitude information, run by the data processing unit anemometry algorithm can revise the influence of flight gesture to wind speed and wind direction, has greatly improved the anemometry precision.
Description
Technical Field
The invention relates to the technical field of meteorological monitoring, in particular to a high-spatial-temporal-resolution wind measuring system and a wind measuring method based on a multi-rotor unmanned aerial vehicle.
Background
Wind is a basic natural phenomenon caused by air flow, which is closely related to human production life, so wind speed and wind direction are important factors for meteorological monitoring since ancient times. With the development of society, people in many industries need to know the characteristics of wind in more detail, so that a wind measuring device is needed to measure the wind more flexibly and more accurately.
However, the traditional wind measuring equipment has difficulty in obtaining dual requirements of flexibility and accuracy in the wind measuring process. For example, the wind cup type, heat dissipation type and ultrasonic type wind measuring instruments have high accuracy, but are fixed in position and inflexible, and can only realize single-point wind measurement; the existing wind measuring radar is flexible, but the wind measuring height is limited to 50-100 m, and the wind measuring precision is generally low. The utility model discloses a be CN 209159994U's utility model patent discloses "a wind measuring device based on many rotor unmanned aerial vehicle platform", this patent is with many rotor unmanned aerial vehicle as the platform of carrying on of wind measuring device, it is more nimble convenient to survey the wind, but survey wind in-process unmanned aerial vehicle is in order to keep balanced gesture of hovering in the wind, can not be in complete horizontally state, there is certain inclination, the existence of this point is not considered in the structure and the algorithm of the wind measuring device that this patent gave, consequently, can not overcome this inclination and to the influence of bringing of wind speed and wind pressure, thereby the wind speed and the wind direction value that lead to finally obtaining are still accurate inadequately.
Disclosure of Invention
In order to solve the technical problem, the invention provides a high spatial and temporal resolution wind measuring system and a wind measuring method based on a multi-rotor unmanned aerial vehicle.
The technical scheme adopted by the invention is as follows: the invention discloses a high-spatial-temporal-resolution wind measurement system and a wind measurement method based on a multi-rotor unmanned aerial vehicle.
The invention has the beneficial effects that: the invention uses the multi-rotor unmanned aerial vehicle as a wind measuring carrier, and has small volume, easy deployment, convenience and high efficiency; when detecting the wind pressure through the pressure sensing unit, through flight gesture collection unit collection testing in-process unmanned aerial vehicle's attitude information to provide a anemometry algorithm according to attitude information, run by the data processing unit anemometry algorithm can revise the influence of flight gesture to wind speed and wind direction, has greatly improved the anemometry precision.
Preferably: still include position monitoring unit for acquire many rotor unmanned aerial vehicle's position and height information, and transmit extremely the data processing unit.
Preferably: the system also comprises an upper computer which is used for receiving and analyzing the data information of the data processing unit and drawing a wind profile.
Preferably: the position detection unit includes a barometric sensor and a GPS radar.
Preferably: the pressure sensing unit comprises a pressure sensing cavity, a pressure guide pipe and a pressure difference sensor, the pressure sensing cavity is arranged at the end part of a supporting cantilever extending out of the multi-rotor unmanned aerial vehicle body, a pressure sensing opening of the pressure sensing cavity faces outwards and is positioned on the same plane, and the pressure sensing cavity is connected with the pressure difference sensor through the pressure guide pipe; the flight attitude acquisition unit is a three-axis acceleration sensor; the data processing unit comprises an FPGA chip, an STM32 single chip microcomputer and a 2.4GHz WiFi module.
Preferably: the four pressure sensing cavities are arranged, and the directions of the four pressure sensing cavities form an angle of 90 degrees with each other on the plane where the four pressure sensing cavities are located; the pressure sensing cavities in opposite directions are connected with the same group of pressure difference sensors through the pressure guide pipes.
Preferably: the pressure sensing cavity is characterized in that a fairing is fixedly arranged on the periphery of a pressure sensing opening of the pressure sensing cavity, and the fairing is an annular hemispherical shell with an opening at the bottom.
A wind measuring method of a high spatial and temporal resolution wind measuring system based on a multi-rotor unmanned aerial vehicle comprises the following steps,
step 1, acquiring wind pressure information;
and 3, correcting and calculating the wind pressure information in the step 1 by using the flight attitude data in the step 2, and acquiring the wind speed and the wind direction.
Preferably: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
and 4, acquiring the position and height information of the multi-rotor unmanned aerial vehicle, and drawing a wind profile by combining the wind speed and the wind direction obtained in the step 3.
Preferably:
step 1 the wind pressure information is obtained by the pressure sensing unit, the pressure sensing unit is including setting up on many rotor unmanned aerial vehicle and pressure sensing mouth is in four pressure sensing chambeies A, B, C, D of coplanar, and wherein pressure sensing chamber A is relative with C, and pressure sensing chamber B is relative with D, four the wind pressure that pressure sensing chamber A, B, C, D was surveyed is P respectivelyA、PB、PC、PD；
In the step 2, the flight attitude data is collected by a three-axis acceleration sensor, and a pitch angle theta and a roll angle phi of the multi-rotor unmanned aerial vehicle are collected;
in the step 3, the wind speed is represented by V, and the algorithm of the wind speed V is as follows:
the wind direction is represented by a wind direction angle alpha, and the algorithm of the wind direction angle alpha is as follows:
drawings
FIG. 1 is a schematic diagram of an embodiment of the present invention.
Fig. 2 is a first schematic workflow diagram of an embodiment of the present invention.
Fig. 3 is another schematic workflow diagram of an embodiment of the present invention.
Fig. 4 is a schematic diagram of the wind measuring principle of the embodiment of the invention.
Fig. 5 is a schematic diagram of a ground coordinate system and a coordinate system of a drone body according to an embodiment of the present invention.
Many rotor unmanned aerial vehicle 1, pressure sensing chamber 2, data processing unit 3, pressure pipe 4, radome fairing 5, support cantilever 6.
Detailed Description
The invention is further described with reference to the following figures and examples.
In an embodiment, as shown in fig. 1 and 2, a high spatial-temporal resolution wind measurement system and a wind measurement method based on a multi-rotor unmanned aerial vehicle are provided, wherein the wind measurement system comprises a pressure sensing unit for acquiring wind pressure information in different directions, a flight attitude acquisition unit for acquiring attitude information of the multi-rotor unmanned aerial vehicle, a data processing unit for receiving the wind pressure information and the attitude information and calculating wind speed and wind direction, and the multi-rotor unmanned aerial vehicle serving as a carrier platform. In the embodiment, the multi-rotor unmanned aerial vehicle is used as a wind measuring carrier, so that the volume is small, the deployment is easy, and the operation is convenient and efficient; when detecting the wind pressure through the pressure sensing unit, through flight gesture collection unit collection testing in-process unmanned aerial vehicle's attitude information to provide a anemometry algorithm according to attitude information, run by the data processing unit anemometry algorithm can revise the influence of flight gesture to wind speed and wind direction, has greatly improved the anemometry precision.
In an embodiment, as shown in fig. 1 and 2, the pressure sensing unit includes a pressure sensing cavity 2, a pressure guiding pipe 4 and a differential pressure sensor, the pressure sensing cavity 2 is disposed at an end of a supporting cantilever 6 extending from the multi-rotor unmanned aerial vehicle body 1, a pressure sensing port of the pressure sensing cavity faces outward and is located on the same plane, and the pressure sensing cavity 2 is connected with the differential pressure sensor through the pressure guiding pipe 4. More specifically, the pressure sensing cavity 2 is four inelastic hard tubes, and the directions of the tubes are 90 degrees on the plane where the tubes are located, so that the wind pressures in different directions can be collected; the pressure sensing cavities 2 in opposite directions are respectively connected with two probes on the same group of pressure difference sensors through pressure guide pipes 4. In the embodiment, as shown in fig. 1, a fairing 5 is fixedly arranged on the periphery of a pressure sensing port of the pressure sensing cavity 2, and the fairing 5 is an annular hemispherical shell with an opening at the bottom; the fairing 5 separates the pressure sensing port from the airflow generated by the multi-rotor unmanned aerial vehicle during flying, so that the interference of a wind field generated by the rotor of the multi-rotor unmanned aerial vehicle on the acquired data is shielded; further, the fairing 5 is arranged to be an annular hemispherical shell with an opening at the bottom, so that incoming wind pressure can be prevented from being generated inside the fairing 5, and secondary interference to wind measurement is avoided. In the embodiment, the flight attitude acquisition unit is a three-axis acceleration sensor and is used for monitoring a pitch angle theta and a roll angle phi of a multi-rotor unmanned aerial vehicle body in the process of measuring wind; the data processing unit comprises an FPGA chip, an STM32 single chip microcomputer and a 2.4GHzWiFi module.
In an embodiment, as shown in fig. 2, in order to improve the spatial resolution of the wind measurement, the wind measurement system further includes a position monitoring unit, configured to acquire position and height information of the multi-rotor drone, and transmit the position and height information to the data processing unit. Specifically, the position detection unit comprises an air pressure sensor and a GPS radar, wherein the air pressure sensor is used for acquiring the height information of the multi-rotor unmanned aerial vehicle, and the GPS radar is used for acquiring the position information of the multi-rotor unmanned aerial vehicle; combine baroceptor and GPS radar and many rotor unmanned aerial vehicle for the anemometry process is more nimble, can satisfy the anemometry needs of co-altitude and position, and application scope is wider.
In an embodiment, as shown in fig. 2, an upper computer is further provided for receiving and analyzing the data information of the data processing unit, and drawing a wind profile.
In the embodiment, pressure differential sensor among data processing unit, flight attitude acquisition unit, position detecting element and the pressure sensing unit concentrates on setting up in a shell, establish fixed point location in the shell, can pass through fixed point location with inside instrument and fix in the shell to fix the shell in many rotor unmanned aerial vehicle's organism 1 below, during anemometry work goes on, avoid the instrument to rock. In the embodiment, as shown in fig. 1, through holes are formed at four corners of the housing, so that the pressure pipe 2 is inserted into and connected with the differential pressure sensor. In an embodiment, the housing is further provided with a through hole for facilitating data communication between the 2.4ghz wifi module and an upper computer.
In an embodiment, a wind measurement method of a high spatial and temporal resolution wind measurement system based on a multi-rotor unmanned aerial vehicle comprises the following steps:
step 1, acquiring wind pressure information through a pressure sensing unit. Specifically, as shown in fig. 1 and 2, when the multi-rotor unmanned aerial vehicle hovers at a certain height, wind acts on the pressure sensing cavity 2, kinetic energy of the wind is converted into pressure potential energy inside the pressure sensing cavity 2, and the pressure potential energy acts on the differential pressure sensor through the pressure guiding pipe 4, and the differential pressure sensor is used for monitoring differential pressure of different pressure sensing cavities 2;
and 2, acquiring flight attitude data of the multi-rotor unmanned aerial vehicle through a flight attitude acquisition unit. Specifically, a three-axis acceleration sensor monitors a pitch angle theta and a roll angle phi of a multi-rotor unmanned aerial vehicle body in the anemometry process.
And 3, correcting and calculating the wind pressure information in the step 1 by using the flight attitude data in the step 2, and acquiring the wind speed and the wind direction.
In the embodiment, in order to improve the space-time resolution of the anemometry, the method further includes a step 4 of acquiring the position and height information of the multi-rotor unmanned aerial vehicle, specifically, monitoring the height information of the multi-rotor unmanned aerial vehicle by using the air pressure sensor, and monitoring the position information of the multi-rotor unmanned aerial vehicle by using the GPS radar; and drawing a wind profile by combining the wind speed and the wind direction obtained in the step 3.
Specifically, as shown in fig. 2, the FPGA chip collects differential pressure data monitored by the differential pressure sensor, attitude data of the multi-rotor unmanned aerial vehicle monitored by the three-axis acceleration sensor, height information of the multi-rotor unmanned aerial vehicle monitored by the air pressure sensor, and position information monitored by the GPS radar, and transmits a signal to the STM32 single chip microcomputer after performing primary processing such as filtering, amplification, a/D conversion, and the like; the STM32 single chip microcomputer is integrated with a wind measuring algorithm, the received signals can be analyzed and inverted according to the wind measuring algorithm to obtain wind speed and wind direction values, and the 2.4GHzWiFi module is controlled to transmit the received signals and the wind speed and wind direction values obtained through analysis to an upper computer; and the upper computer comprehensively analyzes the received data information and draws a wind profile.
In an embodiment, the wind measurement method of the high spatial-temporal resolution wind measurement system based on the multi-rotor unmanned aerial vehicle comprises the following wind measurement algorithms:
assuming that air is an ideal incompressible fluid, the kinetic energy of air flow is converted into pressure potential energy due to the blockage of the air by the object during the movement of the air. At this time, the relationship between the wind pressure and the wind speed can be obtained according to the classical hydrodynamics Bernoulli equation:
the calculation formula of the wind speed can be derived from the formula (1) as follows:
wherein: v is wind speed, P is wind pressure, and ρ is air density.
In this embodiment, the four pressure sensing chambers 2 are A, B, C, D respectively, wherein a and C are opposite in the pressure sensing chamber 2, B and D are opposite, and since A, B, C, D four pressure sensing chambers 2 are installed on one plane under the unmanned aerial vehicle body 1 at an angle of 90 ° with each other, at any time, the inlet of one or two pressure sensing chambers 2 is in the incoming flow of wind. The synthesized real-time wind pressure is solved from the two wind pressure vectors by an orthogonal decomposition method, and then the inversion of the wind speed is completed, as shown in fig. 3, at this time, the wind pressures measured by A and B in the pressure sensing cavity 2 are respectively PA、PB(ii) a Horizontal wind pressure in AO direction is PAOHorizontal wind pressure P in the BO directionBOAt this time, PAO＝PA；PBO＝PBAnd obtaining a wind direction angle:
when P is presentAOA special case is when 0 pa is equal, where the wind direction can be considered as Y-axis parallel, i.e. α is 90 °.
The real-time wind pressure is as follows:
the real-time wind speed V can be obtained by combining the formulas (2) and (4):
in practical measurement, in order to maintain a hovering attitude of the multi-rotor drone in the incoming wind, the airframe 1 may generate a certain pitch angle θ and roll angle Φ, as shown in fig. 4. At the moment, the pressure sensing cavity 2 collects components of incoming flow under corresponding pitch angle and roll angle, and in order to reduce errors, a wind measurement algorithm needs to be corrected according to flight attitude.
In fig. 4, XYZ is a ground coordinate system, and XYZ is a machine 1 coordinate system. Referring to FIG. 3, the horizontal wind pressure P in AO directionAOAnd horizontal wind pressure P in the BO directionBOThe following mathematical relationship is satisfied:
the values of the pitch angle theta and the roll angle phi in the formulas (6) and (7) can be measured by a triaxial acceleration sensor.
When the anemometry method is used on an unmanned aerial vehicle platform, the interference airflow V generated around the unmanned aerial vehicle due to the high-speed rotation of the rotor wing is also consideredd. As shown in FIG. 3, the wind pressures measured at C and D in the pressure-sensing chamber 2 are PC、Pd。
Assuming the velocity of wind is VdThe wind pressure generated by the interference airflow is Pd. At this time, PA＝PAO+Pd；PB＝PBO+Pd；Pc＝PD＝Pd. The relation is substituted into the formula (3), the formula (4), the formula (5), the formula (6) and the formula (7), and then the wind speed and wind pressure formula corrected by the pressure difference can be obtained:
when P is presentA-PCWhen the wind direction is 0 Pa, the wind direction is parallel to the Y axis,
at this time, if PB-PD>0, then α is 90 °; if PB-PD<0, then 90 °.
It should be understood that the above-described embodiments of the present invention are merely examples for illustrating the present invention, and are not intended to limit the embodiments of the present invention. Obvious variations or modifications of the present invention are possible within the spirit of the present invention.
Claims (10)
1. High spatial and temporal resolution anemometry system based on many rotor unmanned aerial vehicle, its characterized in that includes:
the pressure sensing unit is used for acquiring wind pressure information in different directions;
the flight attitude acquisition unit is used for acquiring attitude information of the multi-rotor unmanned aerial vehicle;
the data processing unit is used for receiving the wind pressure information and the attitude information and calculating the wind speed and the wind direction;
many rotor unmanned aerial vehicle as the carrier platform.
2. The multi-rotor drone-based high spatial and temporal resolution anemometry system according to claim 1, characterized in that: still include position monitoring unit for acquire many rotor unmanned aerial vehicle's position and height information, and transmit extremely the data processing unit.
3. The multi-rotor drone-based high spatial and temporal resolution anemometry system according to claim 2, characterized in that: the system also comprises an upper computer which is used for receiving and analyzing the data information of the data processing unit and drawing a wind profile.
4. The multi-rotor drone-based high spatial and temporal resolution anemometry system according to claim 2, characterized in that: the position detection unit includes a barometric sensor and a GPS radar.
5. The multi-rotor drone-based high spatial and temporal resolution anemometry system according to claim 1, characterized in that: the pressure sensing unit comprises a pressure sensing cavity (2), a pressure guide pipe (4) and a pressure difference sensor, the pressure sensing cavity (2) is arranged at the end part of a supporting cantilever (6) extending out of the multi-rotor unmanned aerial vehicle body (1), a pressure sensing opening of the pressure sensing cavity faces outwards and is positioned on the same plane, and the pressure sensing cavity (2) is connected with the pressure difference sensor through the pressure guide pipe (4); the flight attitude acquisition unit is a three-axis acceleration sensor; the data processing unit comprises an FPGA chip, an STM32 single chip microcomputer and a 2.4GHz WiFi module.
6. The multi-rotor drone-based high spatial and temporal resolution anemometry system according to claim 5, characterized in that: the number of the pressure sensing cavities (2) is four, and the directions of the pressure sensing cavities form an angle of 90 degrees with each other on the plane where the pressure sensing cavities are located; the pressure sensing cavities (2) in opposite directions are connected with the same group of pressure difference sensors through the pressure guide pipes (4).
7. The multi-rotor drone-based high spatial and temporal resolution anemometry system according to claim 5, characterized in that: the pressure sensing cavity is characterized in that a fairing (5) is fixedly arranged on the periphery of a pressure sensing opening of the pressure sensing cavity (2), and the fairing (5) is an annular hemispherical shell with an opening at the bottom.
8. A wind measuring method of a high spatial and temporal resolution wind measuring system based on a multi-rotor unmanned aerial vehicle is characterized by comprising the following steps: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
step 1, acquiring wind pressure information;
step 2, acquiring flight attitude data of the multi-rotor unmanned aerial vehicle;
and 3, correcting and calculating the wind pressure information in the step 1 by using the flight attitude data in the step 2, and acquiring the wind speed and the wind direction.
9. The method of claim 8, wherein the method comprises: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
and 4, acquiring the position and height information of the multi-rotor unmanned aerial vehicle, and drawing a wind profile by combining the wind speed and the wind direction obtained in the step 3.
10. The method of claim 8, wherein the method comprises:
step 1 in the wind pressure information is obtained by the pressure sensing unit, the pressure sensing unit is including setting up on many rotor unmanned aerial vehicle and pressure sensing mouth department in four pressure sensing chamber (2) A, B, C, D of coplanar, and pressure sensing chamber (2) A is relative with C in it, and pressure sensing chamber (2) B is relative with D, four the wind pressure that pressure sensing chamber (2) A, B, C, D was surveyed is P respectivelyA、PB、PC、PD；
In the step 2, the flight attitude data is collected by a three-axis acceleration sensor, and a pitch angle theta and a roll angle phi of the multi-rotor unmanned aerial vehicle are collected;
in the step 3, the wind speed is represented by V, and the algorithm of the wind speed V is as follows:
the wind direction is represented by a wind direction angle alpha, and the algorithm of the wind direction angle alpha is as follows:
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114113671A (en) * | 2021-11-24 | 2022-03-01 | 国家电投集团广西灵川风电有限公司 | High-time-width-resolution wind measurement system and wind measurement method based on multi-rotor unmanned aerial vehicle |
| CN114237279A (en) * | 2021-11-24 | 2022-03-25 | 余姚市浙江大学机器人研究中心 | Wind speed and direction detector based on multi-rotor unmanned aerial vehicle and detection method thereof |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109178300A (en) * | 2018-10-18 | 2019-01-11 | 南京信息工程大学 | A kind of wind measuring device based on multi-rotor unmanned aerial vehicle platform |
-
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- 2020-10-30 CN CN202011190728.7A patent/CN112114383A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109178300A (en) * | 2018-10-18 | 2019-01-11 | 南京信息工程大学 | A kind of wind measuring device based on multi-rotor unmanned aerial vehicle platform |
Non-Patent Citations (1)
| Title |
|---|
| 侯天浩 等: "基于多旋翼无人机的正交式风压矢量分解测风法", 《仪器仪表学报》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114113671A (en) * | 2021-11-24 | 2022-03-01 | 国家电投集团广西灵川风电有限公司 | High-time-width-resolution wind measurement system and wind measurement method based on multi-rotor unmanned aerial vehicle |
| CN114237279A (en) * | 2021-11-24 | 2022-03-25 | 余姚市浙江大学机器人研究中心 | Wind speed and direction detector based on multi-rotor unmanned aerial vehicle and detection method thereof |
| CN114113671B (en) * | 2021-11-24 | 2024-03-22 | 国家电投集团广西灵川风电有限公司 | High space-time resolution wind measuring system and wind measuring method based on multi-rotor unmanned aerial vehicle |
| CN114237279B (en) * | 2021-11-24 | 2024-03-29 | 余姚市浙江大学机器人研究中心 | Wind speed and direction detector based on multi-rotor unmanned aerial vehicle and detection method thereof |
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