CN209624628U - A kind of unmanned plane being measured wind direction and wind velocity based on neural network - Google Patents
A kind of unmanned plane being measured wind direction and wind velocity based on neural network Download PDFInfo
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- CN209624628U CN209624628U CN201821734817.1U CN201821734817U CN209624628U CN 209624628 U CN209624628 U CN 209624628U CN 201821734817 U CN201821734817 U CN 201821734817U CN 209624628 U CN209624628 U CN 209624628U
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Abstract
The utility model relates to air vehicle technique fields, more particularly to a kind of unmanned plane for being measured wind direction and wind velocity based on neural network, the unmanned plane includes center body, flight bracket, flight motor, wind sense sensing unit, the center body and the flight bracket collectively constitute unmanned plane main part, and the flight motor is arranged on each flight bracket；The casing body is a cylindrical shell structure, and the wind sense sensing unit includes at least four graphene wind sensors, protection cap and neural network preprocessor；At least four graphene wind sensors are set on four different peripheral directions of the machine housing upper surface, multi-site determination is carried out in some area of space according to the hovering of unmanned plane movement, pass through the wind sense array precise determination wind speed, wind direction, greatly improve the precision of determination data, and by determination data real-time Transmission into remote terminal equipment, it carries out data statistics and data shows that wireless transmission rate is fast, easy to operate.
Description
Technical field
The utility model relates to air vehicle technique fields, and in particular to one kind is measured wind direction and wind velocity based on neural network
Unmanned plane.
Background technique
In recent years, with the progress of the technologies such as new material, micro electronmechanical, quadrotor drone has obtained cracking development；And
Gradually be applied to military affairs, agricultural, various social field.But these applications are confined to indoor or calm steady air current outdoor
Environment, and outdoor weather meteorology includes temperature, air pressure, wind, humidity, cloud, precipitation etc., and for meteorological ocean worker,
Wind direction and wind velocity is particularly important, and solar radiation is the basic reason of Global climate change, and in some sense, wind is to lead to global climate
The major reason of variation.The presence of wind conveys heat, to the transfer that aqueous vapor carries out, to influence weather.
Doppler radar and various fixed survey wind equipments that wind mainly has weather station are surveyed at present.These equipment or
A wide range of mean wind direction wind speed can only be measured or the wind direction and wind velocity of a certain fixed point can only be measured.It works for meteorological ocean
For person, the wind direction and wind velocity in a certain area three-dimensional space has very big help to research.And the development of unmanned plane, unmanned boat is fast
Speed, unmanned boat can long endurance, but the disadvantage is that two-dimensional surface can only be measured；Researcher vertical velocity measurement used at present
Method or sounding balloon.But sounding balloon can not recycle, higher cost, be not suitable for using on a large scale.
And at present often there is determination data lag when measuring wind speed and direction in unmanned plane, data are analyzed not in time, remote
During Distance Transmission, the problems such as data transfer signal is impacted, and there are no occur solving problems on the market at present
Product.
Utility model content
In order to effectively solve the above problems, the utility model, which provides, a kind of is measured wind direction and wind velocity based on neural network
Unmanned plane.
The specific technical solution of the utility model is as follows: it is a kind of wind direction and wind velocity is measured based on neural network nobody
Machine, the unmanned plane include center body, flight bracket, flight motor, wind sense sensing unit, and the center body flies with described
Row bracket collectively constitutes unmanned plane main part, and the flight motor is arranged on each flight bracket；
The center body includes casing body, control unit；
The casing body is a cylindrical shell structure, and the wind sense sensing unit includes at least four graphene wind senses
Device, protection cap and neural network preprocessor；It is arranged at least four on four different peripheral directions of the machine housing upper surface
The neural network preprocessor, institute is arranged in a graphene wind sensor, the center position in the top of the casing body
It states neural network preprocessor to be connected with the graphene wind sensor, locate in advance in the graphene wind sensor and neural network
The protection cap is fixedly installed in the top position for managing device, and the protection cap is fixedly connected with the casing body by support column；
The graphene wind sensor includes a package casing, wind sense module, and the package casing upper inner is provided with
Base top flat, package casing and base top flat define an internal detection space jointly, in the internal detection space described in setting
Wind sense module；
The internal detection space bottom side is provided with a glass pedestal, outside the glass pedestal peripheral side and the encapsulation
Shell medial surface phase mutual connection is set, and the glass pedestal is located at the downside in the internal detection space；
The wind sense module includes wind sense array, and the wind sense array includes multiple wind sense subelements, and wind sense is single
Member is arranged in array, and the quantity in transverse direction and longitudinal direction is identical, and is evenly distributed in the detection space, and it is lateral and
Spacing is all the same between longitudinal direction；
The wind sense subelement is graphene nano film, and the wind sense module further includes the compound of connection wind sense subelement
Electrode, base top flat downside are disposed with the graphene nano membrane array, the transverse direction and longitudinal direction of graphene nano membrane array
Heating resistance is provided at the surrounding position constituted.
Further, the side in internal monitoring space is provided with ceramic substrate, the Ji Ding in the glass pedestal
Piece is bonded with the ceramic substrate by sealing ring, forms anaerobic cavity, inert gas can be filled in cavity.
Further, the combination electrode is separately connected the both ends of graphene nano film.
Further, the neural network preprocessor may include the mind for being embedded with Pulse Coupled Neural Network algorithm
Through network chip and single-chip microcontroller and output interface and input interface；
The single-chip microcontroller is the single-chip microcontroller with analog-digital converter, the single-chip microcontroller and is embedded with Pulse Coupled Neural Network
The neural network chip of algorithm connects；
The neural network chip is connect by the output interface with described control unit, and will be at neural network chip
Processing result after the completion of reason is fed back in remote terminal equipment by described control unit.
Further, described control unit has a wireless communication module for sending or receiving control instruction.
The usefulness of the utility model: application one kind described in the utility model is measured wind direction wind based on neural network
The unmanned plane of speed carries out multi-site determination according to the hovering of unmanned plane movement in some area of space, passes through the wind sense battle array
Column precise determination wind speed, wind direction greatly improve the precision of determination data, and determination data real-time Transmission to remote terminal are set
In standby, carry out data statistics and data show that wireless transmission rate is fast, easy to operate.
Detailed description of the invention
Fig. 1 is the overall structure diagram of the utility model first embodiment；
Fig. 2 is graphene wind sensor appearance diagram described in the utility model embodiment；
Fig. 3 is the schematic diagram of internal structure of graphene wind sensor described in the utility model；
Fig. 4 is graphene wind sensor internal structure top view described in the utility model；
Fig. 5 is graphene wind sense device working schematic diagram described in the utility model；
Fig. 6 is the schematic diagram that unmanned plane described in the utility model measures wind speed and direction.
Specific embodiment
In order to make the purpose of the utility model, technical solutions and advantages more clearly understood, below in conjunction with attached drawing and implementation
Example, is explained in further detail the utility model.It should be appreciated that specific embodiment described herein is used only for explaining
The utility model is not used to limit the utility model.
On the contrary, the utility model cover it is any be defined by the claims do in the spirit and scope of the utility model
Substitution, modification, equivalent method and scheme.Further, right below in order to make the public have a better understanding the utility model
It is detailed to describe some specific detail sections in the datail description of the utility model.Do not have for a person skilled in the art
The utility model can also be understood completely in the description of these detail sections.
As shown in Figure 1, being the overall structure diagram of the utility model first embodiment, this embodiment offers a kind of bases
It is measured the unmanned plane of wind direction and wind velocity in neural network, the unmanned plane includes center body 1, flight bracket 2, flight motor
3, wind sense sensing unit；
The center body 1 collectively constitutes unmanned plane main part with the flight bracket 2, in each flight bracket
The flight motor 3 is set on 2, drive the entire center body 1 and flight bracket 2 to be gone up and down by flight motor 3,
Flight；
The flight bracket 2, the conventional equipment that flight motor 3 is this field are not specifically limited herein, the center machine
Body 1 includes casing body, control unit 10, and it is this field that the casing body, which is the shell mechanism that this field user assembles nobody,
Conventional equipment is not specifically limited herein；
Described control unit 10 is connect with each flight motor 3, and controls the normal work of each flight motor 3, in institute
It states machine housing upper surface and the wind sense sensing unit is set, described control unit 10 is that this field can control unmanned plane normal flight
The singlechip controller of operation；
In the present embodiment, the casing body is a cylindrical shell structure, and the wind sense sensing unit includes at least
Four graphene wind sensors 4, protection cap 6 and neural network preprocessor 5；In four different weeks of the machine housing upper surface
At least four graphene wind sensors 4 are set on edge direction, described in the center position setting of the top of the casing body
Neural network preprocessor 5, the neural network preprocessor 5 is connected with the graphene wind sensor 4, in the graphene
The protection cap 6 is fixedly installed in the top position of wind sensor 4 and neural network preprocessor 5, for protecting the graphene wind
Sensor 4 and neural network preprocessor 5, and the protection cap 6 is fixedly connected with the casing body by support column 7, guarantees institute
State the variation of graphene wind sensor 4 wind speed and wind direction around unmanned plane top position can receive；
The machine housing upper surface extends the support column 7, and the protection cap 6 is connected with the support column 7 by screw
It connects, realizes that the protection cap 6 is fixed above the casing body, the graphene wind sensor 4, neural network preprocessor
5 are fixed on above the casing body, and the fixed form includes but is not limited to be bonded, be threadedly coupled；
As shown in Fig. 2, the graphene wind sensor 4 includes a package casing 40, wind sense module, the package casing 40
Entirety can be cylinder, square, cuboid etc., and be not particularly limited；
40 upper inner of package casing is provided with base top flat 41, and package casing 40 and base top flat 41 define one jointly
The wind sense module is arranged in the internal detection space in inside detection space；
It as shown in Figure 3,4, is the overall structure sectional view of the graphene wind sensor 4, the internal detection space bottom side
It is provided with a glass pedestal 42,42 peripheral side of glass pedestal is set with the 40 medial surface phase mutual connection of package casing, described
Glass pedestal 42 is located at the downside in the internal detection space.
The wind sense module is placed in the internal detection space, and is specifically located at the base top flat 41 towards described interior
The side in space is detected in portion, and the wind sense module includes wind sense array, and the wind sense array includes multiple wind sense subelements 43, institute
It states wind sense subelement 43 to arrange in array, the quantity in transverse direction and longitudinal direction is identical, and it is empty in the detection to be evenly distributed
In, and spacing is all the same between transverse direction and longitudinal direction；
The wind sense subelement 43 is graphene nano film, and the wind sense module further includes connection wind sense subelement 43
Combination electrode 44,41 downside of base top flat are disposed with the graphene nano membrane array, the cross of graphene nano membrane array
To and longitudinal surrounding position constituted at be provided with heating resistance 45, the heating resistance 45 on four direction is used to graphene
Nano thin-film array is symmetrically heated, and base top flat 41 and tested distinguished and admirable body carry out exchanging and graphene being protected to receive for heat
Rice film.
The side in internal monitoring space is provided with ceramic substrate 46 in the glass pedestal 42, the base top flat 41 with
The ceramic substrate 46 is bonded by sealing ring 47, forms anaerobic cavity, inert gas can be filled in cavity, be graphene nano
Membrane array provides anaerobic protection, and ceramic substrate 46 is pasted onto glass pedestal 42 by adiabatic gum 48, and it is downward to have completely cut off heat
Transmitting.
It as shown in Figure 3,4, is the schematic diagram of internal structure and bottom view of first embodiment of the invention graphene wind sensor 4,
The combination electrode 44 is separately connected the both ends of graphene nano film, rings for exporting the electricity in graphene nano film
It answers.Concrete mode is that stem 49 is connected with connection electrode 410, passes through connection electricity through ceramic substrate 46 and glass pedestal 42
Pole 410 connects external circuit, i.e., the described connection electrode 410 is connect with neural network preprocessor 5；
Connection electrode 410 is bonded with connection pad 412 by connecting salient points 411 and is constituted, and combination electrode 44 is by wiring and even
It connects salient point 411 to be electrically connected, heating resistance 45 is electrically connected with connecting salient points 411.
As shown in figure 5, being the schematic diagram of sensor sensing wind speed and direction, the sensor is by heating element and temperature element group
At heating resistance 45 passes to constant current and generates certain Temperature Distribution, and temperature element is graphene nano membrane array, with wind speed
Increase, device aweather in transmit heat increase, so as to cause graphene nano film temperature decline, the resistivity of graphene
It changes, can be obtained the size of wind speed after signal output by the data processing of back-end circuit, graphene array can be with
Reduce error.
The upstream and downstream of wind can generate non-uniform cooling to sensor surface, to generate temperature ladder in chip surface
Degree, and temperature gap of the temperature gradient on wind direction is the largest, and is received by the detection of graphene nano membrane array, data
The algorithm of collection and a segment processing, so that it may determine wind direction, enable the sensor to 360 ° of sensitivities.
The graphene wind sensor 4 is connect with the neural network preprocessor 5 by electric lead and signal conductor, will
Wind sense subelement 43 in each wind sense array is connect with neural network preprocessor 5, and the neural network is located in advance
Reason device 5 may include this be embedded with Pulse Coupled Neural Network algorithm neural network chip 51 and single-chip microcontroller 52 and output
Interface 53 and input interface 54；
The single-chip microcontroller 52 is the single-chip microcontroller 52 with analog-digital converter, the single-chip microcontroller 52 be embedded with pulse-couple
The neural network chip 51 of neural network algorithm connects, and the neural network chip 51 is used for the electricity to each wind sense subelement 43
Flow data is handled, and the input interface 54 is for each wind sense subelement 43 to be connected with single-chip microcontroller 52, the monolithic
Machine 52 is connect with the neural network chip 51, inputs the nerve after current signal is converted to corresponding analog and digital signal
Network chip 51 carries out neural network and is calculated, this is embedded with the working principle of the chip of Pulse Coupled Neural Network algorithm
Are as follows: set each neuron corresponding to a current variable in input current data, neuron also neuron adjacent thereto
Connection receives variable stimulation from them.Importation passes through feeding respectively and links the outside for partially importeding into neuron and this
Ground input.In coupling part, external and local stimulation is combined in internal activation system, and accumulation stimulation is more than dynamic until it
State threshold value, then impulse generator generates pulse output.Pass through iterative calculation, the pulse output of neuron generation time sequence.
Similitude in input current variable leads to associated neuron lock-out pulse, thereby indicate that similar structure or texture.This
The time series of a little pulse outputs includes the information such as wind speed size, wind direction, for measuring the place of the wind speed in specified region, wind direction
Ought to use, be based on above-mentioned working principle, can using digital signal processor (DSP), specific integrated circuit (ASIC), it is ready-made can
Program gate array (FPGA) either the components such as other programmable logic device, transistor logic, isolating hardware realize or
The chip that Pulse Coupled Neural Network algorithm is embedded with disclosed in the present embodiment is executed, details are not described herein.
In the present embodiment, the neural network chip 51 is connected by the output interface 53 with described control unit 10
It connects, and the processing result after the completion of the processing of neural network chip 51 is fed back into remote terminal equipment by described control unit 10
In 12, treated that data result data format is simple for the neural network chip 51, and data volume is few, usually only 10-
The processing result of 500KB, therefore unmanned plane transmitted data rates are fast, reach the real time measure wind speed and direction data, greatly improve survey
The precision of fixed number evidence；
As shown in fig. 6, described control unit 10 has a wireless communication module 11 for sending or receiving control instruction, pass through
Wireless communication module 11 for the processing result of neural network chip 51 to be wirelessly transmitted in remote terminal equipment 12, and connects
Receive the control instruction of remote terminal equipment 12；
The wireless communication module 11 includes but is not limited to the bluetooth communication, WIFI communication module of this field, GSM
Module, the control instruction include but is not limited to digital signal instruction, short-message instruction；
The remote terminal equipment 12 is the intelligent terminal that this field can receive wind speed, wind direction determination data, described
Intelligent terminal includes Intelligent flat equipment, computer equipment.
Using a kind of unmanned plane for being measured wind direction and wind velocity based on neural network, acted according to the hovering of unmanned plane
Multi-site determination is carried out in some area of space, by the wind sense array precise determination wind speed, wind direction, greatly improves measurement
The precision of data, and by determination data real-time Transmission into remote terminal equipment 12, it carries out data statistics and data is shown,
Wireless transmission rate is fast, easy to operate.
For the ordinary skill in the art, introduction according to the present utility model is not departing from the utility model
Principle and spirit in the case where, changes, modifications, replacement and the deformation carried out to embodiment still falls within the utility model
Within protection scope.
Claims (5)
1. a kind of unmanned plane for being measured wind direction and wind velocity based on neural network, which is characterized in that the unmanned plane includes center
Body, flight bracket, flight motor, wind sense sensing unit, the center body and the flight bracket collectively constitute unmanned plane
The flight motor is arranged on each flight bracket in main part；
The center body includes casing body, control unit；
The casing body be a cylindrical shell structure, the wind sense sensing unit include at least four graphene wind sensors,
Protection cap and neural network preprocessor；It is arranged at least four on four different peripheral directions of the machine housing upper surface
The graphene wind sensor, the neural network preprocessor is arranged in the center position in the top of the casing body, described
Neural network preprocessor is connected with the graphene wind sensor, pre-processes in the graphene wind sensor and neural network
The protection cap is fixedly installed in the top position of device, and the protection cap is fixedly connected with the casing body by support column；
The graphene wind sensor includes a package casing, wind sense module, and the package casing upper inner is provided with Ji Ding
Piece, package casing and base top flat define an internal detection space jointly, and the wind sense is arranged in the internal detection space
Module；
The internal detection space bottom side is provided with a glass pedestal, in the glass pedestal peripheral side and the package casing
Side phase mutual connection is set, and the glass pedestal is located at the downside in the internal detection space；
The wind sense module includes wind sense array, and the wind sense array includes multiple wind sense subelements, and the wind sense subelement is in
Array arrangement, the quantity in transverse direction and longitudinal direction is identical, and is evenly distributed in the detection space, and transverse direction and longitudinal direction
Between spacing it is all the same；
The wind sense subelement is graphene nano film, and the wind sense module further includes the compound electric for connecting wind sense subelement
Pole, base top flat downside are disposed with the graphene nano membrane array, the transverse direction and longitudinal direction institute of graphene nano membrane array
Heating resistance is provided at the surrounding position of composition.
2. a kind of unmanned plane for being measured wind direction and wind velocity based on neural network according to claim 1, which is characterized in that In
The glass pedestal is provided with ceramic substrate towards the side in internal monitoring space, and the base top flat passes through with the ceramic substrate
Sealing ring bonding forms anaerobic cavity, inert gas can be filled in cavity.
3. a kind of unmanned plane for being measured wind direction and wind velocity based on neural network according to claim 2, which is characterized in that institute
State the both ends that combination electrode is separately connected graphene nano film.
4. a kind of unmanned plane for being measured wind direction and wind velocity based on neural network according to claim 1, which is characterized in that institute
Stating neural network preprocessor may include the neural network chip and monolithic that are embedded with Pulse Coupled Neural Network algorithm
Machine and output interface and input interface；
The single-chip microcontroller is the single-chip microcontroller with analog-digital converter, the single-chip microcontroller and is embedded with Pulse Coupled Neural Network algorithm
Neural network chip connection；
The neural network chip is connect by the output interface with described control unit, and neural network chip has been handled
Processing result after is fed back in remote terminal equipment by described control unit.
5. a kind of unmanned plane for being measured wind direction and wind velocity based on neural network according to claim 1, which is characterized in that institute
State the wireless communication module that control unit sends or receives control instruction with one.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201821734817.1U CN209624628U (en) | 2018-10-25 | 2018-10-25 | A kind of unmanned plane being measured wind direction and wind velocity based on neural network |
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| CN201821734817.1U CN209624628U (en) | 2018-10-25 | 2018-10-25 | A kind of unmanned plane being measured wind direction and wind velocity based on neural network |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114397474A (en) * | 2022-01-17 | 2022-04-26 | 吉林大学 | FCN-MLP-based arc ultrasonic sensing array wind parameter measurement method |
-
2018
- 2018-10-25 CN CN201821734817.1U patent/CN209624628U/en active Active
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114397474A (en) * | 2022-01-17 | 2022-04-26 | 吉林大学 | FCN-MLP-based arc ultrasonic sensing array wind parameter measurement method |
| CN114397474B (en) * | 2022-01-17 | 2022-11-08 | 吉林大学 | FCN-MLP-based arc ultrasonic sensing array wind parameter measurement method |
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