Flexible atmospheric parameter sensing system

Abstract

The invention discloses a flexible atmospheric parameter sensing system, and relates to the technical field of atmospheric parameter sensing, and the flexible atmospheric parameter sensing system comprises a flexible substrate circuit board, and a sensing array, a control circuit and a microcontroller chip which are attached to the flexible substrate circuit board. A target atmospheric parameter calculation model is integrated in the microcontroller chip; the sensing array is used for collecting flow field information and sending the flow field information to the microcontroller chip through the flexible substrate circuit board under the control of the control circuit; the flow field information comprises pressure, temperature and flow velocity; the microcontroller chip is used for determining a resolving value of a target atmospheric parameter according to the flow field information by using a target atmospheric parameter calculation model; the target atmospheric parameters comprise the air speed, the attack angle, the sideslip angle, the static pressure and the total temperature. The calculation precision of the air speed, the attack angle, the sideslip angle, the total temperature and the static pressure can be improved, and the cost is reduced.

Description

Technical Field

[0001] The present application relates to the field of atmospheric parameter sensing technology, and in particular to a flexible atmospheric parameter sensing system. Background Art

[0002] At present, the widely used commercial probe-type and weathervane-type atmospheric parameter sensing systems have a protruding structure that is easy to damage for small UAV systems facing complex flight environments and with high flight flexibility. They are costly and heavy, which is not conducive to their miniaturization. The embedded atmospheric parameter sensing system includes pressure measuring holes, air bleed pipes and pressure sensors distributed on the nose or wings. There are problems such as complex pipes, signal lag, damage to the fuselage, poor reliability at low speeds, and high costs.

[0003] Therefore, in order to meet the needs of high maneuverability, intelligence and clustering of small UAV systems, a bionic distributed flow field sensing system has been developed to directly obtain the flow field information on the surface of the aircraft, and then calculate the aircraft's airspeed, angle of attack, sideslip angle and other parameters in real time. However, the current bionic distributed flow field sensing system mostly adopts a single sensing principle, which places high demands on the performance, quantity and reliability of the sensing elements. Summary of the invention

[0004] The purpose of this application is to provide a flexible atmospheric parameter sensing system to solve the problems of high cost and low solution accuracy.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] The present application provides a flexible atmospheric parameter sensing system, comprising: a flexible substrate circuit board and a sensor array, a control circuit and a microcontroller chip attached to the flexible substrate circuit board; a target atmospheric parameter calculation model is integrated in the microcontroller chip;

[0007] The sensor array is used to collect flow field information, and under the control of the control circuit, the flow field information is sent to the microcontroller chip through the flexible substrate circuit board; the flow field information includes: pressure, temperature and flow velocity;

[0008] The microcontroller chip is used to determine the solution value of the target atmospheric parameter according to the flow field information by using the target atmospheric parameter calculation model; the target atmospheric parameters include: airspeed, angle of attack, sideslip angle, static pressure and total temperature.

[0009] Optionally, the sensor array includes: N pressure sensing units, M temperature sensing units and Q flow rate sensing units; N and Q are both positive even numbers greater than 2; M is a positive even number;

[0010] N pressure sensing units are staggered and distributed at equal intervals along a straight line, M temperature sensing units are staggered and distributed along a straight line, and Q flow velocity sensing units are staggered and distributed at equal intervals along a straight line;

[0011] Each of the pressure sensing units is used to collect pressure;

[0012] Each of the temperature sensing units is used to collect temperature;

[0013] Each of the flow velocity sensing units is used to collect flow velocity.

[0014] Optionally, the pressure sensing unit is an absolute pressure sensor, the temperature sensing unit is a temperature sensor, and the flow velocity sensing unit is a vector flow velocity sensor.

[0015] Optionally, the flexible atmospheric parameter sensing system is attached to the outer surface of the leading edge of the wing; the center line of the area where the sensor array is located is set at the front end position of the wing section;

[0016] N pressure sensing units, M temperature sensing units and Q flow rate sensing units are respectively distributed axially symmetrically on both sides of the center line;

[0017] The minimum spacing between each sensing unit in the sensing array and the center line is greater than a preset spacing, and the preset spacing is twice the width of the pressure sensing unit.

[0018] Optionally, a gasket is provided between each of the flow velocity sensing units and the flexible base circuit board; the material of the gasket is resin;

[0019] The sum of the thickness of each flow rate sensing unit and the corresponding gasket is equal to the thickness of the pressure sensing unit.

[0020] Optionally, the surface of the flexible substrate circuit board is covered with a rectifying layer;

[0021] The rectifying layer covers the surface of the microcontroller chip and the control circuit; the upper surface of the rectifying layer is flush with the upper surface of each of the pressure sensing units and each of the flow rate sensing units.

[0022] Optionally, the rectifying layer is made of soft glue.

[0023] Optionally, the target atmospheric parameter calculation model includes: a first atmospheric parameter calculation model and a second atmospheric parameter calculation model; the first atmospheric parameter calculation model and the second atmospheric parameter calculation model are both obtained by training a back propagation neural network;

[0024] Using the target atmospheric parameter calculation model and according to the flow field information, determining the solution value of the target atmospheric parameter includes:

[0025] Based on the pressure collected by each group of symmetrical pressure sensing units, the corresponding upper and lower wing pressure differences are calculated;

[0026] Inputting each of the flow velocities and each of the upper and lower wing surface pressure differences into the first atmospheric parameter calculation model to obtain a solution value of the airspeed, a solution value of the angle of attack, and a solution value of the sideslip angle;

[0027] Inputting the calculated values ​​of the pressure, airspeed, angle of attack and sideslip angle into the second atmospheric parameter calculation model to obtain a calculated value of static pressure;

[0028] Each of the temperatures is determined as a calculated value of the total temperature.

[0029] Optionally, the process of determining the first atmospheric parameter calculation model includes:

[0030] By performing dynamic simulation, wind tunnel test or flight test on the wing model of the UAV, sample values ​​of pressure corresponding to each pressure sensing unit and sample values ​​of flow velocity corresponding to each flow velocity sensing unit at different airspeeds, angles of attack, sideslip angles and static pressures are obtained;

[0031] Based on the sample values ​​of the pressures corresponding to the groups of symmetrical pressure sensing units, the corresponding sample values ​​of the pressure differences between the upper and lower wing surfaces are calculated;

[0032] Construct a back-propagation neural network;

[0033] The back propagation neural network is trained with the sample values ​​of each flow velocity and the corresponding sample values ​​of the pressure difference between the upper and lower wing surfaces as input, and the corresponding airspeed, angle of attack, and sideslip angle as output to obtain the first atmospheric parameter calculation model.

[0034] Optionally, the process of determining the second atmospheric parameter calculation model includes:

[0035] By performing dynamic simulation, wind tunnel test or flight test on the wing model of the UAV, sample values ​​of pressure corresponding to each pressure sensing unit under different airspeeds, angles of attack, sideslip angles and static pressures are obtained;

[0036] Construct a back-propagation neural network;

[0037] The back propagation neural network is trained with the sample values ​​of each pressure and the corresponding airspeed, angle of attack and sideslip angle as input and the corresponding static pressure as output to obtain the second atmospheric parameter calculation model.

[0038] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0039] The present application discloses a flexible atmospheric parameter sensing system, including: a flexible substrate circuit board and a sensor array, a control circuit and a microcontroller chip attached to the flexible substrate circuit board; a target atmospheric parameter calculation model is integrated in the microcontroller chip; the sensor array is used to collect flow field information, and under the control of the control circuit, the flow field information is sent to the microcontroller chip through the flexible substrate circuit board; the flow field information includes: pressure, temperature and flow velocity; the microcontroller chip is used to use the target atmospheric parameter calculation model to determine the solution value of the target atmospheric parameter according to the flow field information; the target atmospheric parameters include: airspeed, angle of attack, sideslip angle, static pressure and total temperature. The present application adopts the method of multi-sensor fusion of pressure, flow velocity and temperature to complete the packaging of the sensor array, control circuit and microcontroller chip on the flexible substrate circuit board, and designs and manufactures a flexible atmospheric parameter sensing system that can be attached to the airfoil surface, realizes the integration of flow field information perception and atmospheric parameter solution, and achieves the purpose of low-cost and high-precision solution of airspeed, angle of attack, sideslip angle, total temperature and static pressure. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 A schematic diagram of the structure of a flexible atmospheric parameter sensing system provided in an embodiment of the present application;

[0042] Figure 2 A schematic diagram of the specific structure of a flexible atmospheric parameter sensing system provided in one embodiment of the present application;

[0043] Figure 3 A schematic diagram of the positions of the sensor array, control circuit and microcontroller chip on the flexible substrate circuit board;

[0044] Figure 4 This is a schematic diagram of the installation location of the flexible atmospheric parameter sensing system;

[0045] Figure 5 for Figure 3 The cross-sectional view of the AA position in ;

[0046] Figure 6 This is a schematic diagram of the target atmospheric parameter solution process;

[0047] Figure 7 This is a schematic diagram of the airspeed, angle of attack, and sideslip angle calculation principles;

[0048] Figure 8 It is a schematic diagram of the position angle and circumferential angle of the pressure measuring point;

[0049] Fig. 9 This is a schematic diagram of airspeed solution;

[0050] Fig.10 This is a schematic diagram of angle of attack solution;

[0051] Fig.11 It is a schematic diagram of the sideslip angle solution;

[0052] Fig.12 This is a schematic diagram of static pressure solution.

[0053] Reference numerals:

[0054] Flexible substrate circuit board—1, sensor array—2, pressure sensor unit—201, temperature sensor unit—202, flow velocity sensor unit—203, control circuit—3, microcontroller chip—4, target atmosphere parameter calculation model—5, center line—6, gasket—7, straightening layer—8, wing—9. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0056] The purpose of this application is to provide a flexible atmospheric parameter sensing system, which aims to improve the calculation accuracy of airspeed, angle of attack, sideslip angle, total temperature and static pressure and reduce costs.

[0057] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0058] In an exemplary embodiment, Figure 1 and Figure 2 As shown, a flexible atmospheric parameter sensing system is provided, including: a flexible base circuit board 1 and a sensor array 2, a control circuit 3 and a microcontroller chip 4 attached to the flexible base circuit board 1; a target atmospheric parameter calculation model 5 is integrated in the microcontroller chip 4.

[0059] The sensor array 2 is used to collect flow field information. Under the control of the control circuit, the flow field information is sent to the microcontroller chip through the flexible substrate circuit board; the flow field information includes: pressure, temperature and flow velocity.

[0060] The microcontroller chip 4 is used to determine the solution value of the target atmospheric parameters according to the flow field information by using the target atmospheric parameter calculation model; the target atmospheric parameters include: airspeed, angle of attack, sideslip angle, static pressure and total temperature.

[0061] Specifically, the microcontroller chip 4 mainly completes the collection, storage, and processing of flow field information. The target atmospheric parameter calculation model 5 is integrated in the microcontroller chip 4, and the airspeed, angle of attack, sideslip angle, static pressure, and total temperature can be solved in real time using the flow field information, and transmitted to the flight control system through a specified communication method. The microcontroller chip 4 used in this application is an STM32H series chip.

[0062] The calculated values ​​of the flow field information and the target atmospheric parameters are stored in the SD card, and the flow field information and the target atmospheric parameters are transmitted to the host computer and the flight control system through the Usart serial port interface and the Can bus interface.

[0063] The microcontroller chip completes the entire process within 10ms, and the system output frequency is 100Hz (the frequency can be adjusted by the clock of the microcontroller chip). The upper limit of the frequency depends on the acquisition frequency of the sensor unit.

[0064] As an optional implementation, Figure 3 As shown, the sensor array 2 includes: N pressure sensing units 201, M temperature sensing units 202 and Q flow rate sensing units 203; N and Q are both positive even numbers greater than 2; M is a positive even number.

[0065] The N pressure sensing units 201 are staggered and distributed along the straight line at equal intervals, the M temperature sensing units 202 are distributed along the straight line, and the Q flow velocity sensing units 203 are staggered and distributed along the straight line at equal intervals.

[0066] Each pressure sensing unit 201 is used to collect pressure.

[0067] Each temperature sensing unit 202 is used to collect temperature.

[0068] Each flow velocity sensing unit 203 is used to collect flow velocity.

[0069] Specifically, the pressure is absolute pressure data, and the flow velocity is vector flow velocity data.

[0070] Taking into account the convenience of system installation in practical applications and the adaptability of the system to different airfoils, this application encapsulates all parts on a flexible substrate circuit board, and finally realizes the design and production of a flexible atmospheric parameter sensing system.

[0071] A total of N pressure sensing units, M temperature sensing units and Q flow rate sensing units are installed on the flexible substrate circuit board. Each sensing unit is connected to the control circuit on the flexible substrate circuit board by patch welding, so that the microcontroller chip can collect the electrical signals of the sensing unit through the control circuit. The redundant number of sensing units can further improve the perception accuracy and reliability. The output signal of each sensing unit is ultimately connected to the microcontroller chip pin through the control circuit. Therefore, the upper limit of the number of sensing units depends on the number of pins of the microcontroller chip and the maximum number of peripherals that can be carried. If the airfoil size is too large, multiple sensing units need to be arranged. The number of microcontroller chips can be increased for distributed collection.

[0072] As an optional implementation, the pressure sensing unit 201 is an absolute pressure sensor, the temperature sensing unit 202 is a temperature sensor, and the flow velocity sensing unit 203 is a vector flow velocity sensor.

[0073] Specifically, the pressure sensing unit is an absolute pressure sensor, which can sense absolute pressure information. The sensing principles include piezoresistive, piezoelectric and capacitive, etc. The present application adopts a piezoresistive absolute pressure sensor. The flow velocity sensing unit is a vector flow velocity sensor, which can sense the vector flow velocity information of the incoming flow (i.e., the size of the flow velocity components in the x and y directions parallel to the sensor plane). The sensing principles include calorimetric and ciliary, etc. The present application adopts a calorimetric flow velocity sensor. The temperature sensing unit is a temperature sensor, which can sense the temperature of the environment. The temperature sensor used in the present application uses a thermistor to sense the temperature. Temperature changes will interfere with the pressure sensing unit and the flow velocity sensing unit. The temperature information can compensate for the drift values ​​generated by the pressure and flow velocity sensing units, reduce the impact of temperature changes on the system, and improve the accuracy of the solution of the target atmospheric parameters in practical applications.

[0074] As an optional implementation, Figure 4 As shown, the flexible atmospheric parameter sensing system is attached to the outer surface of the leading edge of the wing 9; the center line 6 of the area where the sensor array 2 is located is set at the front end position of the wing section of the wing 9.

[0075] The N pressure sensing units 201 , the M temperature sensing units 202 and the Q flow rate sensing units 203 are respectively distributed on both sides of the center line 6 in an axisymmetric manner.

[0076] The minimum spacing between each sensing unit in the sensing array 2 and the center line 6 is greater than a preset spacing, and the preset spacing is twice the width of the pressure sensing unit 201 .

[0077] Specifically, a center line is set in the area where the sensor array is located, and the center line position corresponds to the front end position of the wing section of the wing. The sensor units are arranged on both sides of the center line in an axisymmetric distribution. The pressure sensor units are staggered and distributed at equal intervals along a straight line on one side of the center line, which can reduce the influence of the upstream sensor units on the downstream sensor units; the temperature sensor units are distributed along a straight line on one side of the center line; the flow velocity sensor units are staggered and distributed at equal intervals along a straight line on one side of the center line, which can reduce the influence of the upstream sensor units on the downstream sensor units; the temperature sensor units are distributed along a straight line on one side of the center line.

[0078] As an optional implementation, Figure 5 As shown, a gasket 7 is arranged between each flow velocity sensor unit 203 and the flexible base circuit board 1; the material of the gasket 7 is resin.

[0079] The sum of the thickness of each flow rate sensing unit and the corresponding gasket is equal to the thickness of the pressure sensing unit.

[0080] As an optional implementation, the surface of the flexible base circuit board 1 is covered with a rectifying layer 8 .

[0081] The rectifying layer 8 covers the surface of the microcontroller chip 4 and the control circuit 3 ; the upper surface of the rectifying layer 8 is flush with the upper surface of each pressure sensing unit 201 and each flow rate sensing unit 203 .

[0082] As an optional implementation, the rectifying layer 8 is made of soft glue.

[0083] Specifically, the pressure sensing unit, the temperature sensing unit, the microcontroller chip and the components required in the control circuit are directly attached to the flexible substrate circuit board by using the surface mount welding method.

[0084] Since the flow velocity sensing unit is smaller than the pressure sensing unit in the thickness direction, and considering the consistency of the sensing planes of the pressure sensing unit and the flow velocity sensing unit, a resin material gasket is bonded at the flow velocity sensing unit position, and the flow velocity sensing unit is bonded to the gasket to ensure that the upper surfaces of the flow velocity sensing unit and the pressure sensing unit are located in the same plane. The pins of the flow velocity sensing unit are connected to the flexible substrate circuit board by wire welding.

[0085] After installation and welding, the overall thickness of the system's flexible circuit board is 900um, but the pressure sensing unit, flow rate sensing element and other electronic components on the surface of the flexible base circuit board are protruding, and direct use cannot correctly reflect the pressure and flow rate of the flow field without protrusion interference. At the same time, considering the waterproof and dustproof requirements of the system in actual applications, it is necessary to cover the surface of the flexible base circuit board with a rectifier layer to ensure that the surface of the rectifier layer is consistent with the working surface of the pressure sensing unit and the flow rate sensing unit and is flat. First, draw a three-dimensional model of the rectifier layer according to the size and structure of the flexible base circuit board surface, then use soft glue material 3D printing to form it, and finally bond it to the surface of the flexible base circuit board. The thickness of the final system sensor end is less than 1mm.

[0086] As an optional implementation, the target atmospheric parameter calculation model includes: a first atmospheric parameter calculation model and a second atmospheric parameter calculation model; the first atmospheric parameter calculation model and the second atmospheric parameter calculation model are both obtained by training a back propagation (BP) neural network.

[0087] like Figure 6 As shown, the target atmospheric parameter calculation model is used to determine the solution value of the target atmospheric parameter according to the flow field information, including:

[0088] The corresponding upper and lower wing surface pressure differences are calculated based on the pressures collected by each group of symmetrical pressure sensing units.

[0089] Each flow velocity and each upper and lower wing surface pressure difference are input into the first atmospheric parameter calculation model (ie, atmospheric parameter calculation model 1) to obtain the solution values ​​of the airspeed, the angle of attack, and the sideslip angle.

[0090] The calculated values ​​of each pressure, airspeed, angle of attack and sideslip angle are input into the second atmospheric parameter calculation model (ie atmospheric parameter calculation model 2) to obtain the calculated value of static pressure.

[0091] Each temperature is determined as the solved value of the total temperature.

[0092] As an optional implementation manner, the process of determining the first atmospheric parameter calculation model includes:

[0093] By performing dynamic simulation, wind tunnel test or flight test on the wing model of the UAV, sample values ​​of pressure corresponding to each pressure sensing unit and sample values ​​of flow velocity corresponding to each flow velocity sensing unit at different airspeeds, angles of attack, sideslip angles and static pressures are obtained.

[0094] Based on the sample values ​​of the pressure corresponding to each group of symmetrical pressure sensing units, the sample values ​​of the corresponding upper and lower wing surface pressure differences are calculated.

[0095] Construct a back-propagation neural network.

[0096] The sample values ​​of each flow velocity and the corresponding sample values ​​of the pressure difference between the upper and lower wing surfaces are used as input, and the corresponding airspeed, angle of attack and sideslip angle are used as output, and the back propagation neural network is trained to obtain the first atmospheric parameter calculation model.

[0097] Specifically, the sample values ​​of each flow velocity and the corresponding sample values ​​of the pressure difference between the upper and lower wing surfaces are input, and the corresponding airspeed, angle of attack, and sideslip angle are output, and the back propagation neural network is trained to obtain the first atmospheric parameter calculation model, which includes:

[0098] (1) The sample values ​​of each flow velocity, the sample values ​​of the pressure difference between the upper and lower wing surfaces, the airspeed, the angle of attack, and the sideslip angle of all groups are divided into a sample training data set and a sample test data set.

[0099] (2) Using python or matlab and other software to build a BP neural network, taking the sample values ​​of the pressure difference between the upper and lower wing surfaces and the flow rate in the sample training data set as the input of the BP neural network, taking the corresponding airspeed, angle of attack and sideslip angle as the output of the BP neural network, training is performed to optimize the BP neural network model parameters, and establish a nonlinear mapping relationship between input and output; the training process uses the sample test data set as input to evaluate the performance of the trained BP neural network, and uses the average absolute error between the model output value and the true value as the optimization parameter. If the average absolute error is less than or equal to the preset value, the training of the BP neural network is completed, and the model is output as the first atmospheric parameter calculation model.

[0100] As an optional implementation manner, the process of determining the second atmospheric parameter calculation model includes:

[0101] By performing dynamic simulation, wind tunnel test or flight test on the wing model of the UAV, sample values ​​of the pressure corresponding to each pressure sensing unit under different airspeeds, angles of attack, sideslip angles and static pressures are obtained.

[0102] Construct a back-propagation neural network.

[0103] With the sample values ​​of each pressure and the corresponding airspeed, angle of attack and sideslip angle as input and the corresponding static pressure as output, the back propagation neural network is trained to obtain the second atmospheric parameter calculation model.

[0104] Specifically, the sample values ​​of each pressure and the corresponding airspeed, angle of attack and sideslip angle are used as input, and the corresponding static pressure is used as output, and the back propagation neural network is trained to obtain the second atmospheric parameter calculation model, including:

[0105] (1) Divide the sample values ​​of pressure, airspeed, angle of attack, sideslip angle, and static pressure of all groups into a sample training data set and a sample test data set.

[0106] (2) The sample values ​​of pressure, airspeed, angle of attack, and sideslip angle in the sample training data set are used as the input of the BP neural network, and the corresponding static pressure is used as the output of the BP neural network for training, thereby optimizing the parameters of the BP neural network and establishing a nonlinear mapping relationship between the input and the output. The training process uses the sample test data set as input to evaluate the performance of the trained BP neural network, and uses the average absolute error between the model output value and the true value as the optimization parameter. If the average absolute error is less than or equal to the preset value, the training of the BP neural network is completed, and the model is output as the second atmospheric parameter calculation model.

[0107] like Figure 7 and Figure 8 As shown, the atmospheric parameter solution principle of this application includes:

[0108] The airspeed, angle of attack and sideslip angle are mainly sensed and calculated by the fusion of pressure and flow rate. During the change of airspeed and angle of attack, the distribution of pressure and airflow speed (flow velocity) on the upper and lower surfaces of wing 9 will also change accordingly. The specific change process is: when the angle of attack remains unchanged and the airspeed increases, the flow velocity on the upper and lower surfaces of wing 9 will increase and the pressure will decrease, and vice versa when the airspeed decreases; when the airspeed remains unchanged and the angle of attack increases, the flow velocity on the upper surface of wing 9 will increase and the pressure will decrease, and the flow velocity on the lower surface of wing 9 will decrease and the pressure will increase, and vice versa when the angle of attack decreases. However, considering that in actual application, the change of the flight altitude of the drone will bring about the change of the surface pressure of wing 9, the pressure difference of the upper and lower wing surfaces is made to eliminate the influence of the pressure change caused by the flight altitude. Therefore, the pressure difference and flow velocity of the upper and lower wing surfaces of wing 9 can reflect the changes of airspeed and angle of attack.

[0109] However, in the process of changing the sideslip angle, since the wing 9 is a symmetrical structure in the span direction, the flow field distribution from the wing root to the wing tip is uniform, and the pressure distribution in this direction does not change significantly, it is difficult to solve the sideslip angle. At the same time, the flow velocity on the surface of the wing 9 also does not change significantly, but the flow velocity direction will change. Therefore, the vector velocity sensor can sense the airspeed component V generated by the sideslip angle z The size of further reflects the change of the sideslip angle. Therefore, when there is a sideslip angle, the airspeed component V can be reflected by the pressure difference information of the upper and lower wing surfaces and the vector flow velocity information in the chord length direction. xy and the change of the angle of attack α, the airspeed component V is reflected by the spanwise vector velocity information z and the change of sideslip angle β, the airspeed V can be calculated ∞ , angle of attack α and sideslip angle β. The system uses BP neural network to establish the mapping relationship between sensor unit data and airspeed, angle of attack and sideslip angle.

[0110] After the airspeed, angle of attack and sideslip angle parameters are obtained, the static pressure can be calculated. The pressure distribution equation in the flow model of a blunt body is:

[0111] P θ =q c (cos 2 θ+εsin 2 θ)+P ∞ =q c [ε+(1-ε)cos 2 θ]+P ∞ (1)

[0112] Among them, P θ is the pressure measured at a certain point on the leading edge of the wing 9; q c is the dynamic pressure, ρ is the air density; θ is the airflow incident angle at that point; P ∞ is the static pressure; ε is the shape pressure coefficient.

[0113] The airflow incident angle θ at a certain point can be described as:

[0114] cosθ=cosαcosβcosλ+sinβsinφsinλ+sinαcosβcosφsinλ (2)

[0115] Among them, λ is the position angle; φ is the circumferential angle.

[0116] The position angle λ of a point on a sphere is defined as the angle between the line connecting the point to the center of the sphere and the axis of the machine head; the position angle λ of a point on a blunt body is defined as the angle between the direction of the normal at that point and the axis of the machine head. The circumferential angle φ of the pressure measuring point is defined as the angle between the line connecting the center of the cross-section circle at that point to that point and the vertical line, such as Figure 8 As shown. The circumferential angle φ of the pressure measurement point at the leading edge of the wing 9 can be taken as 0°, then equation (2) becomes:

[0117] cosθ=cosαcosβcosλ+sinαcosβsinλ (3)

[0118] From formula (1) and formula (3), we can know that:

[0119]

[0120] From formula (4), we can know that the static pressure P ∞ The size can be determined by the airspeed V ∞ , angle of attack α, sideslip angle β, pressure P θ , position angle λ and pressure coefficient ε are calculated. Among them, airspeed V ∞ , angle of attack α, sideslip angle β, pressure P θ, position angle λ are known parameters, and the pressure coefficient ε can be obtained through calibration. The system uses BP neural network to establish the airspeed V ∞ , angle of attack α, sideslip angle β, pressure P θ With static pressure P ∞ The mapping relationship is used to calculate the static pressure P ∞ size.

[0121] Furthermore, the system of the present application was also used to conduct tests and verifications in a wind tunnel. During the test phase, the experimental airfoil model used was the NACA 0016-MOD airfoil, and 8 pressure sensing units 201, 4 flow velocity sensing units 203, and 2 temperature sensing units 202 were arranged on the flexible substrate circuit board 1. During the test, five conditions of sideslip angle (0, ±4, ±8) and four conditions of airspeed (12, 18, 22, 28) were set up for a total of 20 groups of experimental conditions. Under each experimental condition, nine angle of attack conditions (0, ±3, ±7, ±11, ±15) were used for verification (bad data were removed). The solution results of airspeed, angle of attack, sideslip angle, and static pressure are shown in the following figure. Figure 9-12 shown.

[0122] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0123] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the system and its core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A flexible atmospheric parameter sensing system, characterized in that: The flexible atmospheric parameter sensing system comprises: a flexible substrate circuit board and a sensor array, a control circuit and a microcontroller chip attached to the flexible substrate circuit board; the target atmospheric parameter calculation model is integrated in the microcontroller chip; The sensor array is used to collect flow field information, and under the control of the control circuit, the flow field information is sent to the microcontroller chip through the flexible substrate circuit board; the flow field information includes: pressure, temperature and flow velocity; The microcontroller chip is used to determine the solution value of the target atmospheric parameter according to the flow field information by using the target atmospheric parameter calculation model; the target atmospheric parameters include: airspeed, angle of attack, sideslip angle, static pressure and total temperature.

2. The flexible atmospheric parameter sensing system according to claim 1, characterized in that: The sensor array includes: N pressure sensing units, M temperature sensing units and Q flow rate sensing units; N and Q are both positive even numbers greater than 2; M is a positive even number; N pressure sensing units are staggered and distributed at equal intervals along a straight line, M temperature sensing units are staggered and distributed along a straight line, and Q flow velocity sensing units are staggered and distributed at equal intervals along a straight line; Each of the pressure sensing units is used to collect pressure; Each of the temperature sensing units is used to collect temperature; Each of the flow velocity sensing units is used to collect flow velocity.

3. The flexible atmospheric parameter sensing system according to claim 2, characterized in that: The pressure sensing unit is an absolute pressure sensor, the temperature sensing unit is a temperature sensor, and the flow velocity sensing unit is a vector flow velocity sensor.

4. The flexible atmospheric parameter sensing system according to claim 2, characterized in that: The flexible atmospheric parameter sensing system is attached to the outer surface of the leading edge of the wing; the center line of the area where the sensor array is located is set at the front end position of the wing section; N pressure sensing units, M temperature sensing units and Q flow rate sensing units are respectively distributed axially symmetrically on both sides of the center line; The minimum spacing between each sensing unit in the sensing array and the center line is greater than a preset spacing, and the preset spacing is twice the width of the pressure sensing unit.

5. The flexible atmospheric parameter sensing system according to claim 1, characterized in that: A gasket is arranged between each of the flow velocity sensing units and the flexible base circuit board; the material of the gasket is resin; The sum of the thickness of each flow velocity sensing unit and the corresponding gasket is equal to the thickness of the pressure sensing unit.

6. The flexible atmospheric parameter sensing system according to claim 1, characterized in that: The surface of the flexible substrate circuit board is covered with a rectifying layer; The rectifying layer covers the surface of the microcontroller chip and the control circuit; the upper surface of the rectifying layer is flush with the upper surface of each of the pressure sensing units and each of the flow rate sensing units.

7. The flexible atmospheric parameter sensing system according to claim 6, characterized in that: The rectifying layer is made of soft rubber.

8. The flexible atmospheric parameter sensing system according to claim 4, characterized in that: The target atmospheric parameter calculation model includes: a first atmospheric parameter calculation model and a second atmospheric parameter calculation model; the first atmospheric parameter calculation model and the second atmospheric parameter calculation model are both obtained by training a back propagation neural network; Using the target atmospheric parameter calculation model and according to the flow field information, determining the solution value of the target atmospheric parameter includes: Based on the pressure collected by each group of symmetrical pressure sensing units, the corresponding pressure difference between the upper and lower wing surfaces is calculated; Inputting each of the flow velocities and each of the upper and lower wing surface pressure differences into the first atmospheric parameter calculation model to obtain a solution value of the airspeed, a solution value of the angle of attack, and a solution value of the sideslip angle; Inputting the calculated values ​​of the pressure, airspeed, angle of attack and sideslip angle into the second atmospheric parameter calculation model to obtain a calculated value of static pressure; Each of the temperatures is determined as a calculated value of the total temperature.

9. The flexible atmospheric parameter sensing system according to claim 8, characterized in that: The process of determining the first atmospheric parameter calculation model includes: By performing dynamic simulation, wind tunnel test or flight test on the wing model of the UAV, sample values ​​of pressure corresponding to each pressure sensing unit and sample values ​​of flow velocity corresponding to each flow velocity sensing unit at different airspeeds, angles of attack, sideslip angles and static pressures are obtained; Based on the sample values ​​of the pressures corresponding to the groups of symmetrical pressure sensing units, the corresponding sample values ​​of the pressure differences between the upper and lower wing surfaces are calculated; Construct a back-propagation neural network; The back propagation neural network is trained with the sample values ​​of each flow velocity and the corresponding sample values ​​of the pressure difference between the upper and lower wing surfaces as inputs, and the corresponding airspeed, angle of attack, and sideslip angle as outputs to obtain the first atmospheric parameter calculation model.

10. The flexible atmospheric parameter sensing system according to claim 8, characterized in that: The process of determining the second atmospheric parameter calculation model includes: By performing dynamic simulation, wind tunnel test or flight test on the wing model of the UAV, sample values ​​of pressure corresponding to each pressure sensing unit under different airspeeds, angles of attack, sideslip angles and static pressures are obtained; Construct a back-propagation neural network; The back propagation neural network is trained with the sample values ​​of each pressure and the corresponding airspeed, angle of attack and sideslip angle as input and the corresponding static pressure as output to obtain the second atmospheric parameter calculation model.

Images