Design method and system of embedded flight parameter sensing system for blunt airframe

Abstract

The embodiment of the invention provides an embedded flight parameter sensing system design method and system for a blunt airframe, and the method comprises the steps: building a pressure database of six pressure holes in a flight envelope range based on the collected pressure values of the six pressure holes disposed in a specific region of the surface of a blunt front body of an aircraft; based on the pressure database, constructing a neural network model of pressure values and flight parameters of the pressure measuring holes in a flight envelope range, and determining the maximum pressure value and the minimum pressure value of the pressure measuring holes in the flight envelope; comparing the collected pressure values of the pressure measuring holes with the maximum value and the minimum value of the pressure of the corresponding pressure measuring holes, and if the pressure values of all the pressure measuring holes meet the preset range condition, executing the next step; otherwise, the system is invalid; and inputting the pressure value of the pressure measuring hole, which is acquired in real time, into the constructed neural network model, calculating flight parameters, and outputting a result.

Description

Technical Field

[0001] This document relates to the field of flight parameter measurement and control technology, and more particularly to a design method and system for an embedded flight parameter sensing system for a blunt-nosed aircraft. Background Art

[0002] Accurately calculating flight parameters such as Mach number, angle of attack, sideslip angle and free flow static pressure is crucial for real-time control of aircraft. The embedded flight parameter sensing system uses surface pressure data obtained by pressure gauges configured in specific areas of the aircraft surface to reversely model and calculate flight parameters. As a technologically advanced calculation system, the embedded flight parameter sensing system calculates flight parameters by relying on surface pressure obtained by pressure gauges configured in specific areas of the surface. However, the traditional method has strict constraints on pressure gauges, and the stagnation point pressure gauges have a great impact on the calculation accuracy. However, during the project implementation, due to the actual engineering constraints on the leading edge and the side edge, it is impossible to configure pressure gauges at the leading edge stagnation point and the side edge to sense the surface flow pressure; at the same time, due to the harsh flight environment and hardware configuration requirements of high-speed aircraft, the harsh aerodynamic heating environment of the leading edge is not suitable for configuring stagnation point pressure gauges, resulting in a significant reduction in the accuracy of the traditional method of calculating flight parameters based on surface pressure.

[0003] At the same time, the solution system completely placed inside the aircraft, such as the inertial navigation system, cannot reflect the impact of the actual wind speed on flight control. Therefore, the traditional atmospheric data system based on inverse modeling and solution such as stagnation pressure faces severe challenges and is no longer suitable for accurate atmospheric data solution of aircraft. Summary of the invention

[0004] One or more embodiments of this specification provide a design method for an embedded flight parameter sensing system for a blunt-nosed aircraft, including:

[0005] Based on the collected pressure values ​​of six pressure measuring holes set in specific areas on the blunt forebody surface of the aircraft, a pressure database of these six pressure measuring holes within the flight envelope is established;

[0006] Based on the pressure database, a neural network model of pressure values ​​of pressure measuring holes within the flight envelope and flight parameters is constructed to determine the maximum and minimum pressure values ​​of the pressure measuring holes within the flight envelope;

[0007] Compare the collected pressure values ​​of the pressure measuring holes with the maximum and minimum values ​​of the corresponding pressure measuring holes. If the pressure values ​​of all the pressure measuring holes meet the preset range conditions, execute the next step; otherwise, the system fails.

[0008] The pressure values ​​collected in real time from the pressure measuring holes are input into the constructed neural network model to solve the flight parameters and output the results.

[0009] Furthermore, the six pressure measuring holes are arranged in a specific area on the surface of the blunt front body of the aircraft, and the specific configuration method is as follows:

[0010] The six pressure measuring holes p1, p2, p3, p4, p5, and p6 are respectively arranged at two different stations, where:

[0011] The pressure measuring holes p1 and p2 are located at the first station, and the cone angle of the station is less than 45°;

[0012] The pressure measuring holes p3, p4, p5, and p6 are located at the second station, and the cone angle of the station is between 30° and 60°;

[0013] The difference between the cone angles of the first station and the second station is greater than 10°, and the cone angle of the first station is smaller than the cone angle of the second station.

[0014] Furthermore, the neural network model of the pressure values ​​of the pressure measuring holes within the flight envelope and the flight parameters is constructed based on the pressure database as follows:

[0015] By determining the nonlinear relationship between the pressure value of the pressure measuring hole and the flight parameters, a neural network model of the pressure value of the pressure measuring hole and the flight parameters within the flight envelope is constructed, as shown below:

[0016] f_fp=F3(C2F2(C1F1(C0p+B0)+B1)+B2;

[0017] Among them, f_fp is the flight parameter vector determined according to the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; p is the pressure numerical matrix composed of the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; F1, F2, and F3 are the transfer functions between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; C0, C1, and C2 are defined as the weight coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; B0, B1, and B2 are defined as the threshold coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively.

[0018] Furthermore, the cone angle is the angle between the surface normal direction where the pressure measuring hole is located and the longitudinal axis of the blunt-headed front body, and ranges from 0° to 90°.

[0019] One or more embodiments of the present specification provide a design system for an embedded flight parameter sensing system for a blunt-nosed aircraft, including:

[0020] Data acquisition module: used to establish a pressure database of the six pressure measuring holes within the flight envelope based on the collected pressure values ​​of the six pressure measuring holes set in the specific area of ​​the blunt front body surface of the aircraft;

[0021] Model building module: used to build a neural network model of pressure values ​​of pressure measuring holes within the flight envelope and flight parameters based on the pressure database, and determine the maximum and minimum pressure values ​​of the pressure measuring holes within the flight envelope;

[0022] Condition judgment module: used to compare the collected pressure values ​​of the pressure measuring holes with the maximum and minimum values ​​of the corresponding pressure measuring holes. If the pressure values ​​of all pressure measuring holes meet the preset range conditions, parameter solution is performed; otherwise, the system fails;

[0023] Parameter calculation module: It is used to input the pressure values ​​of the pressure measuring holes collected in real time into the constructed neural network model, calculate the flight parameters, and output the results.

[0024] Furthermore, the six pressure measuring holes are arranged in a specific area on the surface of the blunt front body of the aircraft, and the specific configuration method is as follows:

[0025] The six pressure measuring holes p1, p2, p3, p4, p5, and p6 are respectively arranged at two different stations, where:

[0026] The pressure measuring holes p1 and p2 are located at the first station, and the cone angle of the station is less than 45°;

[0027] The pressure measuring holes p3, p4, p5, and p6 are located at the second station, and the cone angle of the station is between 30° and 60°;

[0028] The difference between the cone angles of the first station and the second station is greater than 10°, and the cone angle of the first station is smaller than the cone angle of the second station.

[0029] Furthermore, the model building module is specifically used for:

[0030] By determining the nonlinear relationship between the pressure value of the pressure measuring hole and the flight parameters, a neural network model of the pressure value of the pressure measuring hole and the flight parameters within the flight envelope is constructed, as shown below:

[0031] f_fp=F3(C2F2(C1F1(C0p+B0)+B1)+B2;

[0032] Among them, f_fp is the flight parameter vector determined according to the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; p is the pressure numerical matrix composed of the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; F1, F2, and F3 are the transfer functions between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; C0, C1, and C2 are defined as the weight coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; B0, B1, and B2 are defined as the threshold coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively.

[0033] Furthermore, the cone angle is the angle between the surface normal direction where the pressure measuring hole is located and the longitudinal axis of the blunt-headed front body, and ranges from 0° to 90°.

[0034] One or more embodiments of the present specification provide an electronic device, including:

[0035] processor; and,

[0036] A memory arranged to store computer executable instructions which, when executed, perform the steps of a method for designing an embedded flight parameter sensing system for a blunt-nosed airframe.

[0037] One or more embodiments of the present specification provide a storage medium for storing computer executable instructions, which, when executed, implement the steps of the above-mentioned method for designing an embedded flight parameter sensing system for a blunt-nosed aircraft.

[0038] The embodiment of the present invention solves the technical problem of obtaining high-precision atmospheric data when stationary pressure measuring holes and side edge pressure measuring holes cannot be configured; solves the problem that traditional design methods have strict constraints on the positions of pressure measuring holes, and has strong engineering applicability; has high solution accuracy; and has a wide application speed range, and is suitable for blunt-nosed aircraft in the full speed range of low-speed, sub-speed, transonic, supersonic and hypersonic speeds.

[0039] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0041] Figure 1 A flowchart of a method for designing an embedded flight parameter sensing system for a blunt-nosed aircraft provided for one or more embodiments of this specification;

[0042] Figure 2 A specific flow chart of a design method for an embedded flight parameter sensing system for a blunt-nosed aircraft provided for one or more embodiments of this specification;

[0043] Figure 3 A configuration diagram of pressure taps at different stations used in a design method for an embedded flight parameter sensing system for a blunt-nosed aircraft provided in one or more embodiments of this specification;

[0044] Figure 4 A pressure tap layout diagram of a design method for an embedded flight parameter sensing system for a blunt-nosed aircraft body provided for one or more embodiments of this specification;

[0045] Figure 5 A comparison chart of Mach number, angle of attack and sideslip angle obtained by a design method of an embedded flight parameter sensing system for a blunt-nosed aircraft provided by one or more embodiments of this specification and wind tunnel test values;

[0046] Figure 6 A distribution diagram of the absolute deviations of Mach number, angle of attack and sideslip angle obtained by a design method of an embedded flight parameter sensing system for a blunt-nosed aircraft body provided by one or more embodiments of this specification from wind tunnel test values;

[0047] Figure 7 A schematic diagram of the composition of a design system for an embedded flight parameter sensing system for a blunt-nosed aircraft provided for one or more embodiments of this specification;

[0048] Figure 8 A schematic diagram of the structure of an electronic device provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0049] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the following will be combined with the drawings in one or more embodiments of this specification to clearly and completely describe the technical solutions in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0050] Method Embodiment

[0051] According to an embodiment of the present invention, a design method for an embedded flight parameter sensing system for a blunt-nosed aircraft is provided. Figure 1 A flowchart of a design method for an embedded flight parameter sensing system for a blunt-nosed aircraft provided in one or more embodiments of this specification, such as Figure 1 As shown, the design method of an embedded flight parameter sensing system for a blunt-nosed aircraft according to an embodiment of the present invention specifically includes:

[0052] S1. Based on the collected pressure values ​​of six pressure measuring holes set in specific areas on the blunt forebody surface of the aircraft, a pressure database of these six pressure measuring holes within the flight envelope is established.

[0053] Six pressure measuring holes are arranged in a specific area on the blunt forebody surface of the aircraft, and the pressure measuring holes are defined as pi (i = 1, ..., 6), such as Figure 2 As shown in the figure, the pressure value collected by the pressure measuring hole pi (i = 1, ..., 6) in actual engineering applications is defined as p i (i=1,2,3,...6). The six pressure measuring holes are arranged in a specific area on the blunt front surface of the aircraft, and the specific configuration method is as follows:

[0054] The six pressure measuring holes p1, p2, p3, p4, p5, and p6 are respectively arranged at two different stations, where:

[0055] The pressure measuring holes p1 and p2 are located at the first station, and the cone angle of the station is less than 45°; the pressure measuring holes p3, p4, p5, and p6 are located at the second station, and the cone angle of the station is between 30° and 60°; the difference between the cone angles of the first station and the second station is greater than 10°, and the cone angle of the first station is smaller than that of the second station. The cone angle is the angle between the surface normal direction of the pressure measuring hole and the longitudinal axis of the blunt forebody, ranging from 0° to 90°. Figure 3 , 4 This is a layout diagram of the pressure measuring holes at different stations used in the present invention.

[0056] Numerical modeling was used to establish a pressure database of six pressure measuring holes configured within the flight envelope. The flight envelope refers to the actual flight state range of the aircraft in actual engineering implementation, including the Mach number, angle of attack, sideslip angle and altitude range.

[0057] S2. Based on the pressure database, a neural network model of the pressure values ​​of the pressure measuring holes within the flight envelope and the flight parameters is constructed to determine the maximum and minimum pressure values ​​of the pressure measuring holes within the flight envelope.

[0058] Based on the pressure database, by determining the nonlinear relationship between the pressure values ​​of the pressure measuring holes and the flight parameters, a neural network model of the pressure values ​​of the pressure measuring holes p1, p2, p3, p4, p5, and p6 within the flight envelope and the flight parameters is established. The established nonlinear mapping relationship between the pressure values ​​of the pressure measuring holes and the angle of attack refers to:

[0059] f_fp=F3(C2F2(C1F1(C0p+B0)+B1)+B2;

[0060] Among them, f_fp is the flight parameter vector determined according to the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; p is the pressure numerical matrix composed of the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; F1, F2, and F3 are the transfer functions between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer respectively; the F1 and F2 transfer functions use hyperbolic tangent functions; the F3 transfer function uses a linear function with a slope of 1 and an intercept of 0; C0, C1, and C2 are defined as the weight coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer respectively; B0, B1, and B2 are defined as the threshold coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer respectively. The neural network algorithm structure based on error back propagation adopts a multi-input single-output algorithm structure with double hidden layers to establish a neural network model of the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6 within the flight envelope and flight parameters.

[0061] Determine the maximum value p of the pressure measuring hole pi (i = 1-6) within the flight envelope according to the pressure database i-max (i=1,...6) and minimum value p i-min (i=1,..6).

[0062] S3. Compare the collected pressure values ​​of the pressure measuring holes with the maximum and minimum values ​​of the corresponding pressure measuring holes. If the pressure values ​​of all the pressure measuring holes meet the preset range conditions, execute the next step; otherwise, the system fails.

[0063] The collected p i(i=1,...6) and the maximum value p of each pressure measuring hole pressure i-max (i=1,...6) and minimum value p i-min (i=1,...6) comparison, determine p i (i=1,...6) whether the preset condition is met, the preset condition is p i-min ≤p i ≤p i-max (i=1,...6). If satisfied, execute step S4, if not satisfied, the system fails.

[0064] S4. Input the pressure values ​​of the pressure measuring holes collected in real time into the constructed neural network model, calculate the flight parameters, and output the results.

[0065] Figure 5 A comparison chart of the Mach number, angle of attack and sideslip angle obtained by the design method of the present invention and the values ​​obtained by wind tunnel test; Figure 6 This is a distribution diagram of absolute deviations between the Mach number, angle of attack and sideslip angle obtained by the design method of the present invention and the wind tunnel test values; it can be seen from the figure that the Mach number, angle of attack and sideslip angle obtained by the design method of the present invention are in good agreement with the wind tunnel test values, and the actual error distribution is small.

[0066] The beneficial effects of the present invention are as follows:

[0067] The technical difficulty of obtaining high-precision atmospheric data when stagnation pressure measuring holes and side edge pressure measuring holes cannot be configured is solved; the traditional solution method is highly dependent on the stagnation pressure, and the traditional solution method fails when there is no stagnation pressure. The design method of the present invention significantly enhances the feasibility of system engineering; the problem that the traditional design method has strict constraints on the position of the pressure measuring holes is solved, the pressure measuring hole configuration constraints are wide, and the engineering applicability is strong; the solution accuracy is high, and the influence of wind speed on the aerodynamic performance of the aircraft can be reflected in real time. Compared with the traditional fully built-in technology, the accuracy is higher; the application speed range is wide, and it is suitable for low-speed, sub-, transonic, supersonic and hypersonic blunt-nosed aircraft in the full speed range.

[0068] System Example

[0069] According to an embodiment of the present invention, a design system for an embedded flight parameter sensing system for a blunt-nosed aircraft is provided. Figure 7 A schematic diagram of a design system for an embedded flight parameter sensing system for a blunt-nosed aircraft provided in one or more embodiments of this specification, such as Figure 7 As shown, the embedded flight parameter sensing system design system for a blunt-nosed aircraft according to an embodiment of the present invention specifically includes:

[0070] The data acquisition module 70 is used to establish a pressure database of the six pressure measuring holes set in a specific area of ​​the blunt front body surface of the aircraft based on the collected pressure values ​​of the six pressure measuring holes.

[0071] The six pressure measuring holes are arranged in a specific area on the surface of the blunt front body of the aircraft, and the specific configuration method is as follows:

[0072] The six pressure measuring holes p1, p2, p3, p4, p5, and p6 are respectively arranged at two different stations, where:

[0073] The pressure measuring holes p1 and p2 are located at the first station, and the cone angle of the station is less than 45°;

[0074] The pressure measuring holes p3, p4, p5, and p6 are located at the second station, and the cone angle of the station is between 30° and 60°;

[0075] The difference between the cone angles of the first station and the second station is greater than 10°, and the cone angle of the first station is smaller than the cone angle of the second station.

[0076] The cone angle is the angle between the surface normal direction of the pressure measuring hole and the longitudinal axis of the blunt-headed front body, and ranges from 0° to 90°.

[0077] Model building module 72: used to build a neural network model of the pressure values ​​of the pressure measuring holes within the flight envelope and the flight parameters based on the pressure database, and determine the maximum and minimum pressure values ​​of the pressure measuring holes within the flight envelope.

[0078] The model building module 72 is specifically used for:

[0079] By determining the nonlinear relationship between the pressure value of the pressure measuring hole and the flight parameters, a neural network model of the pressure value of the pressure measuring hole and the flight parameters within the flight envelope is constructed, as shown below:

[0080] f_fp=F3(C2F2(C1F1(C0p+B0)+B1)+B2;

[0081] Among them, f_fp is the flight parameter vector determined according to the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; p is the pressure numerical matrix composed of the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; F1, F2, and F3 are the transfer functions between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; C0, C1, and C2 are defined as the weight coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; B0, B1, and B2 are defined as the threshold coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively.

[0082] Condition judgment module 74: used to compare the collected pressure values ​​of the pressure measuring holes with the maximum and minimum values ​​of the corresponding pressure measuring holes. If the pressure values ​​of all the pressure measuring holes meet the preset range conditions, parameter solution is performed; otherwise, the system fails;

[0083] Parameter solving module 76: used to input the pressure values ​​of the pressure measuring holes collected in real time into the constructed neural network model, solve the flight parameters, and output the results.

[0084] The embodiment of the present invention is a system embodiment corresponding to the above-mentioned method embodiment. The specific operations of each module can be understood by referring to the description of the method embodiment, which will not be repeated here.

[0085] Device Example 1

[0086] An embodiment of the present invention provides an electronic device, such as Figure 8 As shown, it includes: a memory 80, a processor 82, and a computer program stored in the memory 80 and executable on the processor 82. When the computer program is executed by the processor 82, the following method steps are implemented:

[0087] S1. Based on the collected pressure values ​​of six pressure measuring holes set in specific areas of the blunt forebody surface of the aircraft, a pressure database of the six pressure measuring holes within the flight envelope is established;

[0088] S2. Based on the pressure database, a neural network model of the pressure values ​​of the pressure measuring holes within the flight envelope and the flight parameters is constructed to determine the maximum and minimum pressure values ​​of the pressure measuring holes within the flight envelope;

[0089] S3. Compare the collected pressure values ​​of the pressure measuring holes with the maximum and minimum values ​​of the corresponding pressure measuring holes. If the pressure values ​​of all the pressure measuring holes meet the preset range conditions, execute the next step; otherwise, the system fails;

[0090] S4. Input the pressure values ​​of the pressure measuring holes collected in real time into the constructed neural network model, calculate the flight parameters, and output the results.

[0091] Device Example 2

[0092] An embodiment of the present invention provides a computer-readable storage medium, on which a program for implementing information transmission is stored. When the program is executed by the processor 82, the following method steps are implemented:

[0093] S1. Based on the collected pressure values ​​of six pressure measuring holes set in specific areas of the blunt forebody surface of the aircraft, a pressure database of the six pressure measuring holes within the flight envelope is established;

[0094] S2. Based on the pressure database, a neural network model of the pressure values ​​of the pressure measuring holes within the flight envelope and the flight parameters is constructed to determine the maximum and minimum pressure values ​​of the pressure measuring holes within the flight envelope;

[0095] S3. Compare the collected pressure values ​​of the pressure measuring holes with the maximum and minimum values ​​of the corresponding pressure measuring holes. If the pressure values ​​of all the pressure measuring holes meet the preset range conditions, execute the next step; otherwise, the system fails;

[0096] S4. Input the pressure values ​​of the pressure measuring holes collected in real time into the constructed neural network model, calculate the flight parameters, and output the results.

[0097] The computer-readable storage medium in this embodiment includes, but is not limited to, ROM, RAM, magnetic disk or optical disk, etc.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A design method for an embedded flight parameter sensing system for a blunt-nosed aircraft, characterized in that: include: Based on the collected pressure values ​​of six pressure measuring holes set in specific areas on the blunt forebody surface of the aircraft, a pressure database of these six pressure measuring holes within the flight envelope is established; Based on the pressure database, a neural network model of pressure values ​​of pressure measuring holes within the flight envelope and flight parameters is constructed to determine the maximum and minimum pressure values ​​of the pressure measuring holes within the flight envelope; Compare the collected pressure values ​​of the pressure measuring holes with the maximum and minimum values ​​of the corresponding pressure measuring holes. If the pressure values ​​of all the pressure measuring holes meet the preset range conditions, execute the next step; otherwise, the system fails. The pressure values ​​collected in real time from the pressure measuring holes are input into the constructed neural network model to solve the flight parameters and output the results.

2. The method according to claim 1, characterized in that The six pressure measuring holes are arranged in a specific area on the surface of the blunt front body of the aircraft, and the specific configuration method is as follows: The six pressure measuring holes p1, p2, p3, p4, p5, and p6 are respectively arranged at two different stations, where: The pressure measuring holes p1 and p2 are located at the first station, and the cone angle of the station is less than 45°; The pressure measuring holes p3, p4, p5, and p6 are located at the second station, and the cone angle of the station is between 30° and 60°; The difference between the cone angles of the first station and the second station is greater than 10°, and the cone angle of the first station is smaller than the cone angle of the second station.

3. The method according to claim 1, characterized in that The neural network model of the pressure value of the pressure measuring hole within the flight envelope and the flight parameters is constructed based on the pressure database as follows: By determining the nonlinear relationship between the pressure value of the pressure measuring hole and the flight parameters, a neural network model of the pressure value of the pressure measuring hole and the flight parameters within the flight envelope is constructed, as shown below: f_fp=F3(C2F2(C1F1(C0p+B0)+B1)+B2; Among them, f_fp is the flight parameter vector determined according to the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; p is the pressure numerical matrix composed of the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; F1, F2, and F3 are the transfer functions between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; C0, C1, and C2 are defined as the weight coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; B0, B1, and B2 are defined as the threshold coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively.

4. The method according to claim 1, characterized in that: The cone angle is the angle between the surface normal direction of the pressure measuring hole and the longitudinal axis of the blunt-headed front body, and ranges from 0° to 90°.

5. An embedded flight parameter sensing system design system for a blunt-nosed aircraft, characterized in that: include: Data acquisition module: used to establish a pressure database of the six pressure measuring holes within the flight envelope based on the collected pressure values ​​of the six pressure measuring holes set in the specific area of ​​the blunt front body surface of the aircraft; Model building module: used to build a neural network model of pressure values ​​of pressure measuring holes within the flight envelope and flight parameters based on the pressure database, and determine the maximum and minimum pressure values ​​of the pressure measuring holes within the flight envelope; Condition judgment module: used to compare the pressure values ​​of the collected pressure measuring holes with the maximum and minimum values ​​of the corresponding pressure measuring holes. If the pressure values ​​of all pressure measuring holes meet the preset range conditions, parameter solution is performed; otherwise, the system fails; Parameter calculation module: It is used to input the pressure values ​​of the pressure measuring holes collected in real time into the constructed neural network model, calculate the flight parameters, and output the results.

6. The system according to claim 5, characterized in that The six pressure measuring holes are arranged in a specific area on the surface of the blunt front body of the aircraft, and the specific configuration method is as follows: The six pressure measuring holes p1, p2, p3, p4, p5, and p6 are respectively arranged at two different stations, where: The pressure measuring holes p1 and p2 are located at the first station, and the cone angle of the station is less than 45°; The pressure measuring holes p3, p4, p5, and p6 are located at the second station, and the cone angle of the station is between 30° and 60°; The difference between the cone angles of the first station and the second station is greater than 10°, and the cone angle of the first station is smaller than the cone angle of the second station.

7. The system according to claim 5, characterized in that The model building module is specifically used for: By determining the nonlinear relationship between the pressure value of the pressure measuring hole and the flight parameters, a neural network model of the pressure value of the pressure measuring hole and the flight parameters within the flight envelope is constructed, as shown below: f_fp=F3(C2F2(C1F1(C0p+B0)+B1)+B2; Among them, f_fp is the flight parameter vector determined according to the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; p is the pressure numerical matrix composed of the pressure values ​​of pressure measuring holes p1, p2, p3, p4, p5, and p6; F1, F2, and F3 are the transfer functions between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; C0, C1, and C2 are defined as the weight coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively; B0, B1, and B2 are defined as the threshold coefficient matrices between the first hidden layer and the input layer, the second hidden layer and the first hidden layer, and the output layer and the second hidden layer, respectively.

8. The system according to claim 5, characterized in that The cone angle is the angle between the surface normal direction of the pressure measuring hole and the longitudinal axis of the blunt-headed front body, and ranges from 0° to 90°.

9. An electronic device, characterized in that: include: processor; as well as, A memory arranged to store computer executable instructions, which, when executed, cause the processor to implement the steps of the method for designing an embedded flight parameter sensing system for a blunt-nosed airframe as claimed in any one of claims 1 to 4.

10. A storage medium, characterized in that: Used to store computer executable instructions, which, when executed, implement the steps of the method for designing an embedded flight parameter sensing system for a blunt-nosed aircraft as described in any one of claims 1 to 4.

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