Dropping parachute drag coefficient rapid identification method and system based on low-altitude drop of unmanned aerial vehicle

Abstract

The application discloses a parachute resistance coefficient rapid identification method and system based on unmanned aerial vehicle low-altitude dropping, wherein the parachute is released by the unmanned aerial vehicle from 100m to 300m in height, only basic parameters such as height, falling time and inflation time need to be collected, and the low-cost and high-efficiency determination of the resistance coefficient is realized by combining a segmented time-varying resistance characteristic model, a parachute air-drop dynamics equation and a simulated annealing algorithm. Compared with a traditional method, the test cost of the method is reduced by more than 90%, the single test cycle is less than 2 hours, and no precise sensor is needed on the parachute, and the method is particularly suitable for the rapid iteration verification scene of parachute development.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of parachute aerodynamic performance testing, and particularly relates to a parachute drag coefficient rapid identification method and system based on unmanned aerial vehicle low-altitude release. BACKGROUND

[0002] The parachute drag coefficient is a key parameter for characterizing the aerodynamic performance, predicting the descent trajectory and landing speed of a parachute, and determining the parameter is crucial for the recovery system in the field of aerospace, air-dropped equipment and the development of special parachutes. The traditional parachute drag coefficient determination method has significant defects:

[0003] 1) Wind tunnel test method:

[0004] High cost, high Reynolds number simulation energy consumption is large; the real air-drop dynamic process (such as parachute cloth inflation oscillation) cannot be reproduced, and the measurement deviation is greater than 15%; the sensor is damaged at high speed airflow.

[0005] 2) High-altitude air-drop test method:

[0006] Dependence on manned aircraft, high cost, long airspace approval period, need for parachute-carrying precision sensors, high parachute impact damage rate, poor weather adaptability, and long data processing time. SUMMARY

[0007] The purpose of the present application is to provide a parachute drag coefficient rapid identification method and system based on unmanned aerial vehicle low-altitude release, which is suitable for low-cost and efficient testing scenarios in the development and small-batch production verification of parachutes.

[0008] The technical solution for achieving the purpose of the present application is as follows: in the first aspect, the present application provides a parachute drag coefficient rapid identification method based on unmanned aerial vehicle low-altitude release, comprising:

[0009] S1: measuring the nominal area of the parachute cloth, the mass of the parachute cloth and the mass of the load before air-drop, and synchronously collecting the release height, the total falling time and the inflation time by remote control release after the unmanned aerial vehicle hangs the parachute to the target height during air-drop;

[0010] S2: constructing a parachute air-drop dynamics equation and a time-varying resistance characteristic model;

[0011] S3: taking the target function Minimization as the criterion, using the simulated annealing algorithm to set the initial iteration value of the prior estimate to solve the optimal solution ; wherein: is the parameter to be identified, is the parachute drag coefficient, is the maximum value of the projection area A of the parachute caused by the full inflation of the parachute. The objective function for identification is H; the drop height of the same parachute under different airdrop experiments is H, where the subscript i indicates the result of the i-th experiment, N indicates the total number of experiments, i=1,2,…,N; and h is the height calculated by the parachute airdrop dynamics equation.

[0012] S4: Calculate the drag coefficient , The nominal area of ​​the umbrella canopy, and based on the final identification value. Assess the reliability of identification, if If the value exceeds the set threshold, adjust the time-varying resistance characteristic model in step S2.

[0013] Furthermore, in step S1, the target height is 100m to 300m.

[0014] Furthermore, in step S1, the inflation time is obtained by video analysis at the moment when the canopy is fully deployed. The moment when the canopy is fully deployed is defined as the first frame of the canopy when the edge tension is released and there are no wrinkles.

[0015] Furthermore, in step S2, the parachute and its load will be subject to gravity and atmospheric drag during descent. The parachute drop dynamics equations are established as follows:

[0016] ;

[0017] In the formula: This refers to the parachute descent distance. This refers to the parachute descent time; It is the acceleration due to gravity; The local atmospheric density is determined by... Calculate, where: , These are the air pressure and Kelvin temperature from the local weather station in real time, respectively, R=287 m² / s² / K; The drag characteristic is time-varying, a function that changes with time and remains at its maximum value after the parachute is fully inflated. This maximum value is also the value to be identified (the essence of time-varying drag characteristics is to treat the umbrella's drag coefficient as constant, while the projected area...). As a function that varies with time, to facilitate obtaining the drag of the umbrella in the experiment, the drag coefficient multiplied by the projected area is considered as a whole (the drag characteristic obtained by multiplying the drag coefficient by the projected area). For the quality of the umbrella canopy; Let the load be the mass; the initial condition is that the parachute moves a distance h = 0 m, and the first derivative of the parachute's distance (the parachute's velocity) is given. (0) = 0 m / s, set the total time for the umbrella to land in each experiment. This represents the total time spent on the integration process.

[0018] For time-varying resistance characteristics, when the canopy is not full, i.e. :

[0019]

[0020] In the formula: k is the ratio of the projected area of the parachute in the retracted state to the projected area of the parachute in the full state, t m is the inflation time;

[0021] When the parachute canopy is full, i.e. :

[0022]

[0023] Further, in step S3, when the optimal solution touches the boundary, the boundary is automatically expanded to [0.5 , 1.5 ] and the optimization is restarted, C d A0 is the pre-estimated C d A m initial iteration value.

[0024] Further, in accordance with the final recognition value obtained according to the simulated annealing algorithm, the recognition reliability is evaluated, the smaller the reliability is, the higher the reliability is, m 2 , it is determined as a high confidence result, and N is the total number of experiments; if m 2 , a power function inflation model is used: , in which: is an empirical coefficient of the parachute inflation shape, and n is an inflation index coefficient of the parachute.

[0025] In a second aspect, the present application provides an unmanned aerial vehicle air-drop system for implementing the parachute drag coefficient fast identification method based on unmanned aerial vehicle low-altitude drop of the first aspect, the system comprising:

[0026] Load-carrying unmanned aerial vehicle: as a carrying platform of the entire system, flies to a predetermined target height;

[0027] Automatic throwing device: contains a release mechanism controlled by a solenoid valve or a rudder, and is rigidly connected below the fuselage of the load-carrying unmanned aerial vehicle through a mechanical interface;

[0028] Connecting rotating shaft: the connecting rotating shaft allows the parachute to rotate freely after being released, and the upper end is directly connected with the release hook of the automatic throwing device, and the lower end is connected with the main parachute through a connecting belt;

[0029] Main parachute: as the test object, mounted under the connecting rotating shaft by connecting belt;

[0030] Load: help the parachute fill quickly by gravity, connected with the main parachute through the connecting ring at the top;

[0031] Remote controller of throwing device: control the opening and closing of the automatic throwing device through wireless signals;

[0032] Data acquisition unit: including the flight control system of the unmanned aerial vehicle, the ground stopwatch and the high-speed camera equipment, respectively used for recording the release height, the total falling time and recording the video.

[0033] In a third aspect, the present application provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect when executing the program.

[0034] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, wherein the program is executed by a processor to implement the steps of the method of the first aspect.

[0035] In a fifth aspect, the present application provides a computer program product, comprising a computer program, wherein the computer program is executed by a processor to implement the steps of the method of the first aspect.

[0036] Compared with the prior art, the present application has the following advantages: by mounting the parachute on the unmanned aerial vehicle and releasing it at a height of 100m-300m, only basic parameters such as height, falling time and inflation time need to be collected, and a segmented time-varying resistance characteristic model and a self-adaptive simulated annealing algorithm are combined to realize low-cost and high-efficiency determination of the resistance coefficient; compared with the traditional method, the cost is reduced to 10% of the traditional method by low-altitude release of the unmanned aerial vehicle; the risk of damage to the sensor equipment on the parachute is avoided; the whole process test is completed within 2 hours. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 The figure is the overall idea diagram of the present application.

[0038] Figure 2 The figure is the schematic diagram of the parachute unmanned aerial vehicle air-drop experimental device.

[0039] Figure 3 The figure is the parachute resistance coefficient identification flowchart based on the simulated annealing algorithm. DETAILED DESCRIPTION

[0040] In order to overcome the shortcomings of the prior art, the present application provides a parachute resistance coefficient fast identification method based on low-altitude release of an unmanned aerial vehicle, which combines Figure 1 The steps of the method of the present application are as follows:

[0041] Step 1: UAV air-drop system setup, experimental data acquisition:

[0042] (1) The setup of the UAV air-drop experimental platform is physically connected according to the logic shown in Figure 2 . First, the automatic throwing device is rigidly fixed to the under-hanging interface of the load-carrying UAV. Then, the main parachute, which is pre-deployed according to the specification, is directly mounted on the release mechanism of the automatic throwing device through a connecting belt. At the end of the main parachute rope, a rotating shaft is connected to the lower load, which is a key component to ensure the uncoiled deployment of the parachute rope. Finally, a wireless control link is established between the ground remote controller and the automatic throwing device, thus forming a complete "UAV-throwing device-main parachute-load" vertical experimental system from top to bottom.

[0043] The UAV air-drop system of the present application comprises:

[0044] Load-carrying UAV: as the carrying platform of the entire system, it flies to the predetermined target height;

[0045] Automatic throwing device: contains a release mechanism controlled by a solenoid valve or a rudder, which is rigidly connected to the underside of the UAV's fuselage through a mechanical interface (such as a quick-release plate);

[0046] Connecting rotating shaft: this rotating shaft allows the parachute to rotate freely after release, and is a key component to avoid entanglement of the parachute rope. The upper end is directly connected to the release hook of the automatic throwing device, and the lower end is connected to the main parachute through a connecting belt;

[0047] Main parachute: test object, mounted on the connecting rotating shaft through a connecting belt;

[0048] Load: helps the parachute to fill quickly through gravity, and is connected to the end of the main parachute rope through a connecting ring at the top;

[0049] Throwing device remote controller: held by the ground operator, controls the opening and closing of the automatic throwing device through wireless signals.

[0050] Data acquisition unit: includes the flight control system of the UAV (records the height ), a ground stopwatch (records the total time ), and a high-speed camera device (records video for subsequent analysis of inflation time ).

[0051] (2) Air-drop execution: after controlling the UAV to climb to the target height H (100m ≤ H ≤ 300m), the automatic throwing device is remotely triggered to release the parachute, and the timer is started simultaneously.

[0052] (3) Record the nominal projected area design value of the canopy before air-drop and the umbrella mass is accurately weighed by an electronic scale and the load mass The weighing accuracy is ±0.01 kg. The release height data is obtained and recorded in real time by the UAV flight control system during the parachute drop , with an accuracy controlled within ±0.5 meters; the time from release to landing of a single experimental parachute is measured using an electronic timer , with an accuracy error less than 0.1 seconds; the critical moment of complete unfolding of the canopy is determined by manually analyzing the falling process video taken by a ground camera as the inflation time , with a time resolution of 0.05 seconds; the parameters to be obtained are shown in Table 1.

[0053] Table 1 Parameter acquisition table

[0054]

[0055] Step 2: Kinetic modeling of the parachute and definition of time-varying resistance

[0056] (1) The parachute and its load will be subjected to gravity and atmospheric resistance during descent, and the parachute air-drop dynamics equation is established as follows:

[0057]

[0058] In the formula: is the parachute descent distance; is the acceleration of gravity; is the local atmospheric density, calculated by , in which: , are the real-time data of pressure and Kelvin temperature of the local weather station, respectively, and R = 287 m² / s² / K; is the resistance characteristic, which is a function of time, and remains at the maximum value after the parachute is full, which is also the value to be identified; the initial conditions are set as parachute movement distance h = 0 m, first-order derivative of parachute movement distance (parachute speed) (0) = 0 m / s, and the total parachute landing time of each experiment is set as the integration length; the remaining symbols are explained in Table 1.

[0059] (2) is the time-varying resistance, which is: when not full,

[0060]

[0061] In the formula: k is the ratio of the projected area of ​​the parachute in its uninflated state to the projected area of ​​the parachute in its fully inflated state, which is generally between 0.1 and 0.2 and can be obtained through experimental measurement.

[0062] When the parachute is fully charged ( ):

[0063]

[0064] Step 3: Identify the resistance characteristics using the parameters obtained in Step 1. The specific flowchart is as follows: Figure 3 As shown: (1) The target function for identification Let H be the parachute drop height H in this experiment, and the height H using the parameters to be identified. And the known time of the parachute drop Inflation time The sum of squares of the differences in descent distance h obtained by solving the parachute drop dynamics equations is expressed as follows:

[0065] (i=1,2,…,N)

[0066] In the formula: the subscript i represents the result of the i-th experiment, and N represents the total number of experiments.

[0067] (2) Parameter identification is performed using the simulated annealing algorithm. Given initial values ​​for iteration... This value is the pre-estimated resistance characteristic C. d A m The initial iteration value; the boundary is set to [0.7]. 1.3 ]; Based on the change value of the objective function According to the Metropolis criterion, accepting / rejecting new solutions reduces the J value, and convergence conditions are set. If the final iterative value is on the boundary, the boundary value can be appropriately increased to [0.5]. 1.5 ].

[0068] Step 4: Output and Verification of Identification Results:

[0069] (1) Calculation of drag coefficient: ,in These are the identified resistance characteristics. This refers to the nominal area of ​​the parachute.

[0070] (2) Based on the final identification value Assess the reliability of identification. It should not exceed 20N (N is the experimental parameter involved in the identification). If it is larger, the ratio k of the projected area of the parachute in the stowed state to the projected area of the parachute in the fully inflated state in step 2 can be adjusted appropriately, or a power function inflation model can be used: , wherein is an empirical coefficient of the parachute inflation shape, and is generally 0.6-1.0, and n is an inflation index coefficient of the parachute, and is generally 2.0-3.0.

[0071] The application will be further described below in combination with the drawings and examples.

[0072] Example

[0073] The method provided in this example is a method for quickly identifying the drag coefficient of a parachute based on low-altitude release of a UAV, and a block diagram of the method is shown in Figure 1 . The method is used to quickly obtain the drag coefficient of a parachute based on low-altitude release of a UAV, and the experimental parameters obtained in the experiment are used as an example. The specific implementation method includes the following steps:

[0074] Step 1: UAV aerial delivery system construction, acquisition of experimental data:

[0075] (1) In a test site in Nanping, Fujian Province, a DJI UAV is used to carry a 50 kg sandbag and a parachute with a nominal area of 3.1 m 2 . The parachute rope is connected to the rotating shaft through an on-board quick-release hook to ensure that there is no risk of entanglement. The canopy mass m s = 7.4 kg (measured by an electronic scale), and the load mass m w = 50.0 kg (verified by an electronic scale).

[0076] (2) The UAV is controlled to vertically climb to a height of 116.9, 145.3, 174.9, 116.5, and 173 meters (the flight control system displays the altitude in real time, with an accuracy of ±0.3 meters), and the remote control trigger releases the parachute. The stopwatch function is activated to record the falling time, and a Sony camera (60 fps frame rate) is used to record the entire falling process.

[0077] (3) The canopy is fully deployed in 2.48, 2.88, 1.81, 0.60, and 2.10 seconds after being released in the previous five experiments (the video is identified frame by frame to identify the tension release moment of the canopy edge), and the load is in 8.20, 9.76, 12.00, 8.43, and 12.27 seconds. The stopwatch stops when it touches the ground. The final recorded parameters are shown in Table 2:

[0078] Table 2: Data obtained from five aerial delivery parachutes

[0079]

[0080] Step 2: Dynamic model construction

[0081] (1) Establish the parachute air-drop dynamics equation, define the time-varying resistance characteristic function. The specific modeling process is: the parachute inflation process is divided into two stages, in the 0 second to the full transition period recorded in Table 2, the resistance characteristic increases linearly from the initial value 0.177× to (the initial area ratio k is 0.177; after 2.3 seconds, it enters the stable stage and remains constant value). The data of 5 experiments and the parachute and load mass obtained in step 1 are substituted into the parachute air-drop dynamics equation:

[0082]

[0083] where: air density =1.17 kg / m³, calculated from , where , are the real-time data of the local weather station pressure 997 hPa and temperature 297 K, R=287 m² / s² / K, the initial condition is set as parachute moving distance h=0 m, parachute moving distance first derivative (parachute speed) (0)=0 m / s, set the total time t l of each experiment as the integral time length; weight acceleration g=9.8 m / s 2 .

[0084] Step 3: Parameter identification optimization implementation

[0085] Start the simulated annealing algorithm to solve the optimal resistance characteristic. Initialize the parameter =1.0×3.1=3.10, boundary range [2.17, 4.03] (corresponding to 0.7A0 to 1.3A0). During the algorithm iteration process, when the trial solution =3.914, the objective function value is minimum: =31.595, the identification process detects that the optimal solution does not touch the boundary, and directly outputs the result.

[0086] Step 4: Result output and verification implementation

[0087] Given that the nominal area of the parachute is 3.1 m 2 , calculate the normalized drag coefficient: C d =3.914 / 3.1=1.2625. According to the objective function value 31.595 m², it is determined as a high confidence result (less than 5×20=100 m²), and the model does not need to be replaced. The final test report includes: parachute type specification, air-drop height, falling time, identified drag coefficient, precision evaluation level. Related video files and original data are stored in the test database for subsequent batch comparison and analysis.

[0088] The above description is only the preferred embodiment of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application.

Claims

1. A method for quickly identifying a drag coefficient of a parachute based on low-altitude dropping of a UAV, characterized in that, Includes the following steps: S1: Before airdrop, measure the nominal area, mass and load capacity of the parachute canopy. During airdrop, the drone carries the parachute to the target altitude and then remotely releases it, simultaneously collecting the release altitude, total descent time and inflation time. S2: Construct the parachute airdrop dynamics equations and time-varying drag characteristic model; The parachute and its payload are subject to gravity and atmospheric drag during descent. The dynamic equations for parachute airdrop are as follows: ； In the formula, For parachute descent time, It is the acceleration due to gravity; The local atmospheric density is determined by... Calculate, , These are the air pressure and Kelvin temperature from the local weather station in real time, respectively, R=287 m² / s² / K; The drag characteristic is time-varying, a function that changes with time and remains at its maximum value after the parachute is fully inflated. This maximum value is also the value to be identified; For the quality of the umbrella canopy, Let the load be the mass; initial conditions: the parachute moves a distance h = 0 m, and the parachute's speed is... (0) = 0 m / s, set the total time for the umbrella to land in each experiment. Total time for integration; This exhibits time-varying drag characteristics; when the canopy is not fully inflated, i.e. : ； where k is the ratio of the projected area of the parachute in the stowed condition to the projected area of the parachute in the fully inflated condition, t m is the inflation time; When the parachute canopy is fully inflated, that is... : ； S3: Using the objective function Using minimization as the criterion, the simulated annealing algorithm is used to set a pre-estimated value. initial iteration value Find the optimal solution ;in: For the parameters to be identified, This is the parachute drag coefficient. Let A be the maximum value of the parachute's projected area as it is fully inflated. The objective function for identification is H; the drop height of the same parachute under different airdrop experiments is H, where the subscript i indicates the result of the i-th experiment, N indicates the total number of experiments, i=1,2,…,N; and h is the height calculated by the parachute airdrop dynamics equation. S4: Calculate the drag coefficient , The nominal area of ​​the umbrella canopy, and based on the final identification value. Assess the reliability of identification, if If the value exceeds the set threshold, adjust the time-varying resistance characteristic model in step S2.

2. The method according to claim 1, characterized in that, In step S1, the target height is 100m to 300m.

3. The method according to claim 1, characterized in that, In step S1, the inflation time is obtained by video analysis at the moment when the canopy is fully deployed. The moment when the canopy is fully deployed is defined as the first frame of the canopy when the edge tension is released and there are no wrinkles.

4. The method according to claim 1, characterized in that, In step S3, when the optimal solution When the boundary is reached, the boundary is automatically expanded to [0.5]. 1.5 ], and restarted optimization, C d A0 is the pre-estimated C. d A m Initial iteration value.

5. The method according to claim 1, characterized in that, The final identification value obtained based on the simulated annealing algorithm Assess the reliability of identification. The smaller the value, the higher the reliability. m 2 If it is, then it is judged as a high-confidence result; if m 2 The power function inflation model is adopted: , is the empirical coefficient for the parachute inflation shape, and n is the parachute inflation index coefficient.

6. A drone airdrop system for implementing the rapid identification method for parachute drag coefficient based on low-altitude drone drop as described in any one of claims 1 to 5, characterized in that, The system includes: Heavy-duty drones: serving as the transport platform for the entire system, flying to the predetermined target altitude; Automatic throwing device: includes a release mechanism controlled by a solenoid valve or servo motor, which is rigidly connected to the underside of the fuselage of the heavy-duty UAV via a mechanical interface; Connecting rotating shaft: This connecting rotating shaft allows the parachute to rotate freely after release. The upper end is directly connected to the release hook of the automatic throwing device, and the lower end is connected to the main parachute via a connecting strap. Main umbrella: As a test object, it is attached to the connecting rotation axis via a connecting strap; Load: It helps the parachute fill up quickly through gravity and is connected to the end of the main parachute lines through a connecting ring at the top; Remote control for the throwing device: Controls the automatic throwing device to open and close via wireless signal; Data acquisition unit: includes the drone's flight control system, ground stopwatch, and high-speed camera equipment, used to record release altitude, total descent time, and video recording, respectively.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1-5.

9. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method described in any one of claims 1-5.

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