Method and system for determining the number of flight opening tests of a drone parachute

Abstract

This invention discloses a method and system for determining the number of parachute deployment tests for a drone. The method includes: determining the maximum speed of the drone after a loss of control and fall without a parachute and the steady-state descent speed with a parachute; determining the impact kinetic energy in the corresponding states based on the maximum speed and steady-state descent speed; determining the probability of fatality to ground personnel corresponding to different impact kinetic energies; calculating the required reliability level of the parachute based on the probability of fatality to ground personnel corresponding to different impact kinetic energies, combined with the safety target level required by the drone's operating scenario and the overall safety level of the drone; and determining the minimum number of parachute deployment tests required by a statistical verification model based on a preset statistical significance level. This invention enables the dynamic determination of the parachute reliability level and accurate calculation of the required number of parachute deployment tests based on the drone's parameters and operational safety requirements.

Description

Technical Field

[0001] This invention relates to a method for determining the number of parachute deployment tests for unmanned aerial vehicles (UAVs), and also to a corresponding system, belonging to the field of UAV reliability testing technology. Background Technology

[0002] Parachutes are one of the main methods to mitigate the ground risks associated with civilian drone operations. To ensure the reliability of a particular parachute model, flight deployment tests are required before it is put into service. Before conducting drone parachute flight deployment tests, the number of tests needs to be determined. Currently, the commonly used method is to refer to the American Society for Testing Materials (ASTM) standard, "Standard Specification for Small Unmanned Aircraft System (sUAS) Parachutes" (ASTM F3322). This standard categorizes drones into four types: multi-rotor, helicopter, hybrid-wing, and fixed-wing, and then specifies the required number of flight deployment tests for each type of drone.

[0003] However, in actual operation, besides the differences in type, the actual operating scenarios of various drones are also diverse. The operational risks of drones operating in different scenarios will vary significantly, resulting in different required levels of operational safety. These differences in operational safety levels will affect the required reliability level of the parachutes used. Therefore, even if the same type of parachute is fitted to the same type of drone, the required reliability level will differ under different operating environments.

[0004] The purpose of conducting parachute deployment tests is to verify the reliability level of the parachute. Therefore, the number of parachute deployment tests required should be dynamically adjusted according to different reliability level requirements. However, the current ASTM 3322 standard specifies a fixed number of parachute deployment tests, which cannot meet the requirement of dynamic adjustment based on reliability level. Therefore, a method is urgently needed to dynamically determine the number of UAV parachute deployment tests based on reliability level requirements. Summary of the Invention

[0005] The primary technical problem to be solved by this invention is to provide a method for determining the number of parachute deployment tests during UAV landings.

[0006] Another technical problem to be solved by the present invention is to provide a system for determining the number of parachute deployment tests during unmanned aerial vehicle (UAV) flights.

[0007] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution: According to a first aspect of the present invention, a method for determining the number of parachute deployment tests during unmanned aerial vehicle (UAV) flights is provided, comprising the following steps: Step S1: Based on the flight performance parameters of the UAV, determine the maximum speed V of the UAV after it loses control and falls without a parachute. t Based on the weight m of the UAV and the aerodynamic parameters of its parachute, the steady-state descent velocity V of the UAV after the parachute deploys is determined. s ; Step S2, based on the maximum speed V t and the steady-state descent rate V s Calculate the impact kinetic energy E of the drone colliding with a person on the ground under the corresponding conditions. t and E s ; Step S3: The impact kinetic energy E calculated in step S2. t and E s Using a pre-defined kinetic energy-damage relationship model, the corresponding ground-based lethal probability L is determined. t and L s ; Step S4: Based on the ground personnel lethality probability L determined in step S3 t and L s Based on the safety target level required by the aforementioned drone operation scenario And the overall safety level of the drone itself. Calculate the required reliability level of the parachute. ; Step S5: Based on the reliability level calculated in step S4 By using a statistical validation model, the minimum number of parachute deployment tests n required is determined based on a preset statistical significance level.

[0008] Preferably, in step S1, the flight performance parameters include at least the maximum level flight speed V of the UAV. i and maximum flight altitude h; where, ; The aerodynamic parameters include at least air density. The air drag coefficient C of a parachute D And the effective windward area A; among which, .

[0009] Preferably, in step S3, the preset kinetic energy-damage relationship model is a damage risk assessment model based on a log-normal distribution, and the probability of death of ground personnel L is calculated using the following formula. t and L s ; ; .

[0010] Preferably, in step S4, the required reliability level of the parachute is positively correlated with the safety target level required by the operating scenario and negatively correlated with the probability of death in the state without a parachute.

[0011] Preferably, the required reliability level of the parachute is... Calculated using the following formula: .

[0012] Preferably, in step S5, the statistical verification model is a success-run theorem verification model based on the binomial distribution; The minimum number of parachute deployment tests, n, is the number of all successful tests required at the statistical significance level to verify that the parachute has reached the required level of reliability.

[0013] Preferably, the number of parachute deployment tests, n, is the smallest positive integer that satisfies the following inequality: ; Where α is the significance level allowed for the parachute deployment test.

[0014] According to a second aspect of the present invention, a system for determining the number of parachute deployment tests during unmanned aerial vehicle (UAV) flights is provided, comprising: A parameter acquisition module is used to acquire target parameters; wherein, the target parameters include at least the flight performance parameters of the UAV, the aerodynamic parameters of the parachute, and the operational safety requirements parameters of the UAV. The risk calculation module is communicatively connected to the parameter acquisition module and is used to calculate the risk indicators of the UAV before and after it is equipped with a parachute based on the target parameters. A reliability level determination module, which is communicatively connected to the risk calculation module, is used to determine the required reliability level of the parachute based on the risk indicators and operational safety requirements. The test number determination module is communicatively connected to the reliability level determination module and is used to determine the final minimum number of flight parachute opening tests based on the reliability level and through a preset statistical verification model.

[0015] Preferably, the risk calculation module includes: The velocity calculation unit is used to calculate the maximum speed V that a drone can reach in an uncontrolled fall without a parachute. t And the steady-state descent velocity V reached after the parachute is deployed. s ; Kinetic energy calculation unit, used to calculate based on the maximum speed V t and steady-state descent rate V s Calculate the corresponding impact kinetic energy E respectively. t and E s ; The lethality calculation unit is used to calculate the fatality rate based on the impact kinetic energy E. t and E s By using a pre-defined kinetic energy-damage relationship model, the corresponding ground-based fatality rate L is determined. t and L s ; The required reliability level of the parachute is determined by the ground personnel fatality rate L. t and L s In conjunction with the safety target level required by the aforementioned drone operation scenario, The overall safety level of the drone itself is determined by the design of the drone.

[0016] Compared with the prior art, the present invention has the following technical effects: (1) The embodiments of the present invention realize the scientific quantification and dynamic adjustment of the number of tests, abandoning the fixed number of tests required by the existing standard. By establishing a complete parameterized model, the specific performance parameters of the UAV (such as weight, speed, and flight altitude), parachute characteristics, and safety requirements of the operating scenario are all incorporated into the calculation system, realizing the dynamic and accurate determination of the number of tests based on actual risks. As a result, the scientificity and rationality of the test plan are significantly improved.

[0017] (2) The embodiments of the present invention effectively reduce testing costs while ensuring safety. By decomposing, transmitting and quantifying the top-level operational safety objectives into specific reliability requirements for parachutes, the present invention can "tailor-make" the appropriate verification intensity for operational scenarios with different risk levels.

[0018] (3) The embodiments of the present invention have broad applicability and adaptability. The core logic of the method does not depend on a specific UAV model or parachute type, and can be adapted to various types of UAVs such as multi-rotor and fixed-wing, as well as parachutes of different specifications. At the same time, when the design parameters of the UAV or its operating environment (such as changes in safety requirements due to changes in population density) change, the method can automatically recalculate the required number of tests, which has strong adaptability and flexibility.

[0019] (4) The embodiments of the present invention construct a complete "risk-reliability-verification" technology chain, innovatively combining aerodynamics, biomechanical damage models, system reliability engineering and statistical verification theory to form a complete and closed-loop technical path from "physical impact risk" assessment to "statistical verification scheme" determination. Thus, it provides a systematic solution for the safety design and verification of UAV parachutes, filling the gap in the existing technology. Attached Figure Description

[0020] Figure 1 A flowchart illustrating a method for determining the number of parachute deployment tests during UAV flight, provided in the first embodiment of the present invention; Figure 2 This is a structural diagram of a system for determining the number of parachute deployment tests during UAV flight, provided in the second embodiment of the present invention. Figure 3 This is a structural diagram of a system for determining the number of parachute deployment tests for a drone, provided in the third embodiment of the present invention. Detailed Implementation

[0021] The technical content of the present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0022] This invention provides a method for determining the number of parachute deployment tests required for a UAV based on reliability level requirements, aiming to solve the problem that the number of tests is fixed in existing ASTM standards and cannot be dynamically adjusted according to actual operating scenarios. The core of this embodiment lies in dynamically determining the parachute reliability level based on the specific parameters of the UAV and operational safety requirements, thereby calculating the required number of deployment tests.

[0023] It is important to understand that in this embodiment, the required number of tests is calculated using a mathematical model based on the specific parameters of the UAV (such as weight, speed, altitude, etc.) and the operating environment (such as safety level requirements), rather than using fixed values. Furthermore, the lethality rate is calculated using kinetic energy, thereby converting safety requirements into reliability levels, and then the minimum number of tests is determined using integral inequalities.

[0024] First Embodiment like Figure 1 As shown, the first embodiment of the present invention provides a method for determining the number of parachute deployment tests for a UAV, which specifically includes the following steps: S1: Determine the speed of the drone in both unequipped and parachute-equipped states.

[0025] In this embodiment, based on the flight performance parameters of the UAV, the maximum speed V of the UAV after losing control and falling without a parachute is determined. tFurthermore, based on the weight m of the UAV and the aerodynamic parameters of its parachute, the steady-state descent velocity V of the UAV after parachute deployment is determined. s .

[0026] Specifically, the flight performance parameters include at least the UAV's maximum level flight speed V. i And the maximum flight altitude h. Therefore, the maximum speed V of the drone after losing control and falling without a parachute can be calculated using the following formula. t , .

[0027] In addition, aerodynamic parameters include at least air density. The air drag coefficient C of a parachute D And the effective windward area A. Therefore, the steady-state descent velocity V of the UAV after the parachute deploys when equipped with a parachute can be calculated using the following formula. s .

[0028] S2: Determine the impact kinetic energy under the corresponding states.

[0029] In this embodiment, when the maximum speed V is determined based on the above step S1... t and steady-state descent rate V s Then, based on this maximum speed V t and steady-state descent rate V s Given the maximum takeoff weight m of the drone, calculate the impact kinetic energy E of the drone colliding with a person on the ground under the corresponding conditions. t and E s .

[0030] The impact kinetic energy corresponding to the maximum speed that a drone can reach when it falls out of control without a parachute is calculated using the following formula: .

[0031] Similarly, the impact kinetic energy corresponding to the steady-state descent velocity reached by a drone after it loses control and falls with a parachute and the parachute deploys can be calculated using the following formula: .

[0032] S3: Determine the probability of fatality L for ground personnel corresponding to different impact kinetic energies. t and L s .

[0033] The impact kinetic energy E calculated based on the above step S2 is... t and E sThen, it is necessary to determine the corresponding ground personnel lethality probability L using a pre-defined kinetic energy-damage relationship model. t and L s .

[0034] In this embodiment, the preset kinetic energy-damage relationship model is a damage risk assessment model based on a log-normal distribution, and the probability of death for ground personnel, L, is calculated using the following formula. t and L s ; ; .

[0035] Where x represents the integral variable; e represents the base of the natural logarithm function, which is a constant.

[0036] It's important to understand that the specific values ​​in the above formula for calculating the lethal probability (i.e., 4.007, 0.1593, 0.7022) are not arbitrarily set, but rather a variation of the cumulative distribution function of a standard log-normal distribution. Specifically: 4.007: This is the scaling parameter, representing the mean μ of ln(kinetic energy). Converting it back to a linear scale: e^4.007 ≈ 55 J. This value can be understood as the median lethal kinetic energy of this mortality rate model, that is, the estimated impact kinetic energy that results in a 50% probability of death. This value is a core biomechanical parameter.

[0037] 0.1593: This is a shape parameter, representing the variance σ of ln(kinetic energy). It determines the dispersion of the distribution curve. Understandably, a smaller variance indicates a greater sensitivity of kinetic energy to the lethality rate; a larger variance indicates greater uncertainty due to individual differences or other factors.

[0038] 0.7022: is a normalization constant, specifically... Its function is to ensure that the integral of the entire function from 0 to infinity is 1, that is, to satisfy the axiom of probability distribution.

[0039] Therefore, the figures in this embodiment precisely define a "kinetic energy-lethality" relationship model that has been validated by existing biomechanics and traumatology research. It shows that when the impact kinetic energy is approximately 55 joules, the probability of death is 50%; the lower the kinetic energy, the faster the mortality rate decreases; and the higher the kinetic energy, the closer the mortality rate is to 100%.

[0040] S4: Determine the required level of reliability for the parachute. .

[0041] In this embodiment, based on the lethal probability L of ground personnel determined in step S3... tand L s Combined with the safety target level required by the drone operation scenario And the overall safety level of the drone itself. Calculate the required level of reliability for the parachute. .

[0042] Specifically, the required level of reliability for this parachute Calculated using the following formula: .

[0043] It is understood that, in this embodiment, this reliability level... The underlying logic of the calculation formula is as follows: in the risk spectrum consisting of "no parachute risk" and "ideal parachute risk", the "required parachute reliability" is located according to the "allowable risk".

[0044] Among them, L t This represents the fatality rate without using a parachute; it's the worst-case scenario the system can handle. And L... s The Ls-Lt represents the maximum risk reduction potential that a parachute can provide when it is 100% reliable and functioning properly, which is the ideal situation under perfect protection.

[0045] Based on this, this embodiment is based on the safety target level P required by the drone operation scenario. ground And the overall safety level P of the drone itself design Loc A very important transformation was performed. Specifically, P ground / P Loc This yields a dimensionless ratio representing the normalized risk level allowed at the system level. In other words, it can be understood as the fatality rate budget allocated to this collision. Accordingly, (P ground / P Loc ) -L t It represents the risk gap between "permissible risk" and "worst-case risk".

[0046] Therefore, in order to consider the worst-case scenario L t To reach the permissible safety level P ground / P Loc This risk gap needs to be filled. Parachutes can only fill a maximum of L... s -L t Therefore, to mitigate the risks, the parachute needs to operate at a percentage of its maximum capacity, which is the required reliability level R. para .

[0047] S5: Determine the minimum number of parachute deployment tests n required to be performed.

[0048] When the reliability level R is calculated based on step S4 para Then, through statistical verification of the model, the minimum number of parachute deployment tests n to be performed is determined based on the preset statistical significance level.

[0049] In this embodiment, the statistical verification model is a success-run theorem verification model based on the binomial distribution. The minimum number of parachute deployment tests, n, is the number of all successful tests required at a statistically significant level to verify that the parachute reaches the required reliability level.

[0050] Specifically, the number of parachute deployment tests, n, is the smallest positive integer that satisfies the following inequality: ; Where α is the significance level allowed for the parachute deployment test.

[0051] It is understandable that the method for determining the number of tests described in step S5 is based on the success-run theorem in reliability engineering. This theorem provides a statistical method for determining the number of consecutive success tests required to verify whether the product reliability has reached the predetermined target, given a confidence level.

[0052] The following uses a quadcopter drone and its equipped parachute as a specific embodiment to determine the number of parachute deployment tests required to prove that operational safety requirements are met under a given expected operating scenario, thereby demonstrating the practicality and effectiveness of the method provided by this invention. The parameter values ​​of the quadcopter drone and its equipped parachute, as a specific embodiment, are shown in Table 1.

[0053] Table 1. Parameters of the quadcopter UAV and parachute in the embodiment The simulated operation scenario in the example is: using a quadcopter drone and parachute with the parameters in Table 1 to carry out urban aerial photography, with a maximum flight altitude of no more than 10m.

[0054] The following uses the method provided by the present invention to calculate the number of flight parachute deployment tests required for the UAV and parachute to ensure safe operation in the simulated operation scenario in this embodiment.

[0055] Step 1: Calculate the maximum speed that the drone can reach after losing control and falling without a parachute, and the steady-state speed that the drone reaches after losing control and falling with a parachute and the parachute deploys.

[0056] The maximum level flight speed of the UAV given in Table 1 Gravitational acceleration Maximum flight altitude of drones Maximum takeoff weight of drones air density air drag coefficient and the effective windward area of ​​the parachute Substituting these values ​​into the following formulas, we can obtain the maximum speed a drone can reach after losing control and falling without a parachute: The steady-state velocity reached by a drone after it crashes and deploys its parachute while in a parachute-equipped state is: .

[0057] Step 2: Calculate the corresponding impact kinetic energy based on the maximum speed and steady-state speed that the drone can reach when it falls out of control without a parachute and with a parachute.

[0058] The maximum speed that the drone could reach in a crash without a parachute, calculated in step one. Substituting into the following formula, the maximum kinetic energy of the drone colliding with the human body under this condition can be calculated. ,as follows: ; The steady-state velocity calculated in step one after the drone loses control and crashes with a parachute deployed is used to determine the steady-state velocity reached by the drone after the parachute deploys. Substituting into the following formula, the kinetic energy of the drone colliding with the human body under this condition can be calculated. ,as follows: .

[0059] Step 3: Calculate the corresponding fatality rate of personnel upon impact with the ground based on the maximum impact kinetic energy that the drone can reach when it loses control and falls without a parachute and the steady-state impact kinetic energy after the parachute opens when it loses control and falls without a parachute.

[0060] The maximum impact kinetic energy obtained in step two is the maximum impact kinetic energy achieved by the drone falling uncontrollably without a parachute. Substitute into the following formula to calculate the corresponding mortality rate. ,as follows: ; The impact kinetic energy obtained in step two when the drone, equipped with a parachute, crashes and reaches a steady state after the parachute deploys. Substitute into the following formula to calculate the corresponding mortality rate. ,as follows: .

[0061] Step 4: Calculate the required reliability level of the parachute based on the maximum impact kinetic energy that the drone can achieve when it crashes uncontrollably without a parachute and the impact kinetic energy that the drone reaches in a steady state after the parachute opens when it crashes uncontrollably with a parachute.

[0062] The drone operation safety levels given in Table 1 Overall safety level of drone design And the mortality rate calculated in step three , Substituting into the following formula, the required level of reliability for the parachute can be calculated. ,as follows: .

[0063] Step 5: Calculate the number of parachute deployment tests required based on the required reliability level of the drone parachute.

[0064] The significance levels allowed for parachute deployment tests given in Table 1 are... The required reliability level of the parachute calculated in step four. Substituting the following inequality, we get: ; Integrating the left side of the above equation and rearranging it, we get the following equation: Starting with n=1, substitute into the left side of the above inequality to verify whether the inequality holds. If it does not, add n to 1 and continue to verify until the inequality holds. At this point, n=26, which means that the parachute used in this embodiment needs to undergo 26 flight parachute deployment tests to verify the required level of reliability.

[0065] Comparative Example: To demonstrate the practicality and effectiveness of the method provided by the present invention, the following commonly used method for determining the number of parachute deployment tests for UAVs is applied to this embodiment for comparison with the method provided by the present invention.

[0066] According to the test matrix table provided in section 6.4.3.1 of the reference "Standard Specification for Small Unmanned Aircraft System (sUAS) Parachutes, F3322-24a, ASTM", the minimum number of parachute deployment tests required for the multi-rotor UAV in this embodiment is 49, which is higher than the 26 calculated by the method provided in this invention. Therefore, this invention provides a more accurate and effective method for determining the number of parachute deployment tests while ensuring the operational safety of the UAV.

[0067] Second Embodiment like Figure 2 As shown, based on the first embodiment described above, the second embodiment of the present invention also provides a system for determining the number of parachute deployment tests for a UAV, including a parameter acquisition module 1, a risk calculation module 2, a reliability level determination module 3, and a test number determination module 4.

[0068] Specifically, the parameter acquisition module 1 is used to acquire target parameters. These target parameters include at least the UAV's flight performance parameters, the parachute's aerodynamic parameters, and the UAV's operational safety requirements.

[0069] The risk calculation module 2 is communicatively connected to the parameter acquisition module 1 and is used to calculate the risk indicators of the UAV before and after being equipped with a parachute based on target parameters. In this embodiment, the risk calculation module 2 includes a speed calculation unit 21, a kinetic energy calculation unit 22, and a lethality calculation unit 23. The speed calculation unit 21 is used to calculate the maximum speed V that the UAV can reach in a loss of control during a fall without a parachute. t And the steady-state descent velocity V reached after the parachute is deployed. s This corresponds specifically to step S1 above. The kinetic energy calculation unit 22 is used to calculate based on the maximum speed V. t and steady-state descent rate V s Calculate the corresponding impact kinetic energy E respectively. t and E s This specifically corresponds to step S2 above. The lethality calculation unit 23 is used to calculate the fatality rate based on the impact kinetic energy E. t and E s By using a pre-defined kinetic energy-damage relationship model, the corresponding ground-based fatality rate L is determined. t and L s Specifically, this corresponds to step S3 mentioned above.

[0070] The reliability level determination module 3 is communicatively connected to the risk calculation module 2 and is used to determine the required reliability level of the parachute based on risk indicators and operational safety requirements, specifically corresponding to step S4 above.

[0071] The test number determination module 4 is communicatively connected to the reliability level determination module 3. It is used to determine the final minimum number of flight parachute opening tests based on the reliability level and through a preset statistical verification model, which corresponds to step S5 above.

[0072] It is understood that in this embodiment, the functions and connections of each module unit are only one specific implementation of the method in the first embodiment above. In other embodiments, the functions and connections of each module unit can be adapted as needed, and no specific limitations are made here.

[0073] Third Embodiment like Figure 3 As shown, based on the first embodiment described above, the third embodiment of the present invention further provides a system for determining the number of parachute deployment tests for a UAV. The system includes one or more processors 100 and a memory 200. The memory 200 is coupled to the processor 100 and is used to store one or more programs. When the programs are executed by the processor 100, the processor 100 implements the method for determining the number of parachute deployment tests for a UAV as described in the above embodiment.

[0074] The processor 100 controls the overall operation of the system to complete all or part of the steps of the method for determining the number of parachute deployment tests for a UAV. The processor 100 can be a central processing unit (CPU), graphics processing unit (GPU), field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), digital signal processing (DSP), etc. The memory 200 stores various types of data to support the operation of the system. This data may include, for example, instructions for any application or method operating on the system, and application-related data. The memory 200 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, etc.

[0075] In one exemplary embodiment, the system may be implemented by a computer chip or physical entity, or by a product with certain functions, for performing the method described above for determining the number of parachute deployment tests for a drone, and achieving the same technical effect as the method described above. A typical embodiment is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, an in-vehicle human-machine interface device, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0076] In another exemplary embodiment, the present invention also provides a computer-readable storage medium including program instructions that, when executed by a processor, implement the steps of the method for determining the number of parachute deployment tests for a drone in any of the above embodiments. For example, the computer-readable storage medium may be the memory including the program instructions described above, which can be executed by a system processor to complete the method for determining the number of parachute deployment tests for a drone and achieve the same technical effects as the method described above.

[0077] It should be noted that the above embodiments are merely illustrative examples, and the technical solutions of each embodiment can be combined, all of which are within the protection scope of this invention.

[0078] It should be understood that the terms "upper," "lower," "horizontal," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting the present invention.

[0079] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0080] The method and system for determining the number of parachute deployment tests for a UAV provided by this invention have been described in detail above. Any obvious modifications made to this invention by those skilled in the art without departing from its essential content will constitute an infringement of the patent rights of this invention and will incur corresponding legal liability.

Claims

1. A method for determining the number of parachute deployment tests during unmanned aerial vehicle (UAV) flight, characterized in that... Includes the following steps: Step S1: Based on the flight performance parameters of the UAV, determine the maximum speed V of the UAV after it loses control and falls without a parachute. t Based on the weight m of the UAV and the aerodynamic parameters of its parachute, the steady-state descent velocity V of the UAV after the parachute deploys is determined. s ; Step S2, based on the maximum speed V t and the steady-state descent rate V s Calculate the impact kinetic energy E of the drone colliding with a person on the ground under the corresponding conditions. t and E s ; Step S3: The impact kinetic energy E calculated in step S2. t and E s Using a pre-defined kinetic energy-damage relationship model, the corresponding ground-based lethal probability L is determined. t and L s ; Step S4: Based on the ground personnel lethality probability L determined in step S3 t and L s Based on the safety target level required by the aforementioned drone operation scenario And the overall safety level of the drone itself. Calculate the required reliability level of the parachute. ; Step S5: Based on the reliability level calculated in step S4 By using a statistical validation model, the minimum number of parachute deployment tests n required is determined based on a preset statistical significance level.

2. The method as described in claim 1, characterized in that... In step S1, the flight performance parameters include at least the maximum level flight speed V of the UAV. i and maximum flight altitude h; where, ; The aerodynamic parameters include at least air density. The air drag coefficient C of a parachute D And the effective windward area A; among which, .

3. The method as described in claim 1, characterized in that... In step S3, the preset kinetic energy-damage relationship model is a damage risk assessment model based on a log-normal distribution, and the probability of death of ground personnel L is calculated using the following formula. t and L s ; ； 。 4. The method as described in claim 1, characterized in that... In step S4, the required reliability level of the parachute is positively correlated with the safety target level required by the operating scenario and negatively correlated with the probability of death in the state without a parachute.

5. The method as described in claim 4, characterized in that... The required level of reliability for the parachute Calculated using the following formula: 。 6. The method as described in claim 1, characterized in that... In step S5, the statistical verification model is a success-run theorem verification model based on the binomial distribution; The minimum number of parachute deployment tests, n, is the number of all successful tests required at the statistical significance level to verify that the parachute has reached the required level of reliability.

7. The method as described in claim 6, characterized in that: The number of parachute deployment tests, n, is the smallest positive integer that satisfies the following inequality: ； Where α is the significance level allowed for the parachute deployment test.

8. A system for determining the number of parachute deployment tests during unmanned aerial vehicle (UAV) flights, characterized in that... include: A parameter acquisition module is used to acquire target parameters; wherein, the target parameters include at least the flight performance parameters of the UAV, the aerodynamic parameters of the parachute, and the operational safety requirements parameters of the UAV. The risk calculation module is communicatively connected to the parameter acquisition module and is used to calculate the risk indicators of the UAV before and after it is equipped with a parachute based on the target parameters. A reliability level determination module, which is communicatively connected to the risk calculation module, is used to determine the required reliability level of the parachute based on the risk indicators and operational safety requirements. The test number determination module is communicatively connected to the reliability level determination module and is used to determine the final minimum number of flight parachute opening tests based on the reliability level and through a preset statistical verification model.

9. The system as described in claim 8, characterized in that... The risk calculation module includes: The velocity calculation unit is used to calculate the maximum speed V that a drone can reach in an uncontrolled fall without a parachute. t And the steady-state descent velocity V reached after the parachute is deployed. s ; Kinetic energy calculation unit, used to calculate based on the maximum speed V t and steady-state descent rate V s Calculate the corresponding impact kinetic energy E respectively. t and E s ; The lethality calculation unit is used to calculate the fatality rate based on the impact kinetic energy E. t and E s By using a pre-defined kinetic energy-damage relationship model, the corresponding ground-based fatality rate L is determined. t and L s ; The required reliability level of the parachute is determined by the ground personnel fatality rate L. t and L s In conjunction with the safety target level required by the aforementioned drone operation scenario, The overall safety level of the drone itself is determined by the design of the drone.

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