Testing device and evaluation method for acute injury caused by impact of unmanned aerial vehicle on human body

Abstract

The invention belongs to the technical field of unmanned aerial vehicle safety, and particularly relates to an unmanned aerial vehicle impact human body sharpness damage test device and evaluation method, through introducing a dynamic weight distribution algorithm, weights of various damage parameters are adjusted in real time according to the speed of an unmanned aerial vehicle, the curvature radius of a part and the type of an impacted human body part; and the injury evaluation is more accurate and personalized. The acute injury is quantitatively evaluated by adopting the comprehensive injury index IDI, various factors can be comprehensively considered, comprehensive injury grade evaluation is provided, and subsequent risk analysis and protective measure formulation are facilitated. By combining data acquisition of a physical layer and an optical layer and utilizing cooperative work of a sensor and a high-speed imaging system, comprehensive monitoring and analysis of an impact process are ensured, and accuracy and reliability of data are improved. A high-precision pressure sensor is adopted, dynamic changes at the moment of impact can be captured in real time, and more detailed damage parameters are provided.

Description

Technical Field

[0001] The present application belongs to the field of drone safety technology, and in particular relates to a test device and an evaluation method for sharp injuries caused by drone impact on human body. Background Art

[0002] With the rapid development of the global civil drone industry, small and light drones are increasingly widely used in the market, especially in the low-altitude and slow-speed flight fields. Their number has increased dramatically and has accounted for the vast majority of civil drones. At present, civil light and small drones mainly include multi-rotor drones, fixed-wing drones and helicopter drones. Among them, multi-rotor drones have been widely used due to their simple mechanical structure, highly intelligent system and convenient flight operation. However, due to uncontrollable factors such as the reliability of the drone itself and the technical level of the operator, collision accidents are inevitable in certain applications, especially posing a serious threat to the safety of ground personnel.

[0003] When a small drone collides with a human body, it may cause both blunt trauma and sharp trauma. Blunt trauma is usually caused by the drone hitting the human body at a certain speed, while sharp trauma is caused by the drone's high-speed rotating blades causing sharp damage to the human skin. Due to the light weight and high maneuverability of small drones, the potential threat of sharp trauma is often more serious.

[0004] At present, the measurement means and test methods for sharp trauma are still insufficient. The main reason is that the existing methods cannot simulate the actual working conditions during the actual drone impact process, and there is a lack of test methods and equipment suitable for sharp injuries caused by drone impact on the human body. The authenticity of the test simulation is insufficient, and traditional dummy models (including human skin layers) are difficult to restore the biomechanical properties of the human body. In addition, the data collection dimension is single, and the existing methods mostly rely on length measurement tools, lacking optical dynamic capture and multi-parameter fusion analysis. The injury assessment is also one-sided, and does not consider the dynamic effects of drone speed, blade rotation speed, component curvature radius and differences in human body parts on the injury level.

[0005] Therefore, how to more accurately assess the sharp injuries caused by the collision between drones and human bodies is a problem that needs to be solved. Summary of the invention

[0006] The purpose of this application is to provide a test device and evaluation method for sharp injuries caused by a collision between a drone and a human body, so as to solve the problem that the evaluation of sharp injuries caused by a collision between a drone and a human body in the prior art is relatively one-sided.

[0007] The technical solution of this application is: a method for evaluating sharp injuries caused by drone impact on human body, comprising: Conduct a drone impact test on a human body causing sharp injuries, collect pressure data of a pressure sensor array in a simulated layer of human skin and a highly simulated human body causing sharp injuries; extract features from the pressure data to obtain feature data, including tear length, tear depth, and contact area at the location of the sharp injury on a highly simulated human body dummy; obtain optical imaging data collected by a high-speed camera; and use a trigger signal to synchronize the collected feature data with the optical imaging data; Obtain various input parameters of the drone and the type of human body parts. The various input parameters of the drone include the speed of the drone , Radius of curvature of component , Blade speed and body part type; the speed of the drone Equivalent to the collision speed of a highly simulated human dummy; different weights are applied to different input parameters of drones and types of human body parts, and then the dynamic weight allocation algorithm is used to normalize the weights to obtain the normalized weights of each weight; The sharp injury levels were classified, and the dynamic pressure peak, tear length, tear depth and contact area of ​​the high-simulation human dummy on the head, torso and limbs were obtained respectively. The comprehensive injury index of the high-simulation human dummy was obtained by combining the normalized weights, and the sharp injury level was obtained based on the comprehensive injury index.

[0008] Preferably, the weight formula of each weight is: ; in, is the drone speed weight, is the curvature radius weight, is the blade speed weight, is the weight of the human body part; The normalized weights are: ; After normalizing the weights, we get: UAV speed normalized weights , normalized weight of curvature radius , blade speed normalization weight and human body part normalized weights .

[0009] Preferably, a machine learning module is provided, and the machine learning module adds a weight coefficient to each weight formula; the machine learning module can obtain the historical data of the currently completed drone impact sharp injury tests on the human body under different scenarios and conditions, take the speed of the drone, the radius of curvature of the components and the type of human body part impacted in the historical data as input, and take the various weight values ​​as output, perform neural network training, calculate the deviation between the output weight values ​​and the weight values ​​in the historical data as the weight coefficient, and multiply the weight coefficient by the corresponding weight to obtain a new weight.

[0010] Preferably, the calculation formula of the comprehensive injury index IDI is: IDI ; in, is the peak dynamic pressure, is the tear length, is the tear depth, is the contact area, tear length , tear depth and contact area Normalized to the range 0-1.

[0011] Preferably, the sharp injury level is divided into three levels: level I low risk, level II medium risk and level III high risk; the comprehensive injury index IDI of level I low risk is less than 0.4; the geometric damage threshold of level I low risk is: mm , mm , ; The comprehensive injury index IDI of level II low risk is , and does not include 0.7; the geometric damage threshold for medium risk in level II is: 5 mm mm , 2 mm mm , ; The comprehensive injury index IDI of level III high risk is greater than or equal to 0.7, and the geometric damage threshold of level III high risk is: mm , mm , .

[0012] As a specific implementation, a drone impact human body sharp injury test device includes a hydraulic impact unit, a drone, a drone control unit, a high-speed camera system, a data acquisition system and a data analysis system; The hydraulic impact unit includes a support frame, a hydraulic impact generator, a human body support mechanism and a high-simulation human body dummy; the support frame is horizontally arranged on the ground, and the support frame corresponds to the drone setting; the human body support mechanism is slidably connected to the support frame; the output end of the hydraulic impact generator is connected to the human body support mechanism; the high-simulation human body dummy is fixedly connected to the human body support mechanism; the hydraulic impact generator can push the human body support mechanism to slide horizontally on the support frame; the high-speed camera system is used to record the entire impact process through a high-speed camera, the data acquisition system is used to collect real-time pressure data of the head, torso and limbs of the high-simulation human body dummy, and the data analysis system is used to collect data from the high-speed camera system and the data acquisition system for sharp injury index analysis and injury level classification.

[0013] Preferably, the UAV control unit includes a UAV attitude adjustment system and a UAV suspension device; the UAV attitude adjustment system includes a steel wire rope and a connecting block; the connecting block and the steel wire rope are both provided in multiple groups and are arranged around the UAV, one end of the steel wire rope is slidably connected in the connecting block, and the other end is connected to the side wall of the UAV; the pitch and yaw angles of the UAV can be adjusted by pulling different steel wire ropes; the UAV suspension device includes a support plate, a telescopic rod, a connecting sleeve and a threaded connecting seat; the support plate is horizontally arranged on the roof, the connecting sleeve is vertically connected in the support plate, the threaded connecting seat is ball-hinged on the UAV, one end of the telescopic rod is slidably connected in the connecting sleeve, and the other end is threadedly matched with the threaded connecting seat; the connecting sleeve is provided with a pin that can be connected to the telescopic rod.

[0014] Preferably, a human skin simulation layer is installed in the highly realistic human dummy, and a pressure sensor array is embedded in the human skin simulation layer. The pressure sensor array is used to monitor the pressure data generated during the impact process in real time.

[0015] The drone impact human body sharp injury test device and evaluation method of the present application have the following advantages: By introducing a dynamic weight distribution algorithm, the weights of various damage parameters are adjusted in real time according to the speed of the drone, the radius of curvature of the components, and the type of human body part hit, making the injury assessment more accurate and personalized. The use of the comprehensive injury index IDI to quantitatively evaluate sharp injuries can comprehensively consider multiple factors and provide a comprehensive injury level assessment, which is convenient for subsequent risk analysis and formulation of protective measures.

[0016] Combining data collection at the physical and optical layers, and using sensors and high-speed imaging systems to work together, we ensure comprehensive monitoring and analysis of the impact process and improve data accuracy and reliability. High-precision pressure sensors are used to capture dynamic changes at the moment of impact in real time and provide more detailed damage parameters. Through hardware synchronization and spatial registration technology, we ensure accurate correspondence between physical data and image data, and improve the effectiveness of data analysis.

[0017] On the basis of the existing injury assessment model, it can increase the assessment capabilities of other types of injuries (such as blunt injuries, penetrating injuries, etc.) to form a more comprehensive injury assessment system. Develop a real-time monitoring and early warning system that combines sensor data and comprehensive injury index to sound an alarm when a drone approaches the human body and provide safety protection measures. Establish a virtual simulation platform to simulate collision scenarios between different types of drones and the human body, and conduct systematic testing and verification to optimize the design and assessment methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solution provided by the present application, the following is a brief introduction to the accompanying drawings. Obviously, the accompanying drawings described below are only some embodiments of the present application.

[0019] Figure 1 This is a schematic diagram of the overall structure of a test device for sharp injuries caused by a drone impacting a human body in Example 1 of the present application.

[0020] 1. Support stand; 2. Hydraulic impact generator; 3. Human support mechanism; 4. High-simulation human dummy; 5. Human skin simulation layer; 6. UAV; 7. UAV attitude adjustment system; 8. UAV suspension device; 9. Safety protection system; 10. High-speed camera system; 11. Data acquisition system. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Embodiment 1 is a device for testing sharp injuries caused by a drone impacting a human body. The device uses a dummy to collide with a drone to perform a test on sharp injuries caused by a drone impacting a human body, so as to obtain more accurate test results.

[0023] like Figure 1 As shown, it includes a hydraulic impact unit, a drone 6, a drone control unit, a high-speed camera system 10, a data acquisition system 11 and a data analysis system.

[0024] The hydraulic impact unit includes a support frame 1, a hydraulic impact generator 2, a human support mechanism 3 and a high-simulation human dummy 4. The support frame 1 is horizontally arranged on the ground, and the support frame 1 is arranged corresponding to the drone 6; the human support mechanism 3 is slidably connected to the support frame 1, preferably in the form of a slider rail; the output end of the hydraulic impact generator 2 is connected to the human support mechanism 3; the high-simulation human dummy 4 is fixedly connected to the human support mechanism 3; the hydraulic impact generator 2 can push the human support mechanism 3 to slide horizontally on the support frame 1. The data analysis system is used to collect data from the high-speed camera system 10 and the data acquisition system 11 to perform sharp injury index analysis and injury level classification.

[0025] Preferably, the high-simulation human dummy 4 is made of high-simulation materials and is equipped with a human skin simulation layer 5, which can simulate the shape and characteristics of a real human body; a pressure sensor array is embedded in the human skin simulation layer 5, and the pressure sensor array is used to monitor the pressure data generated during the impact process in real time.

[0026] The drone control unit includes a drone attitude adjustment system 7 and a drone suspension device 8. The drone suspension device 8 is used to suspend the drone 6 under test in the air for impact testing. By adjusting the suspension height and angle, the drone 6 is ensured to remain stable during the test, and the rolling angle of the drone 6 is controlled by angle adjustment. The drone attitude adjustment system 7 is used to adjust the impact attitude of the drone 6 to simulate the impact situation in actual flight.

[0027] The UAV attitude adjustment system 7 includes a steel wire rope and a connecting block. The connecting block and the steel wire rope are arranged in multiple groups around the UAV 6. One end of the steel wire rope is slidably connected to the connecting block, and the other end is connected to the side wall of the UAV 6. By pulling different steel wire ropes, the pitch and yaw angles of the UAV 6 can be adjusted to simulate a real flight collision scene.

[0028] The drone suspension device 8 includes a support plate, a telescopic rod, a connecting sleeve and a threaded connection seat. The support plate is horizontally arranged on the roof, the connecting sleeve is vertically connected to the support plate, the threaded connection seat is ball-hinged to the drone 6, one end of the telescopic rod is slidably connected to the connecting sleeve, and the other end is threadedly engaged with the threaded connection seat. The connecting sleeve is provided with a pin that can be connected to the telescopic rod. The height and angle of the drone 6 are adjusted by the telescopic cooperation between the telescopic rod and the connecting sleeve and the threaded cooperation between the telescopic rod and the threaded connection seat.

[0029] By controlling the pitch, yaw and roll angles of the drone 6, it is ensured that it hits the high-simulation human dummy 4 at a set angle and speed.

[0030] The hydraulic impact generator 2 preferably adopts an actuator. The length and width of the human skin simulation layer 5 should be no less than 1.5 times the blade diameter of the tested drone 6, and the thickness should be 3-8mm , embedded with concentrically distributed piezoresistive sensors (range 0-1500kPa) to monitor the pressure data generated during the impact in real time. These sensors can accurately capture the mechanical changes at the moment of impact.

[0031] The high-speed camera system 10 is arranged on the side of the high-simulation human dummy 4, and specifically adopts multiple sets of high-speed cameras to record the entire impact process and capture the details under high-speed motion for subsequent analysis of the dynamic behavior and impact of the impact.

[0032] The data acquisition system 11 includes multiple groups of pressure sensors arranged on the head, torso and limbs of the high-simulation human dummy 4, which are used to collect real-time pressure data of the head, torso and limbs of the high-simulation human dummy 4, so as to facilitate quantitative analysis and evaluation of sharp injuries caused by collision.

[0033] A safety protection system 9 is also provided, which is used to ensure the safety of operators during the test and prevent accidents. The safety protection system 9 is made of buffer material.

[0034] The test steps are as follows: Step 1, check the functions and status of the drone 6, hydraulic impact generator 2, support stand 1, human support mechanism 3, high-simulation human dummy 4, human skin simulation layer 5, drone attitude adjustment system 7, safety protection system 9, high-speed camera system 10 and data acquisition system 11 to ensure that all equipment is working properly.

[0035] Step 2, install the high-simulation human dummy 4 on the human support mechanism 3, and ensure that the dummy is firmly fixed on the support frame 1 to avoid displacement or tilting during the impact. Use the drone suspension device 8 to safely suspend the tested drone 6 in the air, adjust the suspension height and angle, and ensure that the drone 6 remains stable during the test. Through the drone attitude adjustment system 7, accurately adjust the pitch, yaw and roll angles of the drone 6 to simulate the impact in actual flight, and ensure that the drone 6 hits the dummy at the set angle and speed. Calibrate the pressure sensor array on the human skin simulation layer 5 to ensure that it can accurately monitor the pressure data generated during the impact.

[0036] Step 3, setting the test parameters of the hydraulic impact generator 2 to ensure that it can push the support frame 1 at a set speed, so that the high-simulation human dummy 4 can impact the drone 6.

[0037] Step 4: Start the data acquisition system 11 to ensure real-time collection of pressure data on the human skin simulation layer 5 for subsequent analysis. Start the high-speed camera system 10 to record the entire impact process through a high-speed camera to capture details and dynamic behaviors. Start the hydraulic impact generator 2 to push the support stand 1 so that the high-simulation human dummy 4 impacts the drone 6 at a set speed. Ensure that all sensors and high-speed cameras work normally at the moment of impact.

[0038] Step 5, after the collision is completed, the data acquisition system 11 is stopped to collect pressure data, and quantitative analysis and evaluation are performed to evaluate the sharp damage caused by the collision of the drone 6 to the dummy.

[0039] In summary, this application has the following advantages: The design combines a highly realistic human dummy with a human skin simulation layer. This highly realistic simulation can more realistically reflect the impact of drone collisions on the human body, ensuring the scientificity and accuracy of the test results, thereby providing reliable data support for subsequent safety assessments and protective measures.

[0040] It can comprehensively monitor various parameters during the impact process. At the same time, combined with the dynamic weight distribution algorithm, the weight of the damage parameter is adjusted in real time according to the speed of the drone, the curvature radius of the component and the type of impact site. This method makes the calculation of the integrated injury index (IDI) more accurate, thereby achieving a comprehensive assessment of sharp injuries and improving the scientificity and practicality of the test.

[0041] The use of highly simulated materials to construct human models and simulated human skin can realistically simulate the human body structure of different ages and body types. These materials are not only similar to the real human body in appearance, but also as close as possible to the reaction characteristics of real skin and tissue in terms of physical properties, thereby improving the authenticity and effectiveness of the test. By accurately designing human models of different age groups and body types, the test can more comprehensively reflect the potential impact of drone impacts on various groups of people. This highly simulated simulation not only helps scientific researchers to deeply understand the injury mechanism caused by the impact, but also provides more convincing data support for drone safety assessment, thereby promoting research progress in related fields.

[0042] The invention is not only applicable to the sharp injury test of drone collision with human body, but also can be extended to the sharp injury assessment of damage caused by the loss of control of drones to other ground objects or organisms. This good applicability and extensibility makes the invention have a wide application prospect in drone safety research and related fields, and can meet the safety assessment needs in various scenarios.

[0043] Embodiment 2, a method for evaluating sharp injuries caused by a drone collision on a human body, adopts the above-mentioned test device, introduces a dynamic weight allocation algorithm, and evaluates the sharp injury level by weight normalization and applying the integrated injury index (IDI) to more comprehensively reflect the impact of a drone collision on a human body. The specific steps are as follows: Step S100, conduct a drone impact sharp injury test on the human body, collect pressure data of the pressure sensor array in the human skin simulation layer and the high-simulation human sharp injury; extract features from the pressure data to obtain feature data, the feature data including the tear length, tear depth and contact area at the sharp injury position of the high-simulation human dummy; use a 2000fps high-speed camera (resolution 5μm / pixel) equipped with a multi-spectral ring light source; obtain optical imaging data collected by the high-speed camera; and use a trigger signal to time synchronize the collected feature data and optical imaging data.

[0044] Characteristic data include dynamic pressure peak (Unit: kPa), tear length (unit: mm ), tear depth (unit: mm ) and contact area (unit: mm ); , is the pressure value collected in the pressure data.

[0045] Step S200, obtaining various input parameters of the drone and the type of human body part. The various input parameters of the drone include the drone speed (5-25m / s), component curvature radius (3-15cm), blade speed (1000-10000rpm) and the type of human body part (such as head, torso, limbs). The speed of the drone at this time Equivalent to the collision speed of a high-simulation human dummy.

[0046] Different weights are applied to different UAV input parameters and human body part types, and then the dynamic weight allocation algorithm is used to normalize the weights to obtain the normalized weights of each weight.

[0047] Preferably, the weight formula of each weight is: ; in, is the drone speed weight, is the curvature radius weight, is the blade speed weight, is the weight of human body parts.

[0048] The normalized weights are: ; After normalizing the weights, we get: UAV speed normalized weights , normalized weight of curvature radius , blade speed normalization weight and human body part normalized weights .

[0049] When any of the drone's speed, component curvature radius, and type of human body part impacted changes, the normalized weight will change adaptively, thereby achieving dynamic adjustment of the weights of various damage parameters.

[0050] Preferably, a machine learning module is set in the data analysis system, and the machine learning module adds weight coefficients to various weight formulas; the machine learning module can obtain the historical data of the drone impact sharp injury test under different scenarios and conditions that have been completed, and use the speed of the drone, the radius of curvature of the components, and the type of human body part impacted in the historical data as input, and use the various weight values ​​as output to perform neural network training, calculate the deviation between the output weight values ​​and the weight values ​​in the historical data as the weight coefficient, and multiply the weight coefficient with the corresponding weight to obtain a new weight. By introducing machine learning technology and training the model through historical data, the weight distribution is made more intelligent and can adapt to the impact situations under different scenarios and conditions.

[0051] Step S300, performing sharp injury grade classification, obtaining the dynamic pressure peak value, tear length, tear depth and contact area of ​​the head, torso and limbs of the high-simulation human dummy respectively, obtaining the comprehensive injury index of the high-simulation human dummy in combination with the normalized weights of each item, and obtaining the sharp injury grade based on the comprehensive injury index.

[0052] Preferably, the calculation formula of the comprehensive injury index IDI is: IDI ; in, , and Normalized to the range of 0-1 (the upper limit of the test data is 20 mm , 10 mm , 15 mm ²). Similarly, due to the dynamic changes of the normalized weights, the comprehensive damage index IDI will also change dynamically, so that sharp damage can be evaluated more accurately.

[0053] Preferably, the sharp injury level is divided into three levels: level I (low risk), level II (medium risk) and level III (high risk). The comprehensive injury index IDI of level I (low risk) is less than 0.4; the geometric damage threshold of level I (low risk) is: mm , mm , The comprehensive injury index IDI for level II (low risk) is , and does not include 0.7; the geometric damage threshold of level II (medium risk) is: 5 mm mm , 2 mm mm , The comprehensive injury index IDI of level III (high risk) is greater than or equal to 0.7, and the geometric damage threshold of level III (high risk) is: mm , mm , .

[0054] The injury level must meet both the IDI range and the corresponding geometric damage threshold. If only one of them is met, it will be judged as a lower level risk.

[0055] As a specific implementation method, a specific example is used to illustrate: The input parameters of the drone include: drone speed; 18m / s; component curvature radius; 5cm; blade speed; 8000rpm; human body part type; head; Test process: Adjust the drone's pitch angle to 10°, yaw angle to 0°, and roll angle to 5°; Set the speed of the hydraulic impact generator to 18m / s, and start the data acquisition system and high-speed camera system; Activate the hydraulic impact generator to push the dummy to hit the drone at a set speed; Collect pressure data of the human skin simulation layer (peak pressure 1200kPa, tear length 8 mm , tear depth 3 mm , contact area 10 mm ²); Synchronous optical layer data (high-speed video recording of tearing dynamic behavior).

[0056] Injury level classification: Integrated Injury Index (IDI): ; Geometric damage threshold: Tear length 8mm (Level II threshold: 5-15 mm ); Tear Depth 3 mm (Level II threshold: 2-5 mm ); Contact area 10 mm ²(Level II threshold: 5-15 mm ²).

[0057] Judgment result: IDI=0.58 (Level II medium risk), and the geometric damage all met the Level II threshold, and the final injury level was Level II (medium risk).

[0058] In summary, this application has the following advantages: By introducing a dynamic weight distribution algorithm, the weights of various damage parameters are adjusted in real time according to the speed of the drone, the radius of curvature of the components, and the type of human body part hit, making the injury assessment more accurate and personalized. The use of the comprehensive injury index IDI to quantitatively evaluate sharp injuries can comprehensively consider multiple factors and provide a comprehensive injury level assessment, which is convenient for subsequent risk analysis and formulation of protective measures.

[0059] Combining data collection at the physical and optical layers, and using sensors and high-speed imaging systems to work together, we ensure comprehensive monitoring and analysis of the impact process and improve data accuracy and reliability. High-precision pressure sensors are used to capture dynamic changes at the moment of impact in real time and provide more detailed damage parameters. Through hardware synchronization and spatial registration technology, we ensure accurate correspondence between physical data and image data, and improve the effectiveness of data analysis.

[0060] On the basis of the existing injury assessment model, it can increase the assessment capabilities of other types of injuries (such as blunt injuries, penetrating injuries, etc.) to form a more comprehensive injury assessment system. Develop a real-time monitoring and early warning system that combines sensor data and comprehensive injury index to sound an alarm when a drone approaches the human body and provide safety protection measures. Establish a virtual simulation platform to simulate collision scenarios between different types of drones and the human body, and conduct systematic testing and verification to optimize the design and assessment methods.

[0061] Finally, it should be noted that: the drawings of the embodiments disclosed in the present invention only involve structures related to the embodiments disclosed in the present invention, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other; Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating sharp injuries caused by drone impact on human body, characterized in that: include: Conduct a drone impact test on a human body causing sharp injuries, collect pressure data of a pressure sensor array in a simulated layer of human skin and a highly simulated human body causing sharp injuries; extract features from the pressure data to obtain feature data, including tear length, tear depth, and contact area at the location of the sharp injury on a highly simulated human body dummy; obtain optical imaging data collected by a high-speed camera; and use a trigger signal to synchronize the collected feature data with the optical imaging data; Obtain various input parameters of the drone and the type of human body parts. The various input parameters of the drone include the speed of the drone , Radius of curvature of component , Blade speed and body part type; the speed of the drone Equivalent to the collision speed of a highly simulated human dummy; different weights are applied to different input parameters of drones and types of human body parts, and then the dynamic weight allocation algorithm is used to normalize the weights to obtain the normalized weights of each weight; The sharp injury levels were classified, and the dynamic pressure peak, tear length, tear depth and contact area of ​​the high-simulation human dummy on the head, torso and limbs were obtained respectively. The comprehensive injury index of the high-simulation human dummy was obtained by combining the normalized weights, and the sharp injury level was obtained based on the comprehensive injury index.

2. The method for evaluating sharp injuries caused by a drone hitting a human body as claimed in claim 1, characterized in that: The weight formula for each weight is: ； in, is the drone speed weight, is the curvature radius weight, is the blade speed weight, is the weight of the human body part; The normalized weights are: ； After normalizing the weights, we get: UAV speed normalized weights , normalized weight of curvature radius , blade speed normalization weight and human body part normalized weights .

3. The method for evaluating sharp injuries caused by a drone hitting a human body as claimed in claim 2, characterized in that: Set up a machine learning module, which adds weight coefficients to various weight formulas; The machine learning module can obtain the historical data of the drone impact sharp injury tests under different scenarios and conditions that have been completed, take the speed of the drone, the radius of curvature of the components and the type of human body parts impacted in the historical data as input, take the weight values ​​as output, perform neural network training, and calculate the deviation between the output weight values ​​and the weight values ​​in the historical data as the weight coefficient; The weight coefficient is multiplied by the corresponding weight to obtain the new weight.

4. The method for evaluating sharp injuries caused by a drone hitting a human body as claimed in claim 2, characterized in that: The calculation formula of comprehensive injury index IDI is: ID ; in, is the peak dynamic pressure, is the tear length, is the tear depth, is the contact area, tear length , tear depth and contact area Normalized to the range 0-1.

5. The method for evaluating sharp injuries caused by a drone hitting a human body as claimed in claim 4, characterized in that: The sharp injury level is divided into three levels: level I low risk, level II medium risk and level III high risk; Level I low risk has an IDI of less than 0.4; The geometric damage threshold for level I low risk is: mm , mm , ; The comprehensive injury index (IDI) of level II low risk is , and does not include 0.7; the geometric damage threshold for medium risk in level II is: 5 mm mm , 2 mm mm , ; The comprehensive injury index IDI of level III high risk is greater than or equal to 0.7, and the geometric damage threshold of level III high risk is: mm , mm , .

6. A test device for sharp injuries caused by drone impact on human body, using the evaluation method as described in any one of claims 1 to 5, characterized in that: It includes a hydraulic impact unit, a drone (6), a drone control unit, a high-speed camera system (10), a data acquisition system (11) and a data analysis system; The hydraulic impact unit comprises a support frame (1), a hydraulic impact generator (2), a human body support mechanism (3) and a high-simulation human body dummy (4); the support frame (1) is horizontally arranged on the ground, and the support frame (1) is arranged corresponding to the unmanned aerial vehicle (6); the human body support mechanism (3) is slidably connected to the support frame (1); the output end of the hydraulic impact generator (2) is connected to the human body support mechanism (3); the high-simulation human body dummy (4) is fixedly connected to the human body support mechanism (3); the hydraulic impact generator (2) can push the human body support mechanism (3) to slide horizontally on the support frame (1); the high-speed camera system (10) is used to record the entire impact process through a high-speed camera, the data acquisition system (11) is used to collect pressure data of the head, trunk and limbs of the high-simulation human body dummy (4) in real time, and the data analysis system is used to collect data from the high-speed camera system (10) and the data acquisition system (11) to perform sharp injury index analysis and injury grade classification.

7. The UAV impact human body sharp injury test device as claimed in claim 6, characterized in that: The drone control unit comprises a drone attitude adjustment system (7) and a drone suspension device (8); the drone attitude adjustment system (7) comprises a steel wire rope and a connecting block; the connecting block and the steel wire rope are both provided in multiple groups and are arranged around the drone (6), one end of the steel wire rope is slidably connected to the connecting block, and the other end is connected to the side wall of the drone (6); the pitch and yaw angles of the drone (6) can be adjusted by pulling different steel wire ropes; the drone suspension device (8) comprises a support plate, a telescopic rod, a connecting sleeve and a threaded connecting seat; the support plate is horizontally arranged on the roof, the connecting sleeve is vertically connected to the support plate, the threaded connecting seat is ball-hinged to the drone (6), one end of the telescopic rod is slidably connected to the connecting sleeve, and the other end is threadedly matched with the threaded connecting seat; the connecting sleeve is provided with a pin that can be connected to the telescopic rod.

8. The drone impact human body sharp injury test device as claimed in claim 6, characterized in that: The highly realistic human dummy (4) is provided with a human skin simulation layer (5), and a pressure sensor array is embedded in the human skin simulation layer (5). The pressure sensor array is used to monitor pressure data generated during the impact process in real time.

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