Cold gas thrust response test data processing method, device and equipment and readable medium

Abstract

The application discloses a cold-gas thrust response test data processing method and device, equipment and a readable medium, wherein the method comprises the following steps: in response to a detection terminal uploading a detection response time T m , querying detection parameter data corresponding to the detection response time T m ; inputting the detection parameter data into a correction model after being converted into a parameter matrix to make the correction model output a correction coefficient K and a correction confidence; judging whether the correction confidence is greater than a correction confidence threshold value, if yes, then adopting the correction coefficient K and correcting the detection response time T m according to the correction coefficient K to obtain a real response time T r . The application has the advantages that a cold-gas thrust response test data processing method, device, equipment and readable medium capable of correcting the influence of the detection device itself on the measurement error of the starting response time are provided.

Description

Technical Field

[0001] This application relates to the field of communications, and more specifically, to a method, apparatus, equipment, and readable medium for processing cold gas thrust response test data. Background Technology

[0002] With the continuous advancement of microelectromechanical systems (MEMS) technology and the development of microsatellite technology, the scientific mission capabilities of small and microsatellites have been greatly enhanced. This has placed higher demands on the propulsion systems of microsatellites to meet the demands of these more demanding scientific missions. Employing small-sized and simple-to-control cold gas propulsion technology on microsatellites to meet the needs of attitude adjustment, orbit maintenance, and deorbiting at the end of their lifespan is a viable solution. However, due to the small mass of microsatellites, the thrust response time of the cold gas thruster has a significant impact on the real-time control of satellite attitude adjustment. Measuring the response time of the cold gas thruster is the delay between the thruster receiving a control command and the cold gas being ejected from the thruster nozzle. In conventional cold gas propulsion systems, the propellant is typically ammonia or nitrogen; however, the thrust of cold gas thrusters used on microsatellites is only in the micronewton range, and the cold gas flow rate is extremely weak, making the measurement of the cold gas thruster response time very difficult.

[0003] In related technologies, a swinging component (mica sheet) connected by a suspension wire is used to react to the cold air ejected from the cold air thruster. The start-up response time of the cold air thruster is indirectly measured by the time difference between the detection electrical signal generated by the detection probe when the swinging component moves to the trigger position and the start-up command electrical signal of the cold air thruster. However, due to the distance between the swinging component and the nozzle of the cold air thruster, and between the swinging component and the trigger position, there are time Δt1 for the cold air to move onto the swinging component and time Δt2 for the swinging component to start moving to the trigger position. Therefore, there will still be an error between the detection response time obtained by this method and the actual response time. Summary of the Invention

[0004] The summary section of this application is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description section below. This summary section is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0005] Some embodiments of this application propose a method, apparatus, equipment, and readable medium for processing cold gas thrust response test data to solve the technical problems mentioned in the background section above.

[0006] As a first aspect of this application, some embodiments of this application provide a method for processing cold gas thrust response test data, including: responding to a detection response time T uploaded by a detection terminal. m Query detection response time Tm The corresponding detection parameter data; after converting the detection parameter data into a parameter matrix, it is input into a correction model so that the correction model outputs a correction coefficient K and a correction confidence level; it is determined whether the correction confidence level is greater than the correction confidence threshold. If so, the correction coefficient K is adopted and the detection response time T is corrected according to the correction coefficient K. m To obtain the true response time T r .

[0007] As a second aspect of this application, some embodiments of this application provide a cold gas thrust response test data processing apparatus, including: a query module, configured to respond to a detection response time T uploaded by a detection terminal. m Query detection response time T m The corresponding detection parameter data; the correction module, used to convert the detection parameter data into a parameter matrix and input it into a correction model so that the correction model outputs a correction coefficient K and a correction confidence level; the judgment module, used to determine whether the correction confidence level is greater than the correction confidence threshold. If so, the correction coefficient K is adopted and the detection response time T is corrected according to the correction coefficient K. m To obtain the true response time T r .

[0008] As a third aspect of this application, some embodiments of this application provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0009] As a fourth aspect of this application, some embodiments of this application provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any implementation of the first aspect above.

[0010] The beneficial effects of this application are: it provides a cold gas thrust response test data processing method, apparatus, equipment, and readable medium that can correct for the influence of the properties of the detection device itself to reduce the measurement error of the start-up response time. Attached Figure Description

[0011] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application.

[0012] Furthermore, throughout the accompanying drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the elements are not necessarily drawn to scale.

[0013] In the attached diagram:

[0014] Figure 1 This is a schematic diagram illustrating an application scenario of a cold gas thrust response test data processing method according to an embodiment of this application;

[0015] Figure 2 This is a schematic diagram of the main steps of a cold gas thrust response test data processing method according to an embodiment of this application;

[0016] Figure 3 This is a schematic diagram illustrating the specific steps of step S1 in a cold gas thrust response test data processing method according to an embodiment of this application;

[0017] Figure 4 This is a schematic diagram illustrating the specific steps of step S2 in a cold gas thrust response test data processing method according to an embodiment of this application;

[0018] Figure 5 This is a schematic diagram of a cold gas thruster response time detection scheme according to an embodiment of this application;

[0019] Figure 6 This is a schematic diagram of the structure of a cold gas thrust response test data processing device according to an embodiment of this application;

[0020] Figure 7 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application;

[0021] The meanings of the reference numerals in the attached figures are as follows:

[0022] 101. Server; 102. Detection terminal; 103. Air-cooled thruster; 104. Detection probe; 105. Swinging component; 1051. Thrust reaction surface; 106. Suspension line;

[0023] 201. Query module; 202. Correction module; 203. Judgment module. Detailed Implementation

[0024] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0025] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0026] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0027] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0028] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0029] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0030] like Figure 1 As shown, in one application scenario of this application, the detection terminal 102 is electrically connected to the cold air thruster 103 under test and the detection probe 104 to collect the detection response time T. m And the collected detection response time T m Uploaded to server 101. Specifically, the detection terminal 102 is a digital oscilloscope, which can capture the generation time of the command electrical signal and the detection electrical signal. The generation time of the command electrical signal is defined as the command time T1, and the generation time of the detection electrical signal is defined as the trigger time T2, where T... m =T2-T1.

[0031] like Figure 5 The diagram illustrates a response time detection scheme for a cold gas thruster. A swing element 105 (mica sheet) is positioned in the nozzle direction of the cold gas thruster 103. The swing element 105 provides a thrust reaction surface 1051 perpendicular to the nozzle direction and is freely suspended from one end of a suspension line 106, converting the weak thrust of the cold gas into the swing motion of the swing element 105. A detection probe 104 is positioned along the swing direction of the swing element 105. When the swing element 105 is driven to the trigger position by the cold gas, the detection probe 104 outputs a detectable electrical signal. Both the detection signal from the detection probe 104 and the start command signal from the cold gas thruster 103 are sent to a digital oscilloscope, which then uploads the corresponding data to a server 101 via a wireless network.

[0032] like Figure 2As shown, the cold gas thrust response test data processing method of this application mainly includes the following steps:

[0033] S1: Response time T of a detection terminal upload m Query detection response time T m The corresponding detection parameter data.

[0034] S2: After converting the detection parameter data into a parameter matrix, it is input into a correction model so that the correction model outputs a correction coefficient K and a correction confidence score. The correction model is specifically a PINN neural network.

[0035] S3: Determine whether the corrected confidence level is greater than the corrected confidence threshold. If so, adopt the correction coefficient K and correct the detection response time T according to the correction coefficient K. m To obtain the true response time T r A low confidence level indicates a problem with the reliability of the data. To correct the accuracy of the coefficients, the system will prompt you to re-perform the test. This is to avoid data noise caused by operation and to avoid malfunctions of the test probe or the swinging component itself.

[0036] For example, if the confidence threshold is set to 0.85, the confidence level of the output after inputting the above parameter matrix into the correction model is 0.90, where 0.90 > 0.85, indicating that the correction coefficients output by the correction model are credible.

[0037] Specifically, the detection response time T m =T2-T1, where T1, T2 and T m The unit for all values ​​is milliseconds (ms).

[0038] Specifically, the actual response time T r =K*T m T r The response time is ms.

[0039] Based on the actual response time detection results, the mass M of the swing component 111, its distance L1 from the trigger position, its distance L2 from the cold gas thruster nozzle, and the length L3 of the suspension line will all affect the actual response speed of the swing component, and thus affect the error between the detected response time and the true response time, especially for different thrusts F.

[0040] like Figure 3 As shown, as a specific solution, step S1 specifically includes the following steps:

[0041] S11: Based on the detection response time T m Acquisition and detection response time T m The corresponding attributes of the object being detected and the attributes of the detection system.

[0042] S12: Obtain object parameters based on the attributes of the object being tested. The object parameters reflect the impact of the specifications of the cold gas thruster itself, combined with the testing scenario, on the accuracy of the testing time.

[0043] Specifically, the parameters include: the rated thrust F of the cold gas thruster (in μN), the rated flow velocity V of the cold gas ejected from the cold gas thruster (in mm / ms), and the nozzle diameter D (in mm).

[0044] S13: Obtain environmental parameters based on the detection system attributes. These environmental parameters reflect the impact of the detection system's setup on the accuracy of the detection time.

[0045] Specifically, the environmental parameters include: the mass M of the oscillating component (in g), the distance L1 from the oscillating component to the trigger position (in mm), the distance L2 from the cold gas thruster nozzle to the thrust reaction surface (in mm), and the area S of the thrust reaction surface (in mm²). 2 ) and the length L3 of the suspension line (in mm).

[0046] As a preferred embodiment, to ensure that the cold air ejected from the cold air thruster does not easily diffuse and lose some thrust, and that the cold air can quickly move to the oscillating component, while also ensuring easy control of the oscillating component's motion, the ratio of the distance L1 between the oscillating component and the trigger position to the distance L2 between the oscillating component and the nozzle of the cold air thruster ranges from 0.25 to 0.75, with a preferred range of 0.4 to 0.6, and an even more preferred value of 0.5. By adopting these parameters, the oscillating component can quickly move to the trigger position under the action of cold air thrust, and the response time of the cold air thruster is much longer than the time it takes for the oscillating component to move to the trigger position under the action of thrust.

[0047] Under the constraint of the suspension line, the movement trajectory of the oscillating component approximates an arc. For the same horizontal distance traveled, the shorter the suspension line, the longer the actual path of the oscillating component to the trigger position. To reduce the actual path length of the oscillating component to the trigger position, and simultaneously reduce the impulse of the external force required to change the initial state, the ratio of the suspension line length L3 to the distance L1 between the oscillating component and the trigger position ranges from 2.5 to 7.5, preferably from 4 to 6, and ideally is 5.

[0048] According to the momentum theorem, the impulse of the net external force acting on an object is equal to the change in its momentum. The larger the mass of the oscillating component, the greater the external force required to change its state, and the air-cooled thruster can only output a weak thrust. If the mass of the oscillating component is too small or the suspension line is too long, the oscillating component needs a larger angular velocity to maintain its arc trajectory due to centrifugal force, but the weak air-cooled thrust cannot meet the angular velocity requirement. If the mass of the oscillating component is too large, it will not be able to be propelled by the air or will move slowly. If the suspension line is shorter, the actual path of the oscillating component to the trigger position is longer.

[0049] To enable the oscillating component to react quickly to the cold air and maintain its trajectory under the thrust of the cold air, the ratio of the mass M of the oscillating component 111 to the length L3 of the suspension line is between 0.001 g / mm and 0.003 g / mm. To further improve measurement accuracy, the preferred ratio range is between 0.0015 g / mm and 0.0025 g / mm. After further verification and optimization, the preferred ratio is 0.002 g / mm.

[0050] Based on multiple comparative experiments, the ratio of the mass M of the oscillating component 111 to the length L3 of the suspension line is between 0.005 g / mm and 0.015 g / mm. Under this parameter setting, the oscillating component can achieve a faster response speed and move quickly to the trigger position, thus achieving higher measurement accuracy of the thruster response time. To further improve the measurement accuracy, the preferred ratio of the mass M of the oscillating component 111 to the length L1 of the suspension line is between 0.008 g / mm and 0.012 g / mm. After further optimization, the preferred value is 0.01 g / mm.

[0051] As a preferred option, in order to enable the swinging component to move quickly to the trigger position under the thrust of the cold air, the distance L1 between the swinging component and the trigger position is in the range of 0.5mm to 2mm; in order to further shorten the trigger time, the preferred value is in the range of 0.8mm to 1.5mm; after further verification, the preferred value is 1mm.

[0052] As a preferred embodiment, in order to enable the oscillating component to respond quickly to the cold air output by the cold air thruster, while ensuring that the motion trajectory is not difficult to control due to the oscillating component being too light (the oscillating component floats rather than oscillates under the push of the cold air); the mass M of the oscillating component 111 ranges from 0.005g to 0.02g; to further improve the motion characteristics of the oscillating component (rapid response and stable motion trajectory), the preferred value range is 0.008g to 0.015g; after further verification, the preferred value is 0.01g.

[0053] By combining the above parameters, the oscillating component can respond quickly to different thrusts F, thus improving detection accuracy.

[0054] Optimal values ​​are: M = 0.01g, L1 = 1mm, L2 = 2mm, and L3 = 5mm.

[0055] Because environmental parameters, object parameters, and the motion of the oscillating component are all related, and directly analyzing these independent parameters is insufficient to form effective data for neural network learning, data processing and preprocessing are required.

[0056] like Figure 4 As shown, as a specific solution, step S2 specifically includes the following steps:

[0057] S21: Calculate a first motion parameter based on the distance L2 from the nozzle of the cold gas thruster to the thrust reaction surface and the rated flow velocity V of the cold gas ejected by the cold gas thruster. The formula for calculating the first motion parameter is: A = μL2 / V, where μ represents a motion constant (dimensionless).

[0058] S22: Calculate a gas loss parameter based on the distance L2 from the nozzle of the cold gas thruster to the thrust reaction surface, the rated thrust F, and the nozzle diameter D. The formula for calculating the gas loss parameter is: B=ωFL2 2 / πD 2 Where ω is a normalized variable (unit: ms) 2 / mm).

[0059] S23: Calculate a second motion parameter based on the mass M of the oscillating component, the distance L1 from the oscillating component to the trigger position, the area S of the thrust reaction surface, the length L3 of the suspension line, the rated thrust F, and the air loss parameter B. The calculation formula for the second motion parameter is: C = ηMSL3 / BFL1, where η is a motion constant (dimensionless).

[0060] S24: Treat the first motion parameter, air loss parameter, and second motion parameter as different columns of the parameter matrix.

[0061] Specifically, the parameter matrix is ​​[ABC].

[0062] The above steps allow for the acquisition of the necessary data sets by integrating environmental and object parameters, enabling corresponding analysis and reducing the analytical burden on the correction model, which does not analyze all data. Furthermore, this parameter selection allows the correction model to effectively obtain correction coefficients based on historical training results, thereby correcting the detection response time to obtain the true response time.

[0063] The structure and training of PINN neural networks are common techniques in this field and will not be elaborated upon here.

[0064] As a further alternative, historical data from multiple detection centers' detection terminals can be used to construct input and output data, thereby forming the training set data for the above neural network model. The output accuracy of the modified model can be compared with the detection time obtained by the detection method provided in patent document CN112729641A. The modified model is then modified based on the comparison results, thereby training the above neural network model.

[0065] The above comparison uses the detection time obtained by the detection method provided in patent document CN112729641A. This patent uses a variable dielectric capacitor bridge method to convert the thrust signal into a voltage signal, and obtains the thruster response time by the change in the voltage signal. The measurement accuracy is high. However, the main drawback of this method is that the balanced configuration of the capacitor bridge is very difficult, and the change in capacitance is so small that it is even impossible to distinguish between the background noise of the capacitor bridge output signal and the changing voltage signal. Therefore, the capacitor bridge also requires an ideal AC source and a signal conditioning circuit with a high signal-to-noise ratio, which brings great difficulties to engineering implementation.

[0066] In the detection scheme of this application, the cold air thruster is only used to change the position of the swinging component and does not directly act on the detection probe, thus avoiding coupling with the cold air thruster.

[0067] Therefore, by adopting the above neural network training method, the detection time obtained by the detection method provided in patent document CN112729641A is used to train the neural network model of this application, and the cold gas thrust response test data processing method of this application is combined into the detection scheme, which is relatively easy to implement in engineering.

[0068] like Figure 6 As shown, a cold gas thrust response test data processing device according to one embodiment of this application includes: a query module 201, used to respond to a detection response time T uploaded by a detection terminal. m Query detection response time T m The corresponding detection parameter data; correction module 202, used to convert the detection parameter data into a parameter matrix and input it into a correction model so that the correction model outputs a correction coefficient K and a correction confidence level; judgment module 203, used to judge whether the correction confidence level is greater than the correction confidence threshold. If so, the correction coefficient K is adopted and the detection response time T is corrected according to the correction coefficient K. m To obtain the true response time T r .

[0069] like Figure 7As shown, the electronic device 800 may include a processing unit (e.g., a central processing unit, a graphics processor, etc.) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage device 808 into a random access memory (RAM) 803. The RAM 803 also stores various programs and data required for the operation of the electronic device 800. The processing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0070] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 808 including, for example, magnetic tapes, hard disks, etc.; and communication devices 809. Communication device 809 allows electronic device 800 to communicate wirelessly or wiredly with other devices to exchange data. Although... Figure 7 An electronic device 800 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 7 Each box shown can represent a device or multiple devices as needed.

[0071] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 809, or installed from a storage device 808, or installed from a ROM 802. When the computer program is executed by the processing device 801, it performs the functions defined in the methods of some embodiments of this disclosure.

[0072] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0073] In some embodiments of this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0074] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol, such as HTTP (Hypertext Transfer Protocol), and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0075] The aforementioned computer-readable medium may be included in the aforementioned electronic device, or it may exist independently without being assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: respond to a detection response time Tm uploaded by a detection terminal, query the detection parameter data corresponding to the detection response time Tm; convert the detection parameter data into a parameter matrix and input it into a correction model so that the correction model outputs a correction coefficient K and a correction confidence level; determine whether the correction confidence level is greater than a correction confidence level threshold; if so, adopt the correction coefficient K and correct the detection response time Tm according to the correction coefficient K to obtain the true response time Tr.

[0076] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0077] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function.

[0078] It should also be noted that in some alternative implementations, the functions marked in the box may occur in a different order than those marked in the attached figures.

[0079] For example, two consecutively represented blocks can actually be executed in substantially parallel order, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, as well as combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified functions or operations, or using a combination of dedicated hardware and computer instructions.

[0080] The units described in some embodiments of this disclosure may be implemented in software or in hardware. The described units may also be located in a processor, and the names of these units do not necessarily limit the unit itself.

[0081] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0082] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for processing test data of cold gas thrust response, characterized in that: include: The response time T of a detection terminal upload m Query the detection response time T m The corresponding detection parameter data; The detection parameter data is converted into a parameter matrix and then input into a correction model so that the correction model outputs a correction coefficient K and a correction confidence level. If the corrected confidence level is greater than the corrected confidence level threshold, then the correction coefficient K is accepted and the detection response time T is corrected according to the correction coefficient K. m To obtain the true response time T r ; The response time T is the detection response time uploaded by a detection terminal. m Query the detection response time T m The corresponding detection parameter data includes: According to the detection response time T m Acquisition and detection response time T m Corresponding detection object attributes and detection system attributes; The object parameters are obtained based on the detected object attributes; Environmental parameters are obtained based on the properties of the detection system. The environmental parameters include: the mass M of the oscillating component, the distance L1 from the oscillating component to the trigger position, the distance L2 from the nozzle of the cold gas thruster to the thrust reaction surface, the area S of the thrust reaction surface, and the length L3 of the suspension line. The object parameters include: the rated thrust F of the cold air thruster, the rated flow velocity V of the cold air ejected from the cold air thruster, and the nozzle diameter D. The step of converting the detection parameter data into a parameter matrix and inputting it into a correction model so that the correction model outputs a correction coefficient includes: A first motion parameter is calculated based on the distance L2 from the nozzle of the cold gas thruster to the thrust reaction surface and the rated flow velocity V of the cold gas ejected by the cold gas thruster. The calculation formula for the first motion parameter is: A = μL2 / V, where μ represents a motion constant. Based on the distance L2 from the nozzle of the cold gas thruster to the thrust reaction surface, the rated thrust F, and the nozzle diameter D, a gas loss parameter is calculated. The formula for calculating the gas loss parameter is: B = ωFL2 2 / πD 2 , where ω represents a normal variable; A second motion parameter is calculated based on the mass M of the swinging component, the distance L1 from the swinging component to the trigger position, the area S of the thrust reaction surface, the length L3 of the suspension line, the rated thrust F, and the air loss parameter B. The calculation formula for the second motion parameter is: C = ηMSL3 / BFL1, where η represents a motion constant. The first motion parameter, the air loss parameter, and the second motion parameter are used as different columns of the parameter matrix.

2. The cold gas thrust response test data processing method according to claim 1, characterized in that: The modified model is a PINN neural network.

3. The cold gas thrust response test data processing method according to claim 1, characterized in that: The actual response time Tr = K * T m .

4. A cold gas thrust response test data processing device, used to implement the method as described in any one of claims 1 to 3, comprising: The query module is used to respond to the detection response time T uploaded by a detection terminal. m Query the detection response time T m The corresponding detection parameter data; The correction module is used to convert the detection parameter data into a parameter matrix and input it into a correction model so that the correction model outputs a correction coefficient K and a correction confidence level. The judgment module is used to determine whether the corrected confidence level is greater than the corrected confidence level threshold. If so, the correction coefficient K is accepted and the detection response time T is corrected according to the correction coefficient K. m To obtain the true response time T r .

5. An electronic device, comprising: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the processors implement the method as described in any one of claims 1 to 3.

6. A computer-readable medium having a computer program stored thereon, wherein, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 3.

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