Automatic projectile launching device reliability simulation analysis method and system based on gunpowder gas pressure distribution

Abstract

The invention provides an automatic projectile launching device reliability simulation analysis method and system based on gunpowder gas pressure distribution, and relates to the technical field of computer simulation. According to the method, a gunpowder gas pressure spline curve is taken as a research object, and random distribution characteristic analysis is carried out on a series of similar curves generated in the launching process of the automatic projectile launching device under the same working condition or the same boundary condition by adopting a time section cutting method; time profile characteristic parameters are extracted or a gunpowder gas pressure curve cluster random distribution characteristic model of the automatic projectile launching device is further constructed to serve as simulation software input, the random distribution characteristic of the dynamic load can be fully considered, and therefore the confidence coefficient of the reliability simulation analysis result of the automatic projectile launching device is improved.

Description

Technical Field

[0001] The invention relates to the technical field of computer simulation, and in particular to a reliability simulation analysis method and system for an automatic projectile launching device based on gunpowder gas pressure distribution. Background Art

[0002] The automatic projectile launcher launches the projectile under the action of the gunpowder gas in the barrel to complete the shooting. The gunpowder gas pressure is the power source of the automatic projectile launcher and is an important factor affecting the reliability of the automatic projectile launcher. However, affected by environmental factors such as temperature, dust, rain, and structural factors such as component gaps and key component dimensions, the gunpowder gas pressure curve is often different even under the same constraints or boundary conditions. Therefore, it is currently difficult to accurately analyze the reliability of the automatic projectile launcher based on the gunpowder gas pressure. Summary of the invention

[0003] The purpose of the present invention is to provide a reliability simulation analysis method and system for an automatic projectile launcher based on the gunpowder gas pressure distribution, so as to accurately analyze the reliability of the automatic projectile launcher by accurately estimating the random distribution of the gunpowder gas pressure.

[0004] In a first aspect, a reliability simulation analysis method for an automatic projectile launching device based on the distribution of gunpowder gas pressure is provided, the simulation analysis method comprising: Obtaining a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; Extracting multiple time profile data sequences of the gunpowder gas pressure curve cluster; Performing random distribution characteristic statistics on the time section data sequence to construct a random distribution model for each time section data sequence; Extracting time profile characteristic parameters of the gunpowder gas pressure curve cluster based on the random distribution model; The reliability simulation analysis of the automatic projectile launching device is carried out based on the time profile characteristic parameters.

[0005] In other embodiments, the extracting of multiple time profile data sequences of the gunpowder gas pressure curve cluster includes: Taking the starting point and the end point of the gunpowder gas pressure curve as the interval, select multiple key time points; Based on the multiple key time points, multiple time sections of the gunpowder gas pressure curve cluster are constructed; The gunpowder gas pressure data on each time section of the gunpowder gas pressure curve cluster is extracted to obtain multiple time section data sequences.

[0006] In other embodiments, according to the stages experienced by the automatic projectile launching process, based on the 6σ principle, the key time points are selected within the interval; wherein the stages experienced by the automatic projectile launching action process include the unlocking stage, the locking stage, the shell extraction stage, the shell ejection stage, the recoil stage and the return stage, and the key time points selected corresponding to the unlocking stage, the locking stage, the shell extraction stage and the shell ejection stage are more dense than the key time points selected corresponding to the recoil stage and the return stage.

[0007] In other embodiments, the random distribution characteristics statistics of the time profile data sequence are performed to construct a random distribution model of each time profile data sequence, including: using a kernel density estimation method to perform random distribution characteristics statistics on the time profile data sequence to obtain a kernel probability density function of the time profile data sequence.

[0008] In other embodiments, the extracting of the time section characteristic parameters of the gunpowder gas pressure curve cluster based on the random distribution model includes: taking the mathematical expectation of the random distribution model corresponding to the time section as the characteristic parameter of the time section.

[0009] In other embodiments, the reliability simulation analysis of the automatic projectile launcher based on the time profile characteristic parameters includes: The kernel density estimation method is used to perform random distribution characteristic statistics on the characteristic parameters of the time profile to obtain the kernel probability density function of the characteristic parameters, so as to construct a random distribution model of the gunpowder gas pressure curve cluster; The random distribution model of the gunpowder gas pressure curve cluster is processed by simulation software to obtain reliability simulation analysis results.

[0010] In a second aspect, a reliability simulation analysis system for an automatic projectile launcher based on the gunpowder gas pressure distribution is provided, the simulation analysis system comprising: A data acquisition module, used to obtain a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; A data extraction module, used to extract multiple time profile data sequences of the gunpowder gas pressure curve cluster; A first model building module is used to perform random distribution characteristic statistics on the time profile data sequence to build a random distribution model for each time profile data sequence; A feature extraction module, used for extracting time profile feature parameters of a cluster of gunpowder gas pressure curves based on the random distribution model; The first analysis module is used to perform reliability simulation analysis of the automatic projectile launching device based on the time profile characteristic parameters.

[0011] In a third aspect, another reliability simulation analysis method of an automatic projectile launching device based on the gunpowder gas pressure distribution is provided, and the simulation analysis method comprises: Obtaining a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; Extracting a series of gunpowder gas pressure data of multiple time sections of the gunpowder gas pressure curve cluster; Performing random distribution characteristic analysis on the gunpowder gas pressure data sequence to construct a random distribution model of the gunpowder gas pressure curve cluster; The random distribution model of the gunpowder gas pressure curve cluster is processed by simulation software to obtain reliability simulation analysis results.

[0012] In other embodiments, the random distribution characteristic analysis of the gunpowder gas pressure data sequence to construct a random distribution model of a gunpowder gas pressure curve cluster includes: Using a kernel density estimation method to perform random distribution characteristic statistics on the gunpowder gas pressure data sequence of the time section, a kernel probability density function of the time section data sequence is obtained to construct a random distribution model of each time section data sequence; Extracting time profile characteristic parameters of the gunpowder gas pressure curve cluster based on the random distribution model; The kernel density estimation method is used to perform random distribution characteristic statistics on the time profile characteristic parameters to obtain the kernel probability density function of the characteristic parameters, so as to construct a random distribution model of the gunpowder gas pressure curve cluster.

[0013] In a fourth aspect, another reliability simulation analysis system for an automatic projectile launcher based on gunpowder gas pressure distribution is provided, the simulation analysis system comprising: A data acquisition module, used to obtain a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; A data extraction module, used to extract the gunpowder gas pressure data sequence of multiple time sections of the gunpowder gas pressure curve cluster; A second model building module is used to perform random distribution characteristic analysis on the gunpowder gas pressure data sequence to build a random distribution model of the gunpowder gas pressure curve cluster; The second analysis module uses simulation software to process the random distribution model of the gunpowder gas pressure curve cluster to obtain reliability simulation analysis results.

[0014] The present invention has the following technical effects: The present invention takes the gunpowder gas pressure spline curve as the research object, adopts the time profile cutting method to analyze the random distribution characteristics of a series of similar curves generated in the firing process of an automatic projectile launcher under the same working conditions or the same boundary conditions, extracts the time profile characteristic parameters or further constructs a random distribution characteristic model of the gunpowder gas pressure curve cluster of the automatic projectile launcher as the simulation software input, so that in the process of simulation analysis of the reliability of the whole firing process of the automatic projectile launcher, the random distribution characteristics of the dynamic load are fully considered, thereby improving the confidence of the reliability simulation analysis result of the automatic projectile launcher. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a schematic flow chart of a reliability simulation analysis method of an automatic projectile launching device based on the gunpowder gas pressure distribution according to an embodiment of the present invention; Figure 2 It is a schematic diagram of the composition of a reliability simulation analysis system for an automatic projectile launching device based on the gunpowder gas pressure distribution according to an embodiment of the present invention; Figure 3 It is a schematic flow chart of a reliability simulation analysis method of an automatic projectile launching device based on the gunpowder gas pressure distribution according to another embodiment of the present invention; Figure 4 The figure is a schematic diagram of the composition of a reliability simulation analysis system for an automatic projectile launching device based on the gunpowder gas pressure distribution according to another embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 making creative work are within the scope of protection of the present invention.

[0018] Figure 1 This is a flow chart of a reliability simulation analysis method for an automatic projectile launcher based on the gunpowder gas pressure distribution according to an embodiment of the present invention. Figure 1 As shown, the simulation analysis method includes: Step 101, obtaining a cluster of gunpowder gas pressure curves generated by an automatic projectile launching device under the same working conditions or boundary conditions; Here, "curve cluster" refers to a collection of curves with similar characteristics generated under the same operating conditions or the same boundary conditions. "Same operating conditions" or "same boundary conditions" means that in the experiment or simulation, the key parameters or environmental conditions that affect the gunpowder gas pressure are kept consistent, thereby eliminating the interference of other variables on the results. For example, in the experiment, the initial state of the automatic projectile launcher and external parameters such as ambient temperature, humidity, and atmospheric pressure must be kept consistent. In the numerical simulation, the boundary conditions are set the same. By fixing these conditions, it can be ensured that the differences in the gunpowder gas pressure curves only come from changes in the automatic projectile launcher itself, thereby accurately analyzing the impact of specific factors on the gunpowder gas pressure response.

[0019] As an example, multiple experiments can be carried out under the same working conditions, and pressure data can be collected using a pressure sensor to obtain multiple gunpowder gas pressure curves. When using experiments to obtain curves, it is necessary to ensure the repeatability of the data. Alternatively, software can be used to generate a cluster of gunpowder gas pressure curves using numerical simulation methods (such as finite element analysis). By building an automatic projectile launcher model, setting the same initial conditions and boundary conditions, and solving equations to generate multiple gunpowder gas pressure curves.

[0020] Step 102, extracting multiple time profile data sequences of the gunpowder gas pressure curve cluster; In the time-pressure coordinate system, each gunpowder gas pressure curve in the gunpowder gas pressure curve cluster represents the change trend of the gunpowder gas pressure over time during the entire process of the automatic projectile launcher launching the projectile. Therefore, corresponding to any time point (unit: s), each gunpowder gas pressure curve corresponds to specific gunpowder gas pressure data (unit: Bar).

[0021] In an embodiment, this step includes the following sub-steps: Step 1021, taking the starting point and the ending point of the gunpowder gas pressure curve as the interval, selecting a plurality of key time points; As an example, according to the stages experienced by the automatic projectile launching process, key time points are selected within the interval based on the 6σ principle.

[0022] The automatic projectile launching process goes through the following stages: (1) Unlocking stage: The machine head rotates under the action of the machine frame, so that the locking teeth of the machine head and the meshing surface of the sleeve are disengaged; (2) Locking stage: The machine head rotates under the action of the machine frame, so that the machine head locking teeth engage with the meshing surface of the sleeve; (3) Extraction stage: The extractor extracts the cartridge case from the chamber. (4) Ejection stage: After the cartridge case impacts the ejection mechanism during the extraction process, it is ejected. (5) Recoil stage: The process in which the bolt carrier moves backward and compresses the recoil spring.

[0023] (6) Return stage: The process in which the bolt carrier moves forward under the action of the recoil spring force.

[0024] Among them, for the key action stages of the automatic projectile launching device mechanism movement (such as unlocking stage, locking stage, extraction stage, ejection stage, etc.), additional time points need to be selected in the time intervals corresponding to them on the gunpowder gas pressure curve. For other action stages (such as recoil stage, return stage), considering that the mechanism movement is relatively simple, fewer time points can be selected in the time intervals corresponding to them on the gunpowder gas pressure curve. At the same time, based on the 6σ principle, the time points within the 6σ interval should be denser than the time points outside the 6σ interval. Therefore, when selecting the key time points, the key time points selected for the unlocking stage, locking stage, extraction stage, and ejection stage are denser than the key time points selected for the recoil stage and return stage, and satisfy the 6σ principle.

[0025] As an example, in order to reflect the movement characteristics of the automatic projectile launching device mechanism, key time points are selected at least at the critical positions between the above key action stages and the time points before and after them. For example, assuming that the current action stage ends at time point t and the next action stage starts at time point t, then time point t, the time point t - ∆1 before time point t (in the current action stage), and the time point t + ∆2 after time point t (in the next action stage) can be set as key time points.

[0026] As an example, the number of selected key time points can be set to be greater than 10 and less than 30, that is, 10 < N < 30.

[0027] Step 1022: Based on multiple key time points, construct multiple time profiles of the gunpowder gas pressure curve cluster. A time profile is, in a plane coordinate system, based on the same moment, extracting and combining the values at the same moment on a large number of spline curves in the plane coordinate system, which is the time profile.

[0028] Based on the selected key time points, construct the time profile T of the gunpowder gas pressure curve cluster n , n = 1, 2, 3,... N, 10 < N < 30, that is, one key time point corresponds to constructing one time profile.

[0029] Step 1023: Extract the gunpowder gas pressure data on each time profile of the gunpowder gas pressure curve cluster to obtain multiple time profile data sequences.

[0030] The propellant gas pressure data on each time section of the propellant gas pressure curve cluster are extracted to obtain multiple time section data sequences X n = {x1, x2, x3…x m}, n represents the time section number, n = 1, 2, 3, ... N; m represents the data number on the time section, and x represents the gunpowder gas pressure data on the time section, that is, the gunpowder gas pressure data of the mth gunpowder gas pressure curve on the time section n.

[0031] Step 103, performing random distribution characteristic statistics on the time section data sequence to construct a random distribution model for each time section data sequence; In an embodiment, a kernel density estimation method is used to perform random distribution characteristic statistics on a time profile data sequence to obtain a kernel probability density function of the time profile data sequence, so as to construct a random distribution model for each time profile data sequence.

[0032] The kernel density function expression is:

[0033] in: is the density estimate at point x; is the kernel function; h is the bandwidth parameter; n is the sample size.

[0034] It is understandable that other estimation methods may also be used to perform random distribution characteristic statistics on the time profile data series, and are not limited to the kernel density estimation method.

[0035] Step 104, extracting time profile characteristic parameters of the gunpowder gas pressure curve cluster based on the random distribution model; In an embodiment, the mathematical expectation of the random distribution model corresponding to the time profile is used as the characteristic parameter of the time profile.

[0036] Step 105, performing reliability simulation analysis of the automatic projectile launching device based on the time profile characteristic parameters.

[0037] In one embodiment, during the reliability simulation analysis, only characteristic parameters are input into the simulation software to automatically generate a curve spline as a load input, thereby solving the problem of spline curve loading in the reliability simulation analysis of the automatic projectile launcher.

[0038] In one embodiment, this step includes the following sub-steps: (1) The kernel density estimation method is used to perform random distribution statistics on the characteristic parameters of the time profile, and the kernel probability density function of the characteristic parameters is obtained to construct a random distribution model of the gunpowder gas pressure curve cluster; It is understandable that other estimation methods may also be used to perform random distribution characteristic statistics on time profile characteristic parameters, and are not limited to the kernel density estimation method.

[0039] (2) Use simulation software to process the random distribution model of the gunpowder gas pressure curve cluster to obtain reliability simulation analysis results.

[0040] Here, the simulation software may be, for example, Adams (Automatic Dynamic Analysis of Mechanical Systems) simulation software, which is a simulation software based on multibody dynamics (MBD) and is mainly used to analyze the kinematics, dynamics, and statics characteristics of mechanical systems.

[0041] The constructed random distribution model of the gunpowder gas pressure curve cluster is imported into the Adams software through a user subroutine or an external data file (such as Excel, CSV) to simulate and analyze the reliability of the automatic projectile launching device.

[0042] In the above embodiment, the present invention takes spline curves as the research object to construct a curve cluster random distribution model as the input of the reliability simulation analysis of the automatic projectile launcher. It can completely simulate the load impact on the automatic projectile launcher during the entire process of the action of gunpowder and gas pressure during the launch of the automatic projectile launcher, while considering the random distribution characteristics of the gunpowder and gas pressure curve of the automatic projectile launcher under the same working conditions, thereby solving the problem of inaccurate gunpowder and gas pressure input in the current reliability simulation analysis of the automatic projectile launcher.

[0043] Figure 2 The following is a schematic diagram of the reliability simulation analysis system of the automatic projectile launcher based on the gunpowder gas pressure distribution according to an embodiment of the present invention. Figure 2 As shown, the simulation analysis system includes: The data acquisition module 201 is used to obtain a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; The data extraction module 202 is used to extract multiple time profile data sequences of the gunpowder gas pressure curve cluster; The first model building module 203 is used to perform random distribution characteristic statistics on the time section data sequence to build a random distribution model of each time section data sequence; A feature extraction module 204 is used to extract time profile feature parameters of a cluster of gunpowder gas pressure curves based on a random distribution model; The first analysis module 205 is used to perform reliability simulation analysis of the automatic projectile launching device based on the time profile characteristic parameters.

[0044] According to another embodiment of the present invention, a reliability simulation analysis method for an automatic projectile launching device based on the gunpowder gas pressure distribution is also provided. Figure 3 As shown, the simulation analysis method includes: Step 301, obtaining a cluster of gunpowder gas pressure curves generated by an automatic projectile launching device under the same working conditions or boundary conditions; Step 302, extracting a gunpowder gas pressure data sequence of multiple time sections of the gunpowder gas pressure curve cluster; Step 303, performing random distribution characteristic analysis on the gunpowder gas pressure data sequence to construct a random distribution model of the gunpowder gas pressure curve cluster; Step 304, using simulation software to process the random distribution model of the gunpowder gas pressure curve cluster to obtain reliability simulation analysis results.

[0045] In one embodiment, in step 303, the following sub-steps are used to perform random distribution characteristic analysis on the gunpowder gas pressure data sequence to construct a random distribution model of the gunpowder gas pressure curve cluster: (1) The kernel density estimation method is used to perform random distribution statistics on the time section gunpowder gas pressure data sequence, and the kernel probability density function of the time section data sequence is obtained to construct the random distribution model of each time section data sequence; (2) Extracting the time profile characteristic parameters of the gunpowder gas pressure curve cluster based on the random distribution model; (3) The kernel density estimation method is used to perform random distribution statistics on the characteristic parameters of the time profile, and the kernel probability density function of the characteristic parameters is obtained to construct a random distribution model of the gunpowder gas pressure curve cluster.

[0046] The above steps may be specifically implemented by the method described above, or by other methods known in the art, which will not be described in detail here.

[0047] In the above embodiment, the present invention uses the random distribution characteristic feature parameters of the time profile data sequence of the curve cluster to characterize the key features of a series of similar curves, and constructs a random distribution model of the gunpowder gas pressure curve cluster of the automatic projectile launcher by performing random distribution characteristic analysis on the random distribution characteristic feature parameters of the time profile data sequence, thereby solving the problem that it is difficult to accurately construct random distribution models of a large number of similar curves.

[0048] Correspondingly, an embodiment of the present invention further provides a reliability simulation analysis system for an automatic projectile launching device based on the gunpowder gas pressure distribution, such as Figure 4As shown, the simulation analysis system includes: The data acquisition module 201 is used to obtain a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; The data extraction module 202 is used to extract the gunpowder gas pressure data sequence of multiple time sections of the gunpowder gas pressure curve cluster; That is, in this embodiment, the data acquisition module 201, the data extraction module 202 and Figure 2 The corresponding modules of the simulation analysis system of the illustrated embodiment are the same.

[0049] The second model building module 403 is used to analyze the random distribution characteristics of the gunpowder gas pressure data sequence to build a random distribution model of the gunpowder gas pressure curve cluster; The second analysis module 404 uses simulation software to process the random distribution model of the gunpowder gas pressure curve cluster to obtain reliability simulation analysis results.

[0050] The present invention takes the gunpowder gas pressure spline curve as the research object, adopts the time profile cutting method to analyze the random distribution characteristics of a series of similar curves generated in the firing process of an automatic projectile launcher under the same working conditions or the same boundary conditions, extracts the time profile characteristic parameters or further constructs a random distribution characteristic model of the gunpowder gas pressure curve cluster of the automatic projectile launcher as the simulation software input, so that in the process of simulation analysis of the reliability of the whole firing process of the automatic projectile launcher, the random distribution characteristics of the dynamic load are fully considered, thereby improving the confidence of the reliability simulation analysis result of the automatic projectile launcher.

[0051] According to an embodiment of the present invention, a non-transient computer-readable storage medium is also provided for storing a non-transient software program, a non-transient computer executable program, and a module, such as a program or instruction corresponding to the reliability simulation analysis method of the automatic projectile launcher in the aforementioned embodiment of the present invention. The processor implements the reliability simulation analysis method of the automatic projectile launcher in the aforementioned method embodiment by running the non-transient software program or instruction.

[0052] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components and other chips, or a combination of the above chips.

[0053] Although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments. Without departing from the inventive concept of the present invention, the technical solutions of the embodiments of the present invention may be modified or replaced by equivalents, which shall not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A reliability simulation analysis method for an automatic projectile launching device based on the gunpowder gas pressure distribution, characterized in that: The simulation analysis method comprises: Obtaining a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; Extracting multiple time profile data sequences of the gunpowder gas pressure curve cluster; Performing random distribution characteristic statistics on the time section data sequence to construct a random distribution model for each time section data sequence; Extracting time profile characteristic parameters of the gunpowder gas pressure curve cluster based on the random distribution model; The reliability simulation analysis of the automatic projectile launching device is carried out based on the time profile characteristic parameters.

2. The simulation analysis method according to claim 1, characterized in that: The extracting of multiple time profile data sequences of the gunpowder gas pressure curve cluster comprises: Taking the starting point and the end point of the gunpowder gas pressure curve as the interval, select multiple key time points; Based on the multiple key time points, multiple time sections of the gunpowder gas pressure curve cluster are constructed; The gunpowder gas pressure data on each time section of the gunpowder gas pressure curve cluster is extracted to obtain multiple time section data sequences.

3. The simulation analysis method according to claim 2, characterized in that: According to the stages experienced by the automatic projectile launching process, based on the 6σ principle, the key time points are selected within the interval; wherein, the stages experienced by the automatic projectile launching action process include the unlocking stage, the locking stage, the shell extraction stage, the shell ejection stage, the recoil stage and the return stage, and the key time points selected in the corresponding unlocking stage, the locking stage, the shell extraction stage and the shell ejection stage are more dense than the key time points selected in the corresponding recoil stage and the return stage.

4. The simulation analysis method according to claim 1, characterized in that: The random distribution characteristic statistics of the time profile data sequence are performed to construct a random distribution model of each time profile data sequence, including: using a kernel density estimation method to perform random distribution characteristic statistics on the time profile data sequence to obtain a kernel probability density function of the time profile data sequence.

5. The simulation analysis method according to claim 1, characterized in that: The extracting of the time section characteristic parameters of the gunpowder gas pressure curve cluster based on the random distribution model includes: taking the mathematical expectation of the random distribution model corresponding to the time section as the characteristic parameter of the time section.

6. The simulation analysis method according to claim 1, characterized in that: The reliability simulation analysis of the automatic projectile launcher based on the time profile characteristic parameters includes: The kernel density estimation method is used to perform random distribution characteristic statistics on the characteristic parameters of the time profile to obtain the kernel probability density function of the characteristic parameters, so as to construct a random distribution model of the gunpowder gas pressure curve cluster; The random distribution model of the gunpowder gas pressure curve cluster is processed by simulation software to obtain reliability simulation analysis results.

7. A reliability simulation analysis system for an automatic projectile launcher based on the gunpowder gas pressure distribution, characterized in that: The simulation analysis system comprises: A data acquisition module, used to obtain a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; A data extraction module, used to extract multiple time profile data sequences of the gunpowder gas pressure curve cluster; A first model building module is used to perform random distribution characteristic statistics on the time profile data sequence to build a random distribution model for each time profile data sequence; A feature extraction module, used for extracting time profile feature parameters of a cluster of gunpowder gas pressure curves based on the random distribution model; The first analysis module is used to perform reliability simulation analysis of the automatic projectile launching device based on the time profile characteristic parameters.

8. A reliability simulation analysis method for an automatic projectile launching device based on the pressure distribution of gunpowder gas, characterized in that: The simulation analysis method comprises: Obtaining a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; Extracting a series of gunpowder gas pressure data of multiple time sections of the gunpowder gas pressure curve cluster; Performing random distribution characteristic analysis on the gunpowder gas pressure data sequence to construct a random distribution model of the gunpowder gas pressure curve cluster; The random distribution model of the gunpowder gas pressure curve cluster is processed by simulation software to obtain reliability simulation analysis results.

9. The simulation analysis method according to claim 8, characterized in that: The random distribution characteristic analysis of the gunpowder gas pressure data sequence is performed to construct a random distribution model of the gunpowder gas pressure curve cluster, including: Using a kernel density estimation method to perform random distribution characteristic statistics on the gunpowder gas pressure data sequence of the time section, a kernel probability density function of the time section data sequence is obtained to construct a random distribution model of each time section data sequence; Extracting time profile characteristic parameters of the gunpowder gas pressure curve cluster based on the random distribution model; The kernel density estimation method is used to perform random distribution characteristic statistics on the time profile characteristic parameters to obtain the kernel probability density function of the characteristic parameters, so as to construct a random distribution model of the gunpowder gas pressure curve cluster.

10. A reliability simulation analysis system for an automatic projectile launcher based on the gunpowder gas pressure distribution, characterized in that: The simulation analysis system comprises: A data acquisition module, used to obtain a cluster of gunpowder gas pressure curves generated by the automatic projectile launching device under the same working conditions or boundary conditions; A data extraction module, used to extract the gunpowder gas pressure data sequence of multiple time sections of the gunpowder gas pressure curve cluster; A second model building module is used to perform random distribution characteristic analysis on the gunpowder gas pressure data sequence to build a random distribution model of the gunpowder gas pressure curve cluster; The second analysis module uses simulation software to process the random distribution model of the gunpowder gas pressure curve cluster to obtain reliability simulation analysis results.

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