Spaceflight equipment integrated test design method

Abstract

The invention discloses an aerospace equipment integrated test design method, and belongs to the technical field of system engineering. According to the method, firstly, test spaces of different system subsets, different test modes and subjects are converted and mapped and unified to a Hilbert space with the same base vector, and test space normalization is achieved; secondly, mapping data streams of subsystem test samples into samples of other integrated tests, representing a test space decomposition and calculation method of a complex system in a matrix operation form, and realizing decomposition, optimization, acquisition and aggregation of a test space; and finally, along with the whole-system dynamic iteration evolution process of the development process, comprehensive integrated design is carried out on test subjects and test contents, redundant tests are reduced, parallel tests are convenient to carry out, and comprehensive utilization of test data of different subsystems is also convenient.

Description

Technical Field

[0001] The invention relates to an integrated test design method for aerospace equipment and belongs to the technical field of system engineering. Background Art

[0002] In the new system engineering model under the aerospace equipment "cluster" evolution mode, there are a large number of equipment models and subtypes with similar baselines, sharing the same overall scheme architecture and having a variety of different local design states. Traditional aerospace system engineering projects require a complete overall integration test verification for each baseline. In this state, in order to scientifically and rationally design the overall integration test and make full use of the existing overall test data of the equipment "cluster" and the single-machine test data of the subsystem prototype as much as possible, it is necessary to establish an integrated integration test design method for aerospace equipment, combine and utilize the existing test data through mathematical transformation, reduce the requirements for test samples to obtain complete overall test results, simplify the test design and reduce the test cost. Summary of the invention

[0003] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art, and to propose an integrated test design method for aerospace equipment, normalize the test space of different system subsets, different test modes and subjects, and then decompose, optimize, acquire and aggregate the test space to achieve a comprehensive integrated design of test subjects and test contents, reduce redundant tests, facilitate parallel tests, and facilitate the comprehensive utilization of test data from different subsystems.

[0004] The technical solution of the present invention is: A method for designing an integrated test of aerospace equipment, comprising: S1: Decompose the given aerospace equipment system into subsystems, express the state of each subsystem at each time as a state vector in the Hilbert space, and combine the state vectors of each subsystem to form the state vector of the initial test state of the aerospace equipment system; S2: Based on the state vector of the initial test state of the aerospace equipment system, the state evolution equation of the aerospace equipment system for each test sample is established; according to the obtained state vectors of each subsystem and the correlation between each subsystem, the state evolution equation of each test sample is expressed as a matrix equation composed of the correlation function and the state vectors of each subsystem; S3: classifying the state vectors of each subsystem, decomposing them into a number of orthogonal state vector groups, and then recombining them to obtain the state vector group of the initial test state of the aerospace equipment system; according to the state vector group, transforming the matrix equation of each test sample, and performing diagonal optimization on the transformed matrix equation; S4: For each test sample, tests are carried out separately according to the matrix equation after diagonal optimization to obtain their own test space, and all test spaces are combined to obtain the full system test space.

[0005] Furthermore, the state of each subsystem at each moment is represented as a state vector in the Hilbert space. At the moment The state vector is expressed using Dirac notation as The state vector includes technical state parameters and task state parameters; technical state parameters include but are not limited to the length, width, height, weight, and material properties of the subsystem, and task state parameters include but are not limited to the position, speed, posture, and temperature of the subsystem.

[0006] Furthermore, based on the state vector of the initial test state of the aerospace equipment system, the state evolution equation of the aerospace equipment for each test sample is established:

[0007] In the formula, For aerospace equipment systems At the initial test time The state vector of During the test, the aerospace equipment system At the moment Evolved into state vector , is the state evolution function.

[0008] Furthermore, the state evolution equation of each test sample is expressed as a matrix equation composed of the correlation function and the state vector of each subsystem. The matrix equation is:

[0009] In the formula, ( i =1,2… n ; j =1,2… n ) is a subsystem During the evolution process, the subsystem The impact caused, that is, the correlation function; n is the number of subsystems.

[0010] Furthermore, for ,when i=j When S i Its own state evolution process, only considering S i Its own state parameters, if necessary, can be obtained through physical or simulation tests ( i = j = a ), need to target subsystem Sa Conduct an independent test process, that is, the test object only includes the subsystem. It is necessary to let the prototype or simulation model of the subsystem run under specific working conditions and record its test data. The test data constitutes the test space of the process, including the process S a A time series set of state parameters; according to t The value of is obtained from the test space. S a Status parameter value.

[0011] Furthermore, for ,when i ≠ j When S j The state parameters of the subsystem S i The influence value of the state parameter of The first way to obtain it is to S i and S j The model or prototype is integrated into a small loop subsystem, and runs under the set working conditions, records its test data, and constitutes the test space of the process, including the process S i and S j A time series set of state parameters; according to t The value of is obtained from the test space. S i The value of the state parameter being affected; The second method is to obtain S j The state parameter is S i The test environment of the model or prototype is S i Conduct individual tests and record their test data, which includes the environment S j The state parameter values ​​and the resulting S i The time series of the affected values ​​of the state parameters constitutes the experimental space of the process; according to t The value and S j The state parameter value is obtained from the test space. S i The value of the state parameter to be affected.

[0012] Furthermore, the state vectors of each subsystem are classified and reorganized, and the classification and reorganization method is: The parameters in the state vector of each subsystem are classified according to the discipline or system integration relationship, and the state vector of each subsystem is decomposed into multiple orthogonal state vector groups according to the classification, that is, , u The number of groups of discipline or system integration relationships; Merge similar items of the same subject or the same group of integration relations in the state vector group of each subsystem to complete the reorganization operation.

[0013] Furthermore, according to the reorganized state vector group, the matrix equation of each test sample is transformed, and the transformed matrix equation is:

[0014] In the formula, is the state vector group of the initial test state of the aerospace equipment system obtained by reorganizing the state vector group of the initial test state of all subsystems; in the correlation function matrix Representation state vector Pair state vector The association function of The transformed matrix equation is diagonalized and optimized, that is, if the state vector Pair state vector If the influence of is ignored, the association function Set it to 0 to get a sparse correlation function matrix.

[0015] Furthermore, experiments were carried out according to the matrix equation after diagonal optimization to obtain their respective experimental spaces, specifically: According to the matrix equation after diagonal optimization, for the state vector with only diagonal elements, use Carry out targeted Through simulation or experiment, we can obtain , get the test space of the state vector; For state vectors with off-diagonal elements, block merging calculations are performed using Carry out targeted Joint test or joint simulation to obtain , and obtain the test space of two state vectors.

[0016] Furthermore, all test spaces are combined to obtain the full system test space, which is: Align the time steps of the experimental space of each state vector, that is, each parameter in the state vector is aligned according to arrive The time series is interpolated and a uniform time step is generated from arrive of ; Then, the whole system test space is activated by summing operation, that is .

[0017] The advantages of the present invention compared with the prior art are: Compared with the traditional integrated test design method for aerospace equipment, the present invention constructs a test space in the form of Hilbert space, transforms and maps the test spaces of different system subsets, different test modes and subjects, realizes the normalization of the test space, and comprehensively integrates the test subjects and test contents, which has the following significant advantages: (1) Support the integrated use of equipment "cluster" test data. Existing test data can be decomposed and synthesized through mathematical transformation, reducing the requirements for test samples to obtain complete overall test results.

[0018] (2) It is convenient for test data asset integration. Since each test sample is unified into the mathematical expression of the test space, and the test data of different samples can be decomposed into subsets with common parts, it greatly facilitates the integration and aggregation of data.

[0019] (3) Easy to parallelize experiments. The experimental space in matrix form can be transformed and divided into blocks based on strict mathematical logic, making it easy to carry out experimental subjects of specific disciplines and specific subsystems in parallel, significantly shortening the overall experimental cycle and reducing experimental expenses. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 This is a flow chart of the aerospace equipment integrated test design method of the present invention; Figure 2 This is an exploded view of a solid rocket system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0022] The present invention proposes a method for designing an integrated test of aerospace equipment. Based on the system engineering theory of prototypes and models, the system modeling method based on Dirac symbols is used to describe the state evolution of the whole system integrated model in the form of the evolution of the Hilbert space state vector. The traditional test data stream is upgraded to a test space in the form of a vector set of the Hilbert space, and the representation method of the test data stream is unified. Based on the representation method, the test space conversion mapping of different system subsets, different test modes and subjects can be unified into a Hilbert space with the same basis vector, so as to realize the normalization of the test space. Based on the present invention, the data stream of the subsystem test sample can be mapped to the samples of other integrated tests by the method of regrouping or converting the basis vector, and the test space decomposition and calculation method of the complex system are represented in the form of matrix operation, so as to realize the decomposition, optimization, acquisition and aggregation of the test space. After the test space is decomposed into blocks, the test subjects and test contents can be comprehensively integrated and designed along with the dynamic iterative evolution process of the whole system in the development process, so as to reduce redundant tests, facilitate parallel tests, and facilitate the comprehensive utilization of test data of different subsystems.

[0023] This method is Figure 1 As shown, the specific steps include: S1: Decompose the given aerospace equipment system and establish the generalized coordinate system of the initial test state space using the Hilbert space state vector method For a given aerospace equipment system S , has a certain technical state, that is, parameters such as length, width, height, weight, and material properties; during the use or test of the equipment system, it has a certain task state, that is, parameters such as position, speed, posture, and temperature that change with the use process. Describing the system S All the parameters of form a generalized coordinate system of Hilbert space. S The state at time t can be expressed using Dirac notation as a state vector . Need to ensure Can completely describe the system S status.

[0024] For more complex aerospace equipment systems S , usually consists of multiple subsystems S 1. S 2… The state vector of the system S can be obtained by summing up the state vectors of each subsystem. .

[0025] The second step is to give the experimental space representation of the experimental sample and express the experimental data corresponding to the sample in the form of a Hilbert space vector set.

[0026] For a given system S m The experimental samples can be understood as the state vector of the system , through the evolutionary process m becomes , the evolution process m It can be expressed as a state evolution function, expressed as , where ta and tb are the starting and ending time of the evolution process respectively. The evolution process of this sample can be expressed as , which is the state evolution equation. Representatives can get The method can be in the form of a one-time Physical tests, simulation tests, and empirical functions are the initial values.

[0027] The test space of this sample , is the system S In this evolution process, all state vectors The set of can be expressed as Any experimental process is essentially about obtaining experimental space Whether it is a simulation test or a physical test, the test sampling rate is limited. Therefore, in practical applications, the collection It is a set with a finite number of elements, which is essentially a complete data set of experimental samples.

[0028] When a given system S For a system consisting of multiple subsystems S 1. S 2… When a complex system is composed of It is more difficult and needs to be converted according to the matrix operation mode of Dirac symbols. Decomposed into different matrix elements, the process can be expressed as:

[0029] in (i=1,2… n ; j=1,2… n ) is the subsystem S i In the process of evolution, the system S j In this way, we can Complete system engineering decomposition, due to There are different difficulties in obtaining, so in order to reduce the difficulty of obtaining difficulty and needs to be further optimized.

[0030] for ,when i=j When S i The state evolution process of itself, only considering S i Its own state parameters, if necessary, can be obtained through physical or simulation tests ( i = j = a ), need to target subsystem S a Conduct an independent test process, that is, the test object only includes the subsystem, and the prototype or simulation model of the subsystem needs to be operated under specific working conditions and its test data is recorded. The test data constitutes the test space of the process, including the process S a A collection of time series of state parameters. ( i = j = a ) can be based on t The value of is obtained from the test space. S a State parameter value. S i When the state evolution process of itself has a complete mathematical analytical description form, ( i = j = a ) can be obtained as a vector function whose independent variable is S a The state parameter value at the previous moment, its function value is S a The state parameter value at the next moment.

[0031] for ,when i ≠ j When S j The state parameters of the subsystem S i The influence value of the state parameter.

[0032] The first way to obtain it is to S i and S j The model or prototype is integrated into a small loop subsystem and operated under specific working conditions to record its test data, forming the test space of the process, including the process S i and S j A collection of time series of state parameters. ( i ≠ j ) can be based on t The value of is obtained from the test space. S i The value of the state parameter to be affected.

[0033] The second method is to obtain S j The state parameter is S i The test environment of the model or prototype is S i Conduct individual tests and record their test data, which includes the environment S j The state parameter values ​​and the resulting S i The time series of the affected values ​​of the state parameters constitutes the experimental space of the process. ( i ≠ j ) can be based on t The value and S j The state parameter value is obtained from the test space. S i The value of the state parameter to be affected.

[0034] when S i The state parameters of the subsystem S j When the influence of the state parameters has a complete mathematical analytical description form, ( i ≠ j ) can be obtained as a vector function, whose independent variable is S j The state parameter value of , its function value is S i The value of the state parameter to be affected.

[0035] The third step is to diagonalize the state evolution equation and divide the state evolution function into diagonal matrix combinations as much as possible.

[0036] First, the subsystem The state vector Classify and further decompose. It can be classified according to disciplines or system integration relationships. Decompose into i orthogonal state vector groups, namely , so that The same subject or the same group of integrated relations in the same subject or group of integrated relations are combined to obtain .

[0037] After the state vector is reorganized, the state evolution function will change to:

[0038] because The division takes into account the relationship between disciplines and system integration. The probability of being 0 is relatively high, so the number of matrix elements in the matrix can be significantly reduced.

[0039] Finally, we can further The items with slight effects are defined as 0, which is equivalent to ignoring the relevant effects during the experiment or simulation.

[0040] In addition, the diagonalization of the state evolution equation can also be carried out under certain conditions by using the Hilbert space transformation matrix to perform coordinate transformation on different three-dimensional coordinate system parameters, thereby reducing the complexity of system testing.

[0041] The fourth step is to obtain the test space. Experiments are carried out separately according to the diagonalized optimized state equations to obtain the test space for each discipline or subsystem. After combining them, the test space for the entire system can be obtained.

[0042] The optimized state evolution matrix is ​​a sparse matrix with a small number of off-diagonal elements, that is, the optimized state evolution matrix is ​​a sparse matrix with a small number of off-diagonal elements: , in For a state vector with only diagonal elements, directly use Carry out targeted Simulation or experiment to obtain , and get the experimental space of this part. For the part with non-diagonal elements, we can merge the calculations in blocks and use Carry out targeted Joint test or joint simulation to obtain , and obtain this part of the test space.

[0043] After all the subsystems or sub-discipline test spaces are obtained, their time steps can be aligned, that is, for each parameter in the state vector, arrive The time series is interpolated and a uniform time step is generated from arrive of , and then the whole system test space can be activated by summing operation, that is .

[0044] The present invention is described in detail by taking a solid rocket as an example. The solid rocket system includes a solid engine, a thrust vector servo mechanism, a control system and a power supply system. The relationship between them is simplified as follows: Figure 2 As shown. Among them, the state vectors of the solid engine subsystem, thrust vector servo mechanism, control system and power system are respectively expressed as , , , .

[0045] The system from Work to , the power system always keeps power supply; the control system sends ignition command to the solid engine subsystem and control command to the thrust vector servo mechanism according to the implementation sequence; the solid engine continues to work for 90s after ignition and outputs a certain thrust; the servo system adjusts the thrust vector in real time according to the command. For this working process, the test space can be expressed as:

[0046] The whole system status , state evolution function Represents the full system test or simulation process of the system.

[0047] The state evolution equation of the system is diagonalized by splitting the subsystem state vectors and reorganizing them according to the discipline and integration relationship. Decompose as follows:

[0048] in, It is the dynamics-related state attribute of the solid rocket engine subsystem, including mass, center of mass coordinates, speed, attitude and other parameters. It is the thrust-related status attribute of the engine, including the thrust value.

[0049]

[0050] in, It is the dynamics-related state attribute of the thrust vector servo mechanism, including mass, center of mass coordinates, speed, attitude and other parameters. It is the power supply status parameter of the servo mechanism, including voltage and current. It is the current actuation angle parameter of the servo mechanism, that is, the swing angle.

[0051]

[0052] in, It is the state attribute related to the dynamics of the power system, including parameters such as mass, center of mass coordinates, speed, and posture. It is the output state parameter of the power supply system, including voltage and current.

[0053]

[0054] in, It is the state attribute related to the dynamics of the control system, including mass, center of mass coordinates, speed, posture and other parameters. It is the output state parameter of the control system, including voltage and current. It is the servo control instruction. It is the ignition control command.

[0055] In this way, after re-inducing the state attributes, we can get:

[0056] in, It is the state property related to the dynamics of the whole system.

[0057]

[0058] in, It is the status attribute related to the power supply input and output of the whole system.

[0059] You can get:

[0060] in , .

[0061] The state evolution matrix can be further written as:

[0062] in It is the power supply state evolution function, which is relatively independent and can be obtained through special experiments and simulations on the ground. .

[0063] is the control command evolution function. In this embodiment, there is no external feedback to the control system, so it can be independently obtained through control system testing or simulation. .

[0064] is the flight trajectory evolution function, is the evolution function of the control command’s influence on the thrust vector. In this embodiment, the control command has a unidirectional influence on the servo mechanism angle and thrust, so it can be obtained After the test space, reuse and Calculate by simulation In this process, you do not need to use and The test or simulation equipment represented.

[0065] After the above test spaces are obtained in sequence, they can be collectively referred to as the test space of the entire system.

[0066] The above-described embodiments are only preferred specific implementations of the present invention. Common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for designing integrated test of aerospace equipment, characterized in that: include: S1: Decompose the given aerospace equipment system into subsystems, express the state of each subsystem at each time as a state vector in the Hilbert space, and combine the state vectors of each subsystem to form the state vector of the initial test state of the aerospace equipment system; S2: Based on the state vector of the initial test state of the aerospace equipment system, the state evolution equation of the aerospace equipment system for each test sample is established; according to the obtained state vectors of each subsystem and the correlation between each subsystem, the state evolution equation of each test sample is expressed as a matrix equation composed of the correlation function and the state vectors of each subsystem; S3: classifying the state vectors of each subsystem, decomposing them into a number of orthogonal state vector groups, and then recombining them to obtain the state vector group of the initial test state of the aerospace equipment system; according to the state vector group, transforming the matrix equation of each test sample, and performing diagonal optimization on the transformed matrix equation; S4: For each test sample, tests are carried out separately according to the matrix equation after diagonal optimization to obtain their own test space, and all test spaces are combined to obtain the full system test space.

2. The aerospace equipment integrated test design method according to claim 1 is characterized in that: The state of each subsystem at each moment is represented as the state vector of the Hilbert space. At the moment The state vector is expressed using Dirac notation as , the state vector includes technical state parameters and task state parameters; Technical status parameters include but are not limited to the length, width, height, weight, and material properties of the subsystem; task status parameters include but are not limited to the position, speed, posture, and temperature of the subsystem.

3. The aerospace equipment integrated test design method according to claim 1 is characterized in that: Based on the state vector of the initial test state of the aerospace equipment system, the state evolution equation of the aerospace equipment for each test sample is established: In the formula, For aerospace equipment systems At the initial test time The state vector of During the test, the aerospace equipment system At the moment Evolved into state vector , is the state evolution function.

4. The aerospace equipment integrated test design method according to claim 3 is characterized in that: The state evolution equation of each test sample is expressed as a matrix equation composed of the correlation function and the state vector of each subsystem. The matrix equation is: In the formula, ( i =1,2… n ; j =1,2… n ) is a subsystem During the evolution process, the subsystem The impact caused, that is, the correlation function; n is the number of subsystems.

5. The aerospace equipment integrated test design method according to claim 4 is characterized in that: for ,when i=j When S i Its own state evolution process, only considering S i Its own state parameters, if necessary, can be obtained through physical or simulation tests ( i = j = a ), need to target subsystem S a Conduct an independent test process, that is, the test object only includes the subsystem. It is necessary to let the prototype or simulation model of the subsystem run under specific working conditions and record its test data. The test data constitutes the test space of the process, including the process S a A set of time series of state parameters; according to t The value of is obtained from the test space. S a Status parameter value.

6. The aerospace equipment integrated test design method according to claim 4 is characterized in that: for ,when i ≠ j When S j The state parameters of the subsystem S i The influence value of the state parameter of The first way to obtain it is to S i and S j The model or prototype is integrated into a small loop subsystem, and runs under the set working conditions, records its test data, and constitutes the test space of the process, including the process S i and S j A set of time series of state parameters; according to t The value of is obtained from the test space. S i The value of the state parameter being affected; The second method is to obtain S j The state parameter is S i The test environment of the model or prototype is S i Conduct individual tests and record their test data, which includes the environment S j The state parameter values ​​and the resulting S i The time series of the affected values ​​of the state parameters constitutes the experimental space of the process; according to t The value and S j The state parameter value is obtained from the test space. S i The value of the state parameter to be affected.

7. The aerospace equipment integrated test design method according to claim 2 is characterized in that: The state vectors of each subsystem are classified and reorganized. The classification and reorganization method is: The parameters in the state vector of each subsystem are classified according to the discipline or system integration relationship, and the state vector of each subsystem is decomposed into multiple orthogonal state vector groups according to the classification, that is, , u The number of groups of discipline or system integration relationships; Merge similar items of the same subject or the same group of integration relations in the state vector group of each subsystem to complete the reorganization operation.

8. The aerospace equipment integrated test design method according to claim 7 is characterized in that: According to the reorganized state vector group, the matrix equation of each test sample is transformed, and the matrix equation after transformation is: In the formula, is the state vector group of the initial test state of the aerospace equipment system obtained by reorganizing the state vector group of the initial test state of all subsystems; in the correlation function matrix Representation vector Pair state vector The association function of The transformed matrix equation is diagonalized and optimized, that is, if the state vector Pair state vector If the influence of is ignored, the association function Set it to 0 to get a sparse correlation function matrix.

9. The aerospace equipment integrated test design method according to claim 8 is characterized in that: According to the matrix equation after diagonal optimization, the experiments were carried out respectively to obtain their respective experimental spaces, which are as follows: According to the matrix equation after diagonal optimization, for the state vector with only diagonal elements, use Carry out targeted Through simulation or experiment, we can obtain , get the test space of the state vector; For state vectors with off-diagonal elements, block merging calculations are performed using Carry out targeted Joint test or joint simulation to obtain , and obtain the test space of two state vectors.

10. The aerospace equipment integrated test design method according to claim 9 is characterized in that: After combining all the test spaces, we get the full system test space, which is as follows: Align the time steps of the experimental space of each state vector, that is, each parameter in the state vector is aligned according to arrive The time series is interpolated and a uniform time step is generated from arrive of ; Then, the whole system test space is activated by summing operation, that is .

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