Carrier rocket adapter demand change analysis method based on model

Abstract

The invention provides a model-based carrier rocket adapter demand change analysis method, which is applied to carrier rocket adapter demand change so as to evaluate the influence degree of demand change and meet the user demand to the maximum extent, thereby realizing quick response and cost reduction. According to the method, a complex network model of a carrier rocket structure and a user demand and functional characteristic network are constructed, the influence effect analysis of demand change is carried out, the mutual influence degree of the user demand and the structure network is researched, and the constraint condition of the change and the possibility of the change are analyzed in combination with the real constraint condition of parts. And establishing a carrier rocket adjacency matrix, and evaluating a change propagation probability and an influence degree to realize change risk evaluation. And according to the influence of the demand change and the design production capacity, making a decision to determine whether to accept the change. The method can quickly respond to user requirements, optimize the production process and improve economic benefits.

Description

Technical Field

[0001] The invention belongs to the field of aerospace, and relates to a model-based launch vehicle adapter requirement change analysis method. Background Art

[0002] The development of launch vehicles is a complex system engineering, involving many disciplines and complex systems. Most of the existing launch vehicles for commercial launch missions are mature, and some indicators are adjusted according to the different missions during launch. The technical requirements of satellite users for launch vehicles are mainly in the satellite coordinate system, satellite size envelope, satellite mass characteristics, orbital parameters and attitude requirements, mechanical interfaces, electrical interfaces, etc. In the process of launch vehicles performing commercial launch missions, it is necessary to carry out partial optimization design according to the technical requirements of the payload. Due to the complexity of the launch vehicle and satellite system and the long R&D cycle, changes in requirements are inevitable. Due to the multiple and complex relationships between launch vehicle parts, changes in launch vehicles will lead to changes in other parts associated with them, and even further. Therefore, the propagation characteristics of changes and the complexity of the structure of the launch vehicle adapter itself make it difficult to dynamically analyze the change propagation process based on experience, and it is difficult to accurately evaluate the impact of changes, which ultimately affects the scientific decision-making on changes in user requirements. Therefore, analyzing the propagation process of user demand changes is a key issue in responding to user demand changes.

[0003] Most of the existing change analysis methods are based on the obvious causal logical relationship between components, which cannot fully consider the multiple fuzzy correlation relationships between elements and the dynamic nature of change propagation, resulting in a lack of methods to dynamically describe the change propagation process.

[0004] Since launch vehicles have a large number of subsystems and relationships, and a complex product structure, it is necessary to abstract launch vehicles into networks or matrices for subsequent series of analysis and research. As a highly abstract model of the real world, complex networks have obvious advantages in expressing launch vehicles.

[0005] In view of the above problems, a launch vehicle demand change analysis method based on complex network theory is proposed, which regards the launch vehicle structure as a complex network. The complex network established by complex network theory greatly reduces the complexity of the launch vehicle and can help better understand the structure and dynamic characteristics of the system. Complex networks are usually used to abstractly model objects with hierarchical structures and complex internal associations in reality. According to the functions and characteristics of the parts, the complex product itself has a strong hierarchy. Summary of the invention

[0006] The technical problem solved by the present invention is: by analyzing the change in launch vehicle demand, the impact of the change in demand is evaluated to maximize the satisfaction of user needs, thereby achieving rapid response and reducing costs.

[0007] The technical solution provided by the present invention is:

[0008] A model-based launch vehicle adapter requirement change analysis method includes the following steps:

[0009] (1) Establish a complex network model based on the launch vehicle structure and obtain the component adjacency matrix;

[0010] (2) Based on the component adjacency matrix, conduct a ripple effect analysis on the launch vehicle demand change and determine the change impact matrix;

[0011] (3) Determine the change propagation probability matrix and evaluate the change risk in combination with the change impact matrix;

[0012] (4) Make decisions on user demand changes: Decide whether to accept the change based on the change risk of the user demand change.

[0013] Furthermore, the complex network model is constructed according to the correlation between user needs and the structure and function of the launch vehicle to form a user demand-functional characteristic network.

[0014] Furthermore, the complex network model is established according to the launch vehicle structure, specifically:

[0015] Each component of the launch vehicle adapter is a network node, and the relationship between the components is a network edge;

[0016] Assuming that the launch vehicle adapter has n parts and each part has m edges, the complex network model G is represented by G = (V, E, W);

[0017] Among them, V, E, and W represent the node set, edge set, and weight set of the complex product structure network G, respectively; the closer the relationship between parts, the greater the weight of the network edge.

[0018] Furthermore, in the launch vehicle complex network model G, there are unidirectional edges and bidirectional edges in the network; the unidirectional edges represent the affiliation between parts, and the bidirectional edges represent the constraint relationship between parts.

[0019] Furthermore, the launch vehicle complex network model G is a directed weighted complex network.

[0020] Furthermore, a component adjacency matrix is ​​established: the component is the decomposition of the product adapter, and the component adjacency matrix represents the association between each component of the product. If there is an association, it is 1, and if there is no association, it is 0; for unidirectional edges and bidirectional edges, both indicate an association.

[0021] Furthermore, the impact analysis of the change in launch vehicle demand is carried out to determine the change impact matrix, which is specifically:

[0022] The change impact matrix is ​​used to evaluate and record the impact of changes on different elements in the project, and to express the chain reaction that the changes may bring. The different elements mentioned are functions, modules, costs, and schedules.

[0023] Change impact refers to the proportion of a component that needs to be redesigned after being affected by the changed components associated with it. The change impact matrix uses this proportion as the change impact factor; the elements in the change impact matrix are the change impact factors.

[0024] Further, the evaluation of the change risk is specifically: the determination of the change propagation probability matrix is ​​specifically:

[0025] According to the complex network model G represented by G = (V, E, W) and the component adjacency matrix, the change propagation probability matrix is ​​determined; the elements in the change propagation probability matrix are the change propagation probabilities, which refer to the possibility that a certain component is affected by the changed components associated with it, that is, the weight.

[0026] Furthermore, the risk assessment of the change is specifically: The risk assessment of the change is specifically:

[0027] The change propagation probability matrix is ​​multiplied by the change impact matrix to obtain a change risk matrix, and the elements in the change risk matrix are change risks.

[0028] Furthermore, the decision-making on user demand change is specifically: making a decision based on the change risk caused by the user demand change and combining its own design and production capabilities to decide whether to accept the change.

[0029] The beneficial effects of the present invention are:

[0030] (1) The present invention constructs a complex network model. The complex network model is established according to the launch vehicle structure, and the user demand-function association network model is constructed according to the association relationship between the user demand and the launch vehicle structure function, thereby forming a user demand-function characteristic network.

[0031] (2) The present invention implements ripple effect analysis. In response to changes in user demand, the ripple effect analysis of changes in launch vehicle demand is carried out. Based on the constructed complex network model, the ripple effect of customer demand-structure network is studied to clarify the degree of mutual influence between user demand and launch vehicle structure network. Based on the ripple effect of demand and the actual constraints of the affected components themselves, the possibility of changes in the affected components is analyzed.

[0032] (3) The present invention implements change impact assessment. After establishing the launch vehicle adjacency matrix, the change risk assessment is implemented by determining the change propagation probability and the change impact. This enables user demand change decision-making: based on the impact of the user demand change and combined with its own design and production capabilities, a decision is made to decide whether to accept the change. The present invention can quickly respond to user needs, optimize the production process, and improve economic benefits.

[0033] (4) The present invention is used for changes in the requirements of launch vehicle adapters to evaluate the impact of the changes in requirements and maximize the satisfaction of user needs, thereby achieving rapid response and reducing costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 construct schematic diagrams for complex networks;

[0035] Figure 2 To change the propagation diagram;

[0036] Figure 3 This is a change risk assessment diagram. DETAILED DESCRIPTION

[0037] The present invention proposes a model-based launch vehicle adapter requirement change analysis method, comprising the following steps:

[0038] (1) Establish a complex network model based on the launch vehicle structure and obtain the component adjacency matrix;

[0039] The complex network model is constructed according to the correlation between user needs and the structure and function of the launch vehicle to form a user need-functional characteristic network.

[0040] The complex network model is established according to the launch vehicle structure, specifically:

[0041] Each component of the launch vehicle adapter is a network node, and the relationship between the components is a network edge;

[0042] Assuming that the launch vehicle adapter has n parts and each part has m edges, the complex network model G is represented by G = (V, E, W);

[0043] Among them, V, E, and W represent the node set, edge set, and weight set of the complex product structure network G respectively; the closer the relationship between parts, the greater the weight of the network edge, such as Figure 1 shown.

[0044] In the launch vehicle complex network model G, there are unidirectional edges and bidirectional edges in the network; unidirectional edges represent the affiliation between parts, and bidirectional edges represent the constraint relationship between parts. The launch vehicle complex network model G is a directed weighted complex network.

[0045] Establish a component adjacency matrix: Components are the decomposition of product adapters. The component adjacency matrix represents the association between each component of the product. If there is an association, it is 1, and if there is no association, it is 0. For unidirectional edges and bidirectional edges, both indicate an association.

[0046] (2) Based on the component adjacency matrix, conduct a ripple effect analysis on the launch vehicle demand change and determine the change impact matrix;

[0047] The change impact matrix is ​​used to evaluate and record the impact of changes on different elements in the project, and to express the chain reaction that the changes may bring. The different elements mentioned are functions, modules, costs, and schedules.

[0048] Change impact refers to the proportion of a component that needs to be redesigned after being affected by the changed components associated with it. The change impact matrix uses this proportion as the change impact factor; the elements in the change impact matrix are the change impact factors.

[0049] (3) Determine the change propagation probability matrix and evaluate the change risk in combination with the change impact matrix;

[0050] According to the complex network model G represented by G = (V, E, W) and the component adjacency matrix, the change propagation probability matrix is ​​determined; the elements in the change propagation probability matrix are the change propagation probabilities, which refer to the possibility that a certain component is affected by the changed components associated with it, that is, the weight.

[0051] The risk assessment of the change is specifically: The risk assessment of the change is specifically:

[0052] The change propagation probability matrix is ​​multiplied by the change impact matrix to obtain a change risk matrix. The elements in the change risk matrix are the change risks, such as Figure 3 shown.

[0053] (4) Make decisions on user demand changes: Decide whether to accept the change based on the change risk of the user demand change.

[0054] Specifically: Based on the change risks caused by changes in user requirements and combined with one's own design and production capabilities, make a decision on whether to accept the change.

[0055] Example:

[0056] The following implementation work will be carried out by taking the impact analysis of a launch vehicle user demand change on the adapter as an example. The specific implementation steps are as follows:

[0057] 1. Complex network modeling: Construct a complex network of launch vehicle adapter structures, such as Figure 1As shown in the figure, each component of the launch vehicle adapter is a network node, and the relationship between the parts is a network edge. Assume that the launch vehicle adapter has n parts, and each part has m edges. Therefore, the complex product structure network G can be expressed as G = (V, E, W), where V, E, and W represent the node set, edge set, and weight set of the complex product structure network G, respectively. The closer the relationship between the parts, the greater the weight of the network edge. Since there are affiliation and constraint relationships between the parts, in the launch vehicle structure network, there are unidirectional and bidirectional edges in the network. The unidirectional edge represents the affiliation between the parts, and the bidirectional edge represents the constraint relationship between the parts. Since there are constraint relationships between the parts, the launch vehicle network can be regarded as a directed weighted complex network.

[0058] Table 1 List of launch vehicle adapter parts

[0059]

[0060] According to the complex product structure network G, the component adjacency matrix can be obtained, such as Figure 3 The leftmost matrix in the figure; the components are the decomposition of the product adapter, and the component adjacency matrix represents the relationship between each component of the product. If there is a relationship, it is 1, and if there is no relationship, it is 0; for unidirectional edges and bidirectional edges, both indicate that there is a relationship.

[0061] 2. Spread effect analysis: In response to changes in user requirements, carry out a spread effect analysis of changes in launch vehicle adapter requirements. There are interrelated relationships between launch vehicle adapter components. The change of a component may affect its related components, thereby causing the spread of changes, such as Figure 2 As shown in the figure, different change paths will have different change impacts, so the change propagation analysis of the launch vehicle adapter is performed and the impact of the change propagation is evaluated to assist decision making. In a directed network, the change propagation can be along the direction of the arrow or in the opposite direction of the arrow.

[0062] 3. Change impact assessment: After establishing the launch vehicle adjacency matrix, the change risk is assessed by determining the change propagation probability and change impact, such as Figure 3 shown.

[0063] The change impact matrix is ​​a tool used to evaluate and record the impact of changes on different elements in a project (such as functions, modules, costs, schedules, etc.). It helps project teams understand and manage the chain reactions that changes may bring, so as to more effectively control the quality and schedule of the project. The change impact refers to the proportion of a component that needs to be redesigned after being affected by the changed components associated with it. The change impact matrix uses this proportion as the change impact factor.

[0064] The change propagation probability usually refers to the possibility that a component is affected by the changed components associated with it. The changes in the change propagation probability matrix usually propagate in the direction of the arrows. For example, A propagates to B, B may propagate to C, and may also propagate to D. The weight is set according to the probability of propagation.

[0065] After determining the change propagation probability and change impact of the component, the product of the two is used as the change risk to evaluate the change impact. The evaluation process of the change impact combined with the product component adjacency matrix is ​​as follows: Figure 3 shown.

[0066] The change propagation matrix A is based on the constructed complex network propagation and sets the weight Aij according to the probability of propagation. The change impact matrix B uses the change impact as the change impact factor Bij.

[0067] After determining the change propagation probability matrix A and the change impact matrix B, the product of the two (multiplying the corresponding positions of the matrices, Aij*Bij) is usually taken as the change risk to form the change risk matrix C.

[0068] 4. Product changes: Based on the impact of changes in user needs and combined with our own design and production capabilities, we will make a decision on whether to accept the change.

[0069] The present invention is used for the change of the demand for the launch vehicle adapter, so as to evaluate the impact of the demand change and maximize the satisfaction of user needs, thereby achieving rapid response and reducing costs.

[0070] Parts of the present invention that are not described in detail belong to common knowledge among those skilled in the art.

Claims

1. A model-based launch vehicle adapter requirement change analysis method, characterized in that include: A complex network model is established based on the launch vehicle structure to obtain the component adjacency matrix; Based on the component adjacency matrix, the impact analysis of the change in launch vehicle requirements is carried out to determine the change impact matrix; Determine a change propagation probability matrix, and evaluate the change risk in combination with the change impact matrix; Make decisions on user demand changes: Decide whether to accept the change based on the change risk of the user demand change.

2. The launch vehicle demand change impact domain analysis method according to claim 1, characterized in that: The complex network model is constructed according to the correlation between user needs and the structure and function of the launch vehicle to form a user need-functional characteristic network.

3. The launch vehicle demand change impact domain analysis method according to claim 2, characterized in that: The complex network model is established according to the launch vehicle structure, specifically: Each component of the launch vehicle adapter is a network node, and the relationship between the components is a network edge; Assuming that the launch vehicle adapter has n parts and each part has m edges, the complex network model G is represented by G = (V, E, W); Among them, V, E, and W represent the node set, edge set, and weight set of the complex product structure network G, respectively; the closer the relationship between parts, the greater the weight of the network edge.

4. The launch vehicle demand change impact domain analysis method according to claim 3, characterized in that: In the launch vehicle complex network model G, there are unidirectional edges and bidirectional edges in the network; the unidirectional edges represent the affiliation between parts, and the bidirectional edges represent the constraint relationship between parts.

5. The launch vehicle demand change impact domain analysis method according to claim 4, characterized in that: The launch vehicle complex network model G is a directed weighted complex network.

6. The launch vehicle demand change impact domain analysis method according to claim 4, characterized in that: Establish a component adjacency matrix: Components are the decomposition of product adapters. The component adjacency matrix represents the association between each component of the product. If there is an association, it is 1, and if there is no association, it is 0. For unidirectional edges and bidirectional edges, both indicate an association.

7. The launch vehicle requirement change impact domain analysis method according to claim 1, characterized in that: The above mentioned analysis of the impact of changes in launch vehicle requirements is carried out to determine the change impact matrix, specifically: The change impact matrix is ​​used to evaluate and record the impact of changes on different elements in the project, and to express the chain reaction that the changes may bring. The different elements mentioned are functions, modules, costs, and schedules. Change impact refers to the proportion of a component that needs to be redesigned after being affected by the changed components associated with it. The change impact matrix uses this proportion as the change impact factor; the elements in the change impact matrix are the change impact factors.

8. The launch vehicle demand change impact domain analysis method according to claim 3, characterized in that: The step of evaluating the change risk is specifically as follows: The step of determining the change propagation probability matrix is ​​specifically as follows: According to the complex network model G represented by G = (V, E, W) and the component adjacency matrix, the change propagation probability matrix is ​​determined; the elements in the change propagation probability matrix are the change propagation probabilities, which refer to the possibility that a certain component is affected by the changed components associated with it, that is, the weight.

9. The launch vehicle demand change impact domain analysis method according to claim 8, characterized in that: The risk assessment of the change is specifically: The risk assessment of the change is specifically: The change propagation probability matrix is ​​multiplied by the change impact matrix to obtain a change risk matrix, and the elements in the change risk matrix are change risks.

10. The launch vehicle demand change impact domain analysis method according to claim 9, characterized in that: The user demand change decision is specifically: based on the change risk caused by the user demand change and combined with its own design and production capabilities, a decision is made to decide whether to accept the change.

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