Aerospace system fault identification and modeling method based on model
By using the MBSE method and SysML modeling tools to identify fault information and propagation paths in the forward design of aerospace systems, the problem of insufficient risk assessment in the design phase is solved, and the system reliability is improved.
Patent Information
- Application Number
- CN202511859810.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-10
- Publication Date
- 2026-05-05
AI Technical Summary
In existing technologies, the fault identification and modeling of aerospace systems lack synergy between forward design and risk analysis, resulting in insufficient risk assessment and weak link identification during the design phase.
The Model-Based Systems Engineering (MBSE) approach is adopted. By using SysML forward design modeling, fault information and fault propagation paths are identified layer by layer, and a fault analysis model is established, including SysML parametric model, structural model and behavioral model. The fault element meta-model is embedded to identify abnormal states of function, performance and structure, and to formulate prevention and compensation measures.
It provides a basis for risk analysis and assessment during the design phase, ensures consistency between requirements and design, reduces reliance on reverse engineering, and improves system reliability.
Smart Images
Figure CN121980437A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a model-based method for fault identification and modeling of aerospace systems, belonging to the fields of model-based systems engineering and risk management technology. Background Technology
[0002] Model-based systems engineering (MBSE), as an emerging methodology for developing complex systems, has seen widespread application and rapid development in the aerospace field in recent years. MBSE utilizes formal modeling languages and unified digital models to construct structured, traceable system models starting from the requirements analysis phase, spanning the entire process from design and simulation to verification. This effectively solves the problems of information silos and requirements transmission deviations inherent in traditional methods. Currently, the mainstream approach for digital forward design focuses solely on the functional and performance design modeling of product models, neglecting the relationship between faults and functional performance. Fault identification, modeling, and risk analysis often lag behind forward design, relying heavily on the expert experience of reliability designers. This lack of synergy between forward design and risk analysis hinders risk assessment and vulnerability identification during the design phase. Summary of the Invention
[0003] The technical problem solved by this invention is to overcome the shortcomings of existing technologies and provide a model-based method for fault identification and modeling of aerospace systems. Following the approach of "forward design modeling + fault logic → fault modeling," during the SysML forward design modeling process, fault information and propagation paths are comprehensively identified through fault logic such as functional violations, performance deviations, and structural failures, thus establishing a fault analysis model. This solves the problem of inconsistency between forward design and fault identification, providing a basis for risk analysis and assessment in the design phase, thereby reducing design risks.
[0004] The technical solution of this invention is: a model-based method for fault identification and modeling of aerospace systems, comprising: S0. Based on the top-level functional requirements and descriptions of the system or task, decompose the system into different levels from top to bottom; S1. For the current level, identify the activities to be carried out and define the activity block diagram. Analyze and obtain the input and output performance parameters that meet the corresponding behavior activities of the system. Use the bdd module to define the graph and build the SysML parameter model. S2. Based on the input and output performance parameters of the current level, determine the structural composition and resource flow relationship of the current level, and use the ibd structure diagram to establish a SysML structure model. S3. Create an action activity diagram on the activity block diagram, establish a SysML behavior model, decompose the activities of the current level to the next level, and clarify the specific behaviors that need to be executed in the next level. S4. Return to S1 iteration until the lowest level is reached, and obtain the SysML parameter model established by the bdd module definition diagram, the SysML structural model established by the ibd structure diagram, and the SysML behavioral model established by the act activity diagram for each level; proceed to S5. S5. Using the SysML extension mechanism, define the fault element meta-model by configuring the type stereotype through the profile block diagram in the bdd module definition diagram of the SysML parametric model. S6. For the SysML behavioral model, abnormal states that violate the functional specifications of each activity are identified as functional failure modes, and linked to the activity block diagram of the SysML behavioral model by the Violat relation. S7. For the SysML parameter model, abnormal phenomena that deviate from the specified range of each parameter are identified as fault phenomena and linked to the parameter block diagram in the SysML parameter model by the Devite relation. S8. For the SysML structural model, structural integrity anomalies in each part are identified as structural failure modes and linked to the structural block diagram in the SysML structural model by the Damage relationship. S9. Based on the fault phenomena, functional fault modes, and structural fault modes, establish fault and fault propagation models at each level, and formulate prevention and compensation measures based on the fault and fault propagation models.
[0005] Preferably, in S2, the resources include signals, data, energy, and matter flowing between internal structures of a system, subsystem, or unit.
[0006] Preferably, in S5, the fault element meta-model can be divided into fault information category, logical relationship category, improvement measure category, and risk level category; Fault information includes fault mode, fault impact, and fault cause; Logical relationship classes include: Violate, Deviate, Damage, Lead to, Relate to, Prevent, and Compensate; Improvement measures include preventive measures and compensatory measures; Risk levels are categorized by severity, probability of occurrence, detectability, and risk priority.
[0007] Preferably, the Violat relationship includes: loss of function, partial loss of function, reduction of function, overflow of function, hysteresis of function, interruption of function, and unexpected function.
[0008] Preferably, the Devite relationship includes: parameter with no value, parameter too low, parameter too high, and parameter unstable.
[0009] Preferred Damage relationships include: explosion, damage, buckling, deformation, scratch, injury, cracking, breakage, loosening, detachment, corrosion, wear, generation of excess material, leakage, fire, and burning.
[0010] Preferably, during fault propagation: The failure mode at this level is the cause of the failure mode at the previous level, linked by the Cause relationship. The failure mode at this level is also the failure effect at the next level, linked by the Effect relationship. The phenomenon identified by the parameter deviation at this level is the failure phenomenon of the failure mode at the previous level, linked by the Perform relationship. The final failure effect is linked by the Final Effect relationship.
[0011] Preferably, the fault mode block diagram in the fault and fault propagation model is assigned a Value attribute to define the severity, probability of occurrence, detectability, and risk priority of the fault mode at this level.
[0012] Preferably, risk analysis is conducted, and relevant prevention and compensation measures are developed for each failure mode, linking them to the failure modes through the relationships of Prevent and Compensate.
[0013] Compared with the prior art, the present invention has the following advantages: (1) This invention utilizes the technical advantages of model-based systems engineering (MBSE) forward design modeling to innovatively propose a fault identification method for aerospace systems based on MBSE forward design. Starting from requirements, the system functions and architecture are mapped layer by layer through parameter models, functional models, structural models, etc. By utilizing the logical relationship between fault information and design information such as parameters and functional structures, fault information at each system level can be identified, ensuring the consistency between requirements and design and the comprehensiveness of faults. (2) An innovative approach to aerospace system fault modeling based on MBSE was proposed. Fault models at various levels were established in a bdd diagram (block definition diagram) based on SysML activity diagrams (system modeling language diagrams) and internal structure diagrams. Fault information was embedded into the forward design model, including information such as preventative compensation measures, severity, measurability, and occurrence. The relationships between fault phenomena, causes, and impacts were identified through the logical architecture of the forward design model between systems. A traceable fault model and fault propagation model were constructed from the requirements phase, ensuring that the fault model can be dynamically adjusted and influence the design when system requirements change, reducing reliance on reverse design. This approach supports the development of digital mission risk assessments, breaking down the barriers between forward design and fault modeling, effectively identifying risks in the design phase, and helping to improve the reliability of digital prototypes. Attached Figure Description
[0014] Figure 1 This is a flowchart of the method of the present invention; Figure 2This is a schematic diagram of the fault and fault propagation model of the present invention. Detailed Implementation
[0015] The purpose of this invention is to enable designers to identify fault information from functional, performance, and structural aspects during the forward design process, perform fault modeling, and analyze fault propagation logic and risks. These are critical issues that need to be addressed in the current forward design closed-loop, early design verification, and risk control. This invention provides a model-based method for fault identification and modeling in aerospace systems, such as... Figure 1 As shown, the main steps include: S1. Based on the top-level functional requirements and descriptions of the system or task, identify the top-level activities that the system needs to carry out and define block diagrams. The system needs to input and output corresponding parameters to complete the corresponding behavioral activities. Analyze and obtain the parameters that meet the functional performance. Through the formula relationship of the parameters, use bdd diagrams to establish a SysML system-level parameter model. S2. Based on the system's input and output performance parameters, determine the system's structural composition and resource flow relationships. Resources refer to signals, data, energy, matter, etc., flowing between the internal structures of the system, subsystems, or single machines. Use ibd diagrams (internal module diagrams) to establish a SysML system-level structural model. S3. To complete the system activities identified in S1, an act diagram (activity diagram) needs to be created on the top-level activity block diagram, a SysML system-level behavior model needs to be established, and the system activities need to be decomposed downwards according to the internal structure of the system (that is, the subsystems) to clarify the specific behaviors that need to be executed in each subsystem. S4. For subsystems, stand-alone machines, etc., repeat the steps in S1-S3 until the lowest level is agreed upon. IBD structure diagrams, ACT activity diagrams, etc. can be nested to describe the relationships between system levels. S5. Utilizing the SysML extension mechanism, define the fault and risk element meta-model in the bdd module definition diagram using the "profile" block diagram configuration type "stereotype". This meta-model can be categorized into fault information, logical relationship, improvement measure, and risk level classes. Fault information includes fault mode, fault impact, and fault cause; logical relationship includes violation, lead to, related to, prevent, and compensate; improvement measure includes preventive measures and compensatory measures; and risk level includes severity, probability of occurrence, detectability, and risk priority. S6. For the behavior model, abnormal states that violate the specified states of various activities / functions are identified as functional failure modes, which are linked to the activity block diagram by the "Violate" relationship. These include loss of function, partial loss of function, reduction of function, overflow of function, sluggish function, interruption of function, and unexpected function. S7. For the parameter model, abnormal phenomena that deviate from the specified range of each parameter are identified as fault phenomena and linked to the parameter block diagram by "Deviate". These include parameters with no value, parameters that are too low, parameters that are too high, and parameters that are unstable. S8. For the structural model, structural integrity anomalies in each part are identified as structural failure modes, which are linked to the structural block diagram by "Damage". These include explosion (breakage), damage, buckling, deformation, scratches, injury, cracking, breakage, loosening, detachment, corrosion, wear, generation of excess material, leakage, fire, burning, etc. S9. Establish fault models at all levels and fault propagation models in the bdd diagram, including fault phenomena, fault causes, impact of the previous level fault, impact of the final fault, severity, probability of occurrence, detectability, risk priority, and analyze and formulate prevention and compensation measures.
[0016] like Figure 2 As shown, the fault mode at this level is the cause of the fault mode at the higher level, linked by the "Cause" relationship, and is also the impact of the fault at the next level, linked by the "Effect" relationship. The phenomena identified by the parameter deviation at this level are the fault phenomena of the fault mode at the higher level, linked by the "Perform" relationship. The final fault impact is linked by the "Final Effect" relationship.
[0017] By assigning the Value attribute to the failure mode block diagram, parameters such as severity, probability of occurrence, detectability, and risk priority of the failure mode at this level can be defined.
[0018] Conduct risk analysis and develop relevant prevention and compensation measures for each failure mode, linking them to the failure modes with the relationships of "Prevent" and "Compensate".
[0019] In summary, this invention relates to a model-based method for fault identification and modeling in aerospace systems. Utilizing the Sysml language modeling tool, it conducts forward design modeling based on Sysml, analyzes the top-level requirements of the system, determines input and output parameters based on system performance indicators to establish a system-level parameter model, determines the system structural composition model based on performance indicator requirements and the parameter model, identifies the activities required by the system to meet functional performance requirements, and establishes a system functional activity model, establishes subsystem-level parameter models based on the system functional activity model, and decomposes them downwards in a similar manner, establishes a fault element meta-model through the Sysml extension mechanism, identifies fault information through logical relationships such as "Violate," "Deviate," and "Damage" in forward design information, conducts fault analysis, establishes a fault model and a fault propagation model, and achieves forward design modeling incorporating fault information. This invention achieves fault information identification and fault analysis model establishment simultaneously during system forward design, solving the problem of collaborative modeling of forward design and reverse fault information, providing material basis for risk analysis and assessment, helping the overall system identify risks and optimize design during the design phase, and improving system reliability.
[0020] The contents not described in detail in this specification are existing technologies known to those skilled in the art.
Claims
1. A model-based method for fault identification and modeling of aerospace systems, characterized in that... include: S0. Based on the top-level functional requirements and descriptions of the system or task, decompose the system into different levels from top to bottom; S1. For the current level, identify the activities to be carried out and define the activity block diagram. Analyze and obtain the input and output performance parameters that meet the corresponding behavior activities of the system. Use the bdd module to define the graph and build the SysML parameter model. S2. Based on the input and output performance parameters of the current level, determine the structural composition and resource flow relationship of the current level, and use the ibd structure diagram to establish a SysML structure model. S3. Create an action activity diagram on the activity block diagram, establish a SysML behavior model, decompose the activities of the current level to the next level, and clarify the specific behaviors that need to be executed in the next level. S4. Return to S1 iteration until the lowest level is reached, and obtain the SysML parameter model established by the bdd module definition diagram, the SysML structural model established by the ibd structure diagram, and the SysML behavioral model established by the act activity diagram for each level; proceed to S5. S5. Using the SysML extension mechanism, define the fault element meta-model by configuring the type stereotype through the profile block diagram in the bdd module definition diagram of the SysML parametric model. S6. For the SysML behavioral model, abnormal states that violate the functional specifications of each activity are identified as functional failure modes, and linked to the activity block diagram of the SysML behavioral model by the Violat relation. S7. For the SysML parameter model, abnormal phenomena that deviate from the specified range of each parameter are identified as fault phenomena and linked to the parameter block diagram in the SysML parameter model by the Devite relation. S8. For the SysML structural model, structural integrity anomalies in each part are identified as structural failure modes and linked to the structural block diagram in the SysML structural model by the Damage relationship. S9. Based on the fault phenomena, functional fault modes, and structural fault modes, establish fault and fault propagation models at each level, and formulate prevention and compensation measures based on the fault and fault propagation models.
2. The model-based aerospace system fault identification and modeling method according to claim 1, characterized in that: In S2, resources include signals, data, energy, and matter flowing between the internal structures of systems, subsystems, or individual machines.
3. The model-based aerospace system fault identification and modeling method according to claim 1, characterized in that: In S5, the fault element meta-model can be divided into fault information category, logical relationship category, improvement measure category, and risk level category; Fault information includes fault mode, fault impact, and fault cause; Logical relationship classes include: Violate, Deviate, Damage, Lead to, Related to, Prevent, and Compensate; Improvement measures include preventive measures and compensatory measures; Risk levels are categorized by severity, probability of occurrence, detectability, and risk priority.
4. The model-based aerospace system fault identification and modeling method according to claim 1, characterized in that: Violate relationships include: loss of function, partial loss of function, reduction of function, overflow of function, sluggish function, interruption of function, and unexpected function.
5. The model-based aerospace system fault identification and modeling method according to claim 1, characterized in that: The Deviate relation includes: parameter with no value, parameter with too low a value, parameter with too high a value, and parameter with unstable value.
6. The model-based aerospace system fault identification and modeling method according to claim 1, characterized in that: Damage relationships include: explosion, destruction, buckling, deformation, scratches, damage, cracking, breakage, loosening, detachment, corrosion, wear, the generation of excess material, leakage, fire, and burning.
7. The model-based aerospace system fault identification and modeling method according to claim 1, characterized in that: During fault propagation: The fault mode at this level is the cause of the fault mode at the higher level, linked by the Cause relationship. The fault mode at this level is also the impact of the fault at the next lower level, linked by the Effect relationship. The phenomenon identified by the parameter deviation at this level is the fault phenomenon of the fault mode at the higher level, linked by the Perform relationship. The final failure's impact is linked by the Final Effect relationship.
8. The model-based aerospace system fault identification and modeling method according to claim 1, characterized in that: Assign the Value attribute to the fault mode block diagram in the fault and fault propagation model to define the severity, probability of occurrence, detectability, and risk priority of the fault mode at this level.
9. The model-based aerospace system fault identification and modeling method according to claim 1, characterized in that: Conduct risk analysis and develop relevant prevention and compensation measures for each failure mode, linking them to the failure modes using the Prevent and Compensate relationships.