Model-based hierarchical modeling method for system engineering and meta-object mechanism

Abstract

The invention discloses a hierarchical modeling method for system engineering and a meta-object mechanism based on a model, and relates to the technical field of design and development of an intelligent product service system.The hierarchical modeling method comprises the steps that the construction process of the intelligent product service system is divided into four layers based on the hierarchical thought of the meta-object mechanism, and a model-based system engineering method is adopted; a meta-model layer of the system is expanded and constructed based on a system modeling language, and the intelligent product service system is constructed from a problem domain and a solution domain in the model layer, so that a systematic construction method of the intelligent product service system can be provided based on system engineering and a meta-object mechanism of the model; the problem of complexity of the intelligent product service system in a cross-domain and multi-module system is effectively solved, the meta-model of the intelligent product service system has consistency and expandability and can be expanded along with increase of systems and services, meanwhile, the model is verified through simulation software, and the system performance is improved. And the accuracy and feasibility of the intelligent product service system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of design and development of intelligent product service systems, and in particular to a hierarchical modeling method based on system engineering and meta-object mechanism of a model. Background Art

[0002] With the rapid development of technologies such as the Internet of Things, digital twins, and cyber-physical systems, traditional product service systems (PSS) have gradually evolved into smart product service systems (SPSS), aiming to provide more intelligent, efficient, and personalized services.

[0003] However, the complexity, cross-domain characteristics and internal coupling characteristics of the smart product service system (SPSS) make it difficult for traditional system engineering methods to meet its construction requirements. Therefore, how to build a top-level model that accurately describes the smart product service system and effectively manage the complex internal structure of the system has become an urgent problem in the field of design and development technology of smart product service systems. Summary of the invention

[0004] In order to solve the above problems, the present invention proposes a hierarchical modeling method based on model-based system engineering and meta-object mechanism. By combining model-based system engineering and meta-object mechanism, a systematic and hierarchical method for constructing an intelligent product service system is provided, which effectively solves the complexity problem of the intelligent product service system in a cross-domain and multi-module system. The constructed meta-model of the intelligent product service system is consistent and scalable, and can be easily expanded with the increase of systems and services. At the same time, the model can be verified by simulation software, which improves the accuracy and feasibility of constructing the intelligent product service system.

[0005] In order to achieve the above object, the present invention is implemented by the following technical solutions:

[0006] The present invention is a hierarchical modeling method based on model-based system engineering and meta-object mechanism, comprising the following operations:

[0007] According to the layered idea of ​​the meta-object mechanism, the construction process of the intelligent product service system is divided into four levels: meta-metamodel layer M3, meta-model layer M2, model layer M1 and instance layer M0;

[0008] In the meta-metamodel layer M3, the semantics and common rules of metamodel construction are defined. The class diagram, package diagram and constraint diagram tools in the system modeling language are used to define the high-level rules of the system as the content of the meta-metamodel layer M3, and the metamodel of the metamodel layer M2 is designed.

[0009] In the metamodel layer M2, the metamodel of the intelligent product service system is constructed, and the composition, structure and interaction relationship of each concept in the intelligent product service system are specified. The module definition diagram and internal module diagram in the system modeling language are used to define the general structure and internal structure of the intelligent product, and the behavior modeling tools of activity diagram, state machine diagram and sequence diagram are used to define the behavior of the intelligent product service system;

[0010] In the model layer M1, the intelligent product service system model is created based on the metamodel of the metamodel layer M2. The MagicGrid methodology in model-based system engineering is used to model the intelligent product service system from the problem domain and solution domain. Problem domain modeling includes demand modeling and definition of system use cases, and solution domain modeling includes definition of system structure, subsystem element-level modeling, and behavior modeling.

[0011] In the instance layer M0, the model of the model layer M1 is applied to the actual running system to describe the running instances and physical interactions of the smart devices. The communication between the devices is described using sequence diagrams, the state machine diagram is used to track the runtime state changes, the parameter diagram is used to monitor the physical parameters of the device, and the model of the model layer M1 is mapped and simulated in the simulation software.

[0012] A further improvement of the present invention is that: according to the MOF layering concept, the SPSS construction process is divided into four levels: SPSS meta-metamodel layer M3, SPSS meta-model layer M2, SPSS model layer M1 and SPSS instance layer M0, specifically including:

[0013] Based on the MOF hierarchical concept, the hierarchical structure of MOF and the relationship between each level are obtained, and the modeling process of complex systems is determined to be simplified through stratification;

[0014] According to the characteristics and requirements of the intelligent product service system, the hierarchical structure is determined, including four levels: meta-metamodel layer M3, meta-model layer M2, model layer M1 and instance layer M0;

[0015] Determine the function of each layer. The meta-metamodel layer M3 is used to define the semantics and general rules of model construction; the metamodel layer M2 is used to build the metamodel of the intelligent product service system; the model layer M1 is used to create the intelligent product service system model based on the metamodel of the metamodel layer M2; the instance layer M0 is used to apply the model of the model layer M1 to the actual running system;

[0016] Establish relationships between layers, including defining interfaces, data exchange formats, and interaction protocols between layers.

[0017] A further improvement of the present invention is that: in the meta-metamodel layer M3, the semantics and general rules of metamodel construction are defined, the class diagram, package diagram and constraint diagram tools in the system modeling language are used to define the high-level rules of the system as the content of the meta-metamodel layer M3, and the metamodel of the metamodel layer M2 is designed, which specifically includes:

[0018] Select the system modeling language built by the meta-metamodel layer M3;

[0019] Use class diagram, package diagram, and constraint diagram tools in the system modeling language to define high-level rules for the meta-metamodel layer M3;

[0020] Establish the semantic model of meta-metamodel layer M3;

[0021] Verify and optimize the meta-meta model layer M3, including consistency checking, integrity verification, and performance optimization.

[0022] A further improvement of the present invention is that: in the metamodel layer M2, a metamodel of the intelligent product service system is constructed, and the composition, structure and interaction relationship of each concept in the intelligent product service system are specified, the module definition diagram and internal module diagram in the system modeling language are used to define the general structure and internal structure of the intelligent product, and the behavior modeling tools of the activity diagram, state machine diagram and sequence diagram are used to define the behavior of the intelligent product service system, specifically including:

[0023] Select the modeling tool constructed by the metamodel layer M2, including the module definition diagram and internal module diagram in the system modeling language;

[0024] According to the characteristics and requirements of the intelligent product service system, define the concepts, attributes, and relationships of each element in the metamodel;

[0025] Use the module definition diagram and internal module diagram tools in the system modeling language to establish the structure of the metamodel of the intelligent product service system, including defining the hierarchical relationship, combination relationship, and interaction relationship of each element;

[0026] Verify and optimize the metamodel of the intelligent product service system, including consistency checking, integrity verification, and performance optimization.

[0027] A further improvement of the present invention is that: in the model layer M1, in the model layer M1, the intelligent product service system model is created based on the metamodel of the metamodel layer M2, and the MagicGrid methodology in the model-based system engineering is used to model the intelligent product service system from the problem domain and the solution domain, wherein the problem domain modeling includes demand modeling and definition of system use cases, and the solution domain modeling includes definition of system structure, subsystem element level modeling and behavior modeling, specifically including:

[0028] Select the modeling methodology constructed by the model layer M1, namely the MagicGrid methodology in model-based system engineering, and model SPSS from the problem domain and solution domain;

[0029] Model the problem domain according to the requirements and goals of the intelligent product service system, including requirement modeling and defining system use cases;

[0030] Perform solution domain modeling based on the problem domain model, including definition of system structure, subsystem element-level modeling, and behavior modeling;

[0031] Integrate the problem domain model and the solution domain model to form an intelligent product service system model, and verify and optimize the model.

[0032] A further improvement of the present invention is that: in the instance layer M0, the model of the model layer M1 is applied to the actual running system, the running instance and physical interaction of the intelligent device are described, the communication between the devices is described using a sequence diagram, the state machine diagram is used to track the state change during runtime, the physical parameters of the device are monitored using a parameter diagram, and the model of the model layer M1 is mapped and simulated in the simulation software, specifically including:

[0033] According to the actual needs of the model layer M1, determine the needs of the instance layer M0, including determining the type, quantity, function and physical interaction method of the smart devices;

[0034] Apply the model in the model layer M1 to the actual running system to form the instance layer M0, including mapping the elements, relationships and behaviors in the model to the actual intelligent devices and software systems;

[0035] Use sequence diagrams, state machine diagrams, and parametric diagrams to describe the physical interactions and runtime state changes between smart devices;

[0036] The model in the instance layer M0 is mapped and simulated in the simulation software, the feasibility and correctness of the model are verified through simulation, and the simulation results need to be analyzed and optimized.

[0037] The beneficial effects of the present invention are as follows: the present invention proposes a hierarchical modeling method of system engineering and meta-object mechanism based on a model, and can divide the construction process of an intelligent product service system into four levels according to the hierarchical idea of ​​the meta-object mechanism: a meta-metamodel layer M3, a meta-model layer M2, a model layer M1 and an instance layer M0; in the meta-metamodel layer M3, the semantics and general rules of meta-model construction are defined, and the class diagram, package diagram and constraint diagram tools in the system modeling language are used to define the high-level rules of the system as the content of the meta-metamodel layer M3, and the meta-model of the meta-model layer M2 is designed; in the meta-model layer M2, a meta-model of the intelligent product service system is constructed, and the composition, structure and interaction relationship of each concept in the intelligent product service system are specified, and the module definition diagram and internal module diagram in the system modeling language are used to define the general structure and internal structure of the intelligent product, and the meta-model layer M2 is used to define the general structure and internal structure of the intelligent product. The behavioral modeling tools of activity diagrams, state machine diagrams, and sequence diagrams define the behavior of the intelligent product service system; in the model layer M1, the intelligent product service system model is created based on the metamodel of the metamodel layer M2, and the MagicGrid methodology in model-based system engineering is used to model the intelligent product service system from the problem domain and the solution domain, where problem domain modeling includes demand modeling and definition of system use cases, and solution domain modeling includes definition of system structure, subsystem element-level modeling, and behavioral modeling; in the instance layer M0, the model of the model layer M1 is applied to the actual running system to describe the running instances and physical interactions of intelligent devices, use sequence diagrams to describe the communication between devices, use state machine diagrams to track runtime state changes, use parameter diagrams to monitor the physical parameters of the equipment, and map and simulate the model of the model layer M1 in the simulation software. The present invention provides a systematic and layered method for constructing an intelligent product service system by combining model-based system engineering and meta-object mechanism, which effectively solves the complexity problem of the intelligent product service system in a cross-domain and multi-module system. The constructed intelligent product service system meta-model is consistent and scalable, and can be easily expanded with the increase of systems and services. At the same time, the model can be verified by simulation software, which improves the accuracy and feasibility of constructing the intelligent product service system. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A schematic flow chart of a hierarchical modeling method based on model-based system engineering and meta-object mechanism provided in an embodiment of the present invention;

[0039] Figure 2 A schematic diagram of the SPSS hierarchical design based on MOF provided in an embodiment of the present invention;

[0040] Figure 3 A schematic diagram of the M2 layer construction analysis of the intelligent product service system provided in an embodiment of the present invention;

[0041] Figure 4 A schematic diagram of a problem domain modeling process provided by an embodiment of the present invention;

[0042] Figure 5 A schematic diagram of a domain modeling process provided by an embodiment of the present invention;

[0043] Figure 6 A schematic diagram of the M1 layer construction process provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0045] See also Figure 1 , a hierarchical modeling method based on model-based system engineering and meta-object mechanism of this embodiment includes the following steps:

[0046] S1, according to the layered idea of ​​the meta-object mechanism, the construction process of the intelligent product service system is divided into four levels: meta-metamodel layer M3, meta-model layer M2, model layer M1 and instance layer M0;

[0047] S2, in the meta-metamodel layer M3, defines the semantics and common rules for metamodel construction, uses the class diagram, package diagram, and constraint diagram tools in the system modeling language to define the high-level rules of the system as the content of the meta-metamodel layer M3, and designs the metamodel of the metamodel layer M2;

[0048] S3, in the metamodel layer M2, build the metamodel of the intelligent product service system, and specify the composition, structure and interaction relationship of each concept in the intelligent product service system, use the module definition diagram and internal module diagram in the system modeling language to define the general structure and internal structure of the intelligent product, and use the behavior modeling tools of activity diagram, state machine diagram and sequence diagram to define the behavior of the intelligent product service system;

[0049] S4, in the model layer M1, the intelligent product service system model is created based on the metamodel of the metamodel layer M2, and the MagicGrid methodology in model-based system engineering is used to model the intelligent product service system from the problem domain and the solution domain. The problem domain modeling includes demand modeling and definition of system use cases, and the solution domain modeling includes definition of system structure, subsystem element-level modeling, and behavior modeling.

[0050] S5, in the instance layer M0, the model of the model layer M1 is applied to the actual running system, describing the running instance and physical interaction of the smart device, using sequence diagrams to describe the communication between devices, using state machine diagrams to track runtime state changes, using parameter diagrams to monitor the physical parameters of the device, and mapping and simulating the model of the model layer M1 in the simulation software.

[0051] In practical applications, the present invention adopts the model-based system engineering (MBSE) method to construct the intelligent product service system. As a formal modeling method, MBSE can provide a systematic means of designing, analyzing and verifying complex systems. Compared with traditional system modeling methods, MBSE can model with a process covering the entire life cycle, and at each stage of system construction, it can display the internal information such as the functions and structures of the system in a graphical manner. By introducing the metamodel and using the meta-object mechanism (MOF), the system modeling process is divided into instance, model, metamodel, meta-metamodel and other levels, and each level is defined and modeled respectively, and the construction of the intelligent product service system is efficiently realized from multiple angles and multiple levels.

[0052] See also Figure 2 According to the MOF layered concept, the SPSS construction process is divided into four levels: SPSS meta-metamodel layer M3, SPSS meta-model layer M2, SPSS model layer M1 and SPSS instance layer M0, specifically including:

[0053] Based on the MOF hierarchical concept, the hierarchical structure of MOF and the relationship between each level are obtained, and the modeling process of complex systems is determined to be simplified through stratification;

[0054] According to the characteristics and requirements of the intelligent product service system, the hierarchical structure is determined, including four levels: meta-metamodel layer M3, meta-model layer M2, model layer M1 and instance layer M0;

[0055] Determine the function of each layer. The meta-metamodel layer M3 is used to define the semantics and general rules of model construction; the metamodel layer M2 is used to build the metamodel of the intelligent product service system; the model layer M1 is used to create the intelligent product service system model based on the metamodel of the metamodel layer M2; the instance layer M0 is used to apply the model of the model layer M1 to the actual running system;

[0056] Establish relationships between layers, including defining interfaces, data exchange formats, and interaction protocols between layers.

[0057] Among them, SPSS can be divided into four layers according to the layered idea provided by MOF, namely SPSS meta-metamodel layer M3, SPSS meta-model layer M2, SPSS model layer M1 and SPSS instance layer M0.

[0058] Specifically, the M3 layer is the SPSS meta-metamodel layer. When building an intelligent product service system, the M3 layer can define the semantics and general rules of model construction. The M2 layer is the SPSS metamodel layer, which is used to build the metamodel of the intelligent product service system. These metamodels not only define the composition and structure of each concept in the intelligent product service system, but also define the interactions and relationships between them. The M1 layer is the SPSS model layer. This layer is a specific description of the intelligent product service system and is the core part of the model hierarchy. It shows the specific characteristics of each instance, including requirements, functions, subsystems, etc. The M0 layer is the SPSS instance layer. At the M0 layer, the content defined by the model and metamodel can be used as an actual system. This layer is the final operating layer of the intelligent product service system, that is, the model design scheme corresponding to the intelligent product service system.

[0059] In the meta-metamodel layer M3, the semantics and general rules of metamodel construction are defined, and the class diagram, package diagram and constraint diagram tools in the system modeling language are used to define the high-level rules of the system as the content of the meta-metamodel layer M3, and the metamodel of the metamodel layer M2 is designed, which specifically includes:

[0060] Select the system modeling language built by the meta-metamodel layer M3;

[0061] Use class diagram, package diagram, and constraint diagram tools in the system modeling language to define high-level rules for the meta-metamodel layer M3;

[0062] Establish the semantic model of meta-metamodel layer M3;

[0063] Verify and optimize the meta-meta model layer M3, including consistency checking, integrity verification, and performance optimization.

[0064] Among them, the meta-metamodel domain can provide a unified modeling standard for the intelligent product models in the metamodel domain, making the entire intelligent product service system consistent, scalable and maintainable. By standardizing metamodels and constraints, it can ensure that the metamodels of different intelligent products remain compatible and can be easily expanded as systems and services increase.

[0065] In MBSE, the System Modeling Language (SysML) can provide a common language and rules for describing and defining the common elements and behaviors of the intelligent product service system model. SysML modeling diagrams, namely class diagrams, package diagrams, and constraint diagrams, can define the high-level rules of the system and serve as the M3 layer.

[0066] In order to apply the M3 layer to the construction of the intelligent product service system, a basic package for system modeling can be created to organize all metamodels and determine the module division of the intelligent product service system model in the package diagram.

[0067] See also Figure 3In the metamodel layer M2, the metamodel of the intelligent product service system is constructed, and the composition, structure and interaction relationship of each concept in the intelligent product service system are specified. The module definition diagram and internal module diagram in the system modeling language are used to define the general structure and internal structure of the intelligent product, and the behavior modeling tools of the activity diagram, state machine diagram and sequence diagram are used to define the behavior of the intelligent product service system, which specifically includes:

[0068] Select the modeling tool constructed by the metamodel layer M2, including the module definition diagram and internal module diagram in the system modeling language;

[0069] According to the characteristics and requirements of the intelligent product service system, define the concepts, attributes, and relationships of each element in the metamodel;

[0070] Use the module definition diagram and internal module diagram tools in the system modeling language to establish the structure of the metamodel of the intelligent product service system, including defining the hierarchical relationship, combination relationship, and interaction relationship of each element;

[0071] Verify and optimize the metamodel of the intelligent product service system, including consistency checking, integrity verification, and performance optimization.

[0072] When building an intelligent product service system, the metamodel domain can define the structure and rules of the models in the system and establish metamodels of various models in the intelligent product service system. Each metamodel defines the basic properties, behaviors, relationships, interfaces, etc. of different categories of products, services or system components. At the same time, SysML can be used to build the M2 layer of the intelligent product service system.

[0073] In the model layer M1, in the model layer M1, the intelligent product service system model is created based on the metamodel of the metamodel layer M2, and the MagicGrid methodology in the model-based system engineering is used to model the intelligent product service system from the problem domain and the solution domain, wherein the problem domain modeling includes demand modeling and definition of system use cases, and the solution domain modeling includes definition of system structure, subsystem element level modeling and behavior modeling, specifically including:

[0074] Select the modeling methodology constructed by the model layer M1, namely the MagicGrid methodology in model-based system engineering, and model SPSS from the problem domain and solution domain;

[0075] Model the problem domain according to the requirements and goals of the intelligent product service system, including requirement modeling and defining system use cases;

[0076] Perform solution domain modeling based on the problem domain model, including definition of system structure, subsystem element-level modeling, and behavior modeling;

[0077] Integrate the problem domain model and the solution domain model to form an intelligent product service system model, and verify and optimize the model.

[0078] See also Figure 4 , the modeling of the problem domain can be divided into two key modules: black box and white box. First, the demand modeling is required. The demand comes from the key information provided by stakeholders. The attribute information is displayed in the form of a demand diagram through the demand element derive (Derive), satisfy (Satisfy), etc. The second is to define the system use case. In the early stage of modeling, the functional requirements can be analyzed and used as the basis to define the system use case to build the use case diagram. The third is the system use case analysis. The system use case analysis mainly focuses on analyzing the behavior to build a dynamic behavior model. The black box stage mainly focuses on the interaction between the system and external participants, which can effectively capture various activities in the system and its interaction with the external environment. The fourth is to define the system context. The system environment is designed to depict the external perspective of the system in the use case environment. When creating the system environment, it is first necessary to determine the role and function of the selected system element set in a specific environment, so that the top-level functional modules participating in each system environment can be identified, and the port information between modules can be specified, the module properties can be defined, and how each module in the system element interacts with the external environment through different types of flows, and finally the interface definition of the module is introduced. The fifth is function-flow attribute analysis. After analyzing the system requirements, use cases, and context, it is necessary to perform function-flow attribute analysis on the system and map the specific functional requirements of the system with the flow attributes. This process characterizes the input and output of the system flow attributes through the flow ports and proxy ports of the system modeling language. When performing function-flow attribute analysis, it is necessary to define the ports according to the flow attributes based on the specific functional requirements of the system, and define the direction of the ports according to the logical transfer direction of the functions in the components after identifying the flow attribute types of the components or subsystems. By using activity diagrams or module definition diagrams, the flow paths of flow attributes within the system components can be mapped, and the flow attributes start at a function of a component and end at a specific function of a specific component.

[0079] For white box model analysis, the functions and operations that the system needs to perform can be determined. At the same time, the mapping relationship between functional requirements and interactive information between systems can be realized through proxy ports. Functional analysis can clarify the tasks, behaviors and interaction methods that the system needs to implement, ensuring that the system design meets the requirements and performance goals. In the white box stage, the interactive logic, functional attributes and dynamic behavior of the system can be analyzed to identify the key functions of the system, define the functional blocks of the system, and decompose them into smaller functional modules, while identifying and mapping how these functions depend on the dynamics of various flows. The complete trajectory and dynamic characteristics of information exchange can be ensured through BDD and IBD.

[0080] See also Figure 5 , which is the solution domain modeling process of the embodiment of the present invention. Specifically, the first thing is to determine the system requirements. The second thing is to define the subsystem. All logical subsystems of the system can be divided in a single-layer structure. The subsystem is a component composed of a set of functions. Each subsystem has one or more functions. These subsystems come from the functional modules in the problem domain, which can ensure the logical consistency of the subsystem design. The third is to define the system structure. Modeling can be performed based on the defined subsystems, and the ports and data flows of the subsystems can be defined. The module definition diagram (BDD) and the internal module diagram (IBD) are used to describe the internal architecture of the subsystem in detail. The fourth is subsystem element-level modeling. By analyzing the solution architecture of each subsystem, the elements at the subsystem level are modeled and described from the two dimensions of behavior and structure. For a subsystem, its structural model is one or more possible solutions to specific needs. BDD can be used to define the design module of the subsystem and ensure that it matches the attribute characteristics of the previously defined subsystem module.

[0081] Furthermore, subsystem behavior modeling can be carried out to ensure the integrity of the requirements-structure-behavior system design. The subsystem behavior model can be integrated into the behavior model of the entire system to verify whether each subsystem can communicate effectively through the defined compatible ports and whether their interaction activities conform to the behavior logic of the entire system. The final M1 layer construction process is as follows Figure 6 shown.

[0082] In the instance layer M0, the model of the model layer M1 is applied to the actual running system, the running instance and physical interaction of the intelligent device are described, the communication between the devices is described using a sequence diagram, the state machine diagram is used to track the state changes during runtime, the physical parameters of the device are monitored using a parameter diagram, and the model of the model layer M1 is mapped and simulated in the simulation software, specifically including:

[0083] According to the actual needs of the model layer M1, determine the needs of the instance layer M0, including determining the type, quantity, function and physical interaction method of the smart devices;

[0084] Apply the model in the model layer M1 to the actual running system to form the instance layer M0, including mapping the elements, relationships and behaviors in the model to the actual intelligent devices and software systems.

[0085] Use sequence diagrams, state machine diagrams, and parametric diagrams to describe the physical interactions and runtime state changes between smart devices;

[0086] The model in the instance layer M0 is mapped and simulated in the simulation software, the feasibility and correctness of the model are verified through simulation, and the simulation results need to be analyzed and optimized.

[0087] Through the introduction of the above embodiments, the present invention can divide the construction process of the intelligent product service system into four levels according to the hierarchical idea of ​​the meta-object mechanism through a hierarchical modeling method based on model-based system engineering and meta-object mechanism: meta-metamodel layer M3, metamodel layer M2, model layer M1 and instance layer M0; in the meta-metamodel layer M3, the semantics and general rules of metamodel construction are defined, and the class diagram, package diagram and constraint diagram tools in the system modeling language are used to define the high-level rules of the system as the content of the meta-metamodel layer M3, and the metamodel of the metamodel layer M2 is designed; in the metamodel layer M2, the metamodel of the intelligent product service system is constructed, and the composition, structure and interaction relationship of each concept in the intelligent product service system are specified, the module definition diagram and internal module diagram in the system modeling language are used to define the general structure and internal structure of the intelligent product, and the active The behavioral modeling tools of dynamic diagrams, state machine diagrams and sequence diagrams define the behavior of the intelligent product service system; in the model layer M1, the intelligent product service system model is created based on the metamodel of the metamodel layer M2, and the MagicGrid methodology in model-based system engineering is used to model the intelligent product service system from the problem domain and the solution domain. Among them, problem domain modeling includes demand modeling and definition of system use cases, and solution domain modeling includes definition of system structure, subsystem element-level modeling and behavioral modeling; in the instance layer M0, the model of the model layer M1 is applied to the actual running system to describe the running instances and physical interactions of intelligent devices, use sequence diagrams to describe the communication between devices, use state machine diagrams to track runtime state changes, use parameter diagrams to monitor the physical parameters of the equipment, and the model of the model layer M1 is mapped and simulated in the simulation software. The present invention provides a systematic and layered method for constructing an intelligent product service system by combining model-based system engineering and meta-object mechanism, which effectively solves the complexity problem of the intelligent product service system in a cross-domain and multi-module system. The constructed intelligent product service system meta-model is consistent and scalable, and can be easily expanded with the increase of systems and services. At the same time, the model can be verified by simulation software, which improves the accuracy and feasibility of constructing the intelligent product service system.

[0088] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have the same meaning as in the context of the prior art, and will not be interpreted with an idealized or overly formal meaning unless defined similarly here.

[0089] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A hierarchical modeling method based on model-based system engineering and meta-object mechanism, characterized in that: The steps include: According to the layered idea of ​​the meta-object mechanism, the construction process of the intelligent product service system is divided into four levels: meta-metamodel layer M3, meta-model layer M2, model layer M1 and instance layer M0; In the meta-metamodel layer M3, the semantics and common rules of metamodel construction are defined. The class diagram, package diagram and constraint diagram tools in the system modeling language are used to define the high-level rules of the system as the content of the meta-metamodel layer M3, and the metamodel of the metamodel layer M2 is designed. In the metamodel layer M2, the metamodel of the intelligent product service system is constructed, and the composition, structure and interaction relationship of each concept in the intelligent product service system are specified. The module definition diagram and internal module diagram in the system modeling language are used to define the general structure and internal structure of the intelligent product, and the behavior modeling tools of activity diagram, state machine diagram and sequence diagram are used to define the behavior of the intelligent product service system; In the model layer M1, the intelligent product service system model is created based on the metamodel of the metamodel layer M2. The MagicGrid methodology in model-based system engineering is used to model the intelligent product service system from the problem domain and solution domain. Problem domain modeling includes demand modeling and definition of system use cases, and solution domain modeling includes definition of system structure, subsystem element-level modeling, and behavior modeling. In the instance layer M0, the model of the model layer M1 is applied to the actual running system to describe the running instances and physical interactions of the smart devices. The communication between the devices is described using sequence diagrams, the state machine diagram is used to track the runtime state changes, the parameter diagram is used to monitor the physical parameters of the device, and the model of the model layer M1 is mapped and simulated in the simulation software.

2. A hierarchical modeling method based on model-based system engineering and meta-object mechanism according to claim 1, characterized in that: According to the MOF layered concept, the SPSS construction process is divided into four levels: SPSS meta-metamodel layer M3, SPSS meta-model layer M2, SPSS model layer M1 and SPSS instance layer M0, specifically including: Based on the MOF hierarchical concept, the hierarchical structure of MOF and the relationship between each level are obtained, and the modeling process of complex systems is determined to be simplified through stratification; According to the characteristics and requirements of the intelligent product service system, the hierarchical structure is determined, including four levels: meta-metamodel layer M3, meta-model layer M2, model layer M1 and instance layer M0; Determine the function of each layer. The meta-metamodel layer M3 is used to define the semantics and general rules of model construction; the metamodel layer M2 is used to build the metamodel of the intelligent product service system; the model layer M1 is used to create the intelligent product service system model based on the metamodel of the metamodel layer M2; the instance layer M0 is used to apply the model of the model layer M1 to the actual running system; Establish relationships between layers, including defining interfaces, data exchange formats, and interaction protocols between layers.

3. A hierarchical modeling method based on model-based system engineering and meta-object mechanism according to claim 1, characterized in that: In the meta-metamodel layer M3, the semantics and general rules of metamodel construction are defined, and the class diagram, package diagram and constraint diagram tools in the system modeling language are used to define the high-level rules of the system as the content of the meta-metamodel layer M3, and the metamodel of the metamodel layer M2 is designed, which specifically includes: Select the system modeling language built by the meta-metamodel layer M3; Use class diagram, package diagram, and constraint diagram tools in the system modeling language to define high-level rules for the meta-metamodel layer M3; Establish the semantic model of the meta-metamodel layer M3; Verify and optimize the meta-meta model layer M3, including consistency checking, integrity verification, and performance optimization.

4. A hierarchical modeling method based on model-based system engineering and meta-object mechanism according to claim 1, characterized in that: In the metamodel layer M2, a metamodel of the intelligent product service system is constructed, and the composition, structure and interaction relationship of each concept in the intelligent product service system are specified. The module definition diagram and internal module diagram in the system modeling language are used to define the general structure and internal structure of the intelligent product, and the behavior modeling tools such as activity diagram, state machine diagram and sequence diagram are used to define the behavior of the intelligent product service system, which specifically includes: Select the modeling tool constructed by the metamodel layer M2, including the module definition diagram and internal module diagram in the system modeling language; According to the characteristics and requirements of the intelligent product service system, define the concepts, attributes, and relationships of each element in the metamodel; Use the module definition diagram and internal module diagram tools in the system modeling language to establish the structure of the metamodel of the intelligent product service system, including defining the hierarchical relationship, combination relationship, and interaction relationship of each element; Verify and optimize the metamodel of the intelligent product service system, including consistency checking, integrity verification, and performance optimization.

5. The hierarchical modeling method based on model-based system engineering and meta-object mechanism according to claim 1, characterized in that: In the model layer M1, in the model layer M1, the intelligent product service system model is created based on the metamodel of the metamodel layer M2, and the MagicGrid methodology in the model-based system engineering is used to model the intelligent product service system from the problem domain and the solution domain, wherein the problem domain modeling includes demand modeling and definition of system use cases, and the solution domain modeling includes definition of system structure, subsystem element level modeling and behavior modeling, specifically including: Select the modeling methodology constructed by the model layer M1, namely the MagicGrid methodology in model-based system engineering, and model SPSS from the problem domain and solution domain; Model the problem domain according to the requirements and goals of the intelligent product service system, including requirement modeling and defining system use cases; Perform solution domain modeling based on the problem domain model, including definition of system structure, subsystem element-level modeling, and behavior modeling; Integrate the problem domain model and the solution domain model to form an intelligent product service system model, and verify and optimize the model.

6. A hierarchical modeling method based on model-based system engineering and meta-object mechanism according to claim 1, characterized in that: In the instance layer M0, the model of the model layer M1 is applied to the actual running system, the running instance and physical interaction of the intelligent device are described, the communication between the devices is described using a sequence diagram, the state machine diagram is used to track the state changes during runtime, the physical parameters of the device are monitored using a parameter diagram, and the model of the model layer M1 is mapped and simulated in the simulation software, specifically including: According to the actual needs of the model layer M1, determine the needs of the instance layer M0, including determining the type, quantity, function and physical interaction method of the smart devices; Apply the model in the model layer M1 to the actual running system to form the instance layer M0, including mapping the elements, relationships and behaviors in the model to the actual intelligent devices and software systems; Use sequence diagrams, state machine diagrams, and parametric diagrams to describe the physical interactions and runtime state changes between smart devices; The model in the instance layer M0 is mapped and simulated in the simulation software, the feasibility and correctness of the model are verified through simulation, and the simulation results need to be analyzed and optimized.

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