A sysML-based deep space exploration field collaborative design model delivery method

Abstract

The application discloses a kind of based on SysML's deep space exploration field collaborative design model delivery method under issue, including the following steps: utilize system modeling language to build demand, function, interface and architecture view, encapsulation design model data package;Model element is semantically identified and is associated with analytical resolution, determine the resolution issue strategy of model;According to the permission management rule, determine terminal permission, generate online delivery data package;Export model data as extensible markup language file, generate offline delivery data package;Terminal unpacking data, load and restore model;Analysis influence path of model change in design process;Terminal returns model data and fusion, executes model version management.The application realizes the efficient collaborative delivery of model, significantly improves the efficiency and safety of multi-territory collaborative design in the field of deep space exploration.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of deep space exploration, and particularly relates to a SysML-based deep space exploration field collaborative design model delivery method. BACKGROUND

[0002] Currently, deep space exploration missions are developing in the direction of high system complexity, multiple collaboration units and long task cycle, and cross-regional, multi-specialty collaborative design modes for system engineering design are increasingly valued. Traditional system design methods centered on documents usually rely on manual transmission of design documents or discrete data files, which can easily cause information lag, design errors and data inconsistency, and are difficult to meet the requirements of high-efficiency collaboration and data accuracy of deep space exploration engineering.

[0003] With the rise of model-driven system engineering methods, system modeling languages have gradually become an important technical means to solve the complexity of system engineering design. In the prior art, system modeling languages are usually used to express system architecture and functional requirements, and then the model data is distributed to multiple collaboration units through discrete data files. However, this model distribution method often ignores the security management, data version control and model change impact analysis requirements of multi-specialty, multi-regional collaborative design, resulting in inconsistent model versions, difficult to trace design changes, and obvious data security risks and low efficiency.

[0004] Currently, some design teams try to improve collaboration efficiency through online collaboration, but existing online model collaboration technologies mostly focus on real-time data transmission functions themselves and fail to propose effective technical solutions for model data decomposition management, precise permission control and version fine-grained tracking, making it difficult to solve the integration problem of online and offline delivery mechanisms. At the same time, existing model change analysis solutions are mostly limited to static manual inspection or simple model element comparison, and do not effectively utilize the semantic association relationships between model elements for accurate change impact analysis, so the accuracy and efficiency of model change tracking in the design process need to be improved.

[0005] Therefore, how to provide a SysML-based deep space exploration field collaborative design model delivery method is a problem that needs to be solved by those skilled in the art. SUMMARY

[0006] One purpose of the present application is to propose a SysML-based deep space exploration field collaborative design model delivery method, aiming at the problems of inaccurate model version control, difficult to trace model changes in the design process, and low efficiency of multi-region collaborative design in the existing deep space exploration field design model delivery, a technical solution of constructing a multi-view associated model and encapsulating, model element semantic association analysis and fine decomposition delivery, online and offline delivery mechanism fusion, model change impact path analysis in the design process, and fine-grained model version management is proposed, the present application has the beneficial effects of significantly improving the model delivery accuracy, design collaboration efficiency and model data security.

[0007] According to the SysML-based deep space exploration field collaborative design model delivery method of the embodiment of the present application, comprising:

[0008] According to the overall design requirements of the probe in the deep space exploration task, a collaborative design model containing requirement view, function view, interface view and architecture view is constructed by using system modeling language, and the data encapsulation of the design model is completed according to the association relationship between the views, and the encapsulated data package is formed;

[0009] The semantic recognition and association analysis of the model elements of the completed encapsulated data package are carried out, the decomposition delivery strategy of the model is determined according to the design requirements of the deep space exploration task, and the model data to be delivered is obtained;

[0010] According to the preset permission management rule, the access permission of the model receiving terminal is determined, the model data package to be delivered is transmitted to the multiple terminals with access permission, and the online delivered data package is generated;

[0011] According to the preset data export rule, the model data package to be delivered is exported into a file format that can be used offline, and is transmitted to the target terminal through a physical medium, and the offline delivered data package is generated;

[0012] The model receiving terminal restores the complete design model structure according to the received online delivered data package or offline delivered data package and loads it to the local;

[0013] According to the semantic association relationship between the change data generated in the design process and the model elements, the specific model elements and the influence path involved in the model change in the design process are analyzed, and the change impact analysis result is obtained;

[0014] After the receiving terminal completes the design of the respective model data, the updated model data is returned to the unified model delivery terminal, and the final delivery model is obtained;

[0015] According to the preset model version management rule, the version record and management operation of the fused final delivery model are performed.

[0016] Optionally, the system modeling language is used to build a collaborative design model including a requirement view, a function view, an interface view and an architecture view according to overall design requirements of a probe in a deep space exploration mission, data encapsulation of the design model is completed according to an association relationship between the views, and an encapsulated data package is formed, specifically as follows:

[0017] The requirement view, the function view, the interface view and the architecture view are respectively established based on the system modeling language, and each view respectively defines the model elements belonging to the view;

[0018] The semantic association relationship between the requirement view and the function view is analyzed, and a mapping relationship between the model elements in the requirement view and the model elements in the function view is determined;

[0019] The semantic association relationship between the function view and the interface view is analyzed, and a mapping relationship between the model elements in the function view and the model elements in the interface view is determined;

[0020] The semantic association relationship between the interface view and the architecture view is analyzed, and a mapping relationship between the model elements in the interface view and the model elements in the architecture view is determined;

[0021] According to the mapping relationship, all the model elements and the semantic association relationship among the model elements contained in the requirement view, the function view, the interface view and the architecture view are encapsulated into a complete data package, and the encapsulated data package is obtained.

[0022] Optionally, the encapsulated data package is subjected to semantic recognition and association analysis of model elements, a model decomposition and distribution strategy is determined according to design requirements of the deep space exploration mission, and model data to be distributed is obtained, specifically as follows:

[0023] Based on the system modeling language, the semantic type of each model element in the encapsulated data package is recognized one by one, including system requirements, specific function implementation, interface definition or architecture composition, and each model element is given a unique identification code;

[0024] According to the semantic type of each model element after recognition, the direct association relationship between the model elements in the upper and lower levels, between the horizontal function units and between the interface connections is determined one by one, and a preliminary model element association relationship network with a multi-level structure is obtained;

[0025] Based on the preliminary model element association relationship network, the model element association relationship is subjected to depth analysis, and the direct association and indirect association model elements of each model element are recognized;

[0026] Based on the determined model element association relationship network, a design decomposition boundary condition is determined, the specific requirement range of the model elements by the task requirements is comprehensively analyzed, and the cutting nodes of the model elements between the task stages and the data interface positions between the design specialties are determined.

[0027] According to the decomposition boundary condition and the cutting node, each model element in the packaged data packet is oriented split and reorganized to form the to-be-delivered model data.

[0028] Optionally, the access permission of the model receiving terminal is determined according to the preset permission management rule, the to-be-delivered model data packet is transmitted to the multiple terminals with the access permission, and the online delivery data packet is generated, specifically:

[0029] According to the preset permission management rule, a model collaborative design permission database is established, and the user role type, department affiliation, regional distribution and identity authentication information of all model receiving terminals participating in the collaborative design are recorded in the database;

[0030] According to the user role type recorded in the model collaborative design permission database, the viewing, editing, delivering, delivering and merging permissions of each user role type at the model element level are parsed one by one, and the permission configuration file corresponding to each model receiving terminal is generated according to the mapping relationship between the permission content and the model element;

[0031] Based on the permission configuration file, a permission verification code with a unique terminal identity is generated for each model receiving terminal, and the permission verification code includes an explicit model element access range, an operable model element list, an executable operation type and a permission effective time period;

[0032] Based on the real-time collaborative design platform, a secure network connection for model data interaction is established, and the secure network connection includes a real-time data transmission link between the server port and the multiple model receiving terminal ports after identity authentication and permission verification;

[0033] Through the real-time data transmission link, the to-be-delivered model data packet with the permission verification code is transmitted to each model receiving terminal that has completed identity authentication and permission verification in the form of encrypted data stream, and the model receiving terminal receives and verifies the encrypted data stream to obtain the online delivery data packet after decryption.

[0034] Optionally, the to-be-delivered model data packet is exported to a file format that can be used offline according to the preset data export rule, and is transmitted to the target terminal through a physical medium to generate an offline delivery data packet, specifically:

[0035] According to the preset data export rule, the file format of the to-be-delivered model data packet is determined as an extensible markup language format;

[0036] According to the determined file format, each model element in the to-be-delivered model data packet is parsed one by one to generate data records corresponding to the model elements, each data record explicitly including a unique identification code of the model element, a semantic type to which the model element belongs, a definition of an association relationship, and specific model element content;

[0037] The generated data records are sequentially encapsulated according to a model encapsulation sequence, which is determined by the upper and lower association relationships of the model elements and data requirements in the design stage;

[0038] Data consistency verification is performed on the encapsulated model data records, including comparison of the completeness of the model data records, the consistency of the association relationships between the model elements, and the compliance of the data format, and after the verification is passed, data compression processing is performed on the encapsulated model data records to generate a final offline delivery file;

[0039] The final offline delivery file is stored in a portable physical storage medium according to a preset physical storage rule, and the physical storage medium is delivered to a target terminal through a controlled physical delivery process, and after the target terminal verifies the physical storage medium identification and data integrity, the offline delivery data packet is obtained.

[0040] Optionally, the model receiving terminal restores the complete design model structure and loads it locally according to the received online delivery data packet or offline delivery data packet, specifically:

[0041] The model receiving terminal calls a data unpacking algorithm corresponding to the data packet type according to the received data packet type, and the data unpacking algorithm includes data decryption, data decompression, and data format analysis;

[0042] When the data decryption step is performed, a data decryption key is obtained from the local according to a preset key management rule, and a decryption operation is performed on the data packet to obtain a decrypted data file;

[0043] When the data decompression step is performed on the decrypted data file, data decompression processing is performed according to a preset data compression algorithm to obtain a decompressed complete data file;

[0044] When the data format analysis step is performed on the decompressed complete data file, each model element data record in the data file is parsed one by one to obtain a model element unique identification code, a semantic type, an association relationship definition, and specific model element content, and the association network structure between the model elements is restored;

[0045] According to the correlation network structure between the restored model elements, each parsed model element and its correlation is mapped to the local modeling environment one by one through the locally pre-installed system modeling language model loading engine, the complete design model structure is reconstructed and loaded to the local environment of the model receiving terminal, and the restoration and loading operation of the model structure is completed.

[0046] Optionally, the specific model elements and influence paths involved in the model change in the design process are analyzed according to the semantic correlation between the model change data generated in the design process and the model elements, and a change influence analysis result is obtained, specifically:

[0047] The model change data generated in the model design process is monitored in real time, the unique identification code of the model element that has changed, the semantic content before and after the change, and the change type are obtained;

[0048] According to the obtained model change data, the specific model element that has changed is located according to the model element unique identification code, and the position of the model element in the requirement view, the function view, the interface view and the architecture view is determined through the model element semantic type analysis;

[0049] According to the model element semantic correlation network established in advance, the model elements directly correlated and influenced by the change are analyzed and identified, and the unique identification code of the directly correlated and influenced model elements and the correlation type thereof are determined;

[0050] On the basis of identifying the directly correlated and influenced model elements, the indirectly correlated and influenced model elements are analyzed and identified step by step, and the unique identification code, semantic type, correlation path and correlation strength of all indirectly correlated and influenced model elements are determined;

[0051] According to the correlation network structure of the changed model elements, the directly correlated and influenced model elements and the indirectly correlated and influenced model elements determined by the analysis, a change influence analysis result is formed.

[0052] Optionally, after the receiving terminal completes the respective model data design, the updated model data is transmitted back to the unified model delivery terminal based on the change influence analysis result, and a final delivery model is obtained, specifically:

[0053] After the model receiving terminal completes the local design task, the updated model data packet is generated according to the preset data update rule based on the change influence analysis result;

[0054] According to the preset model data transmission protocol, the data consistency of the updated model data packet is self-checked, and the model element data integrity, semantic type accuracy and correlation validity are verified;

[0055] The updated model data packet after completing the consistency self-check is subjected to data encryption processing, and a unique identity of a corresponding model receiving terminal is added as a data source mark to generate an encrypted data packet with the source mark;

[0056] According to a pre-established data transmission link of the real-time collaborative design platform, the encrypted data packet with the source mark is returned to a unified model delivery terminal.

[0057] The model delivery terminal performs data decryption and source verification steps after receiving the returned data packet.

[0058] Optionally, the version record and management operation of the fused final delivery model are performed according to the preset model version management rule, specifically:

[0059] Each model element in the fused final delivery model is respectively given an independent version mark, and the version mark records the change history of the model element in the entire design collaboration process to form a fine-grained version record of the model element.

[0060] According to the fine-grained version record of the model element, the model element range involved in each model update, the change of the association relationship between the model elements, and the before-and-after states of the model element change are determined.

[0061] The fine-grained version record is subjected to difference comparison to identify the changes of each historical version in the semantic type, the association relationship, the interface definition, or the architecture composition of the specific model element, and generate intuitive difference records.

[0062] Based on the fine-grained version record and the difference record, the model version required by each stage of the design task in the model delivery process is automatically matched.

[0063] Based on the fine-grained version record, a multi-dimensional version view of the model version is generated in real time.

[0064] The beneficial effects of the present application are:

[0065] (1) The present application realizes the precise packaging and efficient delivery of the design model data by adopting the model multi-view integrated packaging based on the system modeling language, the semantic association analysis, and the model element decomposition delivery technology, effectively improves the model delivery precision and the design efficiency, and enhances the security and collaboration in the model delivery process.

[0066] (2) The application realizes accurate recording and tracing of model change data by designing a fine-grained version management mechanism of model elements, significantly improves the accuracy and efficiency of model change analysis in the design process, and shows better adaptability and stability in the multi-specialty cross-regional deep space exploration collaborative design environment.

[0067] (3) In terms of model data security management and version fine management, the application effectively solves the problems of model data version confusion, difficulty in tracing model changes in the design process, and prominent data security risks in the prior art, breaks through the technical bottleneck of the integration of online and offline delivery in the traditional model collaborative delivery method, significantly improves the design collaborative efficiency, and effectively improves the complex system design capability in the field of deep space exploration. BRIEF DESCRIPTION OF DRAWINGS

[0068] The accompanying drawings are included to provide a further understanding of the application, and constitute a part of the specification, together with the embodiments of the application, to explain the application, and do not constitute a limitation on the application. In the drawings:

[0069] Fig. 1 A general implementation flowchart of a SysML-based deep space exploration field collaborative design model delivery method is proposed for the application;

[0070] Fig. 2 A model element semantic recognition and decomposition delivery flowchart of a SysML-based deep space exploration field collaborative design model delivery method is proposed for the application;

[0071] Fig. 3 A model version management and model change influence domain analysis structure diagram in the design process of a SysML-based deep space exploration field collaborative design model delivery method is proposed for the application. DETAILED DESCRIPTION

[0072] The application will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, and only illustrate the basic structure of the application in a schematic manner, and therefore only show the components related to the application.

[0073] REFERENCE Figs. 1-3 A SysML-based deep space exploration field collaborative design model delivery method, comprising:

[0074] According to the overall design requirements of the probe in the deep space exploration task, a collaborative design model containing requirement view, function view, interface view and architecture view is constructed by using system modeling language, the data encapsulation of the design model is completed according to the association relationship between the views, and the encapsulated data packet is formed;

[0075] The semantic recognition and associated analysis of the model elements of the encapsulated data packet are performed, a model decomposition and delivery strategy is determined according to the design requirements of the deep space exploration task, and model data to be delivered is obtained;

[0076] According to the preset permission management rule, the access permission of the model receiving terminal is determined, the model data packet to be delivered is transmitted to the terminals with the access permission, and the data packet for online delivery is generated;

[0077] According to the preset data export rule, the model data packet to be delivered is exported into a file format that can be used offline, and is transmitted to the target terminal through a physical medium, and the data packet for offline delivery is generated;

[0078] The model receiving terminal restores the complete design model structure according to the received data packet for online delivery or the data packet for offline delivery, and loads the complete design model structure to the local terminal;

[0079] According to the semantic association relationship between the change data and the model elements generated in the design process, the specific model elements and the influence path involved in the model change in the design process are analyzed, and the change influence analysis result is obtained;

[0080] After the model data of the receiving terminal is designed, the updated model data is transmitted back to the unified model delivery terminal, and the final delivery model is obtained;

[0081] According to the preset model version management rule, the version record and management operation of the fused final delivery model are performed.

[0082] Through the semantic recognition and associated analysis of the model elements of the multi-view model encapsulation based on the system modeling language, the precise data encapsulation of the design model and the clear model decomposition and delivery strategy can be realized. Meanwhile, through the collaborative application of the permission management rule and the data export rule, the deep fusion of the online and offline delivery modes of the model data can be realized. Through the deep analysis of the model change data and the semantic association relationship, the model elements and the influence path involved in the model change in the design process can be accurately identified, and the accuracy of the model change analysis and the design traceability efficiency in the design process can be significantly improved. In addition, through the model element fine-grained version management and the version difference comparison technology, the version control accuracy and the model data traceability are enhanced.

[0083] In the embodiment, according to the overall design requirements of the probe in the deep space exploration task, a collaborative design model including a requirement view, a function view, an interface view and an architecture view is constructed by using the system modeling language, the data encapsulation of the design model is completed according to the association relationship between the views, and the encapsulated data packet is formed. Specifically,

[0084] The requirement view, the function view, the interface view and the architecture view are respectively established based on the system modeling language, and each view respectively defines the model elements belonging to the view;

[0085] The semantic association relationship between the requirement view and the function view is analyzed, and a mapping relationship between the model elements in the requirement view and the model elements in the function view is determined;

[0086] The semantic association relationship between the function view and the interface view is analyzed, and a mapping relationship between the model elements in the function view and the model elements in the interface view is determined;

[0087] The semantic association relationship between the interface view and the architecture view is analyzed, and a mapping relationship between the model elements in the interface view and the model elements in the architecture view is determined;

[0088] According to the mapping relationship, all the model elements and the semantic association relationship among the model elements contained in the requirement view, the function view, the interface view and the architecture view are unified and encapsulated into a complete data package, and the encapsulated data package is obtained.

[0089] By respectively establishing the requirement view, the function view, the interface view and the architecture view based on the system modeling language, and respectively defining the model elements in each view, the structured encapsulation of the design model data can be realized; by analyzing the semantic association relationship between the model elements in each view and determining the specific mapping relationship, the association relationship between the model elements is clear and specific, thereby effectively ensuring the integrity and accuracy of the design model data encapsulation, which is beneficial to the accurate delivery and delivery of the subsequent design model data, and improves the data consistency and collaboration efficiency in the multi-specialty collaborative design in the deep space exploration field.

[0090] In the embodiment, the semantic recognition and association analysis of the model elements of the encapsulated data package are performed, the decomposition and delivery strategy of the model is determined according to the design requirements of the deep space exploration task, and the model data to be delivered is obtained, specifically:

[0091] Based on the system modeling language, the semantic type of each model element in the encapsulated data package is identified one by one, including system requirement, specific function implementation, interface definition or architecture composition, and each model element is given a unique identification code;

[0092] According to the semantic type of each model element identified, the direct association relationship between each model element in the upper and lower levels, between the horizontal function units and between the interface connections is determined one by one, and a preliminary model element association relationship network with a multi-level structure is obtained;

[0093] On the basis of the preliminary model element association relationship network, the model element association relationship is deeply analyzed, and the direct association and indirect association model elements of each model element are identified;

[0094] Based on the determined model element association relationship network, the specific demand range of the model element by the task demand is comprehensively analyzed by designing the decomposition boundary condition, and the data interface position between the design specialties and the split nodes between the task stages are determined;

[0095] According to the decomposition boundary condition and the split node, each model element in the encapsulated data package is directionally split and reorganized to form the to-be-delivered model data.

[0096] By identifying the semantic types of the model elements in the encapsulated data package one by one and assigning unique identification codes, a preliminary model element association network with multiple levels is established, and on this basis, the direct and indirect association relationships of the model elements are deeply analyzed, so that the position of each model element in the design task can be accurately determined; through the comprehensive analysis of the design decomposition boundary condition, the precise splitting and reorganization of the model elements are realized, and the to-be-delivered model data strictly corresponding to the design task demand is obtained, thereby improving the accuracy and delivery efficiency of the collaborative design model data in the deep space exploration field, and ensuring the consistency and effectiveness of the model data cross-regional and multi-specialty collaborative design.

[0097] In the embodiment, the access rights of the model receiving terminal are determined according to the preset permission management rule, the to-be-delivered model data package is transmitted to the multiple terminals with access rights, and the data package for online delivery is generated, specifically:

[0098] According to the preset permission management rule, a model collaborative design permission database is established, and the database records the user role type, department affiliation, geographical distribution and identity authentication information of all model receiving terminals participating in collaborative design;

[0099] According to the user role type recorded in the model collaborative design permission database, the viewing, editing, delivering, delivering and merging permissions of each user role type at the model element level are analyzed one by one, and the permission configuration file corresponding to each model receiving terminal is generated according to the mapping relationship between the permission content and the model element;

[0100] Based on the permission configuration file, a permission verification code with a unique terminal identity of each model receiving terminal is generated, and the permission verification code includes an explicit model element access range, a list of operable model elements, a type of executable operations and a permission effective time period;

[0101] A secure network connection for model data interaction is established based on a real-time collaborative design platform, and the secure network connection includes a real-time data transmission link between a server port and multiple model receiving terminal ports after identity authentication and permission verification;

[0102] The model data packets to be delivered with the permission verification code are transmitted to each model receiving terminal that has completed identity authentication and permission verification in the form of encrypted data stream through the real-time data transmission link, and the model receiving terminal decrypts the encrypted data stream to obtain the online delivered data packet after receiving and verifying the encrypted data stream.

[0103] By establishing a model collaborative design permission database and explicitly recording user role types, department affiliations and identity authentication information, a refined permission configuration file for each model receiving terminal is parsed and generated one by one, thereby realizing precise permission control of model data; the access range and operation permission of the model elements are explicitly defined by the permission verification code, and the secure network connection and real-time data transmission link are used to ensure that the model data to be delivered is accurately transmitted to the receiving terminal with the corresponding permission, effectively improving the security and accuracy of the permission management of the data in the model data delivery process, significantly reducing the risk of data misuse, and enhancing the security and reliability of deep space exploration collaborative design.

[0104] In the embodiment, the model data packets to be delivered are exported into a file format that can be used offline according to the preset data export rules, and are transmitted to the target terminal through a physical medium to generate offline delivered data packets, specifically:

[0105] According to the preset data export rules, the file format of the model data packets to be delivered is determined to be an extensible markup language format;

[0106] According to the determined file format, each model element in the model data packets to be delivered is parsed one by one, and data records corresponding to the model elements are generated, each data record explicitly including the unique identification code of the model element, the semantic type to which it belongs, the association definition and the specific model element content;

[0107] The generated data records are encapsulated in order according to the model encapsulation sequence, which is determined by the hierarchical association relationship of the model elements and the data requirements of the design stage;

[0108] The encapsulated model data records are subjected to data consistency verification, including comparison of the completeness of the model data records, the consistency of the association relationship between the model elements and the compliance of the data format, and after the verification is passed, the encapsulated model data records are subjected to data compression processing to generate the final offline delivery file;

[0109] The final offline delivery file is stored in a portable physical storage medium according to the preset physical storage rules, and the physical storage medium is transmitted to the target terminal through a controlled physical transmission process, and the target terminal verifies the physical storage medium identification and data integrity to obtain the offline delivered data packet.

[0110] By exporting the to-be-delivered model data packet into an extensible markup language format, the data records corresponding to the model elements are parsed and generated one by one, and the unique identification code, semantic type and association relationship of the model elements and other specific contents are clearly recorded; the data records are subjected to consistency verification and data compression processing according to the model packaging sequence, thereby effectively ensuring the integrity and consistency of the offline delivery data file; the physical medium is used for storage and transmission, and the identification of the physical storage medium and the data integrity are verified, thereby ensuring the safety and reliability of the offline model data delivery process, and significantly improving the delivery efficiency and data quality of the multi-region offline collaborative design in the field of deep space exploration.

[0111] In the embodiment, the model receiving terminal restores the complete design model structure according to the received online-delivered data packet or offline-delivered data packet, and loads the complete design model structure to the local terminal, specifically as follows:

[0112] The model receiving terminal calls the data unpacking algorithm corresponding to the type of the received data packet according to the type of the received data packet, and the data unpacking algorithm includes data decryption, data decompression and data format analysis;

[0113] When the data decryption step is performed, the data decryption key is obtained from the local terminal according to the preset key management rule, the data packet is subjected to decryption operation, and the decrypted data file is obtained;

[0114] When the data decompression step is performed on the decrypted data file, the data is subjected to decompression processing according to the preset data compression algorithm, and the decompressed complete data file is obtained;

[0115] When the data format analysis step is performed on the decompressed complete data file, each model element data record in the data file is parsed one by one, the unique identification code, semantic type, association relationship definition and specific model element content of the model element are obtained, and the association network structure between the model elements is restored;

[0116] According to the restored association network structure between the model elements, each parsed model element and its association relationship are mapped to the local modeling environment one by one through the pre-installed system modeling language model loading engine, the complete design model structure is reconstructed and loaded to the local environment of the model receiving terminal, and the restoration and loading operation of the model structure is completed.

[0117] By calling corresponding data unpacking algorithms according to data packet types, the model data is accurately decrypted, efficiently decompressed and parsed; by parsing each model element data record in the data file one by one, the unique identification code, semantic type and association definition of the model element are restored, and the association network structure between the model elements is accurately reconstructed; further, the parsed model elements and their association are mapped to the local modeling environment one by one by using the system modeling language model loading engine, so that the restoration and loading operation of the design model structure is accurate and efficient, and the loading reliability and collaborative design efficiency of the model data in the terminal environment are significantly improved.

[0118] In the embodiment, according to the semantic association relationship between the change data generated in the design process and the model elements, the specific model elements involved in the model change in the design process and the influence path are analyzed, and the change influence analysis result is obtained, specifically:

[0119] The model change data generated in the model design process is monitored in real time, and the unique identification code of the model element changed, the semantic content before and after the change and the change type are obtained;

[0120] According to the obtained model change data, the specific model element changed is located according to the unique identification code of the model element, and the position of the model element in the requirement view, the function view, the interface view and the architecture view is determined by analyzing the semantic type of the model element;

[0121] According to the model element changed and the pre-established semantic association relationship network of the model element, the model elements directly associated and influenced by the change are analyzed and identified, and the unique identification code of the directly associated and influenced model elements and the association relationship type are determined;

[0122] On the basis of identifying the directly associated and influenced model elements, the indirectly associated and influenced model elements are analyzed and identified step by step, and the unique identification code, semantic type, association path and association strength of all the indirectly associated and influenced model elements are determined;

[0123] According to the association network structure of the model elements changed, the directly associated and influenced model elements and the indirectly associated and influenced model elements determined by analysis, the change influence analysis result is formed.

[0124] By monitoring the change data in the model design process in real time, the model elements and change types that have changed are accurately obtained, and the change model element position is accurately located based on the explicit analysis of the semantic type of the model element. Further, in combination with the pre-established model element semantic association relationship network, the model elements and influence paths that are directly and indirectly associated and influenced are identified and clarified level by level, forming a change influence analysis result with clear structure and clear association strength, effectively improving the accuracy and efficiency of model change tracing and influence domain analysis in the design process, and significantly improving the accuracy and reliability of model change management in the complex collaborative design task in the deep space exploration field.

[0125] In the embodiment, after the receiving terminals complete the respective model data design, the updated model data is returned to the unified model delivery terminal based on the change influence analysis result to obtain the final delivery model, specifically:

[0126] After the model receiving terminal completes the local design task, the updated model data package is generated based on the change influence analysis result and according to the preset data update rule;

[0127] According to the preset model data return protocol, the updated model data package is subjected to data consistency self-checking to verify the model element data integrity, semantic type accuracy and association relationship effectiveness;

[0128] The updated model data package that has passed the consistency self-checking is subjected to data encryption processing, and the unique identity of the corresponding model receiving terminal is added as a data source marker to generate an encrypted data package with a source marker;

[0129] According to the pre-established data transmission link of the real-time collaborative design platform, the encrypted data package with the source marker is returned to the unified model delivery terminal, and the model delivery terminal performs data decryption and source verification steps after receiving the returned data package;

[0130] The model delivery terminal performs data merging and integration one by one according to the verified data source and the decrypted updated model data to obtain the final delivery model.

[0131] The model receiving terminal generates the updated model data package according to the data update rule, clearly records the unique identification code, semantic type and association relationship information of the updated model element, and performs data consistency self-checking, effectively ensuring the integrity and accuracy of the model element data. Further, the updated model data package is subjected to data encryption processing and the unique identity of the terminal is added to realize the clear identification and secure transmission of the model data source. The model delivery terminal accurately completes the fusion and integration of the model data through data decryption and source verification, significantly improving the efficiency, security and consistency of the model data return and integration of multiple terminals.

[0132] In this embodiment, the version record and management operation of the fused final delivery model are performed according to the preset model version management rule, specifically:

[0133] Each model element in the fused final delivery model is respectively given an independent version identifier, and the version identifier records the change history of the model element in the entire design collaboration process, forming a fine-grained version record of the model element.

[0134] According to the fine-grained version record of the model element, the range of model elements involved in each model update, the change of the association relationship between the model elements, and the before-and-after state of the model element change are determined.

[0135] The fine-grained version record is compared and analyzed, the changes of specific model elements between each historical version in semantic type, association relationship, interface definition or architecture composition are identified, and intuitive difference records are generated.

[0136] Based on the fine-grained version record and the difference record, the model version required by the design task at each stage in the model delivery process is automatically matched.

[0137] Based on the fine-grained version record, a multi-dimensional version view of the model version is generated in real time.

[0138] By respectively giving each model element in the fused final delivery model an independent version identifier and forming a fine-grained version record, the complete change history of the model element in the entire design collaboration process is clearly and explicitly recorded. Further, through accurate version difference comparison and analysis, the changes of specific model elements between each historical version in semantic type, association relationship, interface definition or architecture composition are clearly identified, so that the model version required by the design stage can be automatically matched. The multi-dimensional version view generated in real time based on the fine-grained version record effectively improves the accuracy and traceability of version management, and significantly improves the reliability and efficiency of model data in the design collaboration process.

[0139] Embodiment 1:

[0140] In order to verify the feasibility of the application in implementation, the application is applied to a deep space exploration collaborative design task, which involves multiple regional design professional teams for collaborative design and data delivery of deep space explorer overall scheme. In this application scenario, the traditional design mode generally relies on discrete data file transmission, and the design data delivery usually requires manual unpacking and reloading operation, which may cause model version inconsistency, and the model change in the design process cannot be traced and managed in time, seriously affecting the design efficiency and data reliability, and even causing task delay. The version data error rate of some collaborative design tasks once reached more than 15%.

[0141] In actual operation, first, the demand view, the function view, the interface view and the architecture view are established based on the system modeling language respectively by the method, all model elements are determined and the encapsulated data package is formed, then the data package is parsed by the model element semantic recognition and correlation analysis method to obtain the preliminary model element correlation network, and the direct and indirect correlation and influence path between all model elements are determined by deep correlation analysis.

[0142] The design team determines the decomposition and combination mode of the model data according to the decomposition boundary condition, and generates the corresponding online and offline data packages, wherein the online data package is transmitted to multiple terminals with access rights based on the real-time collaborative design platform, and the offline data package is exported in the Extensible Markup Language format and transmitted through physical storage medium.

[0143] After receiving the data package, the model receiving terminal performs decryption and decompression through the preset data decryption key and data compression algorithm, then parses each model element data record, and loads the parsed data into the local modeling environment by using the pre-installed system modeling language model loading engine, to complete the restoration and loading of the design model structure. Then, the system automatically monitors the change data generated in the design process, and identifies the model elements involved in the change in real time, analyzes the correlation network structure to obtain accurate model change influence analysis results in the design process.

[0144] Finally, each terminal performs consistency self-checking and data encryption processing on the completed design model data package, and returns it to the unified model delivery terminal for fusion processing. The unified model delivery terminal performs fine-grained version management and difference comparison analysis on the fused model, forms complete and accurate model version records, and automatically matches the required model versions of each design stage to generate clear multi-dimensional model version views.

[0145] After 3 months of continuous application verification, the project team conducted a detailed effect evaluation on 30 design model data, compared the performance of the method and the traditional method in version control accuracy, model change traceability efficiency in the design process, model loading error rate, data delivery accuracy and delivery cycle shortening rate, and the evaluation data is shown in Table 1:

[0146] Table 1 Effect comparison and analysis table of deep space exploration collaborative design model data delivery method

[0147] ;

[0148] From the effect comparison results of the deep space exploration collaborative design model data delivery method shown in Table 1, after adopting the SysML-based collaborative design model delivery method proposed in the application, the version control accuracy is obviously improved, and the average improvement amplitude reaches 18.9%, and the version control accuracy of the model numbered M-019 is the highest, reaching 98.4%, which is improved by 17.9 percentage points compared with the traditional method.

[0149] In terms of model change tracing efficiency in the design process, the traditional method needs about 16.5 hours to complete a change tracing, while after adopting the method, the average completion time of change tracing is shortened to 3.1 hours, and the efficiency is improved by more than 5 times. Especially, the change tracing time of the model numbered M-019 is the shortest, only 2.7 hours.

[0150] In addition, the model loading error rate is significantly reduced, and the model loading error rate under the traditional method is generally as high as more than 9%, while the error rate is controlled within 1.2% by the method, which greatly improves the accuracy and reliability of model data loading.

[0151] In terms of data delivery accuracy, the method of the application maintains more than 97.7%, while the average accuracy of the traditional method is only about 81.4%, which fully embodies the advantages of the technical scheme of the application in ensuring the accuracy of delivered model data.

[0152] In terms of delivery cycle shortening rate, after adopting the method of the application, the average shortening rate of data delivery cycle reaches 33.2%, which effectively accelerates the progress of the design task and significantly reduces the overall construction period risk of the collaborative design project.

[0153] From the specific application and data analysis of the above embodiments, it can be seen that the SysML-based deep space exploration field collaborative design model delivery method proposed in the application has obvious technical advantages and practical value in version control, model change tracing efficiency in the design process, model data accuracy and delivery cycle, and is suitable for fine management and efficient collaborative delivery of complex collaborative design tasks in the deep space exploration field, and has broad application prospects.

[0154] The above describes only the preferred specific embodiments of the application, but the protection scope of the application is not limited thereto, and any person skilled in the art can make equivalent substitutions or changes to the technical solutions and inventive concepts of the application within the technical scope disclosed by the application, which should be covered within the protection scope of the application.

Claims

1. A SysML-based deep space exploration field collaborative design model delivery method, characterized in that, include: A method for delivering collaborative design models in the field of deep space exploration based on a system modeling language, characterized by the following steps: Using a system modeling language, construct a design model that includes a requirements view, a functional view, an interface view, and an architecture view. Based on the relationships between the views, complete the data encapsulation of the design model to form an encapsulated data package. Semantic recognition and association parsing of model elements are performed on the encapsulated data packets. The decomposition and distribution strategy of the model is determined according to the design task requirements to obtain the model data to be distributed. Based on the preset permission management rules, the access permissions of the model receiving terminals are determined, and the model data packets to be distributed are transmitted to multiple model receiving terminals with access permissions to generate online delivery data packets. According to the preset data export rules, the data package to be distributed is exported into a file format that can be used offline, and then transmitted to the model receiving terminal through the physical medium to generate the data package for offline delivery. The model receiving terminal unpacks the data according to the received online or offline data packets, restores the complete design model structure, and loads it locally; Based on the change data generated by the model during the design process and the semantic relationships between model elements, analyze and identify the specific model elements involved in the design changes and their impact paths to obtain the change impact analysis results. After completing their respective model data design, the receiving terminals send the updated model data back to the unified model delivery terminal to obtain the final delivery model. Perform version recording and management operations on the final delivered model according to the preset model version management rules; The process involves semantic recognition and association parsing of model elements in the encapsulated data packet, determining the model decomposition and distribution strategy based on the design task requirements, and obtaining the model data to be distributed. Specifically: Based on the system modeling language, the semantic type of each model element in the encapsulated data packet is identified one by one, including system requirements, specific function implementation, interface definition or architecture composition, and a unique identifier is assigned to each model element. Based on the semantic type identified for each model element, the direct relationships between each model element in the upper and lower levels, between horizontal functional units, and between interface connections are determined one by one, resulting in a preliminary model element relationship network with a multi-level structure. Based on the preliminary model element relationship network, the relationship between model elements is analyzed in depth to identify the direct and indirect relationships between each model element. Based on the established network of relationships between model elements, the boundary conditions are designed and decomposed. The specific requirements of the task for the model elements are comprehensively analyzed, and the splitting nodes of the model elements between task stages and the data interface positions between design disciplines are determined. Based on the decomposition boundary conditions and splitting nodes, the model elements in the encapsulated data packet are split in a targeted manner and then reassembled to form the model data to be sent out. Based on the semantic relationships between the change data generated during the design process and the model elements, the specific model elements involved in the design changes and their impact paths are analyzed and identified to obtain the change impact analysis results. Specifically: Real-time monitoring model change data generated in the model design process, obtaining the unique identification code of the model element, the semantic content before and after the change and the change type; According to the obtained model change data, the specific model element is located according to the model element unique identification code, and the position of the model element in the demand view, the function view, the interface view and the architecture view is clarified through the model element semantic type analysis; According to the model element semantic association relationship network established in advance, the model elements directly associated with the changed model elements are analyzed and identified, and the unique identification code of the directly associated model elements and the association relationship type are determined; On the basis of identifying the directly associated model elements, the indirectly associated model elements are analyzed and identified step by step, and the unique identification code, semantic type, association path and association strength of all indirectly associated model elements are determined; According to the association network structure of the changed model elements, the directly associated model elements and the indirectly associated model elements determined by analysis, the change influence domain analysis result is formed.

2. The SysML-based collaborative design model delivery method in the deep space exploration field according to claim 1, characterized in that, The system modeling language is used to build a data package containing a demand view, a function view, an interface view and an architecture view, and the data package is formed by completing the data encapsulation of the design model according to the association relationship between the views, specifically: Based on the system modeling language, a demand view, a function view, an interface view and an architecture view are established, and each view is defined respectively to define the model elements belonging to it; The semantic association relationship between the demand view and the function view is analyzed, and the mapping relationship between the model elements in the demand view and the model elements in the function view is determined; The semantic association relationship between the function view and the interface view is analyzed, and the mapping relationship between the model elements in the function view and the model elements in the interface view is determined; The semantic association relationship between the interface view and the architecture view is analyzed, and the mapping relationship between the model elements in the interface view and the model elements in the architecture view is determined; According to the mapping relationship, all model elements and their semantic association relationship contained in the demand view, the function view, the interface view and the architecture view are encapsulated into a complete data package, and the encapsulated data package is obtained.

3. The SysML-based collaborative design model delivery method in the deep space exploration field according to claim 1, characterized in that, According to the preset permission management rule, the access permission of the model receiving terminal is determined, the to-be-downloaded model data package is transmitted to the multiple model receiving terminals with access permission, and the online delivery data package is generated, specifically: According to the preset permission management rule, a model collaborative design permission database is established, and the user role type, department affiliation, regional distribution and identity authentication information of all model receiving terminals participating in collaborative design are recorded in the database; According to the user role type recorded in the model collaborative design permission database, the viewing, editing, downloading, delivering and merging permissions of each user role type at the model element level are analyzed one by one, and the permission configuration file corresponding to each model receiving terminal is generated according to the mapping relationship between the permission content and the model element; Based on the permission profile, a terminal receiving terminal generates a permission verification code with a terminal unique identity for each model, which contains explicit model element access range, operable model element list, executable operation type and permission validity period; Based on the real-time collaborative design platform, a secure network connection for model data interaction is established, which includes real-time data transmission link between server port and multiple model receiving terminal ports after identity authentication and permission verification; Through the real-time data transmission link, the model data package to be delivered with the permission verification code is transmitted to each model receiving terminal that has completed identity authentication and permission verification in the form of encrypted data stream, and the model receiving terminal receives and verifies the encrypted data stream to obtain the online delivered data package after decryption.

4. The SysML-based collaborative design model delivery method in the deep space exploration field according to claim 1, wherein, According to the preset data export rule, the model data package to be delivered is exported into a file format that can be used offline, and is transmitted to the model receiving terminal through a physical medium to generate an offline delivered data package, specifically: According to the preset data export rule, the file format of the model data package to be delivered is determined as an extensible markup language format; According to the determined file format, each model element in the model data package to be delivered is parsed one by one to generate data records corresponding to the model elements, and each data record explicitly includes the unique identification code of the model element, the semantic type it belongs to, the association definition and the specific model element content; According to the model packaging sequence, the generated data records are packaged in sequence, and the model packaging sequence is determined by the upper and lower association relationship of the model elements and the data requirements of the design stage; Perform data consistency verification on the packaged model data records, including comparing the integrity of the model data records, the consistency of the association relationship between the model elements and the compliance of the data format, and performing data compression processing on the packaged model data records after verification to generate the final offline delivered file; The final offline delivered file is stored in a portable physical storage medium according to the preset physical storage rule, and the physical storage medium is delivered to the model receiving terminal through a controlled physical delivery process. After the model receiving terminal verifies the physical storage medium identification and data integrity, the offline delivered data package is obtained.

5. The SysML-based collaborative design model delivery method in the field of deep space exploration according to claim 1, characterized in that, The model receiving terminal restores the complete design model structure according to the received online delivered data package or offline delivered data package and loads it to the local, specifically: The model receiving terminal calls the data unpacking algorithm corresponding to the data package type according to the received data package type, and the data unpacking algorithm includes data decryption, data decompression and data format analysis; When performing the data decryption step, the data decryption key is obtained from the local according to the preset key management rule, and the decryption operation is performed on the data package to obtain the decrypted data file; When performing the data decompression step on the decrypted data file, data decompression processing is performed according to the preset data compression algorithm to obtain the complete data file after decompression; When the decompressed complete data file is subjected to the data format analysis step, each model element data record in the data file is analyzed one by one to obtain a model element unique identification code, a semantic type, a correlation relationship definition and a specific model element content, and the correlation network structure between the model elements is restored; According to the restored correlation network structure between the model elements, each model element and the correlation relationship after the analysis are mapped to the local modeling environment one by one through the pre-installed system modeling language model loading engine, the complete design model structure is reconstructed and loaded to the local environment of the model receiving terminal, and the restoration and loading operation of the model structure is completed.

6. The SysML-based collaborative design model delivery method in the field of deep space exploration according to claim 1, characterized in that, After the receiving terminal completes the respective model data design, the updated model data is returned to the unified model delivery terminal to obtain the final delivery model, specifically: After the model receiving terminal completes the local design task, an updated model data package is generated according to the preset data update rule, and the model data package explicitly includes a unique identification code of an updated model element, an updated semantic type, a specific model element content and correlation relationship information between the model elements; According to the preset model data return protocol, the updated model data package is subjected to data consistency self-checking to verify the model element data integrity, semantic type accuracy and correlation relationship validity; The updated model data package after the consistency self-checking is subjected to data encryption processing, and a unique identity of the corresponding model receiving terminal is added as a data source marker to generate an encrypted data package with the source marker; According to the pre-established data transmission link of the real-time collaborative design platform, the encrypted data package with the source marker is returned to the unified model delivery terminal, and the model delivery terminal performs data decryption and source verification steps after receiving the returned data package; The model delivery terminal performs data merging and integration one by one according to the verified data source and the decrypted updated model data to obtain the final delivery model.

7. The SysML-based collaborative design model delivery method in the field of deep space exploration according to claim 1, characterized in that, According to the preset model version management rule, the final delivery model is subjected to version recording and management operations, specifically: Each model element in the final delivery model is respectively given an independent version identification, the version identification records each change history of the model element in the entire design collaboration process to form a fine-grained version record of the model element; According to the fine-grained version record of the model element, the model element range involved in each model update, the correlation relationship change between the model elements and the before-and-after states of the model element change are determined; The fine-grained version record is subjected to difference comparison to identify the changes of each historical version in the semantic type, correlation relationship, interface definition or architecture composition of the specific model element, and an intuitive difference record is generated; Based on the fine-grained version record and the difference record, specific model versions required by each stage of the design task in the model delivery process are automatically matched; Based on the fine-grained version record, a multi-dimensional version view of the model version is generated in real time.

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