CN113722838A - Python model-based aircraft complex system design method - Google Patents
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Abstract
The invention discloses a Python model-based aircraft complex system design method, which comprises the steps of firstly, applying a uniform naming rule to parameters related to each system requirement in a polar platform for expression, then establishing a database in the polar platform, and assigning values to the parameters related to the system requirements; establishing a link between each system requirement and a corresponding parameter in a database; then, establishing a Python model according to parameters related in a Polarion platform database; then, establishing a Simulink behavior model according to the function and performance requirements of the Polarion platform, and linking the function and performance requirements of the Polarion platform with the corresponding established Simulink behavior model; and finally, linking the Python model with the established Simulink behavior model, wherein the Python model is used as the Simulink model, and the m file supports the Simulink model to run simulation. The invention realizes the uniqueness of the parameters in the system design process, avoids the error caused by the inconsistency of the same parameter in the design and modeling simulation processes, and reduces the system design time and the labor cost.
Description
Technical Field
The invention belongs to the technical field of design of aircraft complex systems, and particularly relates to a Python model-based aircraft complex system design method.
Background
The airplane has the characteristics of multiple fields, high complexity, high precision, high integration and the like, and consists of complex systems for realizing different functions, the design of the airplane complex system is formed by coupling systems with different functions, the integration of the same language and platform of the airplane level is realized through the multi-field collaborative design, and the high-safety and high-reliability airplane can be developed in a short period at low cost.
The invention of publication number CN 106682298A discloses a method for constructing a fault simulation model library of an aviation hydraulic steering engine system, which establishes a fault model library of a hydraulic steering engine through Simulink and establishes fault simulation models under various fault conditions. However, the invention does not describe the integrated model and design of a multi-professional system with mechanical, hydraulic, electrical and control professions, and does not have interfaces among system requirements, models and parameters, and the invention focuses on fault simulation.
The invention of publication number CN 106681726 a discloses a method for converting a Python model into a Modelica model, which combs the Python model, and automatically packages and generates a C language function model and a Modelica language model through the support of a C language generation module and a Modelica language generation module. However, in the invention, an integrated model and design of a system are not described, and interfaces among system requirements, models and parameters are not provided, and the emphasis is on generating a C language function integrated Modelica model.
With the development of scientific technology, model-driven system design is more and more widely applied to system design, and models, requirements and parameters are not independent behaviors any more, but the requirements are expressed by applying the models, links between the models and the requirements are established, and the requirements are transmitted to various professions in the form of texts and models. In addition, in the system design process, parameters in system requirements are often encountered, the problem of parameter inconsistency occurs in a model, the phenomenon that the model expression requirements are incorrect is caused, and the only important problem that needs to be solved is how to link and link the system requirements, the parameters and the model.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a Python model-based aircraft complex system design method, which comprises the steps of firstly, applying a uniform naming rule to parameters related to each system requirement in a Polarion platform for expression, then, establishing a database in the Polarion platform, and assigning values to the parameters related to the system requirements; establishing a link between each system requirement and a corresponding parameter in a database; then, establishing a Python model according to parameters related in a Polarion platform database; then, establishing a Simulink behavior model according to the function and performance requirements of the Polarion platform, and linking the function and performance requirements of the Polarion platform with the corresponding established Simulink behavior model; and finally, linking the Python model with the established Simulink behavior model, wherein the Python model is used as the Simulink model, and the m file supports the Simulink model to run simulation. The invention realizes the uniqueness of the parameters in the system design process, avoids the error caused by the inconsistency of the same parameter in the design and modeling simulation processes, and reduces the system design time and the labor cost.
The technical scheme adopted by the invention for solving the technical problem comprises the following steps:
step 1: the parameters related in each function and performance requirement are expressed by applying a uniform naming rule in a Polarion platform, so that the system requirement cannot be updated due to the change of the parameter value;
step 2: establishing a database in a Polarion platform, and assigning values, namely parameter values, to parameters related in system requirements;
and step 3: establishing a link between each system requirement and a corresponding parameter in a database;
and 4, step 4: establishing a Python model according to parameters related in a Polarion platform database, and mapping parameter names and parameter values in the Polarion database into the Python model one by one;
and 5: establishing a Simulink behavior model according to the function and performance requirements of the Polarion platform, wherein parameters related in the Simulink behavior model correspond to system requirements;
step 6: linking the function and performance requirements of the Polarion platform with the corresponding established Simulink behavior model;
and 7: the Python model is linked with the established Simulink behavior model, and the Python model is used as the Simulink model.
Further, the database contains all parameters involved in the system requirements, the parameters in the database are expressed the same as the parameters in the system requirements, but the parameters in the database have attributes, i.e. parameter values and parameter states.
Further, the parameter states include a determined state and an assumed state.
Further, in the link, i.e. the attribute in step 3, the requirement linked attribute can indicate that it is associated with the corresponding parameter in the database, and likewise, the parameter linked attribute can indicate that it is associated with the requirement.
Further, the behavioral model of the Simulink expresses the system functions, the input information and the output information described by the performance, and the logical relationship between the input and the output, and the related parameters are consistent with the expression in the system requirements.
Further, when the function and performance requirements of the Polarion platform in step 6 are linked with the Simulink behavior model, an interface between the Simulink behavior model and the Polarion platform is firstly established, and the Simulink behavior model is presented in the form of pictures and links to the corresponding requirements of the Polarion platform, and then the linking is completed; the Simulink model corresponding to the system requirements can be opened on the Polarion platform, the corresponding system requirements can be checked in the Simulink model, and the system requirements can be transmitted to various fields in the form of texts and models.
Further, the Python model in step 7 includes all parameter values used for running the Simulink behavior model, and the running Python model transfers the parameter values as inputs to the workbench of Simulink.
The invention has the following beneficial effects:
the invention realizes the uniqueness of the parameters in the system design process, and avoids the error caused by the inconsistency of the same parameter in the design and modeling simulation processes; a tool chain of system design and modeling simulation is established, and the separation phenomenon of a model and the design is solved; the link relation among the requirements, the parameters and the models is established, and the parameters and the models corresponding to the requirements can be quickly positioned by changing the requirements, so that the system design time and the labor cost are reduced; and the display of the requirements and the models on the same platform is realized, the transmission of system requirements in different fields is realized in the form of texts and models, and design errors caused by inconsistent understanding are avoided.
Drawings
FIG. 1 is a system design flow chart based on Python model according to the present invention.
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
Because the model, the system requirement and the parameter can not be directly called, the invention directly calls the parameter name and the parameter value in the polar database by the Python model, and assigns the parameter name and the parameter value to the Simulink model as input, thereby supporting simulation of the Simulink model. Meanwhile, the model in Simulink is mapped to the Polarion requirement in the form of pictures and links, and the links are established.
A method for designing an aircraft complex system based on a Python model comprises the following steps:
step 1: the parameters related in each function and performance requirement are expressed by applying a uniform naming rule in a Polarion platform, so that the system requirement cannot be updated due to the change of the parameter value;
the Polarion platform is used for managing the life cycle of the system, managing the system requirements and analyzing parameters related to each requirement.
Step 2: establishing a database in a Polarion platform, combing the parameters in the system requirements, and assigning the parameters related to the system requirements, namely parameter values;
the database contains all parameters involved in the system requirements, the parameters in the database are expressed identically to the parameters in the system requirements, but the parameters in the database have attributes, i.e. parameter values and parameter states, including determined states and assumed states.
And step 3: and establishing a link, namely an attribute, of each system requirement and corresponding parameter in the database, wherein the link belongs to the requirement and the parameter, the requirement has a link attribute which can indicate that the requirement is associated with the corresponding parameter in the database, and the parameter has a link attribute which can indicate that the parameter is associated with the requirement.
And 4, step 4: establishing a Python model according to parameters related in a Polarion platform database, and mapping parameter names and parameter values in the Polarion database into the Python model one by one;
and establishing a link between the Python model and a database in a policy platform, and mapping parameter names and parameter values in the policy platform to the established Python model.
And 5: establishing a Simulink behavior model according to the function and performance requirements of the Polarion platform, wherein parameters related in the Simulink behavior model correspond to system requirements;
the behavior model of the Simulink expresses the input information and the output information described by the system function and performance and the logical relation between the input and the output, and the related parameters are consistent with the expression in the system requirements.
Step 6: linking the function and performance requirements of the Polarion platform with the corresponding established Simulink behavior model;
firstly, establishing an interface between a Simulink behavior model and a Polarion platform, and displaying the Simulink behavior model on the corresponding requirement of the Polarion platform in the form of pictures and links to finish the links; the Simulink model corresponding to the system requirements can be opened on the Polarion platform, the corresponding system requirements can be checked in the Simulink model, and the system requirements can be transmitted to various fields in the form of texts and models.
And 7: the Python model is linked with the established Simulink behavior model, and the Python model is used as the Simulink model.
The Python model contains all parameter values used for running the Simulink behavior model, and the Python model is run to transfer the parameter values as inputs to the workbench.
In summary, the present invention provides a Python model-based aircraft complex system design method, wherein management of a full life cycle of system design is achieved through a policy platform, management of system requirements is achieved, parameters related to the requirements are extracted into a database, the parameters are assigned in the database, and links between the assigned parameters and corresponding requirements are established. According to system requirements in the Polarion platform, a model corresponding to the requirements is established through Simulink, and the Simulink model is linked to the requirements of the Polarion platform, wherein the names of the model and parameters related to the corresponding requirements are the same. According to parameters in a database of the Polarion platform, a Python model is established and linked to the database of the Polarion platform, and the parameters and the parameter values are mapped into the Python model one by one, so that the value in the Python model for updating the value in the database is automatically updated. And establishing an interface from the Python model to the Simulink model, and realizing that the Python model is used as the Simulink model.
The specific embodiment is as follows:
1. performing item management on the requirement of the airplane wheel braking system in a Polarion platform, and replacing the requirement of the airplane wheel braking system with a parameter name when the requirement of the airplane wheel braking system relates to a parameter;
if the system needs: BCSSYS-1709-the wheel BRAKE system should output the BRAKE pressure corresponding to the PEDAL displacement to the wheels according to the PEDAL displacement pressure CURVE PEDAL _ BRAKE _ CURVE. Wherein BCSSYS-1709 is the number of the requirement and has uniqueness.
The PEDAL displacement pressure profile in demand is named PEDAL _ BRAKE _ CURVE.
2. Establishing an airplane wheel brake system database in the Polarion platform, wherein the database is named as BCS Data Dictionary, the database comprises all parameters related to airplane wheel brake system requirements established in the Polarion platform, and parameter name naming rules in the database are as follows: name, request;
the parameter attributes in the database include: number, name, description, unit, value, link, status;
the parameter pedal displacement pressure CURVE in the database is BCSSYS-1800-BCS.REQ.PEDAL _ BRAKE _ CURVE; a value of [0,50, 100; 0,1500,3000 ]; wherein BCSSYS-1800 is the number of the parameter in the database and has uniqueness.
3. Linking the requirements of the airplane wheel brake system with parameters in a database;
and linking the system requirement BCSSYS-1709 with the database parameter BCSSYS-1800, wherein the display in the attribute link of the system requirement BCSSYS-1709 is linked to the database parameter BCSSYS-1800, and the display in the attribute link of the database parameter BCSSYS-1800 is linked to the system requirement BCSSYS-1709.
4. Building a Python model BCS parameters, and operating the BCS parameters to read the name of the parameter in the polarization platform BCS Data Dictionary and the value of the parameter;
5. establishing a Simulink behavior model according to the function and performance requirements of the Polrion platform, such as system requirements BCSSYS-1709, adopting 1-D Lookup Table in the Simulink, setting the Table data as BCS.REQ.PEDAL _ BRAKE _ CURVE (2): and setting Breakpoints 1 as BCS.REQ.PEDAL _ BRAKE _ CURVE (1): in the prior art.
6. The method comprises the steps of establishing platform interfaces of Polarion and Simulink through Polarion-Simulink, releasing a functional performance model established by Simulink to wheel brake system requirements of a Polarion platform to form a requirement model BCSSYS-1801-pedal brake, linking the requirement model BCSSYS-1801 to system requirements BCSSYS-1709, and linking a display to database parameters BCSSYS-1800 and requirement model BCSSYS-1801 in an attribute link of the system requirements BCSSYS-1709.
7. And operating the Python model to transfer the parameter names and the parameter values in the BCS Data Dictionary read by the Python model to the Workspace of Simulink, and providing the parameter values for simulation of the Simulink model.
Claims (7)
1. A method for designing an aircraft complex system based on a Python model is characterized by comprising the following steps:
step 1: the parameters related in each function and performance requirement are expressed by applying a uniform naming rule in a Polarion platform, so that the system requirement cannot be updated due to the change of the parameter value;
step 2: establishing a database in a Polarion platform, and assigning values, namely parameter values, to parameters related in system requirements;
and step 3: establishing a link between each system requirement and a corresponding parameter in a database;
and 4, step 4: establishing a Python model according to parameters related in a Polarion platform database, and mapping parameter names and parameter values in the Polarion database into the Python model one by one;
and 5: establishing a Simulink behavior model according to the function and performance requirements of the Polarion platform, wherein parameters related in the Simulink behavior model correspond to system requirements;
step 6: linking the function and performance requirements of the Polarion platform with the corresponding established Simulink behavior model;
and 7: the Python model is linked with the established Simulink behavior model, and the Python model is used as the Simulink model.
2. The Python model-based aircraft complex system design method as claimed in claim 1, wherein the database contains all parameters involved in the system requirements, the parameters in the database are expressed in the same way as the parameters in the system requirements, but the parameters in the database have attributes, namely parameter values and parameter states.
3. The Python model-based aircraft complex system design method as claimed in claim 1, wherein the parameter states include determined states and assumed states.
4. The Python model-based aircraft complex system design method as claimed in claim 1, wherein the link or attribute requirement in step 3 has a link attribute indicating that it is associated with a corresponding parameter in the database, and likewise, the parameter has a link attribute indicating that it is associated with a requirement.
5. The Python model-based aircraft complex system design method as claimed in claim 1, wherein the behavioral model of Simulink expresses input information, output information and logical relations between inputs and outputs described by system functions and performances, and parameters involved are consistent with the expression in system requirements.
6. The Python model-based aircraft complex system design method of claim 1, wherein in the step 6, when the functional and performance requirements of the Polarion platform are linked with the Simulink behavior model, an interface between the Simulink behavior model and the Polarion platform is firstly established, and the Simulink behavior model is displayed in the form of pictures and links on the corresponding requirements of the Polarion platform, and then the linking is completed; the Simulink model corresponding to the system requirements can be opened on the Polarion platform, the corresponding system requirements can be checked in the Simulink model, and the system requirements can be transmitted to various fields in the form of texts and models.
7. The method according to claim 1, wherein the Python model in step 7 contains all parameter values used for operating the Simulink behavior model, and the Python model is operated to transfer the parameter values as inputs to Simulink workbench.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8336025B1 (en) * | 2007-02-08 | 2012-12-18 | The Mathworks, Inc. | Pattern modeling methods and systems |
| CN111046568A (en) * | 2019-12-18 | 2020-04-21 | 哈尔滨工程大学 | Control parameter optimization method based on aeroengine and jet nozzle electromechanical liquid multi-system combined simulation |
| CN111507020A (en) * | 2020-05-12 | 2020-08-07 | 中国民航大学 | Graphical display method for distributed simulation results of electromechanical systems of multi-electric aircraft |
| CN111950085A (en) * | 2020-08-12 | 2020-11-17 | 北京航空航天大学 | Multiplexing type missile modeling method based on Simulink and Stateflow |
| CN112347698A (en) * | 2020-11-12 | 2021-02-09 | 东北大学 | Man-machine hybrid enhanced intelligent design method based on aircraft structural member |
| CN113361135A (en) * | 2021-07-01 | 2021-09-07 | 中国计量大学 | Method for building load by using Simulink simulation calling Python language |
| CN113392537A (en) * | 2021-07-01 | 2021-09-14 | 中国计量大学 | Method for constructing distributed power supply in Simulink simulation by Python language |
-
2021
- 2021-09-23 CN CN202111117330.5A patent/CN113722838B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8336025B1 (en) * | 2007-02-08 | 2012-12-18 | The Mathworks, Inc. | Pattern modeling methods and systems |
| CN111046568A (en) * | 2019-12-18 | 2020-04-21 | 哈尔滨工程大学 | Control parameter optimization method based on aeroengine and jet nozzle electromechanical liquid multi-system combined simulation |
| CN111507020A (en) * | 2020-05-12 | 2020-08-07 | 中国民航大学 | Graphical display method for distributed simulation results of electromechanical systems of multi-electric aircraft |
| CN111950085A (en) * | 2020-08-12 | 2020-11-17 | 北京航空航天大学 | Multiplexing type missile modeling method based on Simulink and Stateflow |
| CN112347698A (en) * | 2020-11-12 | 2021-02-09 | 东北大学 | Man-machine hybrid enhanced intelligent design method based on aircraft structural member |
| CN113361135A (en) * | 2021-07-01 | 2021-09-07 | 中国计量大学 | Method for building load by using Simulink simulation calling Python language |
| CN113392537A (en) * | 2021-07-01 | 2021-09-14 | 中国计量大学 | Method for constructing distributed power supply in Simulink simulation by Python language |
Non-Patent Citations (1)
| Title |
|---|
| 陈国慧;张娟;张博强;陆峰;: "基于模型的民用飞机自动刹车***设计与研究", 民用飞机设计与研究, no. 03 * |
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