CN117057171B - Semi-packaging simulation method combining measured data and simulation data - Google Patents

Semi-packaging simulation method combining measured data and simulation data Download PDF

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CN117057171B
CN117057171B CN202311318367.3A CN202311318367A CN117057171B CN 117057171 B CN117057171 B CN 117057171B CN 202311318367 A CN202311318367 A CN 202311318367A CN 117057171 B CN117057171 B CN 117057171B
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simulation
data
model
interface
deduction
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CN117057171A (en
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刘科
陈俞舟
宋丹
戴礼灿
杨拓
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CETC 10 Research Institute
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Abstract

The invention discloses a semi-real-package simulation method combining measured data and simulation data, which comprises the following steps: s1: standardized data interfaces and functional components; s2: generating a model, and generating a simulation model, wherein the simulation model comprises: a digital model corresponding to the actual equipment and a simulation model based on simulation deduction requirements; s3: simulation deduction, constructing an integrated test environment and a simulation system by combining the generated real-time digital model and simulation model with simulation test verification requirements, developing the simulation deduction, configuring and adjusting parameters in a simulation scheme through a visual interface, and storing configuration and adjustment results in a database in real time for analysis; s4: efficiency evaluation, namely outputting an evaluation result; s5: capability feedback and adjustment optimization, by continuously adjusting the simulation model and the simulation scheme, the verification and evaluation of various schemes are completed by means of simulation deduction of the simulation system, and the adjustment of the simulation model and the adjustment of the simulation scheme are completed.

Description

Semi-packaging simulation method combining measured data and simulation data
Technical Field
The invention belongs to the field of system simulation, and particularly relates to a semi-real-package simulation method combining measured data and simulation data.
Background
The system simulation is to simulate the environment, equipment and the like in the real physical world in a digital mode by utilizing a computer technology, and simulate the running state, performance and trend of the equipment through interaction among digital models. Along with the development of technology, the method is an essential important link for carrying out simulation test verification on various types of equipment in various stages of development, production, application and the like, not only can verify the capability of single equipment, but also can verify the system cooperative application capability of the equipment through integration.
Existing simulation methods can be broadly divided into three categories: (1) pure digital simulation. The simulation method needs to perform scene design in advance and perform data preparation in advance according to defined formats, requirements or rules, and the method lacks flexibility, and the reliability and the credibility of the simulation result are insufficient because the data is prepared in advance according to the requirements; and (2) semi-physical simulation. The simulation method is generally carried out under laboratory conditions, belongs to static simulation or limited dynamic simulation, can be used for verifying the capability of single equipment, has the implementation cost and difficulty between pure digital simulation and pure physical simulation, but has certain limitations, such as insufficient simulation of the running environment, incapability of verifying the cooperative application capability of a system of multiple equipment and the like; and (3) pure physical simulation. The simulation method requires that the physical object participates in the simulation test, has high cost, and can only be performed according to the route of 'test-post analysis-retest' in the aspect of improving the guiding capability, and has the characteristics of long period and complex process.
In addition, in the existing simulation method, interaction between models mainly adopts two modes: (1) The one-to-one interaction mode is characterized in that in the model construction process before the simulation test starts, the interaction data format and the like between any two models are subjected to customized configuration so as to ensure smooth interaction between the models in the simulation test process, and the mode belongs to temporary customized development, has poor reusability and is inconvenient for rapid movement in and movement out of the models; (2) The mode of 'broadcasting' interaction is that each model broadcasts own output information outwards in a channel, and according to the prior configuration, the model with 'acquisition authority' extracts corresponding data information from the information to finish the data interaction between the models, and the mode has higher requirement on bandwidth and needs to additionally perform sender/receiver configuration.
Disclosure of Invention
The invention aims at: in order to overcome the problems in the prior art, the invention discloses a semi-real-installation simulation method combining measured data and simulation data.
The aim of the invention is achieved by the following technical scheme:
the semi-real-package simulation method combining measured data and simulation data comprises the following steps:
s1: standardized data interfaces and functional components;
s2: the generation of the model is performed and,
performing custom assembly based on the data interface and the functional component to generate a simulation model, wherein the simulation model comprises: a digital model corresponding to the actual equipment and a simulation model based on simulation deduction requirements;
s3: the simulation deduction is carried out,
constructing an integrated test environment and a simulation system by combining the generated digital model and simulation model with the simulation test verification requirement, developing simulation deduction, configuring and adjusting parameters in a simulation scheme through a visual interface, and storing configuration and adjustment results in a database in real time for analysis;
s4: the performance of the test piece was evaluated,
establishing an evaluation index system based on a test verification scene, receiving simulation operation data generated by a simulation system in real time for efficiency evaluation, and outputting an evaluation result;
s5: the capacity feedback and the adjustment and optimization are carried out,
the simulation model and the simulation scheme are continuously adjusted, simulation deduction is carried out by means of the simulation system, verification and evaluation of various schemes are completed, and adjustment of the simulation model and adjustment of the simulation scheme are completed based on the obtained evaluation result.
According to a preferred embodiment, in step S2, the digitalized model is based on real-time measurement data obtained by using the actual equipment in the simulation test scene, and by analyzing the data content included in the actual measurement data, an association mapping relationship from the actual measurement data to the equipment capability to the model function is established, functional components with corresponding functions are extracted for model assembly, a digitalized model corresponding to the actual equipment is generated, and the state and the display effect of the model are driven by the actual measurement data.
According to a preferred embodiment, in step S2, the simulation model is based on simulation data, and the simulation model with the complementary capability is quickly assembled and generated by man-machine interaction through visual display effect graphs and analysis of performance evaluation data to find out the points lower than the expected links and the capability improvement points, and added into the test scene to participate in simulation.
According to a preferred embodiment, in the step S3 of simulation deduction, the digitalized model is driven by actual measurement data, and the state is changed in the simulation deduction, and the simulation model is driven by a specific simulation scheme, and the position, speed and state are changed according to the simulation scheme setting.
According to a preferred embodiment, step S1 comprises: three types of data interfaces are defined, namely an INPUT interface, an OUTPUT interface and an x interface,
the INPUT interface and the OUTPUT interface are respectively used as an INPUT interface and an OUTPUT interface of the model and are used for carrying out data interaction with other models in the simulation process;
* The interface is used as an internal interface of the model and used for data interaction between the data module and the functional module in the model, and interaction between different functional modules can be performed by means of the data module through the interface;
the interfaces comprise an attitude data interface, a position data interface, an on-off state interface and other internal interfaces.
According to a preferred embodiment, step S1 comprises: the request mode, the parameter submitting mode, the request parameter and the response parameter of each type of interface are defined, and the interfaces are named and distinguished by different names or IDs based on the interactive data content of the interfaces.
According to a preferred embodiment, the evaluation result is used in step S5 to guide the simulation model to adjust specifically: based on the analysis result of the evaluation data, the functional composition and the number of the simulation models are adjusted and added into the joint simulation test.
According to a preferred embodiment, the evaluation result is used in step S5 to guide the simulation scheme adjustment specifically as: based on the analysis result of the evaluation data, the installation and deployment position, the on-off state and the running line direction of the simulation model are configured and adjusted, and the scheme is updated in the joint simulation test.
According to a preferred embodiment, step S5 further comprises a data store for storing simulation run data, performance assessment data in a data warehouse to support subsequent future multiple disk analysis.
The foregoing inventive concepts and various further alternatives thereof may be freely combined to form multiple concepts, all of which are contemplated and claimed herein. Various combinations will be apparent to those skilled in the art from a review of the present disclosure, and are not intended to be exhaustive or all of the present disclosure.
The invention has the beneficial effects that:
(1) The actual equipment is combined with the simulation model, and the actual measurement data is combined with the simulation data, so that the reliability and the reliability of the simulation result can be considered on the basis of improving the simulation efficiency and the effect, and the simulation model is more convincing;
(2) The simulation model generated by the simulation system can be utilized to timely perform blind supplement in the scene test process under the condition that actual equipment participates, the promotion effect of the cooperative application capability of the equipment can be timely evaluated, and the modification and optimization of the scheduling planning scheme can be guided;
(3) The simulation test process can be accelerated, and data support is provided for the development, production and application conversion of new equipment.
Drawings
FIG. 1 is a conceptual block diagram of a semi-solid state simulation method combining measured data with simulation data;
FIG. 2 is a flow chart of a semi-solid state simulation method combining measured data with simulation data in accordance with the present invention;
FIG. 3 is a schematic diagram of a data module and its interface;
FIG. 4 is a schematic diagram of functional modules and their interfaces;
fig. 5 is a schematic diagram of functional modules and their interfaces.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. In addition, in the present invention, if a specific structure, connection relationship, position relationship, power source relationship, etc. are not specifically written, the structure, connection relationship, position relationship, power source relationship, etc. related to the present invention can be known by those skilled in the art without any creative effort.
Examples
Referring to fig. 1 and 2, the invention discloses a semi-real-package simulation method combining measured data and simulation data, which is realized by the following steps.
1. Standardized data interface and functional component
The standardized data interface and the standardized functional components not only can realize the rapid custom assembly of the model, but also can access data and put into use after the model assembly is completed. Therefore, standardized configuration of the data interface and the functional components is a basis and premise for developing a semi-real-installation simulation method combining measured data with simulation data.
As shown in fig. 3 to 5, three types of data interfaces, i.e., an INPUT interface, an OUTPUT interface, and an OUTPUT interface, are defined, where the INPUT interface and the OUTPUT interface in a data module are respectively used as an INPUT interface and an OUTPUT interface of an assembly model, and are used for performing data interaction with other models in a simulation process, the OUTPUT interface in the data module and the function module are used as internal interfaces of the assembly model, and are used for performing data interaction between the data module and the function module, and interaction between different function modules can also be performed by means of the data module through the OUTPUT interface. * Interfaces represent a class of internal interfaces, such as gesture data interfaces, position data interfaces, on-off state interfaces, and the like.
The method comprises the steps of defining request modes, parameter submitting modes, request parameters, response parameters and the like of various interfaces such as an INPUT interface, an OUTPUT interface and the like, and naming and distinguishing the OUTPUT interfaces according to different names or IDs based on data content interacted by the OUTPUT interfaces. The interface types and numbers of different functional modules vary based on functional requirements. The data module's interface type covers all the function modules in the function module library.
2. Model generation
The method is based on the self-defined assembly of the data interface and the functional components, and can quickly generate the simulation model, which is an important link and content for developing simulation deduction. Model generation is mainly divided into two parts: and the digital model corresponds to the actual equipment and the simulation model is based on the simulation deduction requirement.
(1) The corresponding digital model is actually equipped. The model is based on real-time measurement data obtained by specific use of actual equipment in a simulation test scene, an association mapping relation from actual measurement data to equipment capacity to model functions is established by analyzing data content contained in the actual measurement data, functional components with corresponding functions are extracted for model assembly, a digital model corresponding to the actual equipment is generated, and the state and the display effect of the model are driven by the actual measurement data.
(2) And a simulation model based on simulation deduction requirements. The simulation model aims at carrying out blind supplement and improvement on the cooperative application capability of the existing equipment in the test verification scene, so that the simulation model is based on the analysis result of the efficiency evaluation data, a lower than expected link and capability improvement point are found through visual display effect graphs and analysis of the efficiency evaluation data, and the simulation model with the supplementary capability is quickly assembled and generated through a man-machine interaction mode and added into the test scene to participate in simulation.
3. Simulation deduction
The rapid development of computers, particularly high performance computers, provides many possibilities for ultra-real-time simulation deductions, by which hundreds of thousands or even hundreds of millions of repeated simulations and repeated deductions can be completed in the same time as the real world.
And building an integrated test environment and a system by combining the generated digital model and simulation model with the verification requirement of the simulation test.
The real-time digital model is driven by measured data, is mainly subjected to state change in the simulation deduction process, is generated based on evaluation data, is driven by a specific simulation scheme, and is set to change positions, speeds, states and the like according to the simulation scheme, so that capability supplement and lifting effects under different conditions can be evaluated later. Because of adopting standardized data interfaces, the addition and removal of the simulation model can not affect the whole simulation deduction process and data interaction.
In the simulation deduction process, parameters in a simulation scheme are configured and adjusted through a visual interface, and configuration and adjustment results are stored in a database in real time for analysis.
4. Efficacy assessment
The method combines actual equipment with a simulation system, and combines actual measurement data with simulation data to develop semi-real-package simulation, so as to verify the cooperative application capability of the actual equipment in an equipment system and the improvement effect of the addition of new equipment on the whole capability. The new equipment here refers to completely new equipment with different functions and capabilities that has not yet been delivered, or changes in number to existing equipment.
And establishing an evaluation index system based on a test verification scene, receiving simulation operation data generated by a simulation platform (system) in real time, performing efficiency evaluation, and outputting an evaluation result.
5. Capability feedback, adjustment optimization, and data storage
Semi-real simulations involving real equipment increase both the setup time and the test cost compared to pure digital simulations, and require more coordination and consideration. Therefore, in order to more fully utilize single test conditions, capability feedback and adjustment optimization based on an evaluation result are realized by continuously adjusting a simulation model and a simulation scheme, and by means of super-real-time simulation deduction, as many combination schemes as possible are verified.
The evaluation result is used for guiding the adjustment and optimization of the simulation model, namely, based on the analysis result of the evaluation data, the functional composition, the number and the like of the simulation model are adjusted and added into the joint simulation test.
The evaluation result is used for guiding the adjustment and optimization of the simulation scheme, namely, based on the analysis result of the evaluation data, the installation and deployment position, the on-off state, the running line direction and the like of the simulation model are configured and adjusted, and the scheme is updated in the joint simulation test.
The data storage is to store simulation operation data, performance evaluation data and the like into a data warehouse to support subsequent analysis of the disk.
Compared with the existing simulation method, the method of the invention mainly obtains the beneficial effects from the following three aspects: (1) The actual equipment is combined with the simulation model, and the actual measurement data is combined with the simulation data, so that the reliability and the reliability of the simulation result can be considered on the basis of improving the simulation efficiency and the effect, and the simulation model is more convincing; (2) The simulation model generated by the simulation system can be utilized to timely perform blind supplement in the scene test process under the condition that actual equipment participates, the promotion effect of the cooperative application capability of the equipment can be timely evaluated, and the modification and optimization of the scheduling planning scheme can be guided; (3) The simulation test process can be accelerated, and data support is provided for the development, production and application conversion of new equipment.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.

Claims (7)

1. The semi-packaging simulation method combining the measured data with the simulation data is characterized by comprising the following steps of:
s1: standardized data interfaces and functional components;
s2: the generation of the model is performed and,
performing custom assembly based on the data interface and the functional component to generate a simulation model, wherein the simulation model comprises: a digital model corresponding to the actual equipment and a simulation model based on simulation deduction requirements;
in step S2, the digital model corresponding to the actual equipment is based on the real-time measurement data obtained by the actual equipment in the simulation test scene, the association mapping relation from the actual measurement data to the equipment capability to the model function is established by analyzing the data content contained in the actual measurement data, the functional components with the corresponding functions are extracted for model assembly, the digital model corresponding to the actual equipment is generated, and the state and the display effect of the model are driven by the actual measurement data;
in step S2, a simulation model based on simulation deduction requirements is based on simulation data, a simulation model with supplementing capability is quickly assembled and generated in a man-machine interaction mode through visual display effect graphs and analysis of efficiency evaluation data, and the simulation model is added into a test scene to participate in simulation;
s3: the simulation deduction is carried out,
constructing an integrated test environment and a simulation system by combining the generated digital model and simulation model with the simulation test verification requirement, developing simulation deduction, configuring and adjusting parameters in a simulation scheme through a visual interface, and storing configuration and adjustment results in a database in real time for analysis;
s4: the performance of the test piece was evaluated,
establishing an evaluation index system based on a test verification scene, receiving simulation operation data generated by a simulation system in real time for efficiency evaluation, and outputting an evaluation result;
s5: the capacity feedback and the adjustment and optimization are carried out,
the simulation model and the simulation scheme are continuously adjusted, simulation deduction is carried out by means of the simulation system, verification and evaluation of various schemes are completed, and adjustment of the simulation model and adjustment of the simulation scheme are completed based on the obtained evaluation result.
2. The semi-solid state simulation method of claim 1, wherein in the step S3 of simulation deduction, the digitalized model is driven by actual measurement data, and the state is changed in the simulation deduction, the simulation model is driven by a specific simulation scheme, and the position, speed and state are changed according to the simulation scheme setting.
3. The semi-solid state simulation method of claim 1, wherein step S1 includes: three types of data interfaces are defined, namely an INPUT interface, an OUTPUT interface and an x interface,
the INPUT interface and the OUTPUT interface are respectively used as an INPUT interface and an OUTPUT interface of the model and are used for carrying out data interaction with other models in the simulation process;
* The interface is used as an internal interface of the model and used for data interaction between the data module and the functional module in the model, and interaction between different functional modules can be performed by means of the data module through the interface;
the interfaces represent internal interfaces such as an attitude data interface, a position data interface and a startup and shutdown state interface.
4. The semi-solid state simulation method of claim 3, wherein step S1 comprises: the request mode, the parameter submitting mode, the request parameter and the response parameter of each type of interface are defined, and the interfaces are named and distinguished by different names or IDs based on the interactive data content of the interfaces.
5. The semi-solid state simulation method of claim 1, wherein the step S5 of using the evaluation result to guide the simulation model adjustment is specifically: based on the analysis result of the evaluation data, the functional composition and the number of the simulation models are adjusted and added into the joint simulation test.
6. The semi-solid state simulation method of claim 1, wherein the step S5 of using the evaluation result to guide the simulation scheme adjustment is specifically: based on the analysis result of the evaluation data, the installation and deployment position, the on-off state and the running line direction of the simulation model are configured and adjusted, and the scheme is updated in the joint simulation test.
7. The semi-solid state simulation method of claim 1, wherein step S5 further comprises data storage for storing simulation run data, performance assessment data in a data warehouse to support subsequent post-processing analysis.
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