Virtual test planning design and operation evaluation method based on mechanism data fusion model

Abstract

The invention provides a virtual test planning design and operation evaluation method based on a mechanism data fusion model, and relates to the field of digital twinning of complex equipment. Implementation steps of the virtual test planning design and operation evaluation method based on the mechanism data fusion model comprise three step modules of data fusion model construction, virtual test planning design and virtual test operation evaluation. The data fusion model construction module comprises three steps of mechanism model construction, data-driven model construction and fusion strategy design, and the virtual test planning design step module comprises three steps of test target definition, test design optimization and test plan generation. According to the method, the mechanism model and the data driving model are combined to optimize and evaluate the virtual test process, and the method is widely applied to the fields of engineering design, product development, system optimization and the like.

Description

Technical Field

[0001] The present invention relates to the field of digital twins of complex equipment, and specifically to a virtual test planning, design and operation evaluation method based on a mechanism data fusion model. Background Art

[0002] In modern engineering design and system development, virtual testing is an important research method that can simulate the actual test process and reduce costs and time. However, traditional virtual testing methods are usually based on a single data source or model, such as a mechanism model or a data-driven model. The mechanism model is based on physical laws and theories and can provide more accurate simulations, but usually requires a lot of computing resources and time. The data-driven model uses historical data for modeling and can generate prediction results quickly, but lacks a deep understanding of the mechanism.

[0003] However, the current virtual test methods have the following shortcomings: 1. Insufficient data fusion. Existing methods usually fail to fully integrate the information of mechanism models and data-driven models. 2. Unoptimized test planning. In the test planning stage, the mechanism and data models are not fully utilized for optimization design. 3. Operation evaluation lacks comprehensiveness. During the operation of virtual tests, the evaluation method is often limited to the evaluation of a single model, and the contribution of various data sources cannot be comprehensively considered. Therefore, the present invention proposes a virtual test planning and design and operation evaluation method based on a mechanism data fusion model, so as to effectively improve the above-mentioned shortcomings of the virtual test method. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In view of the shortcomings of the prior art, the present invention provides a virtual experiment planning, design and operation evaluation method based on a mechanism data fusion model. For complex systems or experiments involving multiple factors, the data fusion model can comprehensively analyze various types of data and provide more comprehensive evaluation results, thereby better supporting the design and operation of complex systems. The data fusion model can integrate data from different sources, so that experiments and design decisions are based on more comprehensive and accurate information, thereby improving data utilization and the scientific nature of decision-making.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a virtual experiment planning, design and operation evaluation method based on a mechanism data fusion model, the implementation steps of the virtual experiment planning, design and operation evaluation method based on a mechanism data fusion model include three step modules: data fusion model construction, virtual experiment planning and design, and virtual experiment operation evaluation. The data fusion model construction module includes three steps: mechanism model construction, data-driven model construction, and fusion strategy design. The virtual experiment planning and design step module includes three steps: experiment goal definition, experiment design optimization, and experiment plan generation. The virtual experiment operation evaluation step module includes three steps: operation monitoring, evaluation index calculation, and result analysis and feedback.

[0008] Preferably, in the data fusion model construction step module, mechanism model construction is to build a mechanism model based on physical principles and engineering experience based on the multi-domain unified modeling language Model li ca to describe the basic behavior and laws of the system; data-driven model construction is to build a data-driven model through historical data and machine learning technology to capture the complexity and nonlinear characteristics of the system; fusion strategy design is to design a data fusion strategy to effectively fuse the outputs of the mechanism model and the data-driven model to improve the overall prediction ability of the model.

[0009] Preferably, in the virtual experiment planning and design step module, the experiment goal definition is to clarify the goals and requirements of the virtual experiment and determine the key parameters and indicators that need to be tested. The experiment design optimization is based on the fusion model to optimize the design of the virtual experiment, including the experiment conditions, input variables and experimental configuration. The experiment plan generation is to generate a detailed experiment plan and program.

[0010] Preferably, the operation monitoring in the virtual test operation evaluation step module is to monitor the running status of the virtual test, record the test data and intermediate results, the evaluation index calculation is based on the prediction results of the fusion model, and calculates the key evaluation indicators of the virtual test, such as accuracy, stability and reliability, and the result analysis and feedback is to conduct a comprehensive analysis of the virtual test results, evaluate the advantages and disadvantages of the design scheme, and feed back the results to the test planning and design stage to make necessary adjustments and improvements.

[0011] (III) Beneficial effects

[0012] The present invention provides a virtual test planning, design and operation evaluation method based on a mechanism data fusion model. It has the following beneficial effects:

[0013] 1. The present invention provides a virtual test planning, design and operation evaluation method based on a mechanism data fusion model. Through the data fusion model, different design schemes can be evaluated and optimized in a virtual environment, thereby reducing the number of actual tests, saving time and resources, and improving test efficiency.

[0014] 2. The present invention provides a virtual test planning, design and operation evaluation method based on a mechanism data fusion model. Comprehensive testing and evaluation are carried out in a virtual environment, which can discover potential problems before actual manufacturing or operation, thereby reducing risks in actual operations and improving safety.

[0015] 3. The present invention provides a virtual experiment planning, design and operation evaluation method based on a mechanism data fusion model. For experiments on complex systems or involving multiple factors, the data fusion model can comprehensively analyze various types of data and provide more comprehensive evaluation results, thereby better supporting the design and operation of complex systems.

[0016] 4. The present invention provides a virtual test planning, design and operation evaluation method based on a mechanism data fusion model. The data fusion model can integrate data from different sources so that the test and design decisions are based on more comprehensive and accurate information, thereby improving data utilization and the scientific nature of decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The operating steps of the virtual test planning, design and operation evaluation method based on the mechanism data fusion model of the present invention;

[0018] Figure 2 It is a schematic diagram of the steam generator unit mechanism data fusion system of the present invention;

[0019] Figure 3 It is a schematic diagram of the fault mode characteristic rule base of the present invention;

[0020] Figure 4 A schematic diagram of a steam generator set fault test sample set of the present invention;

[0021] Figure 5 It is a schematic diagram of the fault mode identification result of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In the description of this application, it should be noted that the terms used here are only for describing specific implementations, and are not intended to limit the exemplary implementations according to the present application. For ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The techniques, methods and devices known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the techniques, methods and devices should be regarded as part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary, not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0023] Embodiment 1:

[0024] like Figure 1-5 As shown, an embodiment of the present invention provides a virtual test planning, design and operation evaluation method based on a mechanism data fusion model. The implementation steps of the virtual test planning, design and operation evaluation method based on a mechanism data fusion model are as follows:

[0025] S1: Data fusion model construction. The data fusion model construction module includes three steps: mechanical model construction, data-driven model construction, and fusion strategy design.

[0026] S2: Virtual test planning and design. The virtual test planning and design step module includes three steps: test goal definition, test design optimization, and test plan generation.

[0027] S3: Virtual test operation evaluation. The virtual test operation evaluation step module includes three steps: operation monitoring, evaluation index calculation, and result analysis and feedback.

[0028] Embodiment 2:

[0029] like Figure 1-5 As shown, the embodiment of the present invention provides a virtual test planning, design and operation evaluation method based on a mechanism data fusion model, which can be further explained by taking a steam turbine generator set as an example through the following aspects:

[0030] S1: Construction of the data fusion model of the steam turbine generator unit mechanism

[0031] Step 1: Establishment of mechanism model. By analyzing the physical process and engineering characteristics of the system, relying on the multi-domain unified modeling and simulation platform MWORKS.System, we build mechanism models of condensers, pipelines, valves, etc. based on basic physical laws such as differential equations, fluid mechanics, and thermodynamics. This model takes into account the main behaviors and key parameters of the system. The mechanism model is verified and calibrated through design / experimental data to ensure the accuracy of the model for the actual system.

[0032] Step 2: Establishment of data-driven model. Collect historical data of steam turbine main engine operation, including experimental data, operation data, etc. Based on MWORKS.Sys l ab, Python and other tools, use statistical analysis and machine learning algorithms (such as regression analysis, neural network, support vector machine, etc.) to establish steam turbine data-driven model, train the data-driven model, and verify and optimize the model through hyperparameter optimization, feature selection and other technologies to ensure its accuracy in actual prediction;

[0033] Step 3: Model fusion and integration. Design a model fusion method (series, parallel, and hybrid) to combine the prediction results of the mechanism model and the data-driven model. In this example, the series method is used for fusion. The fusion model is adjusted and optimized to ensure that its comprehensive performance is better than that of a single model, forming a complete steam generator unit mechanism data fusion system. Figure 2 As shown;

[0034] S2: Virtual experiment planning and design;

[0035] Step 1: Define the test objectives, clarify the purpose of the virtual test, and carry out the condenser performance fault virtual test by fault injection;

[0036] Step 2: Experimental design optimization, using the fusion model to design fault injection experiments, combining and screening the entire set of experiments through the MWORKS.System Experiment Design Optimization Toolbox, and finally obtaining the best experimental plan, extracting the variation rules of each key parameter, and using the membership function to fuzzify the data to grasp the characteristic matrix of performance failures, such as Figure 3 As shown, it serves as the basis for fault diagnosis;

[0037] Step 3: Test plan generation: Generate the corresponding fault test sample set according to the test design, such as Figure 4 As shown;

[0038] S3: Virtual test operation and evaluation;

[0039] Step 1: Operation monitoring: During the virtual test operation, monitor the status of the test system, record the test data and intermediate results, and use data acquisition and processing technology to ensure the accuracy and completeness of the data;

[0040] Step 2: Evaluation index calculation: According to the prediction results of the fusion model, calculate the relevant parameters in the fault feature matrix, compare the results under different test conditions, and analyze their impact on the target indicators;

[0041] Step 3: Result analysis and feedback: Comprehensively analyze the test results to identify potential problems and optimization directions, such as Figure 5 As shown, the results are fed back into the trial planning stage to make necessary adjustments and improvements.

[0042] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A virtual test planning, design and operation evaluation method based on a mechanism data fusion model, characterized by: The implementation steps of the virtual experiment planning, design and operation evaluation method based on the mechanism data fusion model include three step modules: data fusion model construction, virtual experiment planning and design, and virtual experiment operation evaluation. The data fusion model construction module includes three steps: mechanism model construction, data-driven model construction, and fusion strategy design. The virtual experiment planning and design step module includes three steps: experiment goal definition, experiment design optimization, and experiment plan generation. The virtual experiment operation evaluation step module includes three steps: operation monitoring, evaluation index calculation, and result analysis and feedback.

2. According to claim 1, a virtual experiment planning, design and operation evaluation method based on a mechanism data fusion model is characterized by: In the data fusion model construction step module, the mechanism model construction is to build a mechanism model based on physical principles and engineering experience based on the multi-domain unified modeling language Modelica to describe the basic behavior and laws of the system. The data-driven model construction is to build a data-driven model through historical data and machine learning technology to capture the complexity and nonlinear characteristics of the system. The fusion strategy design is to design a data fusion strategy to effectively fuse the outputs of the mechanism model and the data-driven model to improve the overall prediction ability of the model.

3. The method for virtual test planning, design and operation evaluation based on a mechanism data fusion model according to claim 1 is characterized by: In the virtual experiment planning and design step module, the experiment goal definition is to clarify the goals and requirements of the virtual experiment and determine the key parameters and indicators that need to be tested. The experiment design optimization is based on the fusion model to optimize the design of the virtual experiment, including the experiment conditions, input variables and experimental configuration. The experiment plan generation is to generate a detailed experiment plan and program.

4. The method for virtual test planning, design and operation evaluation based on a mechanism data fusion model according to claim 1 is characterized by: The operation monitoring in the virtual test operation evaluation step module is to monitor the operation status of the virtual test, record the test data and intermediate results, the evaluation index calculation is based on the prediction results of the fusion model, and calculates the key evaluation indicators of the virtual test, such as accuracy, stability and reliability, and the result analysis and feedback is to conduct a comprehensive analysis of the virtual test results, evaluate the advantages and disadvantages of the design scheme, and feed back the results to the test planning and design stage to make necessary adjustments and improvements.

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