Meterable parameter constraint method for FTIR spectrometer based on MBSE

Abstract

The invention provides an MBSE-based FTIR spectrometer measurable parameter constraint method, which comprises the following steps of: determining value attribute indexes of function requirements and performance requirements related to Fourier transform infrared spectrometer magnitude traceability, and establishing constraint conditions comprising value attribute indexes of element parameters and element items to generate a constraint module; constructing a multi-level architecture model of the Fourier transform infrared spectrometer, and integrating the element parameters, the element items and the constraint module into the multi-level architecture model through a binding chain to generate a measurable model; based on pre-established system design requirements, external simulation software is utilized to perform simulation analysis on design performance of a measurable model, a simulation result is fed back to an MBSE system model to automatically verify and update the simulation result, various parameters are debugged in iteration to obtain a plurality of results, and the accuracy of the simulation result is improved. And selecting a result meeting the requirement from the plurality of results as output. In this way, the measurability is made throughout the entire design stage of the common design model.

Description

Technical Field

[0001] This invention relates to the fields of metrology and systems engineering methodology, and in particular to a method for constraining the metrability parameters of a Fourier Transform Infrared (FTIR) spectrometer based on model-based systems engineering (MBSE). Background Technology

[0002] Metrology is the activity of achieving unit standardization and accurate and reliable measurement values. By definition, metrology is a special type of measurement, a science concerning measurement, including activities such as verification, calibration, value determination, degree determination, comparison, and testing (of measuring instruments). Fourier transform infrared (FTIR) spectrometers, as core equipment in modern analytical science, are widely used in materials testing, pharmaceuticals, chemicals, and gas analysis. The accuracy and reliability of their values ​​depend on the measurability of key parameters. Traditional design methods typically employ a document-driven systems engineering model, dispersing key parameters such as wavenumber, transmittance, resolution, and noise across requirements documents, simulation tools, and test reports, making it difficult to globally visualize and dynamically verify the constraints between parameters. The MBSE method provides a new paradigm for the development of complex instruments. It constructs a unified Requirement-Function-Logic-Physical (RFLP) architecture model through standardized system modeling languages ​​(such as SysML), supporting dynamic correlation and constraint optimization of multidisciplinary parameters.

[0003] Currently, MBSE modeling is a commonly used technique, and the MagicGrid methodology version 2.0 has been released, introducing the dimensions of safety and reliability. Subsequently, drawing on the ideas of safety and reliability, measurability was introduced as a constraint for MBSE modeling. However, in measurability assurance, because it increases design costs, measurability cannot be consistently applied throughout the entire design phase in commonly used design models. Summary of the Invention

[0004] The purpose of this invention is to provide a method for constraining the metrability parameters of an FTIR spectrometer based on MBSE, thereby solving the problem that metrability cannot be maintained throughout the entire design phase in commonly used design models in the prior art.

[0005] To address the aforementioned technical problems, the embodiments of the present invention provide the following technical solutions: The first aspect of this invention provides a method for constraining the metrability parameters of an FTIR spectrometer based on MBSE, comprising: Determine the value attribute indicators of the functional and performance requirements related to the traceability of Fourier transform infrared spectrometer values, and establish the constraints of the value attribute indicators to generate constraint modules. The value attribute indicators include element parameters and element items. In the MBSE environment, a multi-level architecture model of the Fourier transform infrared spectrometer is constructed. The constraint module, the element parameters and element items in the value attribute index are integrated into the multi-level architecture model through binding chains to generate a quantifiability model of the Fourier transform infrared spectrometer. Based on the pre-established system design requirements, the design performance of the measurability model is simulated and analyzed using external simulation software. The simulation results are fed back to the MBSE system model, and the MBSE system model is used to automatically verify and update the simulation results. During the iteration process, various parameters are adjusted according to the updated simulation results to obtain multiple results. One result that meets the requirements is selected from the multiple results as the output to achieve the measurability parameter constraints of the Fourier transform infrared spectrometer.

[0006] A second aspect of the present invention provides a metrological parameter constraint device for an FTIR spectrometer based on MBSE, comprising: A module is established to determine the value attribute indicators of functional and performance requirements related to the traceability of Fourier transform infrared spectrometer measurements, and to establish the constraints of the value attribute indicators to generate a constraint module. The value attribute indicators include element parameters and element items. The integration module is used to build a multi-level architecture model of the Fourier transform infrared spectrometer in the MBSE environment. It integrates the constraint module, the element parameters and element items in the value attribute index into the multi-level architecture model through binding chains to generate a measurability model of the Fourier transform infrared spectrometer. The verification and update module is used to perform simulation analysis on the design performance of the measurability model based on pre-established system design requirements using external simulation software. The simulation results are fed back to the MBSE system model, and the MBSE system model is used to automatically verify and update the simulation results. During the iteration process, various parameters are adjusted according to the updated simulation results to obtain multiple results. One result that meets the requirements is selected as the output to achieve the measurability parameter constraints of the Fourier transform infrared spectrometer.

[0007] Compared to existing technologies, the MBSE-based method for constraining the measurability parameters of FTIR spectrometers provided in this invention determines the value attribute indicators of functional and performance requirements related to the traceability of Fourier transform infrared spectrometer measurements, and establishes constraint conditions for these value attribute indicators to generate constraint modules. The value attribute indicators include element parameters and element items. A multi-level architecture model of the Fourier transform infrared spectrometer is constructed in the MBSE environment. The constraint modules, element parameters, and element items from the value attribute indicators are integrated into the multi-level architecture model through binding chains to generate a measurability model of the Fourier transform infrared spectrometer. Based on pre-established system design requirements, the design performance of the measurability model is simulated and analyzed using external simulation software. The simulation results are fed back to the MBSE system model, and the MBSE system model automatically verifies and updates the simulation results. During the iteration process, various parameters are adjusted based on the updated simulation results to obtain multiple results. One result that meets the requirements is selected as the output to achieve the constraint of the measurability parameters of the Fourier transform infrared spectrometer. In this way, the corresponding metrological characteristics of the element parameters and element items can be added to the model design. Based on the constraint update of the MBSE system model, the element parameters, element items and constraint modules are integrated into the multi-level architecture model of the Fourier transform infrared spectrometer. This allows for the addition of measurable parameter constraints to the multi-level architecture model of the Fourier transform infrared spectrometer, resulting in a measurable model of the Fourier transform infrared spectrometer that integrates measurable parameter constraints. This enables a closed-loop Fourier transform infrared spectrometer design management that spans the entire chain from requirement decomposition to parameter constraints, ensuring that measurability is integrated throughout the entire design phase of commonly used design models. Attached Figure Description

[0008] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the invention are illustrated by way of example and not limitation, with the same or corresponding reference numerals denoteing the same or corresponding parts, wherein: Figure 1 A flowchart illustrating the MBSE-based method for constraining the metrability parameters of an FTIR spectrometer is shown schematically. Figure 2 A schematic diagram illustrating the element parameters and element items is provided. Figure 3 A schematic diagram of a multi-level architecture model of a Fourier transform infrared spectrometer is shown. Figure 4 A schematic diagram of the module for element parameters, element items, and measurement characteristic threshold constraints is shown. Figure 5 A schematic diagram illustrating the quantifiability constraint relationship of the light source module in a Fourier transform infrared spectrometer is shown. Figure 6 A schematic diagram of the structure of the metrological parameter constraint device for an MBSE-based FTIR spectrometer is shown. Detailed Implementation

[0009] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0010] It should be noted that, unless otherwise stated, the technical or scientific terms used in this invention should have the ordinary meaning as understood by one of ordinary skill in the art.

[0011] The methods described in the embodiments of the present invention will be explained in detail below.

[0012] Figure 1 A flowchart illustrating the method for constraining metrological parameters of an MBSE-based FTIR spectrometer in an embodiment of the present invention is shown schematically. See [link to relevant documentation]. Figure 1 As shown, the MBSE-based method for constraining the metrability parameters of an FTIR spectrometer may include: S101. Determine the value attribute indicators of the functional and performance requirements related to the traceability of Fourier transform infrared spectrometer values, and establish the constraint conditions of the value attribute indicators to generate the constraint module.

[0013] Among them, value attribute indicators include two types: feature parameters and feature items.

[0014] Figure 2 A schematic diagram illustrating feature parameters and feature items is shown below. Figure 2 As shown, the key parameters include wavenumber indication error, wavenumber repeatability, transmittance repeatability, resolution, background spectral energy distribution, flatness of the 100% line, noise, calibration cycle, calibration time, and calibration cost; the key items include the metrology interface and metrology method. Resolution includes the number of resolution parameters, resolution depth, and half-maximum width at half-maximum (FWHM) of water.

[0015] Specifically, the element parameters are indicators that can fully describe the measurability performance of a product. They are value attributes related to the performance requirements of Fourier transform infrared spectrometers for traceability, including metrological characteristics (which generally include: accuracy, stability, repeatability, resolution, error, uncertainty, etc.; the corresponding metrological characteristics for Fourier transform infrared spectrometers are: wavenumber indication error, wavenumber repeatability, transmittance repeatability, resolution, background spectral energy distribution, flatness of the 100% line, and noise), calibration cycle, and calibration time. The sources of element parameter requirements include JJF 1319-2011 "Calibration Specification for Fourier Transform Infrared Spectrometers," product design requirements, and user department requirements.

[0016] Element items are indicators used to describe the degree of measurability of a product. They are value attributes of functional requirements related to the traceability of Fourier transform infrared spectrometers. These functional requirements generally include: metrology interface design and its generalization requirements, and requirements for supporting online / in-situ / offline calibration. These requirements are quantified using functions. The sources of element item requirements include product design requirements and user department requirements. For Fourier transform infrared spectrometers, the element items are: metrology interface and metrology method.

[0017] Specifically, a constraint module is established to constrain element parameters and element items. This module contains constraint formulas for element parameters and element items. The constraint formulas for element parameters include: Wavenumber indication error constraint formula: Wavenumber indication error ≤ Maximum permissible wavenumber error. Wavenumber repeatability constraint formula: Wavenumber repeatability ≤ Wavenumber repeatability threshold. Transmittance repeatability constraint formula: Transmittance repeatability ≤ Transmittance repeatability threshold. Resolution number constraint formula: Resolution number ≥ Resolution number threshold. Resolution depth constraint formula: Resolution depth ≥ Resolution depth threshold. Water half-width constraint formula: Water half-width ≤ Water half-width threshold. Background spectral energy distribution constraint formula: Background spectral energy distribution ≥ Background spectral energy distribution threshold. 100% line straightness constraint formula: 100% line straightness ≤ 100% line straightness threshold. Noise constraint formula: Noise ≤ Noise threshold. Calibration cycle constraint formula: ,in, For total cost, , For calibration costs, , For calibration cycle, The unreliability cost factor, For calibration reliability, , This is the failure rate parameter. The constraint formulas for calibration time and calibration cost are: ,in, For calibration costs, Calibration cost rate per unit time The time required for calibration.

[0018] The maximum permissible error for wavenumber is ±(1~5) cm. -1 The wavenumber repeatability threshold ranges from 0.5 to 2.5 cm. -1 The transmittance repeatability threshold is 0.5%, the resolution threshold is 7, the resolution depth threshold is 12-18%, and the half-width at half-maximum (WHM) threshold for water is 2 cm. -1 The background spectral energy distribution threshold is 20%, the flatness threshold of 100% line ranges from 1 to 4%, and the noise threshold is 1%.

[0019] Simultaneously, establishing value attribute indicators for various thresholds in the feature parameters requires first obtaining the values ​​of these thresholds. Specifically, this involves obtaining the values ​​of various thresholds in the feature parameters that have been pre-set manually, set using expert databases, obtained through software simulation analysis, or through simulation iterations after pre-setting. Alternatively, it can involve obtaining the values ​​of various thresholds in the feature parameters that have been set through design schemes, calibration specifications, or requirements from users or metrology institutions.

[0020] The formula for constraint on element items is: ,in, It is the overall quantitative score of the element items. ,in, It is the first weighting coefficient. It is the second weighting coefficient. , It is the quantization function of the metering interface. It is a quantization function of the measurement method. These are the relevant parameters of the metering interface. These are the relevant parameters for the measurement method. The target score generally needs to be greater than 0. The specific expression of the quantization function in the measurement interface is: For Fourier transform infrared spectrometers, if the measurement window supports the placement of polystyrene infrared wavelength standard materials, then the metrology interface meets the calibration requirements. The metrology quantization function is... .

[0021] S102. Construct a multi-level architecture model of the Fourier transform infrared spectrometer in the MBSE environment. Integrate the constraint module, the element parameters and element items in the value attribute index into the multi-level architecture model through binding chains to generate a measurability model of the Fourier transform infrared spectrometer.

[0022] Specifically, the SysML modeling language is used for MBSE modeling. Requirements are input according to design requirements to establish stakeholder needs. Behavioral and functional requirements are analyzed through use case diagrams. The system automatically captures stakeholder needs, and the action structure is analyzed through system context. Finally, value attributes are assigned in a black-box environment (an analysis state that cannot be explicitly defined, generally based on the system's existing modeling database), thus obtaining the requirements captured in the black-box environment. Then, in a white-box environment (analysis activities conducted in a defined application scenario, requiring the application scenario and activities to be defined), the logical functions of the Fourier transform infrared spectrometer are analyzed. Its logical architecture is analyzed to obtain the corresponding subsystem logical architecture, and value attributes are assigned to the subsystem logical architecture, thus obtaining a complete requirements analysis result.

[0023] Specifically, the constraint module, the feature parameters and feature items in the value attribute indicators are integrated into a multi-level architecture model through binding chains to generate a measurability model for the Fourier transform infrared spectrometer, including: Step A1: Bind the value attribute metrics to the elements of each level in the multi-level architecture model and assign values ​​to obtain the assigned value attribute metrics.

[0024] Figure 3 A schematic diagram of a multi-level architecture model of a Fourier transform infrared spectrometer is shown below. Figure 3 As shown, before binding and assigning values ​​to the attributes and elements of each level in the multi-level architecture model, it is necessary to construct a multi-level architecture model of the Fourier transform infrared spectrometer. A module definition diagram is used to represent the multi-level architecture model of the Fourier transform infrared spectrometer. The multi-level architecture model of the Fourier transform infrared spectrometer includes a first-level model and a second-level model. The first-level model is the Fourier transform infrared spectrometer itself, and the second-level model includes a light source module, an interferometer module, a detector module, an optical device module, and a data processing module. The multi-level architecture model of the Fourier transform infrared spectrometer also includes a third level, which consists of the devices that make up each module. The first-level Fourier transform infrared spectrometer is constructed, and then the second-level models are constructed separately: the light source module model, the interferometer module model, the detector module model, the optical device module model, and the data processing module model.

[0025] By establishing the Fourier transform infrared spectrometer architecture model, the assignment of quantifiable index values ​​can be completed. For the value attributes of each module in the Fourier transform infrared spectrometer architecture model, the value attribute indicators of the feature parameters are assigned values ​​by establishing a transmission chain through the relationship. After conventional design (such as document design, simulation design, etc.), the changed value attributes are transmitted back to the feature parameters through the transmission chain.

[0026] Step A2: Based on the constraint module and the assigned value attribute index, establish measurable index constraint relationships between the elements of each level in the multi-level architecture model.

[0027] Specifically, step A2 includes: Step A21: Construct a constraint model, which includes a feature parameter module, a feature item module, a measurement characteristic threshold module, and a constraint module.

[0028] The constraint module uses constraint formulas to constrain or calculate the values ​​of feature parameters and feature items.

[0029] Figure 4 A schematic diagram illustrating the module for element parameters, element items, and measurement characteristic threshold constraints is shown below. Figure 4 As shown, the constraint model includes an element parameter module, an element item module, a metrological characteristic threshold module, and a constraint module. The element parameter module includes wavenumber indication error, wavenumber repeatability, transmittance repeatability, number of resolutions, resolution depth, water's half-maximum width (FWHM), background spectral energy distribution, flatness of the 100% line, noise, calibration cycle, calibration time, and calibration cost. The element item module includes the metrological interface and metrological method. The metrological characteristic threshold module includes wavenumber indication error threshold, wavenumber repeatability threshold, transmittance repeatability threshold, number of resolutions threshold, resolution depth threshold, water's FWHM threshold, background spectral energy distribution threshold, flatness of the 100% line threshold, and noise threshold. The constraint module includes constraint formulas for element parameters and element item constraints.

[0030] Step A22: Establish the relationship between the constraint model and the Fourier transform infrared spectrometer, light source module, interferometer module, detector module, optical device module, and data processing module, so that the constraint model forms a binding chain with the Fourier transform infrared spectrometer and each module.

[0031] The established relationships enable the connection between the constraint model and multiple modules in the above 5 models. Since the constraint model and each module have value attributes, the value attributes of the constraint model and the connected modules form a transmission chain. Generally, the transmission of value attributes is carried out through the binding chain.

[0032] Step A23: Using the binding chain, transfer and assign the value attribute indicators assigned in the constraint model to the value attribute indicators of the Fourier transform infrared spectrometer, light source module, interferometer module, detector module, optical device module, and data processing module.

[0033] New value attributes defined in the Fourier Transform Infrared Spectrometer and its light source, interferometer, detector, optical device, and data processing models (which may be of the same value type as the feature parameters, related to the feature parameters, or unrelated to the feature parameters) are created after the constraint modules. Passed according to the binding chain definition order, the constraint models copy the corresponding value attributes to the Fourier Transform Infrared Spectrometer, light source, interferometer, detector, optical device, and data processing modules.

[0034] In the multi-level architecture model of the Fourier transform infrared spectrometer, the constraints of the measurability indicators at three different levels are logically structured as follows: the element parameter module allocates indicators (element parameters) from the upper level to the lower level, distributing the indicator relationships layer by layer. Then, the lower level uses use case analysis and simulation software to invert the indicators obtained from the simulation design back to the upper level, ultimately obtaining the element parameter indicators based on the simulation design. When the element parameters meet their corresponding threshold requirements, the solution results will show that they meet the design requirements during subsequent simulation calculations and verifications. Alternatively, element parameters can be directly allocated from the upper level to the lower level, refining each parameter individually, and then the device performance data from the third level (device level) is aggregated layer by layer to the upper level.

[0035] Step A24: When the value of any value attribute indicator in the multi-level architecture model changes, the changed value of any value attribute indicator is passed through the binding chain, and the value of the corresponding value attribute indicator in the constraint model is updated.

[0036] When the value of any module's value attribute changes, the value of the connected value attribute also changes. At this time, the value attribute is no longer passed in the order defined by the binding chain, but is passed from the changed end to the unchanged end. That is, the value after simulation design will change, and the changed value will be passed to the value attribute of the feature parameter module along with the connection.

[0037] For element items, the quantization function requirements of the element item module are passed as requirements to the upper level (Fourier Transform Infrared Spectrometer) by constructing requirement modules. The upper level (Fourier Transform Infrared Spectrometer) prioritizes the element item requirements (those with a quantization function of 1 are given priority; if a priority requirement conflicts with the design, it needs to be changed to the next lower requirement, for example...). The priority requirement for the metrology method is to meet online calibration. If meeting the online calibration requirement conflicts with the design, it will switch to meeting the in-situ calibration requirement. If the in-situ calibration requirement is not met, it will switch to meeting the offline calibration requirement. The data is then assigned to the lower levels (light source module model, interferometer module model, detector module model, optical device module model, and data processing module model). When designing the lower levels, the requirements of the element items (metrology interface and metrology method) must be considered.

[0038] Step A25: Associate the measurability-related indicators with conventional design to decompose the first-level indicators to the second level, and establish physical relationships between the value attribute indicators in the constraint model and the value attribute indicators in the design to establish measurability indicator constraint relationships.

[0039] Constraint blocks are used to represent the measurability constraints between elements. These constraints include measurability index constraints for the same product within the Fourier transform infrared spectrometer system, as well as upper- and lower-level measurability index constraints within the system. The purpose of the constructed constraint model is to correlate measurability-related indicators with conventional design. The constructed constraints are a common practice in conventional design, aiming to decompose higher-level indicators to lower-level indicators, while simultaneously establishing physical relationships between the value attributes in the constraint model and the value attributes in the design. For example, Figure 5 A schematic diagram illustrating the quantifiability constraint relationships of the light source module in a Fourier transform infrared spectrometer is shown below. Figure 5 As shown, for the light source module, the constraints for establishing the measurability indicators at this level include constraints 1 to 5. The parameters in the light source module include beam range, light source stability, and spectral radiant flux, which can be measured using a metrology interface and metrology methods. This involves constraints on transmittance repeatability, background spectral energy distribution formulas, 100% line flatness formulas, and noise formulas within the constraint model. Constraints 1 to 5 include voltage stability formulas, transmittance repeatability formulas, background spectral energy distribution formulas, 100% line flatness formulas, and noise formulas.

[0040] Step A3: Based on the constraints of measurability indicators, construct the traceability relationship of measurability indicators in a multi-level architecture model to generate the measurability model of the Fourier transform infrared spectrometer.

[0041] Once the quantifiable indicator constraints are established, the normal design process can also include these constraints when building traceability relationships. Building them separately is simply for greater clarity and visibility.

[0042] Specifically, step A3 includes: Step A31: Create a detailed demand matrix based on the constraints of measurable indicators.

[0043] The detailed requirements matrix stores the design parameters, design requirements, and relationships between the design parameters and design requirements for each module in the multi-level architecture model. The detailed requirements matrix includes activity and value attributes for each module.

[0044] Create a Refine Requirement Matrix that stores the stakeholder requirements and relationships in the Fourier Transform Infrared Spectrometer model described above, and includes stakeholder activities and value attributes.

[0045] Step A32: By adjusting the activity and value attributes, the relationships and design results at each level are adjusted in a coordinated manner to form a traceable relationship of measurable indicators.

[0046] By adjusting the linkage between activities and value attributes, the relationship and results between upper and lower levels can be adjusted to form a traceable relationship chain, thereby better capturing and refining the needs of stakeholders.

[0047] S103. Based on the pre-established system design requirements, use external simulation software to simulate and analyze the design performance of the measurability model, feed the simulation results back to the MBSE system model, and use the MBSE system model to automatically verify and update the simulation results. During the iteration process, adjust various parameters according to the updated simulation results to obtain multiple results, and select a result that meets the requirements from the multiple results as the output to realize the measurability parameter constraints of the Fourier transform infrared spectrometer.

[0048] The overall concept of step S103 is to carry out the design based on the measurability model established in step S102, and to conduct simulations using different simulation software to determine the structure, behavior and parameters of each level of the Fourier transform infrared spectrometer.

[0049] Based on the design requirements, input the needs and establish the physical hierarchy design requirements for the Fourier Transform Infrared Spectrometer's structure, behavior, and parameters. Perform logical analysis on the system, subsystems, and components, and construct the traceability relationships between modules. Based on MBSE, the metrological design of the Fourier Transform Infrared Spectrometer can be carried out.

[0050] Specifically, design performance includes the structure, behavior, and parameter attributes of each layer in the multi-level architecture model; based on pre-established system design requirements, external simulation software is used to simulate and analyze the design performance of the measurability model, and the simulation results are fed back to the MBSE system model, including: Step B1: Based on the pre-established system design requirements, use the MBSE system model and integrate external simulation software to perform simulation analysis on the structure, behavior and parameter attributes of each level, and obtain simulation results.

[0051] Step B2: Based on the simulation results, construct a physical hierarchy in the MBSE system model that includes the structure, behavior and parameter attributes of each level.

[0052] Because MBSE can be integrated with various optoelectronic simulation software, such as ZEMAX, COMSOL, and MATLAB, the structure, behavior, and parameters of each level in the multi-level architecture model of the Fourier Transform Infrared Spectrometer were simulated according to design requirements. The simulation results were then used to guide the construction of the physical hierarchy of the structure, behavior, and parameters of each level of the Fourier Transform Infrared Spectrometer. An example of data conversion between the simulation software and the MBSE model is shown below: The simulated optical cavity structure was exported from ZEMAX via the ZOS-API application programming interface, verified by MATLAB, and then converted into a JSON file for import into the SysML model. The corresponding Python code is as follows: # Connect to Zemax # Connect to Zemax optical design software (Note) # zos = ZOSAPI() # Creates an API interface object for Zemax OpticStudio # zos.System.LoadFile("filename.zmx") # Load an existing optical design file named "filename" using the Zemax API # # Get optical parameters # Get optical parameter comments # focal_length = zos.System.GetFocalLength() # Call the API's "GetFocalLength()" to get the focal length parameter of the optical system and assign it to the variable "focal_length". f_number = zos.System.GetFNumber() # Call the API's "GetFNumber()" function to retrieve the aperture value parameter of the optical system and assign it to the variable "f_number". transmittance = zos.System.GetTransmittance() # Call the API's "GetTransmittance()" to get the transmittance parameter of the optical system and assign it to the variable "transmittance". # Save parameters as JSON format # Save parameters as JSON format (comment) # import json # Use Python's built-in json module to convert data structures to JSON format # optical_params = { "focal_length": focal_length, "f_number": f_number, "transmittance": transmittance} # Create a Python dictionary named "optical_params" to store the three optical parameters mentioned above, forming a JSON data structure. # with open("optical_params.json", "w") as f: `json.dump(optical_params, f)` # Dumps the Python dictionary "optical_params" into a JSON file named "optical_params.json". The above content pertains to format conversion and is general knowledge content.

[0053] Specifically, the MBSE system model is used to automatically verify and update simulation results. During the iteration process, various parameters are adjusted based on the updated simulation results to obtain multiple results. One result that meets the requirements is selected as the output to achieve the metrability parameter constraints of the Fourier transform infrared spectrometer, including: Step C1: Based on the model tree in the MBSE system model, establish a requirement matrix between design requirements and measurable model elements.

[0054] The demand matrix has functions such as mapping, visualization, and tracing between elements and demands.

[0055] Step C2: Based on the traceability mechanism formed by the demand matrix, the measurability model is iterated and updated multiple times. During the iteration process, various parameters are adjusted according to the updated simulation results to obtain multiple results. Among the multiple results, one that meets the requirements is selected as the output to realize the measurability parameter constraints of the Fourier transform infrared spectrometer.

[0056] Specifically, after establishing the physical hierarchy corresponding to the various levels of structure, behavior, and parameter attributes of the Fourier transform infrared spectrometer, the model tree is organized, and a matrix of user-captured satisfaction relationships, i.e., a demand matrix, is created. In the demand matrix, each demand is satisfied by one or more elements of the system configuration model, forming a demand table of quantifiable configurable satisfaction relationships. Furthermore, by tracing these relationships, design iterations can be better realized to achieve quantifiable parameter constraints for the Fourier transform infrared spectrometer.

[0057] Based on MBSE, measurability is used as a constraint or constraint model to constrain the design, thereby enabling the consideration of measurability in the design process.

[0058] When designing the multi-level architecture model of a Fourier transform infrared spectrometer, its metrological characteristics, such as wavenumber indication error, beam repeatability, and transmittance repeatability, are incorporated into the model design, ensuring that metrability is integrated throughout the entire design phase.

[0059] Based on the above Figure 1 As can be seen from the implementation method, the embodiments of the present invention determine the value attribute indicators of functional and performance requirements related to the traceability of Fourier transform infrared spectrometers, and establish constraints on the value attribute indicators to generate constraint modules. The value attribute indicators include element parameters and element items. A multi-level architecture model of the Fourier transform infrared spectrometer is constructed in the MBSE environment. The constraint modules, element parameters and element items in the value attribute indicators are integrated into the multi-level architecture model through binding chains to generate a measurability model of the Fourier transform infrared spectrometer. Based on the pre-established system design requirements, the design performance of the measurability model is simulated and analyzed using external simulation software. The simulation results are fed back to the MBSE system model, and the simulation results are automatically verified and updated using the MBSE system model. During the iteration process, various parameters are adjusted according to the updated simulation results to obtain multiple results. One result that meets the requirements is selected from the multiple results as the output to realize the measurability parameter constraints of the Fourier transform infrared spectrometer. In this way, the corresponding metrological characteristics of the element parameters and element items can be added to the model design. Based on the constraint update of the MBSE system model, the element parameters, element items and constraint modules are integrated into the multi-level architecture model of the Fourier transform infrared spectrometer. This allows for the addition of measurable parameter constraints to the multi-level architecture model of the Fourier transform infrared spectrometer, resulting in a measurable model of the Fourier transform infrared spectrometer that integrates measurable parameter constraints. This enables a closed-loop Fourier transform infrared spectrometer design management that spans the entire chain from requirement decomposition to parameter constraints, ensuring that measurability is integrated throughout the entire design phase of commonly used design models.

[0060] Based on the same inventive concept, as an implementation of the above-mentioned MBSE-based method for constraining the metrability parameters of an FTIR spectrometer, this embodiment of the invention also provides an MBSE-based device for constraining the metrability parameters of an FTIR spectrometer. Figure 6 This is a structural diagram of the device in an embodiment of the present invention. See also: Figure 6 As shown, the MBSE-based FTIR spectrometer metrology parameter constraint device may include: Module 601 is established to determine the value attribute indicators of the functional and performance requirements related to the traceability of Fourier transform infrared spectrometer measurements, and to establish the constraints of the value attribute indicators to generate a constraint module. The value attribute indicators include element parameters and element items. Integration module 602 is used to build a multi-level architecture model of the Fourier transform infrared spectrometer in the MBSE environment. It integrates the constraint module, the element parameters and element items in the value attribute index into the multi-level architecture model through the binding chain to generate a quantifiability model of the Fourier transform infrared spectrometer. The verification and update module 603 is used to perform simulation analysis on the design performance of the measurability model based on the pre-established system design requirements using external simulation software, feed the simulation results back to the MBSE system model, and automatically verify and update the simulation results using the MBSE system model. During the iteration process, various parameters are adjusted according to the updated simulation results to obtain multiple results. One of the multiple results that meets the requirements is selected as the output to realize the measurability parameter constraints of the Fourier transform infrared spectrometer.

[0061] In integration module 602, the constraint module, the element parameters and element items in the value attribute indicators are integrated into the multi-level architecture model through binding chains to generate a measurability model for the Fourier transform infrared spectrometer. This includes: binding and assigning values ​​to the value attribute indicators with each level element of the multi-level architecture model to obtain assigned value attribute indicators; establishing measurability indicator constraint relationships between each level element of the multi-level architecture model based on the constraint module and the assigned value attribute indicators; and constructing a measurability indicator traceability relationship for the multi-level architecture model based on the measurability indicator constraint relationships to generate a measurability model for the Fourier transform infrared spectrometer.

[0062] In integration module 602, based on the constraint module and assigned value attribute indicators, quantifiable indicator constraint relationships are established between elements at each level of the multi-level architecture model. This includes: constructing a constraint model, which includes an element parameter module, an element item module, a quantifiable characteristic threshold module, and the constraint module; establishing the association between the constraint model and the Fourier transform infrared spectrometer, light source module, interferometer module, detector module, optical device module, and data processing module, so that a binding chain is formed between the constraint model and the Fourier transform infrared spectrometer and each module; and using the binding chain, the assigned value attribute indicators in the constraint model are... The system transmits and assigns value attributes to the Fourier transform infrared spectrometer, light source module, interferometer module, detector module, optical device module, and data processing module. When the value of any value attribute in the multi-level architecture model changes, the changed value is transmitted through the binding chain, and the corresponding value attribute in the constraint model is updated. The system associates measurability-related indicators with conventional design to decompose the first-level indicators to the second level and establishes physical relationships between the value attribute indicators in the constraint model and the value attribute indicators in the design, thereby establishing measurability indicator constraint relationships.

[0063] In the integration module 602, based on the constraints of measurable indicators, a traceability relationship of measurable indicators for a multi-level architecture model is constructed to generate a measurable model for the Fourier transform infrared spectrometer. This includes: creating a refined requirement matrix based on the constraints of measurable indicators. The refined requirement matrix is ​​used to store the design parameters, design requirements, and relationships between design parameters and design requirements for each module in the multi-level architecture model. The refined requirement matrix includes the activity and value attributes of each module. By adjusting the activity and value attributes, the relationships and design results of each level are adjusted in a coordinated manner to form a traceability relationship of measurable indicators.

[0064] In the verification and update module 603, the design performance includes the structure, behavior, and parameter attributes of each level in the multi-level architecture model. Based on the pre-established system design requirements, the design performance of the measurability model is simulated and analyzed using external simulation software, and the simulation results are fed back to the MBSE system model. This includes: based on the pre-established system design requirements, using the MBSE system model and integrating external simulation software, simulating and analyzing the structure, behavior, and parameter attributes of each level to obtain simulation results; and based on the simulation results, constructing physical layers in the MBSE system model that contain the structure, behavior, and parameter attributes of each level.

[0065] In the verification and update module 603, the simulation results are automatically verified and updated using the MBSE system model. During the iteration process, various parameters are adjusted based on the updated simulation results to obtain multiple results. One of the multiple results that meets the requirements is selected as the output to achieve the metrability parameter constraints of the Fourier transform infrared spectrometer. This includes: establishing a requirement matrix between design requirements and metrability model elements based on the model tree in the MBSE system model; performing multiple rounds of iterative updates on the metrability model based on the traceability mechanism formed by the requirement matrix; adjusting various parameters based on the updated simulation results during the iteration process to obtain multiple results; and selecting one of the multiple results that meets the requirements as the output to achieve the metrability parameter constraints of the Fourier transform infrared spectrometer. The requirement matrix is ​​a matrix with functions of mapping, visualization, and tracing between elements and requirements.

[0066] It should be noted that the above description of the embodiment of the MBSE-based FTIR spectrometer metrology parameter constraint device is similar to the description of the MBSE-based FTIR spectrometer metrology parameter constraint method embodiment, and has similar beneficial effects. For any technical details not disclosed in the embodiments of the MBSE-based FTIR spectrometer metrology parameter constraint device of this invention, please refer to the description of the MBSE-based FTIR spectrometer metrology parameter constraint method embodiment of this invention for understanding.

[0067] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for constraining the metrability parameters of an FTIR spectrometer based on MBSE, characterized in that, include: The value attribute indicators related to the functional and performance requirements of Fourier transform infrared spectrometer measurement traceability are determined, and the constraints of the value attribute indicators are established to generate a constraint module. The value attribute indicators include element parameters and element items. In the MBSE environment, a multi-level architecture model of the Fourier transform infrared spectrometer is constructed. The constraint module, the element parameters and the element items in the value attribute index are integrated into the multi-level architecture model through binding chains to generate the quantifiability model of the Fourier transform infrared spectrometer. Based on the pre-established system design requirements, the design performance of the measurability model is simulated and analyzed using external simulation software. The simulation results are fed back to the MBSE system model, and the simulation results are automatically verified and updated using the MBSE system model. During the iteration process, various parameters are adjusted according to the updated simulation results to obtain multiple results. One of the multiple results that meets the requirements is selected as the output to achieve the measurability parameter constraints of the Fourier transform infrared spectrometer.

2. The method for constraining the metrability parameters of an FTIR spectrometer based on MBSE according to claim 1, characterized in that, The element parameters include wavenumber indication error, wavenumber repeatability, transmittance repeatability, resolution, background spectral energy distribution, flatness of the 100% line, noise, calibration cycle, calibration time required, and calibration cost; the element items include metrology interface and metrology method.

3. The method for constraining the metrability parameters of an FTIR spectrometer based on MBSE according to claim 1, characterized in that, The multi-level architecture model of the Fourier transform infrared spectrometer includes a first-level model and a second-level model. The first-level model is the first-level Fourier transform infrared spectrometer, and the second-level model includes a light source module, an interferometer module, a detector module, an optical device module, and a data processing module.

4. The MBSE-based method for constraining the metrability parameters of an FTIR spectrometer according to claim 3, characterized in that, The step of integrating the constraint module, the element parameters and the element items in the value attribute index into the multi-level architecture model through a binding chain to generate the quantifiability model of the Fourier transform infrared spectrometer includes: The value attribute index is bound and assigned to each level element of the multi-level architecture model to obtain the assigned value attribute index. Based on the constraint module and the assigned value attribute index, a measurable index constraint relationship is established between the elements of each level in the multi-level architecture model. Based on the aforementioned quantifiability constraint relationship, the quantifiability traceability relationship of the multi-level architecture model is constructed to generate the quantifiability model of the Fourier transform infrared spectrometer.

5. The MBSE-based method for constraining the metrability parameters of an FTIR spectrometer according to claim 4, characterized in that, The establishment of measurable index constraint relationships among the elements of each level of the multi-level architecture model based on the constraint module and the assigned value attribute index includes: Construct a constraint model, which includes an element parameter module, an element item module, a measurement characteristic threshold module, and the constraint module. Establish the association between the constraint model and the Fourier transform infrared spectrometer, the light source module, the interferometer module, the detector module, the optical device module, and the data processing module, so that the constraint model forms a binding chain with the Fourier transform infrared spectrometer and each module; Using the binding chain, the value attribute indexes assigned in the constraint model are passed and assigned to the value attribute indexes of the Fourier transform infrared spectrometer, the light source module, the interferometer module, the detector module, the optical device module, and the data processing module; When the value of any value attribute indicator in the multi-level architecture model changes, the changed value of any value attribute indicator is passed through the binding chain, and the value of the corresponding value attribute indicator in the constraint model is updated. The measurability-related indicators are associated with conventional design to decompose the first-level indicators to the second level, and to establish physical relationships between the value attribute indicators in the constraint model and the value attribute indicators in the design, thereby establishing the constraint relationship of the measurability indicators.

6. The MBSE-based method for constraining the metrability parameters of an FTIR spectrometer according to claim 4, characterized in that, The step of constructing the measurable index traceability relationship of the multi-level architecture model based on the measurable index constraint relationship to generate the measurable model of the Fourier transform infrared spectrometer includes: Based on the aforementioned measurability index constraints, a detailed requirement matrix is ​​created. This detailed requirement matrix stores the design parameters and design requirements of each module in the multi-level architecture model, as well as the relationship between the design parameters and the design requirements. The detailed requirement matrix includes the activity and value attributes of each module. By adjusting the activities and value attributes, the relationships and design results at each level are adjusted in a coordinated manner to form the traceability relationship of the measurable indicators.

7. The method for constraining the metrability parameters of an FTIR spectrometer based on MBSE according to claim 1, characterized in that, The design performance includes the structure, behavior, and parameter attributes of each layer in the multi-level architecture model; the simulation analysis of the design performance of the measurability model based on pre-established system design requirements using external simulation software, and the feedback of the simulation results to the MBSE system model, includes: Based on the pre-established system design requirements, the MBSE system model is used and the external simulation software is integrated to perform simulation analysis on the hierarchical structure, the behavior and the parameter attributes, and obtain the simulation results. Based on the simulation results, a physical hierarchy is constructed in the MBSE system model, which includes the hierarchical structures, behaviors, and parameter attributes.

8. The MBSE-based method for constraining the metrability parameters of an FTIR spectrometer according to claim 7, characterized in that, The process of automatically verifying and updating the simulation results using the MBSE system model, adjusting various parameters based on the updated simulation results during the iteration process to obtain multiple results, and selecting a result that meets the requirements as the output, in order to achieve the metrability parameter constraints of the Fourier transform infrared spectrometer, includes: Based on the model tree in the MBSE system model, a requirement matrix is ​​established between design requirements and measurable model elements. The requirement matrix is ​​a matrix with functions of mapping, visualization, and tracing between elements and requirements. Based on the traceability mechanism formed by the demand matrix, the measurability model is iteratively updated multiple times. During the iteration process, the various parameters are adjusted according to the updated simulation results to obtain multiple results. Among the multiple results, one that meets the requirements is selected as the output to realize the measurability parameter constraints of the Fourier transform infrared spectrometer.

9. The MBSE-based method for constraining the metrability parameters of an FTIR spectrometer according to claim 2, characterized in that, The resolution includes the number of resolution parameters, the resolution depth, and the half-peak width of water.

10. A device for constraining the metrability parameters of an FTIR spectrometer based on MBSE, characterized in that, include: A module is established to determine the value attribute indicators of functional and performance requirements related to the traceability of Fourier transform infrared spectrometer measurements, and to establish the constraints of the value attribute indicators to generate a constraint module. The value attribute indicators include element parameters and element items. An integration module is used to build a multi-level architecture model of a Fourier transform infrared spectrometer in the MBSE environment. The constraint module, the element parameters and the element items in the value attribute index are integrated into the multi-level architecture model through a binding chain to generate a measurability model of the Fourier transform infrared spectrometer. The verification and update module is used to perform simulation analysis on the design performance of the measurability model based on pre-established system design requirements using external simulation software, feed the simulation results back to the MBSE system model, and automatically verify and update the simulation results using the MBSE system model. During the iteration process, various parameters are adjusted according to the updated simulation results to obtain multiple results. One of the multiple results that meets the requirements is selected as the output to realize the measurability parameter constraints of the Fourier transform infrared spectrometer.

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