Natural gas flow checking calculation method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a natural gas flow checking calculation method and device, electronic equipment and a storage medium, and relates to the technical field of energy application. The method comprises the steps of obtaining component data and working condition parameters of natural gas and a first volume flow output by a flow computer; determining a target checking calculation model matched with the data type from a plurality of checking calculation models based on the data type of the component data; determining a second volume flow rate of the natural gas according to the target checking calculation model and the working condition parameters; according to the first volume flow and the second volume flow, a checking calculation judgment report is generated. The method can be used in the natural gas flow checking calculation process, and is used for solving the problems of low efficiency and insufficient accuracy of the existing natural gas flow checking calculation.

Description

Technical Field

[0001] This application relates to the field of energy application technology, and in particular to a method, apparatus, electronic device and storage medium for calculating natural gas flow. Background Technology

[0002] In the metering and trading of natural gas, flow computers are one of the core pieces of equipment. Their main function is to process data collected by natural gas flow sensors and transmitters, including volumetric flow conversion, temperature and pressure compensation, compressibility factor (Z-value) calculation, energy metering, and data storage and transmission. This directly affects the accuracy of the metering results and the fairness of the transaction. However, in practical applications, the natural gas flow verification process based on flow computers has become an efficiency bottleneck. In existing technologies, natural gas verification methods based on flow computers typically rely on manual calculations or distributed software tools, resulting in numerous operational steps, long processing times, low efficiency, and a high risk of errors. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, electronic device and storage medium for calculating natural gas flow rate, with the aim of improving the efficiency and accuracy of natural gas flow rate calculation.

[0004] Firstly, a method for verifying natural gas flow rate is provided. The method includes: acquiring natural gas composition data, operating parameters, and a first volumetric flow rate output by a flow computer; determining a target verification model that matches the data type from multiple verification models based on the data type of the composition data; determining a second volumetric flow rate of natural gas based on the target verification model and operating parameters; and generating a verification judgment report based on the first volumetric flow rate and the second volumetric flow rate.

[0005] The natural gas flow rate verification method provided in this application acquires natural gas composition data, operating parameters, and the first volumetric flow rate from the flow computer, providing a data foundation for subsequent verification. Then, based on the data type of the composition data, a target verification model is matched from multiple verification models. This allows for the application of appropriate calculation methods for natural gas from different sources or compositions (such as standard dry gas, gases containing impurities, etc.), effectively improving the adaptability and accuracy of the verification model. Next, a second volumetric flow rate is determined based on the target verification model and real-time operating parameters, enabling verification of the flow computer's output and effectively identifying potential deviations in the flow rate verification process. Finally, a verification judgment report is generated by comparing the first and second volumetric flow rates, providing users with intuitive verification conclusions. This enhances the reliability and transparency of the natural gas metering system, effectively prevents natural gas settlement risks, and ensures the safety and efficiency of production operations.

[0006] In conjunction with the first aspect mentioned above, in one possible implementation, based on the data type of the component data, a target verification model matching the data type is determined from multiple verification models. This includes: when the data type of the component data is molar component data, a first verification model is determined as the target verification model; the first verification model is constructed based on a first-class national standard for calculating the natural gas compressibility factor; when the data type of the component data is physical property parameter data, a second verification model is determined as the target verification model; the second verification model is constructed based on a second-class national standard for calculating the natural gas compressibility factor; the first-class national standard and the second-class national standard employ different calculation logics and input parameter requirements.

[0007] In conjunction with the first aspect mentioned above, in one possible implementation, the second volumetric flow rate is determined based on the target verification model and operating parameters, including: determining the compressibility factor of natural gas based on the target verification model and operating parameters; and determining the second volumetric flow rate based on the compressibility factor and operating parameters using the volumetric flow rate calculation formula.

[0008] In conjunction with the first aspect mentioned above, in one possible implementation, the operating parameters include the operating pressure, operating temperature, and operating volumetric flow rate of the natural gas in the pipeline; the volumetric flow rate is calculated using the following expression:

[0009] in, This represents the second volumetric flow rate calculated based on the compressibility factor and operating parameters. This indicates the volumetric flow rate measured by the flow meter under operating conditions. This indicates the operating pressure collected by a pressure sensor. This represents the reference pressure under standard conditions as determined by natural gas metering standards. This indicates the operating temperature collected by the temperature sensor. This represents the reference temperature under standard conditions as determined by natural gas metering standards. This represents the compression factor determined based on the target verification model. This represents the baseline compression factor under standard conditions.

[0010] In conjunction with the first aspect mentioned above, in one possible implementation, a verification judgment report is generated by comparing a first volumetric flow rate with a second volumetric flow rate, including: obtaining the relative error between the first volumetric flow rate and the second volumetric flow rate; when the relative error exceeds a preset threshold, generating a verification judgment report by analyzing the sources of error; the sources of error include at least one of the following: measurement drift of the pressure sensor and / or temperature sensor, abnormal changes in gas composition, and mismatch between the selected verification model and the current operating conditions; the verification judgment report includes input parameter records, calculation process, error analysis conclusions, and calibration recommendations.

[0011] In conjunction with the first aspect mentioned above, one possible implementation involves analyzing the sources of error, including: evaluating the measurement stability of the pressure sensor and / or temperature sensor based on historical data sequences of operating parameters to determine the measurement drift of the pressure sensor and / or temperature sensor; analyzing the fluctuation trend of gas component parameters based on historical data of component data to determine abnormal changes in gas components; and analyzing the corresponding changes in the compressibility factor by changing the pressure and temperature values ​​in the operating parameters to determine the degree of matching between the selected verification model and the current operating parameters.

[0012] Secondly, this application provides a natural gas flow rate verification device, comprising: a data acquisition module, a model selection module, a flow rate calculation module, and a report generation module; the data acquisition module is used to acquire natural gas composition data, operating parameters, and a first volumetric flow rate output by a flow computer; the model selection module is used to determine a target verification model with a matching data type from multiple verification models based on the data type of the composition data; the flow rate calculation module is used to determine a second volumetric flow rate of natural gas according to the target verification model and operating parameters; and the report generation module is used to generate a verification judgment report based on the first volumetric flow rate and the second volumetric flow rate.

[0013] In conjunction with the second aspect above, in one possible implementation, the model selection module is specifically used for: determining the first verification model as the target verification model when the data type of the component data is molar component data; the first verification model is constructed based on the first type of national standard for calculating the natural gas compressibility factor; determining the second verification model as the target verification model when the data type of the component data is physical property parameter data; the second verification model is constructed based on the second type of national standard for calculating the natural gas compressibility factor; the first type of national standard and the second type of national standard adopt different calculation logic and input parameter requirements.

[0014] Thirdly, this application provides an electronic device comprising: a processor and a memory; the memory storing processor-executable instructions; when the processor is configured to execute the instructions, the electronic device implements the method of the first aspect described above.

[0015] Fourthly, this application provides a computer-readable storage medium comprising: computer software instructions; which, when executed in an electronic device, cause the electronic device to implement the method described in the first aspect.

[0016] Fifthly, this application provides a computer program product that, when run on a computer, causes the computer to perform the steps of the relevant method described in the first aspect above, so as to implement the method of the first aspect above.

[0017] The beneficial effects of the second to fifth aspects mentioned above can be referred to the corresponding description of the first aspect, and will not be repeated here. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a natural gas flow rate verification method provided in this application embodiment; Figure 2 A flowchart illustrating a method for determining a target verification model provided in an embodiment of this application; Figure 3 A flowchart illustrating a method for determining a second volumetric flow rate provided in an embodiment of this application; Figure 4 A flowchart illustrating a method for determining a verification judgment report provided in an embodiment of this application; Figure 5 A schematic diagram of the composition of a natural gas flow verification device provided in this application embodiment; Figure 6 This is a schematic diagram of a natural gas flow verification device provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] It should be noted that in the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0022] In the embodiments of this application, the terms "first," "second," "third," "fourth," "fifth," and "sixth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," "third," "fourth," "fifth," and "sixth" may explicitly or implicitly include one or more of that feature.

[0023] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0024] "A and / or B" includes the following three combinations: A only, B only, and a combination of A and B.

[0025] As described in the background section, flowmeters are one of the core devices in the metering and trading of natural gas. Their main function is to process data collected by natural gas flow sensors and transmitters, including volumetric flow conversion, temperature and pressure compensation, compressibility factor (Z-value) calculation, energy metering, and data storage and transmission. This directly affects the accuracy of the metering results and the fairness of the transaction. However, in practical applications, the natural gas flow verification process based on flowmeters has become an efficiency bottleneck. In existing technologies, natural gas verification methods based on flowmeters typically rely on manual calculations or distributed software tools, resulting in numerous steps, long processing times, low efficiency, and a high risk of errors.

[0026] Based on this, this application provides a natural gas flow rate verification method. By acquiring natural gas composition data, operating parameters, and the first volumetric flow rate of the flow computer, a data foundation is provided for subsequent verification. Then, based on the data type of the composition data, a target verification model is matched from multiple verification models. This allows for the application of appropriate calculation methods for natural gas from different sources or compositions (such as standard dry gas, gases containing impurities, etc.), thereby effectively improving the adaptability and accuracy of the verification model. Next, a second volumetric flow rate is determined based on the target verification model and real-time operating parameters, enabling verification of the flow computer's output and effectively identifying potential deviations in the flow rate verification process. Finally, a verification judgment report is generated by comparing the first and second volumetric flow rates, providing users with intuitive verification conclusions. This improves the reliability and transparency of the natural gas metering system, effectively prevents natural gas settlement risks, and ensures the safety and efficiency of production operations.

[0027] The natural gas flow verification method provided in this application can be applied to a natural gas metering and monitoring system (hereinafter referred to as the system) with computing and data storage capabilities. This application does not impose any restrictions on the specific implementation form of the natural gas metering and monitoring system.

[0028] For example, a natural gas metering and monitoring system can be deployed on a cloud server in the natural gas industry. This cloud server can be a single centralized server, or a server cluster consisting of multiple sub-servers. In some embodiments, the server cluster can also be a distributed cluster where edge cloud and central cloud collaborate, enabling local collection, processing, and centralized aggregation and verification of natural gas composition data and operating parameters. This application does not impose any limitations on this approach.

[0029] For example, the natural gas metering and monitoring system can also be directly deployed on field metering terminal devices. These field metering terminal devices can be referred to as: natural gas flow verification terminals, field metering data processing devices, intelligent flow monitoring units, etc. Specifically, they can be flow computer-supported verification modules with real-time data processing and storage capabilities, smart gas meter expansion units, field metering controllers, etc. Furthermore, the natural gas metering and monitoring system can also be deployed on remote monitoring and management terminals, such as monitoring terminals in natural gas transmission and distribution dispatch centers, and metering management terminals of gas companies—terminal devices that can establish communication connections with field metering equipment or natural gas data networks. This application does not limit this specific deployment.

[0030] The following describes in detail a natural gas flow verification method provided by the embodiments of this application, with reference to specific examples and accompanying drawings.

[0031] Figure 1 This is a flowchart illustrating a natural gas flow rate verification method provided in an embodiment of this application. Specifically, as shown... Figure 1 As shown, it includes the following: S101. Obtain natural gas composition data, operating parameters, and the first volumetric flow rate output by the flow computer.

[0032] In this embodiment of the application, the composition data is relevant data used to characterize the material composition or core physical properties of natural gas, the operating condition parameters are the operating status parameters monitored in real time during the pipeline transportation of natural gas, and the first volumetric flow rate is the natural gas volumetric flow rate data under standard conditions output by the flow computer after processing the collected raw data.

[0033] In one implementation, the acquisition of natural gas composition data, operating parameters, and the first volumetric flow rate can be achieved through multiple input methods, ensuring the flexibility and applicability of data sources. For example, composition data can be uploaded by the user based on actual monitoring conditions; this can be data related to the molar composition of natural gas, or physical property parameters such as relative density and molar mass. Operating parameters are collected in real time by sensors deployed on the pipeline, including the operating pressure, operating temperature, and operating volumetric flow rate of the natural gas within the pipeline. The first volumetric flow rate is directly obtained from the flow computer used for target verification, serving as the benchmark data for subsequent comparative analysis.

[0034] In one implementation, the data acquisition process supports a combination of automatic acquisition and manual entry, improving the convenience and efficiency of data acquisition. For example, component data can be automatically read through the communication connection established between the system and the chromatograph without manual intervention. Operating parameters are captured in real time from sensors or transmitters via standard communication interfaces such as serial ports and Modbus. If the flow computer supports remote data transmission, the first volumetric flow rate is automatically synchronized to this system; if remote transmission is not supported, the operator can manually enter the displayed value from the flow computer.

[0035] In one implementation, a preliminary validity check is performed simultaneously during data acquisition to ensure that the input data meets the requirements for subsequent calculations. For example, the system checks whether the component data is complete; if only partial molar component data is uploaded, it prompts the user to complete the data. Operating parameters are checked for range; if the collected pressure and temperature values ​​exceed the normal operating range, an error message is issued. The data format of the first volumetric flow rate is verified to ensure it is consistent with the system's preset format, avoiding errors that could affect subsequent calculations.

[0036] In one possible implementation, the system supports collaborative communication with multiple monitoring devices when acquiring data, enabling real-time synchronous acquisition of multi-source data. For example, the system can simultaneously connect to a chromatograph, pressure sensor, temperature sensor, and flow computer, automatically summarizing component data, operating parameters, and first volumetric flow rate through a unified data transmission protocol. This eliminates the need for separate data collection from each device, reduces manual operation steps, and improves the timeliness and accuracy of data acquisition.

[0037] In one possible implementation, the raw data acquired during data acquisition is temporarily stored and backed up, while the timestamp of data acquisition is recorded. For example, the system caches component data, operating parameter change curves, and continuous values ​​of the first volumetric flow rate within the past period, facilitating comparison with historical data during subsequent error analysis. This helps to quickly locate the cause of data anomalies and improves the efficiency of error tracing.

[0038] In one possible implementation, customizable data acquisition frequency and priority settings are supported to meet the data acquisition needs of different scenarios. For example, in a natural gas flow transmission scenario with large fluctuations, the acquisition frequency of operating parameters can be set to once per second to ensure the capture of real-time changes; in a scenario where the composition data is relatively stable, the acquisition frequency can be reduced to prioritize the real-time acquisition of operating parameters and the first volume flow rate, which satisfies the verification requirements while avoiding resource waste.

[0039] As can be seen from S101 above, obtaining the composition data, operating parameters, and first volume flow rate of natural gas can provide complete and accurate basic data support for the subsequent matching of the target verification model, the calculation of the second volume flow rate, and the error determination.

[0040] S102. Based on the data type of the component data, determine the target verification model that matches the data type from multiple verification models.

[0041] In this embodiment of the application, the data type of the component data refers to the data classification form that characterizes the composition or physical properties of natural gas, the verification model is a preset algorithm model used to calculate the relevant flow parameters of natural gas, and the target verification model is a specific model selected from multiple verification models that is compatible with the data type of the component data.

[0042] In one implementation, the system's built-in identification logic can automatically determine data type and match models without manual intervention. For example, the system first performs feature analysis on the acquired component data to identify whether it belongs to the type representing the composition of a substance or the type representing physical properties. Then, it retrieves a model that is fully compatible with the type from a preset verification model library as the target verification model.

[0043] In one implementation, the verification model library is categorized and stored according to the data type of the component data for convenient and rapid matching. For example, the model library is pre-divided into model subsets corresponding to different data types. Once the data type of the component data is identified, the corresponding subset is directly located, and the best-fitting model is selected as the target verification model, thus shortening the matching time.

[0044] In one implementation, the model matching process includes a compatibility check to ensure that the target verification model can effectively handle the corresponding type of component data. For example, after initial model matching, the system verifies whether the model's input parameter requirements are consistent with the format and dimensions of the component data. If they are consistent, the model is confirmed as the target verification model; otherwise, it is re-selected.

[0045] In one possible implementation, the system supports adaptation and extension to newly added data types. When an unpreset component data type appears, the system can automatically identify and associate it with the corresponding newly added verification model. This design allows the system to adapt to verification needs in different scenarios, improving the universality and scalability of model matching.

[0046] In one possible implementation, the model matching process records a matching log, which retains detailed records of data type identification results, model selection paths, and final matching conclusions. This log can be used for subsequent data traceability and problem investigation, helping operators quickly locate anomalies in the model matching process and ensuring the traceability of the verification process.

[0047] In one possible implementation, for complex component data, the system can employ a multi-level matching mechanism. First, it performs a rapid preliminary matching based on core features, and then uses detailed parameters to accurately confirm the target verification model. This approach ensures matching efficiency while improving the accuracy of model matching, avoiding matching deviations caused by data complexity.

[0048] As shown in S102 above, the automatic matching of the target verification model based on the data type of the component data saves the tedious step of manually selecting the model and reduces verification deviations caused by human selection errors. This provides suitable algorithmic support for subsequent flow calculations, ensuring the standardization and accuracy of the natural gas flow verification process.

[0049] S103. Determine the second volumetric flow rate of natural gas based on the target verification model and operating parameters.

[0050] In this embodiment, the second volumetric flow rate is the natural gas volumetric flow rate data under standard conditions obtained by processing the operating parameters through the target verification model. Its calculation process relies on the preset logic of the model and the actual values ​​of the operating parameters, and it is the core reference data for subsequent flow verification and comparison.

[0051] In one implementation, the system can automatically substitute operating parameters into the target verification model to calculate the second volumetric flow rate. For example, the system first extracts the calculation rules of the determined target verification model, then calls the collected operating parameters, performs data calculations according to the logical order required by the model, and finally outputs the corresponding second volumetric flow rate.

[0052] In one implementation, the operating parameters are format-adapted before calculation to ensure they match the input requirements of the target verification model. For example, if the target verification model requires operating parameters to be input in a specific unit or data format, the system will automatically convert the collected raw operating parameters, adapt them, and then substitute them into the model for calculation, avoiding calculation errors caused by format mismatch.

[0053] In one implementation, the calculation process for the second volumetric flow rate supports real-time computation and result feedback. When operating parameters change dynamically, the system synchronously updates the input data, recalculates using the target verification model, and outputs the latest second volumetric flow rate. For example, the operating parameters of natural gas in the pipeline fluctuate in real time during the transportation process. The system can capture these changes in real time and repeat the calculation steps to ensure that the second volumetric flow rate matches the actual operating conditions.

[0054] In one possible implementation, the system generates a computation log during the calculation process, recording in detail the time of inputting operating parameters, model calculation steps, intermediate results, and the final second volume flow rate. This log can be used for subsequent calculation process traceability, facilitating the investigation of potential computational anomalies and ensuring the verifiability of the results.

[0055] In one possible implementation, for complex operating conditions, the system employs a step-by-step calculation mechanism. First, the operating parameters are segmented, then each segment is substituted into the target verification model for calculation, and finally, the results are integrated to obtain the second volumetric flow rate. This approach reduces the impact of complex parameters on calculation accuracy, further improving the accuracy of the second volumetric flow rate.

[0056] As can be seen from S103 above, by relying on the target verification model and operating parameters to calculate the second volume flow rate, human calculation errors are avoided, the reliability of the second volume flow rate is ensured, and accurate and effective data support is provided for the subsequent comparison and verification of the first and second volume flow rates.

[0057] S104. Generate a verification and judgment report based on the first volumetric flow rate and the second volumetric flow rate.

[0058] In this embodiment of the application, the verification judgment report is a standardized document formed by integrating relevant process data and core conclusions based on the comparative analysis results of the first volumetric flow rate and the second volumetric flow rate. It is used to clearly present the final result of the natural gas flow rate verification and key related information.

[0059] In one implementation, the system can perform data integration analysis and report compilation based on the acquired data. For example, the system first compares and analyzes the first volumetric flow rate and the second volumetric flow rate, then summarizes key information from data acquisition, model matching, flow calculation, and other stages, and automatically generates a structural specification verification report according to a preset template.

[0060] In one implementation, the verification report includes core comparative data and clear judgment conclusions, ensuring that the information is intuitive and easy to understand. For example, the report clearly lists the specific values ​​of the first volumetric flow rate and the second volumetric flow rate, the differences between the two, and gives a clear conclusion of "verification qualified" or "further analysis required" based on preset judgment rules, making it convenient for users to quickly grasp the verification results.

[0061] In one implementation, the report generation process supports the highlighting of key data, improving information retrieval efficiency. For example, the system will present core information such as the difference between the first and second volumetric flow rates and the judgment conclusions in a prominent manner, while auxiliary information such as data sources and calculation steps will be arranged in logical order, balancing the emphasis on key points with the completeness of the report.

[0062] In one possible implementation, the system supports user-defined report templates, allowing users to adjust the content modules and presentation format of reports according to actual usage scenarios. For example, users can add or remove auxiliary information modules in the report based on regulatory requirements or internal management needs, making the report more suitable for specific usage scenarios and improving its usability.

[0063] In one possible implementation, the verification report supports the export of related raw data files to facilitate subsequent in-depth analysis. For example, the report may include a compressed package of raw data, containing component data, operating parameter records, model matching logs, etc., which users can export and view as needed, providing complete data support for possible subsequent review or troubleshooting.

[0064] As shown in S104 above, the verification report is generated based on the first and second volumetric flow rates, achieving a standardized and intuitive presentation of the verification results. This avoids the omissions and inefficiencies caused by manual operation, providing users with clear and complete verification result documentation, helping them quickly grasp the natural gas flow verification status, and thus providing a reliable reference for subsequent related decisions and operations.

[0065] In this embodiment of the application, when determining the target verification model, the system can match the corresponding verification model from multiple verification models as the target verification model based on the data type of the component data. Specifically, as shown... Figure 2 As shown, it includes the following: S201. When the data type of the component data is molar component data, determine the first verification model as the target verification model.

[0066] The first verification model is constructed based on the first national standard for calculating the natural gas compressibility factor.

[0067] In this embodiment of the application, the molar composition data is a dataset used to reflect the molar percentage of each component in natural gas, the first verification model is a flow verification model specifically adapted to the molar composition data, and the first type of national standard refers to the industry-unified technical standard formulated for calculating the compressibility factor of natural gas using molar composition data.

[0068] In one implementation, the system can automatically match molar component data with a first verification model through preset type identification and model mapping rules. For example, when the system identifies the acquired component data as molar fraction information of each component, it will directly call the first verification model as the target verification model. This model is constructed based on the first type of national standard (such as GB / T17747.2), follows the compressibility factor calculation logic in the standard, and can be adapted to verification scenarios within the conventional pressure and temperature range of pipeline natural gas.

[0069] In one implementation, before determining the first verification model, the system performs a preliminary verification of the completeness of the molar composition data to ensure that the data meets the input requirements of the first-class national standard. For example, the system checks whether the molar composition data covers all components with molar fractions exceeding the standard threshold, including C1 to C6. + After confirming that the hydrocarbons and common non-hydrocarbon components such as N2 and CO2 meet the analytical range requirements of the first category of national standards (such as GB / T17747.2), the first verification model is formally determined as the target verification model.

[0070] In one implementation, the first verification model incorporates the core calculation parameters and processes of the first type of national standard, enabling adaptation calculations without the need to call external standard files. For example, the model pre-integrates key elements such as the extended virial equation coefficients and the comparative density calculation relationship specified in GB / T17747.2. Once the composition data is confirmed to be of molar component type, the model can directly enter the calculation state without the need for manual configuration of standard-related parameters.

[0071] In one possible implementation, the system supports dynamic adaptation to the first type of national standard version. The system will periodically detect standard updates and automatically synchronize model parameters. For example, when an updated version of GB / T17747.2 is released, the system can remotely upgrade to incorporate the new calculation rules, parameter ranges, etc., into the first verification model, ensuring that the model always meets the requirements of the current standard and improving the authority of the verification results.

[0072] In one possible implementation, for natural gas scenarios containing artificial admixtures, the system will make targeted parameter adjustments to the first verification model to ensure compliance with the specific adaptation requirements of national standards. For example, when the molar composition data includes artificial gas components such as H2 and CO, the system will adjust the calculation logic of the temperature and composition function coefficients in the model according to the calculation instructions for special components in GB / T17747.2, so that the model can adapt to the verification requirements of unconventional natural gas components, thus expanding the applicability of the method.

[0073] As can be seen from S201 above, the first verification model built based on the first national standard for accurate matching of molar component data ensures the standardization of the model's calculation logic, provides core algorithm support that conforms to the industry's unified standards for subsequent flow verification based on molar component data, and improves the credibility of the verification results.

[0074] S202. When the data type of the component data is physical property parameter data, determine the second verification model as the target verification model.

[0075] The second verification model is constructed based on the second national standard for calculating the natural gas compressibility factor. The first and second national standards use different calculation logics and input parameter requirements.

[0076] In this application embodiment, the physical property parameter data is the core data used to characterize the physical properties of natural gas, the second verification model is a dedicated flow verification model adapted to the physical property parameter data, and the second type of national standard is an industry-unified technical standard formulated for calculating the compressibility factor of natural gas using physical property parameters. It is clearly different from the first type of national standard in terms of input parameter requirements and core calculation logic.

[0077] In one implementation, the system automatically binds physical property parameter data to the second verification model through preset type identification rules. For example, when the system identifies the component data as macroscopic physical property parameters such as relative density and molar mass, it directly determines the second verification model as the target verification model. This model is built based on the second type of national standard (GB / T17747.3) and adopts a different calculation logic than the first type of national standard. It does not rely on the molar ratio of each component and can complete the derivation of the compression factor only through physical property parameters, thus adapting to verification scenarios where detailed component data is not available.

[0078] In one implementation, before determining the second verification model, the system verifies the validity of the physical property parameter data to ensure compliance with the input specifications of the second category of national standards. For example, the system checks whether the relative density data is within the conventional relative density range of natural gas (e.g., 0.55-0.90) and whether the molar mass data accurately corresponds to the compositional characteristics of natural gas. After confirming that the data meets the input parameter requirements of GB / T17747.3, the system officially locks the second verification model as the target verification model.

[0079] In one implementation, the second verification model incorporates the complete calculation process of the second type of national standard, achieving deep integration of standard logic and calculation modules. For example, the model pre-defines core content such as the compressibility factor calculation correlation and physical property parameter conversion formula specified in GB / T17747.3, clearly distinguishing it from the calculation logic of the first type of national standard based on component analysis. This allows for direct processing of physical property parameter data without manual intervention in standard interpretation and parameter configuration.

[0080] In one possible implementation, the system supports dynamic updates and compatibility with the second category of national standards. When the standard version is iterated or the technical requirements are adjusted, the system can automatically update the calculation logic of the second verification model. This design ensures that the model always remains consistent with current industry standards, avoids verification deviations caused by standard updates, and improves the long-term applicability of the method.

[0081] In one possible implementation, after matching the second verification model, the system automatically generates a standard adaptation description, clearly indicating the second type of national standard number, core calculation logic, and differences from the first type of national standard. This description can be embedded in subsequent verification reports to help users understand the rationality of the model selection, while providing clear standard basis for regulatory verification and enhancing the transparency of the process.

[0082] In one possible implementation, for scenarios where a single physical property parameter is missing, the system supports derivation and completion using existing physical property parameters before matching with a second verification model. For example, if only relative density data is obtained, the system can derive the molar mass based on the correlation specified in GB / T17747.3, complete the data, and then activate the second verification model, thus expanding the applicable range of physical property parameter data and improving the flexibility of the method.

[0083] As shown in S202 above, the second verification model, based on the second category of national standards, accurately matches the physical property parameter data, complementing and adapting to the first category of national standards, and covering verification needs under different data acquisition conditions. The model incorporates standard calculation logic, avoiding errors caused by manual standard selection and interpretation, ensuring the standardization and accuracy of the verification process, and improving overall verification efficiency.

[0084] In this embodiment of the application, when determining the second volumetric flow rate, the system can first calculate the natural gas compressibility factor according to the target verification model, and then obtain the second volumetric flow rate based on the natural gas compressibility factor. Specifically, as shown... Figure 3 As shown, it includes the following: S301. Determine the compressibility factor of natural gas based on the target verification model and operating parameters.

[0085] In the embodiments of this application, the compressibility factor is a key parameter characterizing the deviation of natural gas from the characteristics of an ideal gas. Its value depends on the composition of natural gas, operating conditions and corresponding calculation standards. It can be obtained by calculating the operating conditions through the target verification model and is the core intermediate parameter for subsequent accurate calculation of volumetric flow rate.

[0086] In one implementation, the system can automatically substitute operating parameters into the target verification model to calculate the compressibility factor. For example, if the target verification model is a first verification model adapted to molar composition data, the system will derive the compressibility factor based on the national standard logic corresponding to the model, combined with the collected operating pressure, temperature, and other parameters, through a preset state equation or correlation. If it is a second verification model adapted to physical property parameter data, the compressibility factor is obtained solely through the linkage calculation of operating parameters and physical property parameters based on the corresponding standard calculation rules.

[0087] In one implementation, the operating parameters are preprocessed before calculating the compressibility factor to ensure they meet the input requirements of the target verification model. For example, the system converts the collected operating pressure and temperature data into the unit format required by the target verification model, and removes abnormal data that is significantly outside the reasonable range, thus avoiding deviations in the compressibility factor calculation due to incompatible parameter formats or abnormal data.

[0088] In one implementation, the calculation of the compressibility factor supports real-time response to changes in operating parameters, ensuring dynamic adaptation of parameters. For example, when the operating pressure and temperature of natural gas in the pipeline fluctuate during the transportation process, the system will capture the updated operating parameters in real time, re-substitute them into the target verification model, and synchronously calculate the latest compressibility factor to ensure that the compressibility factor always matches the actual operating conditions.

[0089] In one possible implementation, the compression factor is automatically compared and verified with historical data from the same period after calculation. If the deviation exceeds a reasonable range, a prompt is issued. For example, the system retrieves historical compression factor data under the same operating conditions for comparison to confirm the rationality of the current calculation result, avoiding errors caused by temporary model failures or abnormal parameter acquisition, and improving the reliability of the compression factor.

[0090] In one possible implementation, for extreme operating conditions (such as ultra-high pressure and low temperature), the system optimizes the calculation weights of the target verification model, strengthening the influence of key operating parameters on the compressibility factor. This optimization can improve the calculation accuracy of the compressibility factor under extreme conditions, making the results more consistent with the actual gas state and expanding the applicable scenarios of the method.

[0091] As can be seen from S301 above, the compression factor is determined based on the target verification model and operating parameters, realizing the automated and accurate calculation of this core intermediate parameter, avoiding errors caused by manual derivation, and providing key support for the accurate calculation of the subsequent second volume flow rate.

[0092] S302. Based on the compressibility factor and operating parameters, the second volumetric flow rate is determined using the volumetric flow rate calculation formula.

[0093] In this embodiment, the volumetric flow rate calculation formula is a preset mathematical expression used to correlate the compressibility factor with operating parameters to derive the volumetric flow rate of natural gas under standard conditions. The second volumetric flow rate is obtained by calculating the compressibility factor and operating parameters using this formula, and is the core reference data for comparison with the first volumetric flow rate in flow rate verification.

[0094] In one implementation, the system employs a standardized volumetric flow rate calculation formula, combined with a predetermined compressibility factor and collected operating parameters, to complete the second volumetric flow rate calculation. For example, the operating parameters specifically include the operating pressure (P), operating temperature (T), and operating volumetric flow rate of the natural gas in the pipeline. The formula for calculating volumetric flow rate uses the following expression: ; in, For the second volumetric flow rate, This is the reference pressure under standard conditions as determined by natural gas metering standards. Z represents the reference temperature under standard conditions as determined by the natural gas metering standard, and Z is the compressibility factor obtained in S301. The system uses the standard compressibility factor as a reference. After substituting the parameters into the formula, the system automatically completes the calculation and outputs the second volumetric flow rate.

[0095] In one implementation, the system calibrates the units of all parameters in the formula before inputting them into the calculation to ensure consistent computational logic. For example, if the collected operating pressure is in MPa, but the formula requires kPa, the system will automatically perform the unit conversion; if the operating temperature is in degrees Celsius, it will be converted to Kelvin as required by the formula to avoid errors in the calculation of the second volumetric flow rate due to unit differences.

[0096] In one possible implementation, the system supports dynamically adjusting the benchmark parameters in the formula according to the natural gas metering standards of different regions or industries. , , The value of ) can be set. For example, users can preset the corresponding reference pressure and reference temperature according to the standard requirements of different regions, and the system will automatically adapt the formula parameters, thereby improving the regional adaptability and universality of the method.

[0097] In one possible implementation, for scenarios where operating parameters exhibit slight fluctuations, the system can determine the second volumetric flow rate by averaging multiple calculations. For example, multiple sets of operating parameters and corresponding compressibility factors can be collected within a short period, substituted into the formula for calculation, and the average value can be taken as the final result. This reduces the impact of parameter fluctuations on calculation accuracy and improves the stability of the second volumetric flow rate.

[0098] As shown in S302 above, the second volumetric flow rate is determined using a standardized volumetric flow rate calculation formula based on the compressibility factor and operating parameters, thus achieving standardization and automation of the calculation process. The formula is strictly correlated with core parameters, avoiding errors caused by manually selecting calculation methods or substituting parameters, ensuring the accuracy of the second volumetric flow rate. This provides a reliable data foundation for subsequent comparative analysis of the first and second volumetric flow rates, guaranteeing the validity of the core logic of natural gas flow rate verification.

[0099] In this embodiment of the application, when outputting the verification judgment report, the system can obtain the verification judgment report based on the relative error between the first volumetric flow rate and the second volumetric flow rate. Specifically, as shown... Figure 4 As shown, it includes the following: S401, Obtain the relative error between the first volumetric flow rate and the second volumetric flow rate.

[0100] In this embodiment, relative error is a core indicator used to quantify the degree of difference between the first volumetric flow rate and the second volumetric flow rate. It is derived through a preset mathematical calculation logic, and its value directly reflects the deviation between the two sets of flow data, which is the key basis for subsequent verification and judgment.

[0101] In one implementation, the system can automatically substitute the first volumetric flow rate and the second volumetric flow rate, and solve for the relative error using an error calculation formula. For example, the system first retrieves the already acquired first volumetric flow rate ( ) and the calculated second volumetric flow rate ( Then, the relative error (E) is calculated according to the preset logic, specifically through the expression E=( - ) / The calculation is completed 100% of the time, eliminating the need for manual calculation and ensuring accurate results.

[0102] In one implementation, consistency checks are performed on the two sets of traffic data before calculation to avoid data confusion or misrepresentation. For example, the system verifies the source of the first volume traffic and the calculation link of the second volume traffic. After confirming that both sets of data correspond to the same verification object and the same time dimension of traffic value, the system substitutes them into the formula to calculate the relative error, thus avoiding distortion of error results due to data mismatch.

[0103] In one implementation, the calculation result of the relative error retains significant digits according to a preset precision rule, improving data usability. For example, the system defaults to retaining two decimal places for the relative error result. If the verification scenario has higher precision requirements, the number of digits retained can be adjusted through system settings to ensure that the error data is both intuitive and meets the needs of subsequent judgment.

[0104] In one possible implementation, the system supports tracing the calculation process and automatically records a calculation log of the relative error, including information such as the values ​​of the two sets of traffic data, the order of substitution, and the process of formula application. This log can be used for subsequent review or troubleshooting, improving the verifiability of the error calculation.

[0105] In one possible implementation, when the calculated relative error exceeds a reasonable range, the system will automatically trigger a data verification prompt, reminding the user to check whether the acquisition of the first volumetric flow rate is accurate and whether there are any abnormalities in the calculation of the second volumetric flow rate. This ensures that data problems are detected in a timely manner and avoids erroneous results affecting subsequent judgments.

[0106] In one possible implementation, the system supports batch calculation of the relative error of multiple sets of flow data, which is suitable for continuous monitoring scenarios. For example, the system can automatically batch process multiple sets of first volume flow and second volume flow collected at the same time according to a set time interval, calculate the corresponding relative error one by one, and form a continuous error data sequence, which facilitates subsequent analysis of flow deviation trends.

[0107] As can be seen from S401 above, by automating the calculation of relative error, the omissions and errors caused by manual calculation are avoided, the efficiency of error solving is improved, and objective and accurate core indicators are provided for subsequent verification and judgment.

[0108] S402. When the relative error exceeds the preset threshold, an audit judgment report is generated by analyzing the source of the error.

[0109] The sources of error include at least one of the following: measurement drift of the pressure sensor and / or temperature sensor, abnormal changes in gas composition, or mismatch between the selected verification model and the current operating conditions. The verification report includes input parameter records, calculation process, error analysis conclusions, and calibration recommendations.

[0110] In this embodiment, the preset threshold is a relative error allowable range pre-set based on the accuracy requirements of natural gas flow metering. Error sources are various potential factors that cause deviations between the first and second volumetric flow rates. The verification and judgment report is a standardized document integrating input parameters, calculation processes, error analysis results, and calibration recommendations, used to clarify the causes of flow deviations and subsequent processing directions.

[0111] In one implementation, when the relative error exceeds a preset threshold, the system analyzes the sources of error one by one according to preset logic, and then generates a complete verification and judgment report. For example, regarding the measurement drift of pressure sensors and / or temperature sensors, the system retrieves historical data sequences of operating parameters, compares the fluctuation trends of measurement values ​​at different times, evaluates the measurement stability of the sensors, and determines whether drift exists. The report records in detail the changes in historical sensor data, the basis for drift judgment, and provides recommendations for calibrating or replacing the sensors.

[0112] In one implementation, the system analyzes historical data on gas composition to identify anomalous changes, serving as a crucial step in error detection. For example, the system extracts composition data from a past period, compares current parameters with historical baseline values, and analyzes composition fluctuation trends. If the content of a key component changes beyond the normal range, it is determined to be an anomalous gas composition change. The verification report will specify the exact parameters of the anomalous composition, the magnitude of the fluctuation, and recommendations for adjusting the gas processing procedure or re-testing the components.

[0113] In one implementation, the system uses sensitivity analysis to determine the degree of matching between the selected verification model and the current operating conditions, thereby improving the analysis of error sources. For example, the system will change the pressure and temperature values ​​in the operating condition parameters within a reasonable range and observe the corresponding changes in the compressibility factor. If the compressibility factor changes abnormally drastically, it indicates that the selected verification model is not well-suited to the current operating conditions. The report will record the model matching analysis process, sensitive parameter change data, and provide suggestions for replacing the suitable model or adjusting the operating condition monitoring range. The report will also fully present core information such as input parameter records and the calculation process of each stage.

[0114] In one possible implementation, the system supports prioritizing error sources according to their impact, and presenting the main error sources and corresponding recommendations in the report first, thereby helping users quickly focus on core issues, shorten the calibration and rectification cycle, and improve problem-solving efficiency.

[0115] In one possible implementation, the error source analysis process automatically correlates with the operational logs of relevant equipment, such as sensor maintenance records and flow computer parameter adjustment records. Cross-validation using multi-dimensional data can further improve the accuracy of error analysis conclusions, making calibration recommendations more targeted.

[0116] As shown in S402 above, when the relative error exceeds the preset threshold, a complete verification and judgment report is generated through multi-dimensional error source analysis, achieving accurate location and standardized presentation of the error cause. The error analysis process relies on specific data support, avoiding the bias of subjective judgment, and effectively solving the problems of difficulty in tracing the source of error and unclear rectification direction in traditional verification.

[0117] The natural gas flow rate verification method provided in this application provides a data foundation for subsequent verification by acquiring natural gas composition data, operating parameters, and the first volumetric flow rate of the flow computer. Then, based on the data type of the composition data, a target verification model is matched from multiple verification models. This allows for the application of appropriate calculation methods for natural gas from different sources or compositions (such as standard dry gas, gases containing impurities, etc.), effectively improving the adaptability and accuracy of the verification model. Next, a second volumetric flow rate is determined based on the target verification model and real-time operating parameters, enabling verification of the flow computer's output and effectively identifying potential deviations in the flow rate verification process. Finally, a verification judgment report is generated by comparing the first and second volumetric flow rates, providing users with intuitive verification conclusions. This improves the reliability and transparency of the natural gas metering system, effectively prevents natural gas settlement risks, and ensures the safety and efficiency of production operations.

[0118] In an exemplary embodiment, Figure 5 This is a schematic diagram illustrating the composition of a natural gas flow verification device provided in an embodiment of this application. Figure 5 As shown, the natural gas flow rate verification device includes: a data acquisition module 501, a model selection module 502, a flow rate calculation module 503, and a report generation module 504. The data acquisition module 501 acquires the natural gas composition data, operating parameters, and the first volumetric flow rate output by the flow computer. The model selection module 502 determines a target verification model from multiple verification models based on the data type of the composition data. The flow rate calculation module 503 determines the second volumetric flow rate of the natural gas based on the target verification model and operating parameters. The report generation module 504 generates a verification judgment report based on the first and second volumetric flow rates.

[0119] In this embodiment, the model selection module 502 is specifically used to: determine a first verification model as the target verification model when the data type of the component data is molar component data; and determine a second verification model as the target verification model when the data type of the component data is physical property parameter data. The first verification model is constructed based on a first-class national standard for calculating the natural gas compressibility factor, and the second verification model is constructed based on a second-class national standard for calculating the natural gas compressibility factor. The first-class national standard and the second-class national standard employ different calculation logics and input parameter requirements.

[0120] In an exemplary embodiment, this application also provides an electronic device, which may be the natural gas flow verification device in the above method embodiments. Figure 6 This is a schematic diagram of a natural gas flow verification device provided in an embodiment of this application. Figure 6As shown, the natural gas flow verification device may include: a processor 601 and a memory 602; the memory 602 stores instructions executable by the processor 601; when the processor 601 is configured to execute instructions, it causes an electronic device or network device or manager to perform the system functions described in the foregoing method embodiments.

[0121] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0122] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0123] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0124] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0125] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0126] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for verifying natural gas flow rate, characterized in that, The method includes: Acquire natural gas composition data, operating parameters, and the first volumetric flow rate output by the flow computer; Based on the data type of the component data, a target verification model matching the data type is determined from multiple verification models; The second volumetric flow rate of the natural gas is determined based on the target verification model and the operating parameters. A verification report is generated based on the first volumetric flow rate and the second volumetric flow rate.

2. The method according to claim 1, characterized in that, The determination of a target verification model matching the data type from multiple verification models based on the data type of the component data includes: When the data type of the component data is molar component data, the first verification model is determined as the target verification model; the first verification model is constructed based on the first type of national standard for natural gas compressibility factor calculation; When the data type of the component data is physical property parameter data, the second verification model is determined as the target verification model; the second verification model is constructed based on the second type of national standard for natural gas compressibility factor calculation; the first type of national standard and the second type of national standard adopt different calculation logic and input parameter requirements.

3. The method according to claim 1, characterized in that, The step of determining the second volumetric flow rate based on the target verification model and the operating parameters includes: Based on the target verification model and the operating parameters, the compressibility factor of natural gas is determined; Based on the compressibility factor and the operating parameters, the second volumetric flow rate is determined using the volumetric flow rate calculation formula.

4. The method according to claim 3, characterized in that, The operating parameters include the operating pressure, operating temperature, and operating volumetric flow rate of the natural gas in the pipeline. The formula for calculating the volumetric flow rate is as follows: in, This represents the second volumetric flow rate calculated based on the compressibility factor and operating parameters. This indicates the volumetric flow rate under the stated operating conditions as measured by the flow meter. This indicates the operating pressure as collected by a pressure sensor. This represents the reference pressure under standard conditions as determined by natural gas metering standards. This indicates the operating temperature as collected by a temperature sensor. This represents the reference temperature under standard conditions as determined by natural gas metering standards. This represents the compression factor determined based on the target verification model. This represents the baseline compression factor under standard conditions.

5. The method according to claim 1, characterized in that, The step of generating a verification report by comparing the first volumetric flow rate with the second volumetric flow rate includes: Obtain the relative error between the first volumetric flow rate and the second volumetric flow rate; When the relative error exceeds a preset threshold, a verification judgment report is generated by analyzing the sources of error. The sources of error include at least one of the following: measurement drift of pressure sensor and / or temperature sensor, abnormal changes in gas composition, and mismatch between the selected verification model and the current operating conditions. The verification judgment report includes input parameter records, calculation process, error analysis conclusions, and calibration recommendations.

6. The method according to claim 5, characterized in that, The analysis of error sources includes: Based on the historical data sequence of the operating parameters, the measurement stability of the pressure sensor and / or temperature sensor is evaluated to determine the measurement drift of the pressure sensor and / or temperature sensor. Based on the historical records of the component data, the fluctuation trends of gas component parameters are analyzed to determine abnormal changes in gas components. By changing the pressure and temperature values ​​in the operating parameters, the degree of change in the compressibility factor is analyzed to determine the degree of matching between the selected verification model and the current operating parameters.

7. A natural gas flow rate verification device, characterized in that, The device includes: a data acquisition module, a model selection module, a traffic calculation module, and a report generation module; The data acquisition module is used to acquire the composition data, operating parameters, and first volume flow rate output by the flow computer of natural gas. The model selection module is used to determine a target verification model that matches the data type of the component data from multiple verification models; The flow calculation module is used to determine the second volume flow rate of the natural gas based on the target verification model and the operating parameters. The report generation module is used to generate a verification and judgment report based on the first volumetric flow rate and the second volumetric flow rate.

8. The apparatus according to claim 7, characterized in that, The model selection module is specifically used for: When the data type of the component data is molar component data, the first verification model is determined as the target verification model; the first verification model is constructed based on the first type of national standard for natural gas compressibility factor calculation; When the data type of the component data is physical property parameter data, the second verification model is determined as the target verification model; the second verification model is constructed based on the second type of national standard for natural gas compressibility factor calculation; the first type of national standard and the second type of national standard adopt different calculation logic and input parameter requirements.

9. An electronic device, characterized in that, The controller includes: a processor and a memory; The memory stores instructions that the processor can execute; When the processor is configured to execute the instructions, the controller causes the controller to implement the method as described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes: computer software instructions; When the computer software instructions are executed in an electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-6.

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