Method for measuring flow velocity of fluid in pipeline based on fluid medium parameter analysis

Abstract

The invention discloses a method for measuring the flow velocity of fluid in a pipeline based on fluid medium parameter analysis, and relates to the technical field of fluid mechanics and fluid engineering. In order to solve the problems that in the prior art, flow velocity measurement data acquisition node arrangement and operation environment analysis of fluid in a pipeline are insufficient, the robustness of a measurement result is reduced, and the accuracy and reliability of flow velocity measurement are affected due to dependence on a single measurement model. Characteristic parameters such as fluid density and sound velocity are calculated and dynamically input into the flow velocity calculation model, real-time changes of the fluid parameters are comprehensively considered, the accuracy of the flow velocity measurement result is improved, the relation between the flow velocity and the sound wave propagation time difference is accurately established, the calculation result is compared with the flow velocity characteristic value and trend of historical data, and the accuracy of the flow velocity measurement result is improved. And the calculation precision of the flow velocity calculation model is evaluated based on the verification result, so that the adaptability, robustness and economy of the method are remarkably enhanced while the flow velocity measurement precision is improved.

Description

Technical Field

[0001] The invention relates to the technical field of fluid mechanics and fluid engineering, and in particular to a method for measuring the flow rate of a fluid in a pipeline based on fluid medium parameter analysis. Background Art

[0002] Traditional flow rate measurement methods, such as static pressure method, float method, etc., although they can meet the measurement requirements to a certain extent, often have problems such as low measurement accuracy and limited scope of application. For example, the patent application with publication number: CN110895285A discloses a measuring device and a measuring method for measuring the flow rate of a fluid in a pipeline, wherein the pipeline includes a variable diameter section and a non-variable diameter section, and the measuring device includes a first pressure source that delivers a fluid medium to the non-variable diameter section of the pipeline according to a first preset pressure P0; a first sensor that measures the pressure difference δP1 between the inlet and outlet ends of the first pipeline or is used to measure the flow rate V0 of the fluid medium in the first pipeline to obtain a first detection value; a second pressure source that delivers a fluid medium to the variable diameter section of the pipeline according to a second preset pressure P0'; a second sensor that measures the pressure difference δP1' between the inlet and outlet ends of the second pipeline or measures the flow rate V0' of the fluid medium in the second pipeline to obtain a second detection value; and a data processing module that calculates the flow rate of the fluid in the pipeline according to the first preset pressure P0, the second preset pressure P0', the first detection value, and the second detection value.

[0003] Although the above patents can expand the scope of application, extend the service life and improve the measurement reliability, they still have the following problems:

[0004] 1. In the prior art, the pipeline operating environment is complex and changeable, and the layout of data acquisition nodes and the analysis of their operating environment are not sufficiently considered. The collected data may have noise, omissions or transmission interference problems, and cannot provide reliable input for subsequent flow velocity calculations, resulting in poor robustness of the measurement results;

[0005] 2. The traditional method lacks in-depth analysis and dynamic correction of fluid medium parameters, ignores the significant changes in sound velocity under different fluid compositions and temperature conditions, thus affecting the accuracy of flow velocity calculation, and only relies on a single measurement model, which affects the measurement accuracy and reliability of flow velocity measurement. Summary of the invention

[0006] The purpose of the present invention is to provide a method for measuring the flow rate of a fluid in a pipeline based on the analysis of fluid medium parameters. By accurately establishing the relationship between the flow rate and the time difference of sound wave propagation, a dynamic correlation model is constructed, so that the measurement method can adapt to changes in complex working conditions such as fluid medium composition and pipeline operating conditions. While improving the flow rate measurement accuracy, the adaptability, robustness and economy of the method are significantly enhanced to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] The method for measuring the flow rate of a fluid in a pipeline based on the analysis of fluid medium parameters comprises the following steps:

[0009] Step 1: Install data acquisition sensors at each acquisition node in the pipeline, and collect parameter data of the fluid in the pipeline in real time based on the data acquisition sensors;

[0010] Step 2: Analyze the correlation between the collected parameter data and the fluid flow rate, and calculate the characteristic parameters of the fluid medium based on the correlation;

[0011] Step 3: Based on the principles of fluid mechanics and acoustics, a flow velocity calculation model based on the sound propagation time difference method is constructed, and the parameter data of the fluid in the pipeline and the characteristic parameters of the fluid medium are input into the flow velocity calculation model for calculation to obtain the flow velocity of the fluid in the pipeline;

[0012] Step 4: Verify the calculated flow velocity of the fluid in the pipeline, evaluate the calculation accuracy of the flow velocity calculation model based on the verification results, and generate optimization suggestions for the flow velocity calculation model based on the evaluation results.

[0013] Furthermore, the real-time acquisition of parameter data of the fluid in the pipeline in step 1 also includes:

[0014] Reading the physical parameter data collected by the data acquisition sensor, determining the type of the physical parameter data, and matching corresponding physical parameter sample data in the fluid parameter database according to the type of the physical parameter data;

[0015] Determine the fluctuation range of the physical parameter sample data and its corresponding data type based on the physical parameter sample data, and verify the physical parameter data based on the fluctuation range and the data type;

[0016] Based on the verification result, physical parameter data that meets the fluctuation range and data type are selected as target physical parameter data, and at least one sub-physical parameter data set is generated based on the type of the target physical parameter data;

[0017] The sub-physical parameter data set is checked for integrity. When there are omissions in the sub-physical parameter data set, the average value of the adjacent data is taken as the estimated value of the missing data to supplement the missing data and generate a complete target parameter data transmission file.

[0018] Furthermore, in the step 1, data acquisition sensors are installed at each acquisition node in the pipeline, and further comprises:

[0019] Monitor the operating conditions of pipelines, evaluate the operating environment of acquisition nodes, and determine the environmental parameters at each acquisition node;

[0020] Analyze and deduce the acquisition nodes to determine the longitudinal pressure load and transverse shear load borne by each acquisition node during pipeline operation, and evaluate the mechanical properties of the acquisition nodes;

[0021] Analyze the impact of the location of the acquisition node on signal transmission, including signal interference, attenuation, and noise ratio, to ensure that the acquisition node can stably transmit parameter data;

[0022] Verify the sensitivity of the acquisition nodes to the key physical parameters of fluid pressure, temperature, density, sound velocity and flow rate, and eliminate the acquisition nodes with insensitive response and high noise based on the verification results;

[0023] The selected acquisition nodes are optimized and calibrated, the performance parameters of each acquisition node are recorded, and the working status of each acquisition node is monitored in real time during the actual operation.

[0024] Furthermore, the selected collection nodes are optimized, including: based on the key position priority principle, the areas where the fluid parameters change significantly are given priority for collection node layout; based on the redundant design principle, redundant collection nodes are arranged in key areas to ensure that they can still work effectively in the event of a single point failure; based on the uniform distribution principle, the collection nodes are avoided from being too concentrated or sparse, ensuring the comprehensiveness and representativeness of parameter collection.

[0025] Furthermore, the step 2 specifically includes:

[0026] Extract various types of physical parameter data based on the target parameter data transmission file;

[0027] Based on the type of physical parameter data and the fluid state equation, a correlation model between pressure, temperature and density is constructed. At the same time, a correlation model between the speed of sound and the characteristics of the fluid medium is established based on acoustic theory.

[0028] Based on the correlation model between pressure, temperature and density, the correlation between fluid density and pressure and temperature is analyzed to generate a density calculation expression;

[0029] Based on the correlation model between sound velocity and fluid medium characteristics, the dependence between sound velocity and fluid medium composition and temperature is analyzed, and the sound velocity calculation expression is generated.

[0030] Furthermore, the step 2 of calculating the characteristic parameters of the fluid medium specifically includes:

[0031] Extracting real-time measured pressure and temperature data from the target parameter data transmission file, and calculating characteristic parameters of density and sound velocity of the fluid medium based on the real-time measured values ​​of pressure and temperature by combining density calculation expression and sound velocity calculation expression;

[0032] The calculated characteristic parameters such as density and sound velocity are verified to verify whether the characteristic parameters meet the physical property range of the fluid medium, and the characteristic parameters of the fluid medium that have passed the verification are integrated to generate a characteristic parameter data set.

[0033] Furthermore, the calculated characteristic parameters such as density and sound velocity are verified, including:

[0034] Compare the calculated characteristic parameters of density and sound velocity with the physical characteristic range of the fluid medium, and when the characteristic parameters exceed the physical characteristic range, mark the abnormal values ​​based on the association model;

[0035] The calculated characteristic parameters of density and sound velocity are associated with the real-time collected pressure and temperature data, and the trend of characteristic parameters changing with pressure and temperature is analyzed to see whether it conforms to the known behavior characteristics of the fluid medium. Based on the analysis results, the associated parameters in the correlation model of pressure, temperature, density and sound velocity are adjusted.

[0036] Furthermore, the step three specifically includes:

[0037] According to the principles of fluid mechanics and acoustics, the flow velocity of the fluid in the pipeline and the time difference between the propagation of sound waves in the fluid downstream and upstream are determined, and a flow velocity calculation model is constructed based on the sound propagation time difference method;

[0038] Determine the required parameter type of the flow rate calculation model, and extract corresponding parameter data from the target parameter data transmission file based on the required parameter type;

[0039] The extracted corresponding parameter data are input into the flow velocity calculation model to obtain the preliminary result of the fluid flow velocity. At the same time, the path length deviation, sound speed deviation and flow velocity deviation are corrected to obtain the fluid flow velocity in the pipeline.

[0040] Furthermore, the flow rate of the fluid in the pipeline also includes: performing data smoothing processing on the flow rate of the fluid in the pipeline based on a weighted moving average method, optimizing based on a time series of the flow rate of the fluid in the pipeline, and obtaining an average flow rate value of the fluid in the pipeline.

[0041] Furthermore, the step 4 of verifying the calculated flow rate of the fluid in the pipeline also includes:

[0042] Obtain historical data of the flow velocity of the fluid in the pipeline, and draw a flow velocity change curve and a change curve of associated parameters based on the historical data of the flow velocity of the fluid in the pipeline;

[0043] Determine the velocity characteristic values ​​of the fluid in the pipeline under different associated parameters based on the velocity variation curve, including the maximum velocity, the minimum velocity, the average velocity and the fluctuation range;

[0044] Comparing the calculated flow velocity result with the flow velocity characteristic value to determine whether the current flow velocity value meets the characteristic range in the historical data;

[0045] At the same time, based on the correlation change curve between flow velocity and associated parameters, the change trend between pipeline fluid flow velocity and associated parameters is analyzed;

[0046] When the current flow velocity value exceeds the characteristic range, the error type of the flow velocity calculation model is analyzed based on the change trend between the flow velocity and the associated parameters.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] By calculating characteristic parameters such as fluid density and sound velocity and dynamically inputting them into the flow velocity calculation model, the real-time changes of fluid parameters are fully considered, the accuracy of flow velocity measurement results is improved, the relationship between flow velocity and sound wave propagation time difference is accurately established, and a dynamic correlation model is constructed, so that the measurement method can adapt to changes in complex working conditions such as fluid medium composition and pipeline operating conditions. The flow velocity characteristic values ​​and trends of the calculated results are compared with those of historical data, and the calculation accuracy of the flow velocity calculation model is evaluated based on the verification results. While improving the flow velocity measurement accuracy, the adaptability, robustness and economy of the method are significantly enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a flow chart of a method for measuring fluid flow rate in a pipeline based on fluid medium parameter analysis of the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] In order to solve the technical problems in the prior art that the data acquisition node layout and operating environment analysis of the fluid flow velocity measurement in the pipeline are insufficient, the robustness of the measurement results is reduced, and the single measurement model is relied on, thus affecting the accuracy and reliability of the flow velocity measurement, please refer to Figure 1 , this embodiment provides the following technical solutions:

[0052] The method for measuring the flow rate of a fluid in a pipeline based on the analysis of fluid medium parameters comprises the following steps:

[0053] Step 1: Install data acquisition sensors at each acquisition node in the pipeline, and collect parameter data of the fluid in the pipeline in real time based on the data acquisition sensors, including pressure, temperature, density, sound velocity, flow rate and other parameters;

[0054] Step 2: Analyze the correlation between the collected parameter data and the fluid flow rate, and calculate characteristic parameters of the fluid medium such as density and sound velocity based on the correlation;

[0055] Step 3: Based on the principles of fluid mechanics and acoustics, a velocity calculation model based on the time difference method of sound propagation is constructed. The parameter data of the fluid in the pipeline and the characteristic parameters of the fluid medium are input into the velocity calculation model for calculation to obtain the velocity of the fluid in the pipeline, which includes:

[0056] According to the principles of fluid mechanics and acoustics, the flow velocity of the fluid in the pipeline and the time difference between the propagation of sound waves in the fluid downstream and upstream are determined, and a flow velocity calculation model is constructed based on the sound propagation time difference method;

[0057] Determine the required parameter types of the flow velocity calculation model, including sound velocity, fluid density, pipe diameter, distance between the sound wave transmitter and the receiver, etc., and extract corresponding parameter data from the target parameter data transmission file based on the required parameter types;

[0058] The extracted corresponding parameter data is input into the flow velocity calculation model to obtain the preliminary result of the fluid flow velocity. At the same time, the path length deviation, sound velocity deviation and flow velocity deviation are corrected to obtain the fluid flow velocity in the pipeline;

[0059] The flow velocity of the fluid in the pipeline is smoothed based on the weighted moving average method, and the time series of the flow velocity of the fluid in the pipeline is optimized to obtain the average flow velocity value of the fluid in the pipeline;

[0060] Step 4: Verify the calculated flow velocity of the fluid in the pipeline, evaluate the calculation accuracy of the flow velocity calculation model based on the verification results, and generate optimization suggestions for the flow velocity calculation model based on the evaluation results.

[0061] In this embodiment, by calculating characteristic parameters such as fluid density and sound velocity and dynamically inputting them into the flow velocity calculation model, the real-time changes of fluid parameters are fully considered, the accuracy of the flow velocity measurement results is improved, the relationship between the flow velocity and the sound wave propagation time difference is accurately established, and a dynamic correlation model is constructed, so that the measurement method can adapt to changes in complex working conditions such as fluid medium composition and pipeline operating conditions. The flow velocity characteristic values ​​and trends of the calculated results are compared with those of historical data, and the calculation accuracy of the flow velocity calculation model is evaluated based on the verification results. While improving the flow velocity measurement accuracy, the adaptability, robustness and economy of the method are significantly enhanced.

[0062] In this embodiment, the step 1 of collecting parameter data of the fluid in the pipeline in real time also includes:

[0063] Read the physical parameter data collected by the data acquisition sensor, determine the type of the physical parameter data, including parameter types such as pressure, temperature, density, sound velocity and flow rate, and match the corresponding physical parameter sample data in the fluid parameter database according to the type of the physical parameter data;

[0064] Determine the fluctuation range of the physical parameter sample data and its corresponding data type based on the physical parameter sample data, and verify the physical parameter data based on the fluctuation range and the data type;

[0065] Based on the verification result, physical parameter data that meets the fluctuation range and data type are selected as target physical parameter data, and at least one sub-physical parameter data set is generated based on the type of the target physical parameter data;

[0066] The sub-physical parameter data set is checked for integrity. When there are omissions in the sub-physical parameter data set, the average value of the adjacent data is taken as the estimated value of the missing data to supplement the missing data and generate a complete target parameter data transmission file.

[0067] In this embodiment, by collecting parameter data of the fluid in the pipeline in real time and performing a series of data processing steps, efficient monitoring and management of the fluid parameters are achieved. By generating multiple sub-physical parameter data sets, data processing is further refined, and the integrity of the sub-physical parameter data sets is checked. By supplementing the missing data, the integrity of the target parameter data transmission file is ensured, the accuracy and reliability of data monitoring are improved, and strong support is provided for pipeline operation and maintenance.

[0068] In this embodiment, the step 1 of installing a data acquisition sensor at each acquisition node in the pipeline also includes:

[0069] Monitor the operating conditions of the pipeline (such as fluid pressure, temperature range, vibration frequency, and corrosiveness of fluid components), evaluate the operating environment of the acquisition node, and determine the environmental parameters of each acquisition node, such as high-temperature areas, bend areas, or areas with more eddy currents and backflows;

[0070] Analyze and deduce the acquisition nodes to determine the longitudinal pressure load and transverse shear load borne by each acquisition node during pipeline operation, and evaluate the mechanical properties of the acquisition nodes;

[0071] Analyze the impact of the location of the acquisition node on signal transmission, including signal interference, attenuation, and noise ratio, to ensure that the acquisition node can stably transmit parameter data;

[0072] Verify the sensitivity of the acquisition nodes to the key physical parameters of fluid pressure, temperature, density, sound velocity and flow rate, and eliminate the acquisition nodes with insensitive response and high noise based on the verification results;

[0073] Optimize the selected acquisition nodes, calibrate the optimized acquisition nodes, record the performance parameters of each acquisition node (such as range, sensitivity, anti-interference ability, etc.), and monitor the working status of each acquisition node in real time during the actual operation;

[0074] In this embodiment, the selected collection nodes are optimized, specifically including: based on the key position priority principle, areas where fluid parameters change significantly (such as areas with obvious velocity gradients) are given priority for collection node layout; based on the redundant design principle, redundant collection nodes are arranged in key areas to ensure that they can still work effectively in the event of a single point failure; based on the uniform distribution principle, the collection nodes are avoided from being too concentrated or sparse, ensuring the comprehensiveness and representativeness of parameter collection.

[0075] In this embodiment, by comprehensively analyzing and screening the load characteristics and carrying capacity of the acquisition nodes, comprehensive screening is performed from multiple aspects such as mechanical performance, signal reliability, sensitivity, etc., combined with optimized layout and dynamic adaptive management, it is ensured that the selected acquisition nodes can meet the needs of the complex pipeline operating environment, ensure the stability of the acquisition nodes and the validity of the collected data, thereby providing reliable support for the measurement of fluid flow rate in complex pipelines.

[0076] In this embodiment, the step 2 specifically includes:

[0077] Extract various types of physical parameter data such as pressure, temperature, density, and sound speed based on the target parameter data transmission file;

[0078] Based on the type of physical parameter data and the fluid state equation, a correlation model between pressure, temperature and density is constructed. At the same time, a correlation model between the speed of sound and the characteristics of the fluid medium is established based on acoustic theory.

[0079] Based on the correlation model between pressure, temperature and density, the correlation between fluid density and pressure and temperature is analyzed to generate a density calculation expression;

[0080] Based on the correlation model between sound velocity and fluid medium characteristics, the dependence between sound velocity and fluid medium composition and temperature is analyzed, and the sound velocity calculation expression is generated.

[0081] In this embodiment, the characteristic parameters of the fluid medium are calculated in step 2, specifically including:

[0082] Extracting real-time measured pressure and temperature data from the target parameter data transmission file, and calculating characteristic parameters of density and sound velocity of the fluid medium based on the real-time measured values ​​of pressure and temperature by combining density calculation expression and sound velocity calculation expression;

[0083] Verify the calculated characteristic parameters such as density and sound velocity to verify whether the characteristic parameters meet the physical property range of the fluid medium, and integrate the characteristic parameters of the fluid medium that have been verified to be qualified to generate a characteristic parameter data set;

[0084] In this embodiment, the calculated characteristic parameters such as density and sound velocity are verified, specifically including:

[0085] Compare the calculated characteristic parameters of density and sound velocity with the physical characteristic range of the fluid medium, and when the characteristic parameters exceed the physical characteristic range, mark the abnormal values ​​based on the association model;

[0086] The calculated characteristic parameters of density and sound velocity are associated with the real-time collected pressure and temperature data, and the trend of characteristic parameters changing with pressure and temperature is analyzed to see whether it conforms to the known behavior characteristics of the fluid medium. Based on the analysis results, the associated parameters (such as compression factor, component ratio, etc.) in the correlation model of pressure, temperature, density and sound velocity are adjusted to adapt to changes in the fluid operating environment and improve the calculation accuracy of the characteristic parameters.

[0087] In this embodiment, by constructing the correlation model between pressure, temperature and density and the correlation model between the speed of sound and the characteristics of the fluid medium, the density calculation expression and the speed of sound calculation expression are further generated, thereby realizing the accurate calculation of the characteristic parameters of the density and speed of sound of the fluid medium, comparing the calculated characteristic parameters with the physical characteristic range of the fluid medium, marking the abnormal values, and analyzing the trend of the density and speed of sound changing with the environmental parameters in combination with the real-time collected pressure and temperature data, and effectively verifying the rationality of the characteristic parameters. At the same time, by adjusting the key parameters in the correlation model to adapt to the changes in the operating environment, the calculation accuracy of the characteristic parameters and the adaptability of the model are significantly improved.

[0088] In this embodiment, the step 4 of verifying the calculated flow rate of the fluid in the pipeline further includes:

[0089] Obtain historical data of fluid flow velocity in the pipeline, and draw a velocity change curve and a change curve of associated parameters (such as pressure, temperature, etc.) based on the historical data of fluid flow velocity in the pipeline;

[0090] Determine the velocity characteristic values ​​of the fluid in the pipeline under different associated parameters based on the velocity variation curve, including the maximum velocity, the minimum velocity, the average velocity and the fluctuation range;

[0091] Comparing the calculated flow velocity result with the flow velocity characteristic value to determine whether the current flow velocity value meets the characteristic range in the historical data;

[0092] At the same time, based on the correlation change curve between flow velocity and associated parameters, the change trend between pipeline fluid flow velocity and associated parameters is analyzed;

[0093] When the current flow velocity value exceeds the characteristic range, the error type of the flow velocity calculation model is analyzed based on the change trend between the flow velocity and the associated parameters, including abnormal input parameters, unreasonable model coefficient settings, etc.

[0094] In this embodiment, by acquiring historical data and drawing a velocity change curve and a change curve of the velocity and associated parameters, the velocity characteristic value can be effectively analyzed, and the calculation result can be compared with the historical characteristic range. At the same time, the change trend between the velocity and the associated parameters is analyzed, which not only ensures the accuracy and reliability of the velocity calculation results, but also can timely discover and diagnose the potential errors of the velocity calculation model, thereby improving the accuracy of pipeline fluid velocity monitoring, optimizing pipeline operation management, and helping to identify velocity anomalies and prevent possible operational risks. Through the analysis of the model error type, the input parameters or model coefficients can be adjusted in a targeted manner to ensure that the velocity monitoring system adapts to the actual operating conditions of the pipeline, providing an important guarantee for the safe and efficient operation of the pipeline.

[0095] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for measuring the flow rate of a fluid in a pipeline based on fluid medium parameter analysis, characterized in that: The following steps are involved: Step 1: Install data acquisition sensors at each acquisition node in the pipeline, and collect parameter data of the fluid in the pipeline in real time based on the data acquisition sensors; Step 2: Analyze the correlation between the collected parameter data and the fluid flow rate, and calculate the characteristic parameters of the fluid medium based on the correlation; Step 3: Based on the principles of fluid mechanics and acoustics, a flow velocity calculation model based on the sound propagation time difference method is constructed, and the parameter data of the fluid in the pipeline and the characteristic parameters of the fluid medium are input into the flow velocity calculation model for calculation to obtain the flow velocity of the fluid in the pipeline; Step 4: Verify the calculated flow velocity of the fluid in the pipeline, evaluate the calculation accuracy of the flow velocity calculation model based on the verification results, and generate optimization suggestions for the flow velocity calculation model based on the evaluation results.

2. The method for measuring the flow rate of fluid in a pipeline based on fluid medium parameter analysis according to claim 1, characterized in that: The step 1 of collecting parameter data of the fluid in the pipeline in real time also includes: Reading the physical parameter data collected by the data acquisition sensor, determining the type of the physical parameter data, and matching corresponding physical parameter sample data in the fluid parameter database according to the type of the physical parameter data; Determining a fluctuation range and a corresponding data type of the physical parameter sample data based on the physical parameter sample data, and verifying the physical parameter data based on the fluctuation range and the data type; Based on the verification result, physical parameter data that meets the fluctuation range and data type are selected as target physical parameter data, and at least one sub-physical parameter data set is generated based on the type of the target physical parameter data; The sub-physical parameter data set is checked for integrity. When there are omissions in the sub-physical parameter data set, the average value of the adjacent data is taken as the estimated value of the missing data to supplement the missing data and generate a complete target parameter data transmission file.

3. The method for measuring the flow rate of fluid in a pipeline based on fluid medium parameter analysis according to claim 2, characterized in that: The step 1 of installing a data acquisition sensor at each acquisition node in the pipeline also includes: Monitor the operating conditions of pipelines, evaluate the operating environment of acquisition nodes, and determine the environmental parameters at each acquisition node; Analyze and deduce the acquisition nodes to determine the longitudinal pressure load and transverse shear load borne by each acquisition node during pipeline operation, and evaluate the mechanical properties of the acquisition nodes; Analyze the impact of the location of the acquisition node on signal transmission, including signal interference, attenuation, and noise ratio; Verify the sensitivity of the acquisition nodes to fluid pressure, temperature, density, sound velocity and flow rate, and remove the acquisition nodes with insensitive response and high noise based on the verification results; The selected acquisition nodes are optimized and calibrated, the performance parameters of each acquisition node are recorded, and the working status of each acquisition node is monitored in real time during the actual operation.

4. The method for measuring the flow rate of fluid in a pipeline based on fluid medium parameter analysis according to claim 3, characterized in that: The selected acquisition nodes are optimized, specifically including: based on the key position priority principle, areas where fluid parameters change significantly are given priority for acquisition node layout, and based on the redundant design principle, redundant acquisition nodes are arranged in key areas.

5. The method for measuring the flow rate of fluid in a pipeline based on fluid medium parameter analysis according to claim 4, characterized in that: The step 2 specifically includes: Extract various types of physical parameter data based on the target parameter data transmission file; Based on the type of physical parameter data and the fluid state equation, a correlation model between pressure, temperature and density is constructed. At the same time, a correlation model between the speed of sound and the characteristics of the fluid medium is established based on acoustic theory. Based on the correlation model between pressure, temperature and density, the correlation between fluid density and pressure and temperature is analyzed to generate a density calculation expression; Based on the correlation model between sound velocity and fluid medium characteristics, the dependence between sound velocity and fluid medium composition and temperature is analyzed, and the sound velocity calculation expression is generated.

6. The method for measuring the flow rate of fluid in a pipeline based on fluid medium parameter analysis according to claim 5, characterized in that: The characteristic parameters of the fluid medium are calculated in step 2, specifically including: Extracting real-time measured pressure and temperature data from the target parameter data transmission file, and calculating characteristic parameters of density and sound velocity of the fluid medium based on the real-time measured values ​​of pressure and temperature by combining density calculation expression and sound velocity calculation expression; The calculated density and sound velocity characteristic parameters are verified to verify whether the characteristic parameters meet the physical property range of the fluid medium, and the characteristic parameters of the fluid medium that have been verified to be qualified are integrated to generate a characteristic parameter data set.

7. The method for measuring the flow rate of fluid in a pipeline based on fluid medium parameter analysis according to claim 6, characterized in that: Verify the calculated density and sound velocity characteristic parameters, including: Compare the calculated characteristic parameters of density and sound velocity with the physical characteristic range of the fluid medium, and when the characteristic parameters exceed the physical characteristic range, mark the abnormal values ​​based on the association model; The calculated characteristic parameters of density and sound velocity are associated with the real-time collected pressure and temperature data, and the trend of characteristic parameters changing with pressure and temperature is analyzed to see whether it conforms to the known behavior characteristics of the fluid medium. Based on the analysis results, the associated parameters in the correlation model of pressure, temperature, density and sound velocity are adjusted.

8. The method for measuring the flow rate of fluid in a pipeline based on fluid medium parameter analysis according to claim 7, characterized in that: The step three specifically includes: According to the principles of fluid mechanics and acoustics, the flow velocity of the fluid in the pipeline and the time difference between the propagation of sound waves in the fluid downstream and upstream are determined, and a flow velocity calculation model is constructed based on the sound propagation time difference method; Determine the required parameter type of the flow rate calculation model, and extract corresponding parameter data from the target parameter data transmission file based on the required parameter type; The extracted corresponding parameter data are input into the flow velocity calculation model to obtain the preliminary result of the fluid flow velocity. At the same time, the path length deviation, sound speed deviation and flow velocity deviation are corrected to obtain the fluid flow velocity in the pipeline.

9. The method for measuring the flow rate of fluid in a pipeline based on fluid medium parameter analysis according to claim 8, characterized in that: The flow rate of the fluid in the pipeline also includes: performing data smoothing processing on the flow rate of the fluid in the pipeline based on a weighted moving average method, optimizing based on a time series of the flow rate of the fluid in the pipeline, and obtaining an average flow rate value of the fluid in the pipeline.

10. The method for measuring the flow rate of fluid in a pipeline based on fluid medium parameter analysis according to claim 9, characterized in that: The step 4 verifies the calculated flow rate of the fluid in the pipeline, and further includes: Obtain historical data of the flow velocity of the fluid in the pipeline, and draw a flow velocity change curve and a change curve of associated parameters based on the historical data of the flow velocity of the fluid in the pipeline; Determine the velocity characteristic values ​​of the fluid in the pipeline under different associated parameters based on the velocity variation curve, including the maximum velocity, the minimum velocity, the average velocity and the fluctuation range; Comparing the calculated flow velocity result with the flow velocity characteristic value to determine whether the current flow velocity value meets the characteristic range in the historical data; At the same time, based on the correlation change curve between flow velocity and associated parameters, the change trend between pipeline fluid flow velocity and associated parameters is analyzed; When the current flow velocity value exceeds the characteristic range, the error type of the flow velocity calculation model is analyzed based on the change trend between the flow velocity and the associated parameters.

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