Metrological verification method and system for fuel dispenser

Abstract

The invention discloses a metrological verification method and system for a fuel dispenser, particularly relates to the technical field of metrological verification, and is used for solving the problem that the fuel gasification effect influences the metering precision under the existing high flow rate condition. The influence of the friction effect of the contact area of the inner wall of the pipeline and fuel oil on local heat accumulation is analyzed and evaluated through micro-scale friction loss, and the area where shear stress is abnormally increased is monitored and marked through shear stress change, so that a gasification high-risk area is determined; for the gasification high-risk area, the change rate of Van der Waals force among fuel molecules is monitored, and the sudden change process of the Van der Waals force is analyzed; monitoring the energy dissipation rate of the turbulent vortex, and identifying the abrupt change point of the energy dissipation rate so as to evaluate the gasification occurrence probability of the local area; and the dramatic change degree of the intermolecular interaction force and the gasification occurrence probability are comprehensively evaluated, the influence degree of the gasification effect on the fuel oil metering precision is determined, and then metrological verification of the oiling machine is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of metrology and verification, and more specifically, to a metrology and verification method and system for a fuel dispenser. Background Art

[0002] The metrological verification of fuel dispensers refers to the process of measuring and calibrating the accuracy of the metering device of the dispenser to ensure that the amount of fuel displayed during the refueling process is consistent with the actual amount of fuel flowing into the vehicle tank. Meterological verification is usually carried out by statutory metrology institutions in accordance with standard regulations and involves the measurement and verification of key parameters such as fuel flow, pressure, temperature, etc.

[0003] In the existing technology, the influence of the fuel vaporization effect on the metering accuracy under high flow rate conditions is not monitored in a timely manner in the metering calibration of fuel dispensers. Under high flow rate conditions, due to factors such as friction in the pipeline, pressure changes, and local temperature rise, the fuel may partially vaporize, forming bubbles that mix into the metering system. However, most of the existing technologies only measure based on macro parameters such as fuel flow rate, pressure, and temperature, and do not fully consider this vaporization effect and its influence on metering accuracy, which will cause bubbles to enter the metering system, thereby affecting the accuracy of flow measurement, which may not only cause metering errors, but also affect the overall performance of the dispenser, and then cause the metering results to be inconsistent with the actual amount of fuel delivered.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a measurement and calibration method and system for a fuel dispenser to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: A method for measuring and verifying a fuel dispenser comprises the following steps: S1: collect the flow state parameters and fluid boundary layer characteristic data of the fuel in real time to generate the initial data set; S2: By performing micro-scale friction loss analysis on the initial data set, the impact of the friction effect in the contact area between the inner wall of the pipeline and the fuel on the local heat accumulation is evaluated; by monitoring the shear stress change, the dynamic changes of the local shear stress during the fuel flow process are analyzed in real time, and the areas with abnormal shear stress growth are marked; S3: Based on the influence of friction effect between the inner wall of the pipeline and the fuel in contact area on local heat accumulation and the marking of areas with abnormal shear stress growth, determine the high-risk areas for gasification; S4: For areas with high risk of gasification: by real-time monitoring the rate of change of van der Waals force between fuel molecules under high flow rate conditions, the sudden change process of van der Waals force is analyzed to evaluate the degree of sudden change of interaction force between fuel molecules; by monitoring the change of energy dissipation rate of turbulent vortices during fuel flow, the mutation point of energy dissipation rate is identified to evaluate the probability of gasification in local areas of fuel; S5: Through a comprehensive analysis of the degree of drastic changes in the interaction force between fuel molecules and the probability of local fuel vaporization, the influence of the vaporization effect in the high-risk area of ​​vaporization on the fuel metering accuracy is evaluated.

[0007] In a preferred embodiment, the flow state parameters of the fuel and the fluid boundary layer characteristic data are collected in real time to generate an initial data set, specifically: The flow state parameters of the fuel include the flow rate, pressure, temperature and density of the fuel; generating a flow state subset according to the obtained flow rate, pressure, temperature and density of the fuel; Acquire the boundary layer characteristic data of the contact area between the fuel and the pipeline in real time and generate a boundary layer subset; the boundary layer characteristic data includes velocity gradient, shear stress and boundary layer thickness; The flow state subset and boundary layer subset are combined to generate the initial data set.

[0008] In a preferred embodiment, micro-scale friction loss analysis is performed on the initial data set to evaluate the influence of the friction effect of the contact area between the inner wall of the pipeline and the fuel on the local heat accumulation, specifically: Extracting boundary layer characteristic data of the contact area between fuel and inner wall of pipeline from the initial data set; According to the boundary layer characteristic data and flow state parameters, the friction loss formula of the contact area between the inner wall of the pipeline and the fuel is established; Based on the friction loss formula, the friction effect between the inner wall of the pipeline and the fuel in contact with the fuel is analyzed to determine the impact on energy conversion at different flow rates and pressures, and the local heat accumulation caused by friction is evaluated; The energy generated by the friction effect is converted into local heat accumulation, and the high friction area is identified by combining the boundary layer data to derive the heat distribution of the friction effect in different areas; By analyzing the friction effect and heat distribution in each area, the influence value of friction effect on local heat accumulation in the pipeline is obtained.

[0009] In a preferred embodiment, the dynamic changes of local shear stress during fuel flow are analyzed in real time by monitoring shear stress changes, and the areas with abnormal shear stress growth are marked, specifically: Extract the real-time shear stress values ​​of the fuel at different positions in the pipeline from the initial data set to obtain the shear stress data of each position during the fuel flow process; Based on the extracted shear stress data, a dynamic model of shear stress variation with time and position is established; The shear stress variation model is analyzed, the shear stress variation rate at each position is calculated, and the shear stress variation rate over time is obtained; The shear stress change rate is compared with the abnormal growth threshold, and the area where the shear stress change rate is greater than the abnormal growth threshold is marked to identify the shear stress abnormal growth area.

[0010] In a preferred embodiment, based on the influence of the friction effect of the contact area between the inner wall of the pipeline and the fuel on the local heat accumulation and the marking of the area with abnormal shear stress growth, the high-risk area of ​​gasification is determined, specifically: Set the threshold corresponding to the influence value of friction effect on local heat accumulation in the pipeline; The area where the influence value of the friction effect on the local heat accumulation of the pipeline is greater than the corresponding threshold is marked as a heat accumulation potential area; The area corresponding to the union of the heat accumulation potential risk area and the shear stress abnormal growth area is marked as a gasification high risk area.

[0011] In a preferred embodiment, the drastic change process of the van der Waals force is analyzed by real-time monitoring of the change rate of the van der Waals force between fuel molecules under high flow rate conditions, and the degree of drastic change of the interaction force between fuel molecules is evaluated, specifically: When the fuel is at a high flow rate, the van der Waals force data between fuel molecules in the high-risk area of ​​gasification is obtained in real time; A time-varying model of van der Waals force is constructed based on the extracted van der Waals force data. The time-varying model of van der Waals force is used to describe the dynamic characteristics of the interaction force between fuel molecules. The model of the van der Waals force changing with time is: ;in, Indicates time The van der Waals force, Indicates time The distance between the fuel molecules, is the material constant; Based on the model of van der Waals force changing with time, the rate of change of van der Waals force is calculated; the rate of change of van der Waals force is: ;in, Indicates time The rate of change of the van der Waals force, It indicates the rate of change of distance between fuel molecules over time; Based on the degree to which the rate of change of the van der Waals force deviates from normal, the van der Waals force change deviation index is calculated to evaluate the degree of drastic change in the interaction force between fuel molecules under high flow rate conditions.

[0012] In a preferred embodiment, by monitoring the change in energy dissipation rate of turbulent vortices during the fuel flow process, the mutation point of the energy dissipation rate is identified to evaluate the probability of gasification in a local area of ​​the fuel, specifically: Real-time extraction of vortex energy dissipation rate data of fuel in high-risk areas of vaporization; Multi-scale wavelet transform is performed on the vortex energy dissipation rate data to decompose the energy variation characteristics at different time scales; Based on the energy variation characteristics at different time scales, the fractal analysis method is used to identify the complex self-similar structure in the vortex energy dissipation rate: Calculate the fractal dimension: ;in, is the fractal dimension, is the scale used to cover the energy dissipation rate signal The minimum number of covers under Indicates the coverage scale; Using the Bayesian change point detection algorithm, we can identify the mutation points of energy dissipation rate in the time series and mark the local mutation areas: The formula for Bayesian change point detection is: ;in, Indicates that the observed data Then change the position The posterior probability of Indicates the position of a given change point The likelihood of the posterior observation data, is the prior probability, It is observed data The marginal likelihood of A data series representing the rate of vortex energy dissipation, represents the location of the change point in the energy dissipation rate time series; The identified mutation points of energy dissipation rate and complex self-similar structures are combined to evaluate the probability of gasification in local areas.

[0013] In a preferred embodiment, the influence of the gasification effect in the gasification high risk area on the fuel metering accuracy is evaluated by comprehensively analyzing the degree of sudden change in the interaction force between fuel molecules and the probability of occurrence of gasification in the local area of ​​fuel, specifically: The van der Waals force variation deviation index and the probability of gasification occurrence are normalized; The normalized van der Waals force variation deviation index and gasification occurrence probability are assigned weight coefficients respectively, and the gasification metering accuracy influence coefficient is calculated. Compare the gasification metering accuracy impact coefficient with the gasification metering accuracy impact threshold: When the gasification metering accuracy influence coefficient is greater than the gasification metering accuracy influence threshold, it is determined that the gasification effect has a greater impact on the fuel metering accuracy; When the gasification metering accuracy influence coefficient is less than or equal to the gasification metering accuracy influence threshold, it is determined that the gasification effect has a normal influence on the fuel metering accuracy.

[0014] On the other hand, the present invention provides a metrological verification system for a fuel dispenser, comprising a data acquisition module, a friction analysis module, a shear stress analysis module, a gasification risk determination module, a van der Waals force monitoring module, an energy dissipation analysis module, and a gasification effect evaluation module; Data acquisition module: collects fuel flow state parameters and fluid boundary layer characteristic data in real time to generate initial data sets; Friction Analysis Module: This module conducts micro-scale friction loss analysis on the initial data set to evaluate the impact of friction effects on local heat accumulation in the contact area between the inner wall of the pipeline and the fuel. Shear stress analysis module: Through shear stress change monitoring, the dynamic changes of local shear stress during fuel flow are analyzed in real time, and the areas with abnormal shear stress growth are marked; Gasification risk determination module: Based on the influence of the friction effect of the contact area between the inner wall of the pipeline and the fuel on the local heat accumulation and the marking of the area with abnormal shear stress growth, the high-risk area of ​​gasification is determined; Van der Waals force monitoring module: For high-risk areas of gasification, the drastic change process of the van der Waals force is analyzed by real-time monitoring of the change rate of the van der Waals force between fuel molecules under high flow rate conditions, and the degree of drastic change of the interaction force between fuel molecules is evaluated; Energy dissipation analysis module: For areas with high risk of gasification, the module monitors the change in energy dissipation rate of turbulent vortices during fuel flow and identifies the mutation point of energy dissipation rate to assess the probability of gasification in local areas of fuel; Gasification effect assessment module: Through comprehensive analysis of the degree of drastic changes in the interaction force between fuel molecules and the probability of fuel gasification in local areas, the impact of gasification effect in high-risk areas on fuel metering accuracy is assessed.

[0015] The technical effects and advantages of the measurement and verification method and system for a fuel dispenser of the present invention are as follows: 1. The present invention generates an initial data set by real-time collection of fuel flow state parameters and fluid boundary layer characteristic data, providing accurate basic data for subsequent analysis. On this basis, micro-scale friction loss analysis is used to evaluate in detail the impact of the friction effect of the contact area between the inner wall of the pipeline and the fuel on local heat accumulation. This analysis can effectively identify the risk of local temperature rise caused by the friction effect. In addition, by monitoring the dynamic changes of shear stress during the flow of fuel and marking the areas where the shear stress increases abnormally, possible gasification risk points can be discovered in time. Based on the comprehensive analysis of friction effect and shear stress, the present invention can more accurately determine high-risk areas for gasification and improve the accuracy of identifying local abnormal phenomena during the flow of fuel.

[0016] 2. By monitoring the rate of change of the van der Waals force between fuel molecules under high flow rate conditions, the drastic change process of the intermolecular interaction force is accurately analyzed, and combined with the change in the energy dissipation rate of the turbulent vortex, the mutation point of the energy dissipation rate is identified. Through these two monitoring methods, the probability of gasification in the local area can be evaluated in detail. On the basis of a comprehensive analysis of high-risk areas for gasification, the present invention combines the degree of drastic changes in the intermolecular interaction force and the probability of gasification to evaluate the impact of the gasification phenomenon on the accuracy of fuel metering. This multi-dimensional analysis method helps to ensure the high accuracy of fuel metering, avoid metering errors caused by gasification, and provide a basis for optimizing the metering accuracy of the fuel dispenser. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of a measurement and verification method for a fuel dispenser according to the present invention; Figure 2 The present invention is a schematic structural diagram of a measurement and calibration system for a fuel dispenser. DETAILED DESCRIPTION

[0018] 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.

[0019] Example 1 Figure 1 The present invention provides a method for measuring and verifying a fuel dispenser, which comprises the following steps: S1: Collect the flow state parameters and fluid boundary layer characteristic data of the fuel in real time to generate an initial data set.

[0020] S2: By performing micro-scale friction loss analysis on the initial data set, the impact of the friction effect in the contact area between the inner wall of the pipeline and the fuel on the local heat accumulation is evaluated; by monitoring the shear stress change, the dynamic changes of the local shear stress during the fuel flow process are analyzed in real time, and the areas with abnormal shear stress growth are marked.

[0021] S3: Based on the influence of the friction effect between the inner wall of the pipeline and the contact area with the fuel on the local heat accumulation and the marking of the area with abnormal shear stress growth, the high-risk area of ​​gasification is determined.

[0022] S4: For areas with high risk of vaporization: By real-time monitoring the rate of change of van der Waals force between fuel molecules under high flow rate conditions, the sudden change process of van der Waals force is analyzed to evaluate the degree of sudden change of interaction force between fuel molecules; by monitoring the change of energy dissipation rate of turbulent vortices during fuel flow, the mutation point of energy dissipation rate is identified to evaluate the probability of occurrence of vaporization in local areas of fuel.

[0023] S5: Through a comprehensive analysis of the degree of drastic changes in the interaction force between fuel molecules and the probability of local fuel vaporization, the influence of the vaporization effect in the high-risk area of ​​vaporization on the fuel metering accuracy is evaluated.

[0024] The flow state parameters and fluid boundary layer characteristic data of the fuel are collected in real time to generate the initial data set, specifically: The flow state parameters of the fuel include the flow rate, pressure, temperature and density of the fuel: The flow rate, pressure and temperature data of the fuel are obtained in real time through flow sensors, pressure sensors and temperature sensors; density sensing equipment is used to obtain the density changes of the fuel in the flow process in real time. Based on turbine or ultrasonic flow meters, the flow rate of fuel can be accurately measured, and the sensor acquisition frequency is set to at least once per second to ensure real-time feedback of the flow rate.

[0025] Pressure sensors are deployed at multiple key locations in the pipeline to detect the pressure changes of fuel under different flow rate conditions in real time, and the sensor accuracy reaches ±0.1%.

[0026] The temperature of the fuel is monitored in real time by temperature sensors installed in different areas of the fuel flow in the pipeline. The temperature data is collected once a second with an accuracy of ±0.05°C.

[0027] The density sensor detects the density change of fuel in the flow process in real time. The density sensor senses the slight fluctuation of fuel density through the vibration tube principle, with an accuracy of ±0.0005 g / cm³. The density data is collected synchronously with the flow rate, pressure and temperature data, and the timestamp is aligned with other parameters.

[0028] Generate a flow state subset based on the obtained fuel flow rate, pressure, temperature and density: The flow rate, pressure, temperature and density data obtained by flow sensors, pressure sensors, temperature sensors and density sensing devices are integrated to generate a flow state subset. The subset is stored in the form of a multidimensional data matrix, with each row representing the flow rate, pressure, temperature and density value of the fuel at a certain moment, ensuring that complete real-time fuel state data is provided for subsequent analysis.

[0029] Acquire the boundary layer characteristic data of the contact area between the fuel and the pipeline in real time and generate the boundary layer subset: Boundary layer characteristic data include velocity gradient, shear stress and boundary layer thickness, which reflect the flow behavior of fluid when it approaches the solid boundary.

[0030] The boundary layer monitoring equipment is used to obtain the boundary layer characteristic data of the contact area between the fuel and the pipeline in real time. The boundary layer monitoring equipment uses laser Doppler velocimetry technology to monitor the velocity gradient, shear stress and thickness changes in the fuel boundary layer to ensure that detailed characteristic data of the contact area between the fuel and the inner wall of the pipeline is captured. The data is collected once a second to reflect the interaction between the fuel flow state and the inner wall of the pipeline in real time.

[0031] Combine the flow state subset and the boundary layer subset to generate the initial data set for subsequent analysis: The flow state subset and the boundary layer subset are integrated to generate an initial data set. The initial data set contains the flow rate, pressure, temperature, density and boundary layer characteristics of the fuel. All data are synchronized through a unified timestamp for subsequent gasification effect analysis. The initial data set is stored in the system database in a matrix form to ensure data consistency and real-time performance.

[0032] By performing micro-scale friction loss analysis on the initial data set, the influence of friction effect on local heat accumulation in the contact area between the inner wall of the pipeline and the fuel is evaluated, specifically: Extract the boundary layer characteristics data of the contact area between the fuel and the inner wall of the pipe from the initial data set: From the initial data set, the boundary layer characteristic data of the contact area between the fuel and the inner wall of the pipe are extracted, including key parameters such as velocity gradient, shear stress and boundary layer thickness. These data are used to describe the flow behavior of the fuel in the boundary layer, especially the velocity change and shear stress in the contact area. The velocity gradient represents the change of the fuel flow velocity with the distance from the pipe wall, the shear stress represents the force on the fuel when it flows, and the boundary layer thickness reflects the distance required for the fluid velocity to approach the maximum value.

[0033] According to the boundary layer characteristic data and flow state parameters, the friction loss formula of the contact area between the inner wall of the pipeline and the fuel is established: A formula is established to quantify the friction effect in the contact area between the inner wall of the pipeline and the fuel. The friction loss formula is: ;in, Indicates friction loss power, in watts (W), used to indicate the energy loss caused by the friction between the fuel and the inner wall of the pipeline; It indicates the shear stress in the contact area between the fuel and the inner wall of the pipe, in Pascal (Pa), which is used to describe the friction between the inner wall of the pipe and the fuel; It represents the effective area where the inner wall of the pipe is in contact with the fuel, measured in square meters (m²), and is used to describe the size of the area where the friction effect occurs.

[0034] According to the friction loss formula, the friction effect between the inner wall of the pipeline and the fuel in contact with the fuel is analyzed to determine the impact on energy conversion at different flow rates and pressures, and to evaluate the local heat accumulation caused by friction: Through the determined friction loss formula, combined with different flow rates and pressure conditions, the influence of the friction effect of the contact area between the inner wall of the pipeline and the fuel on energy conversion is analyzed. In this process, the shear stress changes with the flow rate and pressure, which directly affects the energy loss caused by the friction effect.

[0035] Among them, the energy caused by the friction effect is converted into local heat accumulation, which is expressed by the following formula: ;in, It represents the heat accumulation caused by friction effect, and its unit is joule (J), which is used to quantify the increase of heat energy caused by friction effect; Represents time in seconds (s), used to describe the duration of the friction effect.

[0036] By converting the energy caused by friction effect into local heat accumulation, the local heat accumulation caused by friction effect at different flow rates and pressures of fuel can be evaluated.

[0037] The energy generated by the friction effect is converted into local heat accumulation, and the high friction area is identified by combining the boundary layer data, and the heat distribution of the friction effect in different areas is derived: High friction areas are usually areas with large velocity gradients and strong shear stresses, and the heat accumulation in these areas will be significantly higher than other parts.

[0038] The heat distribution in each area is derived using the following formula: ;in, It represents the local heat accumulation at different locations on the inner wall of the pipe, and the unit is joule (J), which describes the heat generated at each location; Represents the friction loss power at each position, in watts (W), which quantifies the energy loss due to friction effect at that position; and It is used to represent the coordinates of a specific position on the inner wall of the pipe. Represents the coordinates of the inner wall of the pipe along the length direction, Represents the coordinate of the inner wall of the pipe perpendicular to the flow direction.

[0039] By analyzing the friction effect and heat distribution in each area, the influence of friction effect on local heat accumulation in the pipeline is obtained: The influence of friction effect on local heat accumulation in pipeline is calculated as follows: ;in, is the influence of friction effect on local heat accumulation in the pipeline, represents the total heat accumulation at all locations, Represents the total contact area of ​​the inner wall of the pipe.

[0040] The greater the impact of the friction effect on the local heat accumulation in the pipeline, the more obvious the local temperature of the fuel will rise, and the stronger the gasification effect of the fuel will be. The increase in local heat accumulation will accelerate the gasification tendency of the fuel, especially under high flow rate and high pressure conditions, which will make it easier for the fuel to produce bubbles and affect the metering accuracy.

[0041] By monitoring the shear stress changes, the dynamic changes of local shear stress during fuel flow are analyzed in real time, and the areas with abnormal shear stress growth are marked, specifically: Extract the real-time shear stress values ​​of the fuel at different locations in the pipeline from the initial data set to obtain the shear stress data at each location during the fuel flow process: During the fuel flow process, shear stress is the result of the combined effect of fuel velocity change and viscosity. First, the real-time shear stress data of the fuel at different positions is extracted from the initial data set. The magnitude of shear stress is usually determined by the fuel viscosity and velocity gradient, and is calculated by combining the flow state parameters of the fuel (such as flow velocity, pressure and density) with the boundary layer characteristic data.

[0042] Based on the extracted shear stress data, a dynamic model of shear stress changing with time and position is established to describe the real-time change of shear stress: Shear stress at time and location The change formula is: ;in, Indicates time Location The shear stress at Indicates time and location The fuel flow rate at Indicates location The velocity gradient at (indicates the change of fuel flow rate with the distance perpendicular to the inner wall of the pipe), Indicates the dynamic viscosity of the fuel. is the partial derivative, represents the radial position in the pipe, Indicates the distance perpendicular to the inner wall of the pipe (the vertical distance between the fuel and the inner wall of the pipe).

[0043] The shear stress change model is analyzed, the shear stress change rate at each position is calculated, and the change rate of shear stress over time is obtained: Through the dynamic model of shear stress, the shear stress change rate at each location can be calculated and the rate of change of shear stress over time can be quantified.

[0044] The formula for the rate of change of shear stress is: ;in, It represents the rate of change of shear stress with time.

[0045] By calculating the shear stress change rate at each location, the dynamic change of shear stress over time can be determined, making it easier to identify areas of abnormal growth.

[0046] Compare the shear stress change rate with the abnormal growth threshold, mark the area where the shear stress change rate is greater than the abnormal growth threshold, and identify the area of ​​abnormal shear stress growth: After the shear stress change rate is obtained, it is compared with the preset abnormal growth threshold. The threshold is set by experimental data and fuel flow characteristics, indicating the critical point of abnormal growth. The preset abnormal growth threshold can be derived from the actual data of flow velocity and shear stress.

[0047] when When , the position is marked as the area of ​​abnormal shear stress growth.

[0048] in, is the abnormal growth threshold.

[0049] Based on the influence of the friction effect of the contact area between the inner wall of the pipeline and the fuel on the local heat accumulation and the marking of the area with abnormal shear stress growth, the high-risk areas of gasification are determined, specifically: Set the threshold value corresponding to the impact value of the friction effect on the local heat accumulation of the pipeline. The threshold value corresponding to the impact value of the friction effect on the local heat accumulation of the pipeline is determined based on experimental and theoretical analysis. Combined with parameters such as fuel flow rate, pressure, temperature, and the thermal conductivity characteristics of different fuel types and pipeline materials, numerical simulation is used to compare with actual operation data to derive the critical point where local heat accumulation leads to vaporization. When setting the threshold, ensure that under high flow rate conditions, the heat accumulation caused by the friction effect does not exceed this value, so as to avoid the triggering of vaporization effect due to temperature rise in local areas.

[0050] The area where the influence of friction effect on local heat accumulation in the pipeline is greater than the corresponding threshold is marked as a heat accumulation potential area.

[0051] The area corresponding to the union of the heat accumulation potential risk area and the shear stress abnormal growth area is marked as a gasification high risk area.

[0052] By combining the two major risk factors of local heat accumulation caused by friction effect and abnormal growth of shear stress, a dual judgment mechanism is formed to improve the accuracy of identifying high-risk areas for gasification. By setting the union area as the high-risk area for gasification, the combined effects of fluid dynamics and heat accumulation are comprehensively evaluated, and the prediction ability of fuel gasification effect under complex working conditions is enhanced.

[0053] By real-time monitoring the rate of change of van der Waals force between fuel molecules under high flow rate conditions, the dramatic change process of van der Waals force is analyzed and the degree of dramatic change of interaction force between fuel molecules is evaluated, specifically: When the fuel is at a high flow rate, the van der Waals force data between fuel molecules in the high-risk area of ​​gasification is obtained in real time: Molecular force sensing equipment is used to monitor high-risk areas of gasification in real time to obtain real-time data on the van der Waals forces between fuel molecules. The intermolecular van der Waals forces are used to describe the weak interaction forces between fuel molecules, which will change under high flow conditions.

[0054] The specific van der Waals force formula is: ;in, represents the van der Waals force, is a material constant (depending on the molecular properties of the fuel), Represents the distance between fuel molecules, is the fuel temperature, is the flow rate of fuel.

[0055] Based on the extracted van der Waals force data, a time-varying model of van der Waals force is constructed. The time-varying model of van der Waals force is used to describe the dynamic characteristics of the interaction force between fuel molecules: Based on the real-time van der Waals force data obtained, a model of van der Waals force variation over time is constructed. This model is used to describe the variation of the interaction force between fuel molecules under high flow conditions. The variation of van der Waals force not only depends on temperature and flow rate, but also changes dynamically over time, especially when the fuel flows violently.

[0056] The model of the van der Waals force changing with time can be expressed as: ;in, Indicates time The van der Waals force, Indicates time The distance between fuel molecules.

[0057] Based on the model of van der Waals force changing with time, calculate the rate of change of van der Waals force: By differentiating the model of the van der Waals force changing with time, we can get the rate of change of the van der Waals force in a short period of time. The rate of change of the van der Waals force can be expressed as: ;in, Indicates time The rate of change of the van der Waals force, Indicates the rate at which the distance between fuel molecules changes with time.

[0058] Based on the degree to which the rate of change of the van der Waals force deviates from the normal, the degree of drastic change in the interaction force between fuel molecules under high flow rate conditions is evaluated: The upper limit of the normal range of the van der Waals force change rate and the lower limit of the normal range of the van der Waals force change rate are set.

[0059] Calculate the van der Waals force variation deviation index, the expression is: ;in, represents the exponential deviation of the van der Waals force change, and They are respectively the lower limit of the normal range of the van der Waals force change rate and the upper limit of the normal range of the van der Waals force change rate.

[0060] The larger the van der Waals force variation deviation index is, the greater the degree of drastic change in the interaction force between fuel molecules under high flow rate conditions. The van der Waals force variation deviation index quantifies the degree of deviation of the van der Waals force variation rate from the normal range. The larger the van der Waals force variation deviation index is, the more significant the deviation of the van der Waals force variation rate is from the normal variation range. This deviation indicates that the interaction force between fuel molecules has undergone a drastic change, which is usually related to a drastic change in the fuel flow environment, such as a sharp change in the distance between molecules under high flow rate conditions or a significant change in the force state of fuel molecules.

[0061] in, and It is derived from experimental or historical data of the van der Waals force change rate when the fuel is under normal working conditions (i.e., there is no violent interaction or risk of gasification). Through a large number of experiments, the van der Waals force change rate of the fuel under different flow rates, pressures and temperatures is measured, and the statistical change rate range is used as a reference to determine the upper and lower limits of the normal working range.

[0062] For areas with high risk of gasification: By monitoring the change in energy dissipation rate of turbulent vortices during fuel flow, the mutation point of energy dissipation rate is identified to assess the probability of gasification in local areas of fuel, specifically: Real-time extraction of vortex energy dissipation rate data of fuel in high-risk areas of vaporization: The vortex energy dissipation rate of the fuel in the high-risk area of ​​gasification is obtained in real time through turbulence monitoring equipment. The vortex energy dissipation rate refers to the rate at which energy is transferred from large-scale flow to small-scale flow during the turbulent process of the fuel and finally dissipated through viscosity. These vortex energy dissipation rates can reflect the local vortex intensity and local turbulence properties of the fuel in the pipeline.

[0063] The data of vortex energy dissipation rate can be expressed as a function of time and space: ;in, Indicates time and spatial location The vortex energy dissipation rate at Indicates the density of the fuel. Indicates flow rate In spatial position Top edge The velocity gradient in the direction, It is used to describe the change of spatial position in a specific direction during the fuel flow process. Represents the coordinates of different locations in the pipeline.

[0064] The vortex energy dissipation rate data is subjected to multi-scale wavelet transform to decompose the energy change characteristics at different time scales: Wavelet transform is a method that can decompose a signal into different time scales, which helps to capture the energy changes in different time ranges.

[0065] The wavelet transform formula is expressed as: ;in, Representation scale and displacement The wavelet transform results of vortex energy dissipation rate under ; It is a wavelet function, which is used to decompose the signal and help capture changes at different time scales; Represents the scale parameter in wavelet transform, which determines the transform resolution; Represents the displacement parameter, which determines the time point at which the signal is decomposed.

[0066] By performing wavelet transform on the vortex energy dissipation rate data, it can be decomposed into signals of different time scales, thereby effectively capturing short-term rapid fluctuations and changes in long-term trends.

[0067] Based on the energy variation characteristics at different time scales, the fractal analysis method is used to identify the complex self-similar structure in the vortex energy dissipation rate: Based on the multi-time scale features decomposed by wavelet transform, fractal analysis is applied to conduct an in-depth analysis of the vortex energy dissipation rate. Fractal analysis is used to identify complex self-similar structures in vortices, which reflect the similarities of vortices at different scales, thus revealing the irregularity and complexity of the energy dissipation process.

[0068] Calculate the fractal dimension, the calculation formula is: ;in, is the fractal dimension, is the scale used to cover the energy dissipation rate signal The minimum number of covers under Indicates the coverage scale.

[0069] Fractal analysis can identify self-similar features in vortices, and measure their complexity through fractal dimensions. The larger the fractal dimension, the more complex the complex self-similar structure in the vortex energy dissipation rate. The larger the fractal dimension, the more details and irregularities the self-similar structure in the vortex energy dissipation rate shows at different scales, reflecting that the turbulent behavior in the vortex region is more complex and unstable. In general, complex vortex structures are associated with stronger local energy dissipation and may also mean a higher risk of vaporization.

[0070] Using the Bayesian change point detection algorithm, we can identify the mutation points of energy dissipation rate in the time series and mark the local mutation areas: Bayesian change point detection is a probability-based algorithm that can effectively identify the moment when a feature in a time series changes significantly. The algorithm determines whether a time point is a change point based on the difference between historical data and current data.

[0071] The formula for Bayesian change point detection can be expressed as: ;in, Indicates that the observed data Then change the position The posterior probability of Indicates the position of a given change point The likelihood of the post-observation data; is the prior probability, indicating the change point location Likelihood of occurrence; It is observed data The marginal likelihood of A data series representing the rate of vortex energy dissipation; Represents the location of the change point in the energy dissipation rate time series.

[0072] Through Bayesian change point detection, we can identify the mutation points of the energy dissipation rate over time and mark the specific time and location where the mutation occurs.

[0073] The identified mutation points of energy dissipation rate and complex self-similar structures are combined to evaluate the probability of gasification in local areas: The sudden change of vortex energy dissipation rate often indicates a violent energy release in the local area, and the complexity of the fractal structure further indicates that the vortex structure in the area has nonlinear characteristics. By combining the identified mutation points of energy dissipation rate and the complex self-similar structure, the risk of gasification in the local area can be effectively assessed.

[0074] Calculate the probability of gasification occurrence, the expression is: ;in, represents the probability of gasification in a local area, is the vortex energy dissipation rate.

[0075] The greater the probability of gasification, the greater the probability of gasification in the local area of ​​the fuel: it means that the physical conditions in the local area of ​​the fuel (such as the sudden change in the vortex energy dissipation rate, the existence of complex self-similar structures, etc.) are more conducive to the occurrence of gasification. High energy dissipation means that there is strong turbulence and temperature rise in the local area, which may trigger the phase change process of the fuel, causing the fuel to change from liquid to gas. Therefore, the greater the probability of gasification, the higher the risk of gasification in the local area, and the greater the possibility of gasification.

[0076] Among them, in the calculation formula of the probability of gasification occurrence, is a multivariable function that combines the vortex energy dissipation rate, fractal dimension, and the change point position obtained by Bayesian change point detection to calculate the probability of gasification in the local area of ​​the fuel. Specifically, Represents the complex relationship between various parameters and their impact on the probability of gasification. This multivariable function can be constructed based on experimental data, physical models, or machine learning algorithms, and its specific form depends on the specific definition of the relationship between these variables.

[0077] Through a comprehensive analysis of the degree of drastic changes in the interaction force between fuel molecules and the probability of local fuel gasification, the impact of the gasification effect in the high-risk area of ​​gasification on the fuel metering accuracy is evaluated, specifically: The van der Waals force variation deviation index and the probability of gasification occurrence are normalized to ensure that the values ​​of different dimensions can be weighted and summed.

[0078] The van der Waals force variation deviation index and the probability of gasification occurrence after normalization are assigned weight coefficients respectively, and the gasification metering accuracy influence coefficient is calculated, which can be specifically achieved by the following formula: ;in, is the gasification metering accuracy influence coefficient, and are the normalized van der Waals force variation deviation index and the probability of gasification occurrence, and are the van der Waals force variation deviation index and the weight coefficient of the gasification occurrence probability, and and Both are greater than 0.

[0079] The larger the gasification metering accuracy influence coefficient is, the more serious the impact of the gasification effect in the high-risk area on the fuel metering accuracy is. The gasification metering accuracy influence coefficient combines the van der Waals force change deviation index and the gasification occurrence probability, reflecting the gasification risk at the molecular level and under macro-turbulent conditions in the local area. When the gasification metering accuracy influence coefficient increases, it means that the gasification effect in the local area may cause changes in fuel volume, increased measurement errors, and fluid dynamics instability, thereby significantly interfering with the metering accuracy of the fuel dispenser.

[0080] Compare the gasification metering accuracy impact coefficient with the gasification metering accuracy impact threshold: When the gasification metering accuracy influence coefficient is greater than the gasification metering accuracy influence threshold, it is determined that the gasification effect has a greater impact on the fuel metering accuracy, indicating that the gasification effect has a greater impact on the fuel metering accuracy. At this time, the physical properties of the fuel and the local flow conditions lead to the intensification of the gasification phenomenon, and the metering system may be significantly disturbed. To optimize the metering verification, the following measures can be taken: Reduce fuel flow rate: Reduce the fuel flow rate to reduce the intensity of turbulence and vortex generation. The fuel flow rate and vaporization tendency can be reduced by adjusting the pump speed or pipeline design of the fuel dispenser.

[0081] Regulate fuel temperature: Keep it within a low and stable range. Temperature control equipment, cooling equipment outside the pipeline, or thermal insulation materials can be used to reduce the temperature of the fuel and reduce the occurrence of vaporization.

[0082] When the gasification metering accuracy influence coefficient is less than or equal to the gasification metering accuracy influence threshold, it is determined that the gasification effect has a normal impact on the fuel metering accuracy, indicating that the impact of the gasification effect on the fuel metering accuracy is within an acceptable range and the performance of the metering system can be maintained normally. At this time, the gasification effect is relatively weak.

[0083] Among them, the setting of the threshold for the impact of gasification metering accuracy is based on comprehensive consideration of experimental data, historical measurement records and theoretical analysis. By analyzing the impact of different gasification effects on fuel metering accuracy, an acceptable error range is determined as a benchmark. During the experiment, the van der Waals force change deviation index and the probability of gasification are measured, and combined with actual usage, the relationship between metering error and gasification effect is found. When setting the threshold, it should be ensured that within this threshold range, the impact of gasification on fuel metering accuracy is within a controllable range. If the threshold is exceeded, corresponding optimization measures need to be taken.

[0084] Example 2 The difference between Example 2 of the present invention and Example 1 is that this example introduces a measurement and calibration system for a fuel dispenser.

[0085] Figure 2 A structural schematic diagram of a metrological verification system for a fuel dispenser of the present invention is given, which includes a data acquisition module, a friction analysis module, a shear stress analysis module, a gasification risk determination module, a van der Waals force monitoring module, an energy dissipation analysis module and a gasification effect evaluation module.

[0086] Data acquisition module: collects fuel flow state parameters and fluid boundary layer characteristic data in real time to generate initial data sets.

[0087] Friction Analysis Module: This module conducts micro-scale friction loss analysis on the initial data set to evaluate the impact of friction effects on local heat accumulation in the contact area between the inner wall of the pipeline and the fuel.

[0088] Shear stress analysis module: Through shear stress change monitoring, the dynamic changes of local shear stress during fuel flow are analyzed in real time, and areas with abnormal shear stress growth are marked.

[0089] Gasification risk determination module: Determine the high-risk areas for gasification based on the influence of the friction effect between the inner wall of the pipeline and the contact area with the fuel on the local heat accumulation and the marking of the area with abnormal shear stress growth.

[0090] Van der Waals force monitoring module: For high-risk areas of gasification, the rate of change of van der Waals force between fuel molecules under high flow rate conditions is monitored in real time to analyze the dramatic change process of van der Waals force and evaluate the degree of dramatic change of interaction force between fuel molecules.

[0091] Energy dissipation analysis module: For areas with high risk of gasification, the energy dissipation rate of turbulent vortices during fuel flow is monitored and the mutation point of energy dissipation rate is identified to evaluate the probability of gasification in local areas of fuel.

[0092] Gasification effect assessment module: Through comprehensive analysis of the degree of drastic changes in the interaction force between fuel molecules and the probability of fuel gasification in local areas, the impact of gasification effect in high-risk areas on fuel metering accuracy is assessed.

[0093] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0094] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or may be transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium may be a solid-state hard disk.

[0095] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0096] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0097] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0098] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0099] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0100] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0101] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0102] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for measuring and verifying a fuel dispenser, characterized in that: The steps include: S1: collect the flow state parameters and fluid boundary layer characteristic data of the fuel in real time to generate the initial data set; S2: By performing micro-scale friction loss analysis on the initial data set, the impact of the friction effect in the contact area between the inner wall of the pipeline and the fuel on the local heat accumulation is evaluated; by monitoring the shear stress change, the dynamic changes of the local shear stress during the fuel flow process are analyzed in real time, and the areas with abnormal shear stress growth are marked; S3: Based on the influence of friction effect between the inner wall of the pipeline and the fuel in contact area on local heat accumulation and the marking of areas with abnormal shear stress growth, determine the high-risk areas for gasification; S4: For areas with high risk of gasification: by real-time monitoring the rate of change of van der Waals force between fuel molecules under high flow rate conditions, the sudden change process of van der Waals force is analyzed to evaluate the degree of sudden change of interaction force between fuel molecules; by monitoring the change of energy dissipation rate of turbulent vortices during fuel flow, the mutation point of energy dissipation rate is identified to evaluate the probability of gasification in local areas of fuel; S5: Through a comprehensive analysis of the degree of drastic changes in the interaction force between fuel molecules and the probability of local fuel vaporization, the influence of the vaporization effect in the high-risk area of ​​vaporization on the fuel metering accuracy is evaluated.

2. A method for measuring and verifying a fuel dispenser according to claim 1, characterized in that: The flow state parameters and fluid boundary layer characteristic data of the fuel are collected in real time to generate the initial data set, specifically: The flow state parameters of the fuel include the flow rate, pressure, temperature and density of the fuel; generating a flow state subset according to the obtained flow rate, pressure, temperature and density of the fuel; Acquire the boundary layer characteristic data of the contact area between the fuel and the pipeline in real time and generate a boundary layer subset; the boundary layer characteristic data includes velocity gradient, shear stress and boundary layer thickness; The flow state subset and boundary layer subset are combined to generate the initial data set.

3. A method for measuring and verifying a fuel dispenser according to claim 2, characterized in that: By performing micro-scale friction loss analysis on the initial data set, the influence of friction effect on local heat accumulation in the contact area between the inner wall of the pipeline and the fuel is evaluated, specifically: Extracting boundary layer characteristic data of the contact area between fuel and inner wall of pipeline from the initial data set; According to the boundary layer characteristic data and flow state parameters, the friction loss formula of the contact area between the inner wall of the pipeline and the fuel is established; Based on the friction loss formula, the friction effect between the inner wall of the pipeline and the fuel in contact with the fuel is analyzed to determine the impact on energy conversion at different flow rates and pressures, and the local heat accumulation caused by friction is evaluated; The energy generated by the friction effect is converted into local heat accumulation, and the high friction area is identified by combining the boundary layer data to derive the heat distribution of the friction effect in different areas; By analyzing the friction effect and heat distribution in each area, the influence value of friction effect on local heat accumulation in the pipeline is obtained.

4. A method for measuring and verifying a fuel dispenser according to claim 3, characterized in that: By monitoring the shear stress changes, the dynamic changes of local shear stress during fuel flow are analyzed in real time, and the areas with abnormal shear stress growth are marked, specifically: Extract the real-time shear stress values ​​of the fuel at different positions in the pipeline from the initial data set to obtain the shear stress data of each position during the fuel flow process; Based on the extracted shear stress data, a dynamic model of shear stress variation with time and position is established; The shear stress variation model is analyzed, the shear stress variation rate at each position is calculated, and the variation rate of the shear stress over time is obtained; The shear stress change rate is compared with the abnormal growth threshold, and the area where the shear stress change rate is greater than the abnormal growth threshold is marked to identify the shear stress abnormal growth area.

5. A method for measuring and verifying a fuel dispenser according to claim 4, characterized in that: Based on the influence of the friction effect of the contact area between the inner wall of the pipeline and the fuel on the local heat accumulation and the marking of the area with abnormal shear stress growth, the high-risk areas of gasification are determined, specifically: Set the threshold corresponding to the influence value of friction effect on local heat accumulation in pipeline; The area where the influence of friction effect on the local heat accumulation of the pipeline is greater than the corresponding threshold is marked as a heat accumulation potential area; The area corresponding to the union of the heat accumulation potential risk area and the shear stress abnormal growth area is marked as a gasification high risk area.

6. A method for measuring and verifying a fuel dispenser according to claim 5, characterized in that: By real-time monitoring the rate of change of van der Waals force between fuel molecules under high flow rate conditions, the dramatic change process of van der Waals force is analyzed and the degree of dramatic change of interaction force between fuel molecules is evaluated, specifically: When the fuel is at a high flow rate, the van der Waals force data between fuel molecules in the high-risk area of ​​gasification is obtained in real time; A time-varying model of van der Waals force is constructed based on the extracted van der Waals force data. The time-varying model of van der Waals force is used to describe the dynamic characteristics of the interaction force between fuel molecules. The model of the van der Waals force changing with time is: ;in, Indicates time The van der Waals force, Indicates time The distance between the fuel molecules, is the material constant; Based on the model of van der Waals force changing with time, the rate of change of van der Waals force is calculated; the rate of change of van der Waals force is: ;in, Indicates time The rate of change of the van der Waals force, Indicates the rate of change of the distance between fuel molecules over time; Based on the degree to which the rate of change of the van der Waals force deviates from normal, the van der Waals force change deviation index is calculated to evaluate the degree of drastic change in the interaction force between fuel molecules under high flow rate conditions.

7. A method for measuring and verifying a fuel dispenser according to claim 6, characterized in that: By monitoring the change in energy dissipation rate of turbulent vortices during fuel flow, the mutation point of energy dissipation rate is identified to evaluate the probability of local fuel gasification, specifically: Real-time extraction of vortex energy dissipation rate data of fuel in high-risk areas of vaporization; Multi-scale wavelet transform is performed on the vortex energy dissipation rate data to decompose the energy variation characteristics at different time scales; Based on the energy variation characteristics at different time scales, the fractal analysis method is used to identify the complex self-similar structure in the vortex energy dissipation rate: Calculate the fractal dimension: ;in, is the fractal dimension, is the scale used to cover the energy dissipation rate signal The minimum number of covers under Indicates the coverage scale; Using the Bayesian change point detection algorithm, we can identify the mutation points of energy dissipation rate in the time series and mark the local mutation areas: The formula for Bayesian change point detection is: ;in, Indicates that the observed data Then change the position The posterior probability of Indicates the position of a given change point The likelihood of the posterior observation data, is the prior probability, It is observed data The marginal likelihood of A data series representing the rate of vortex energy dissipation, represents the location of the change point in the energy dissipation rate time series; The identified mutation points of energy dissipation rate and complex self-similar structures are combined to evaluate the probability of gasification in local areas.

8. A method for measuring and verifying a fuel dispenser according to claim 7, characterized in that: Through a comprehensive analysis of the degree of drastic changes in the interaction force between fuel molecules and the probability of local fuel gasification, the impact of the gasification effect in the high-risk area of ​​gasification on the fuel metering accuracy is evaluated, specifically: The van der Waals force variation deviation index and the probability of gasification occurrence are normalized; The normalized van der Waals force variation deviation index and gasification occurrence probability are assigned weight coefficients respectively, and the gasification metering accuracy influence coefficient is calculated. Compare the gasification metering accuracy impact coefficient with the gasification metering accuracy impact threshold: When the gasification metering accuracy influence coefficient is greater than the gasification metering accuracy influence threshold, it is determined that the gasification effect has a greater impact on the fuel metering accuracy; When the gasification metering accuracy influence coefficient is less than or equal to the gasification metering accuracy influence threshold, it is determined that the gasification effect has a normal influence on the fuel metering accuracy.

9. A measurement and verification system for a fuel dispenser, used to implement a measurement and verification method for a fuel dispenser as claimed in any one of claims 1 to 8, characterized in that: It includes data acquisition module, friction analysis module, shear stress analysis module, gasification risk determination module, van der Waals force monitoring module, energy dissipation analysis module and gasification effect evaluation module; Data acquisition module: collects fuel flow state parameters and fluid boundary layer characteristic data in real time to generate initial data sets; Friction Analysis Module: This module conducts micro-scale friction loss analysis on the initial data set to evaluate the impact of friction effects on local heat accumulation in the contact area between the inner wall of the pipeline and the fuel. Shear stress analysis module: Through shear stress change monitoring, the dynamic changes of local shear stress during fuel flow are analyzed in real time, and the areas with abnormal shear stress growth are marked; Gasification risk determination module: Based on the influence of the friction effect of the contact area between the inner wall of the pipeline and the fuel on the local heat accumulation and the marking of the area with abnormal shear stress growth, the high-risk area of ​​gasification is determined; Van der Waals force monitoring module: For high-risk areas of gasification, the drastic change process of the van der Waals force is analyzed by real-time monitoring of the change rate of the van der Waals force between fuel molecules under high flow rate conditions, and the degree of drastic change of the interaction force between fuel molecules is evaluated; Energy dissipation analysis module: For areas with high risk of gasification, the module monitors the change in energy dissipation rate of turbulent vortices during fuel flow and identifies the mutation point of energy dissipation rate to assess the probability of gasification in local areas of fuel; Gasification effect assessment module: Through comprehensive analysis of the degree of drastic changes in the interaction force between fuel molecules and the probability of fuel gasification in local areas, the impact of gasification effect in high-risk areas on fuel metering accuracy is assessed.

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