A method and system for flow metering of an ultrasonic water meter

Abstract

The present application relates to flow metering technical field, specifically be a kind of flow metering method and system of ultrasonic water meter, method includes using excitation transducer and signal simulation module to the actual signal and simulation signal of ultrasonic water meter are analyzed to obtain signal effective time difference and the effective signal set of ultrasonic water meter;According to ultrasonic wave propagation expression and effective signal set obtains after correction ultrasonic wave propagation velocity, further analyzes attenuation influence coefficient and constructs flow prediction model;According to flow velocity distribution compensation factor and effective signal set obtains flow velocity distribution compensation analysis model, obtains flow analysis model based on flow velocity distribution to analysis model deduction;Combined with flow prediction model and flow analysis model to establish full working condition flow analysis model, the present application full working condition flow analysis model comprehensively considers ultrasonic wave propagation characteristic, signal attenuation, flow velocity distribution and so on Factor, can adapt to different measurement working condition and environmental condition, realizes flow accurate calculation.

Description

Technical Field

[0001] This invention relates to the field of flow measurement technology, specifically to a flow measurement method and system for an ultrasonic water meter. Background Technology

[0002] Ultrasonic flow meters are a commonly used non-contact flow meter that has been widely applied in many fields such as industry, agriculture, and daily life. They determine the flow rate and volume of fluid by measuring the propagation time and speed of ultrasonic waves. However, in actual use, they face the problem that the measurement accuracy is difficult to meet the actual needs.

[0003] Traditional ultrasonic water meter flow measurement methods calculate flow rate by directly measuring the time difference of ultrasonic wave propagation upstream and downstream. However, the flight time of ultrasonic waves is extremely small and is easily affected by changes in flow rate and fluctuations in environmental conditions. Changes in ambient temperature and fluctuations in fluid velocity can cause deviations in flight time, resulting in calculation errors and adversely affecting measurement accuracy, ultimately leading to inaccurate measurement results.

[0004] Meanwhile, existing flow calculation methods fail to fully consider the combined effects of numerous factors, including fluid medium characteristics, pipe conditions, fluid velocity, and temperature, on the calculated flow results. In actual measurements, the density, viscosity, and other properties of different fluid media vary significantly, all affecting ultrasonic wave propagation. Pipe material, inner diameter, and roughness also alter the propagation path and velocity of ultrasonic waves. Fluid velocity distribution and temperature variations further interfere with ultrasonic wave propagation characteristics. Existing calculation methods neglect these crucial factors, resulting in significant deviations between measured results and actual flow rates, thus compromising the accuracy of flow measurement.

[0005] Therefore, it is necessary to optimize the existing flow calculation method. On the one hand, the detection information of ultrasonic water meters needs to be adjusted and optimized. On the other hand, it is necessary to comprehensively consider the effects of factors such as fluid characteristics, pipeline conditions, fluid velocity, and temperature on flow calculation, which will help to calculate pipeline flow more accurately and reflect the actual flow conditions in the pipeline. Summary of the Invention

[0006] To address the shortcomings of existing methods and meet the needs of practical applications, and in order to adjust and optimize the detection information of ultrasonic water meters, this paper comprehensively and deeply considers the combined influence of factors such as fluid characteristics, pipeline conditions, fluid velocity distribution, and temperature changes on the flow calculation results. Based on the above influencing factors, the existing flow calculation method is optimized, which is conducive to more accurate calculation of pipeline flow and ensures that the flow value can truly and accurately reflect the actual flow conditions in the pipeline. On one hand, this invention provides a flow measurement method for ultrasonic water meters. The method includes the following steps: analyzing the actual and simulated signals of the ultrasonic water meter using an excitation transducer and a signal simulation module to obtain the effective time difference of the signals; obtaining the effective signal set of the ultrasonic water meter based on the effective time difference of the signals; obtaining the corrected ultrasonic propagation velocity according to the ultrasonic propagation expression and the effective signal set; analyzing the attenuation influence coefficient according to the corrected ultrasonic propagation velocity; constructing a flow prediction model based on the attenuation influence coefficient; obtaining a flow velocity distribution compensation analysis model according to the flow velocity distribution compensation factor and the effective signal set; deriving the flow velocity distribution compensation analysis model to obtain a flow analysis model based on the flow velocity distribution; establishing a full-condition flow analysis model by combining the flow prediction model and the flow analysis model; and achieving accurate flow calculation through the full-condition flow analysis model.

[0007] This invention combines a flow prediction model and a flow analysis model to establish a full-condition flow analysis model. It can comprehensively consider the influence of various factors such as signal quality, propagation speed, attenuation effect, and flow velocity distribution on flow measurement. It can achieve accurate flow calculation under various complex operating conditions, improve the performance and reliability of ultrasonic water meters, and meet the monitoring and calculation needs of different application scenarios.

[0008] Optionally, the step of analyzing the actual and simulated signals of the ultrasonic water meter using the excitation transducer and signal simulation module to obtain the effective time difference of the signal includes: generating the actual signal of the ultrasonic water meter through the excitation transducer; generating the simulated signal of the ultrasonic water meter using the signal simulation module; extracting and analyzing the actual signal and the simulated signal, and obtaining the actual signal extraction result and the simulated signal extraction result. This invention extracts and analyzes the actual and simulated signals, and by comparing the relevant extraction results, it can identify the differences between the actual signal and the ideal simulated signal, which helps to further understand the changes in the actual signal during propagation.

[0009] Optionally, the step of analyzing the actual and simulated signals of the ultrasonic water meter using an excitation transducer and a signal simulation module to obtain the effective time difference of the signal, and obtaining the effective signal set of the ultrasonic water meter based on the effective time difference of the signal, includes: randomly selecting three adjacent information sampling points, setting an offset based on the three adjacent information sampling points; analyzing the cross-correlation value of the simulated signal window and the actual signal window under the offset according to the offset, the actual signal extraction result, and the simulated signal extraction result; obtaining a preliminary time difference based on the cross-correlation value; introducing an interpolation method, and adjusting the preliminary time difference in combination with the interpolation method and the cross-correlation value to obtain the effective time difference of the ultrasonic water meter signal; and obtaining the effective signal set of the ultrasonic water meter based on the effective time difference of the signal.

[0010] This invention comprehensively considers multiple characteristics and factors of the signal, and has strong anti-interference ability and robustness. Even if there is a certain amount of noise and interference in the signal, or if the shape and characteristics of the signal change to a certain extent, the effective time difference of the signal can still be accurately calculated and an effective signal set can be obtained, which helps to ensure the accurate measurement and stable operation of the ultrasonic water meter.

[0011] Optionally, obtaining the corrected ultrasonic propagation velocity based on the ultrasonic propagation expression and the effective signal set includes: obtaining still water temperature characteristic data based on the effective signal set; performing fitting analysis on the still water temperature characteristic data to obtain a temperature-sound speed mapping relationship expression; analyzing the ultrasonic propagation expression, the temperature-sound speed mapping relationship expression, and the effective signal set to obtain the ultrasonic propagation velocity at different water temperatures; correcting the different water temperatures using interpolation to obtain the corrected different water temperatures; and adjusting the ultrasonic propagation velocity at the different water temperatures according to the corrected different water temperatures to obtain the corrected ultrasonic propagation velocity.

[0012] This invention can obtain the ultrasonic propagation speed at the current water temperature in real time based on the effective signal set, and correct it by interpolation, so that the water meter can adapt to the measurement needs under different water temperature environments, which helps to ensure the accuracy of the measurement results.

[0013] Optionally, the step of analyzing the attenuation influence coefficient based on the corrected ultrasonic propagation velocity includes: introducing fluid dynamic viscosity, fluid density, and thermal conductivity characteristic parameters; combining the corrected ultrasonic propagation velocity, the fluid dynamic viscosity, the fluid density, and the thermal conductivity characteristic parameters to obtain an ultrasonic attenuation coefficient; and obtaining the attenuation influence coefficient between flow rate and attenuation based on the ultrasonic attenuation coefficient. This invention can effectively reduce the interference of environmental factors on measurement results and accurately capture the influence of different parameter changes on ultrasonic attenuation.

[0014] Optionally, the step of obtaining the corrected ultrasonic propagation velocity based on the ultrasonic propagation expression and the effective signal set, analyzing the attenuation influence coefficient based on the corrected ultrasonic propagation velocity, and constructing a flow prediction model based on the attenuation influence coefficient includes: introducing a basic flow analysis formula based on time-of-flight difference; obtaining a basic flow analysis result based on time-of-flight difference through the basic flow analysis formula; and constructing a flow prediction model by combining the basic flow analysis result and the attenuation influence coefficient.

[0015] This invention introduces a basic flow analysis formula based on time-of-flight difference and combines it with a modified sound velocity and attenuation influence coefficient to construct a flow prediction model. This enables the model to adapt to the measurement requirements of different fluids and allows the prediction model to effectively predict flow.

[0016] Optionally, the step of obtaining a velocity distribution compensation analysis model based on the velocity distribution compensation factor and the effective signal set, and deriving the velocity distribution compensation analysis model to obtain a flow analysis model based on velocity distribution includes: establishing a velocity compensation factor distribution function based on the Reynolds coefficient distribution of the fluid; obtaining a velocity distribution compensation factor using the velocity compensation factor distribution function; constructing a velocity distribution compensation analysis model based on the velocity distribution compensation factor and the effective signal set; introducing a flow analysis model based on average velocity; and deriving the flow analysis model based on velocity distribution by combining the flow analysis model based on average velocity and the velocity distribution compensation analysis model.

[0017] This invention introduces the fluid Reynolds coefficient, which can automatically adjust the velocity compensation factor distribution function according to the characteristics of different fluids, thereby adapting to the measurement needs of different fluids and accurately calculating the velocity distribution compensation factor.

[0018] Optionally, the step of establishing a full-condition flow analysis model by combining the flow prediction model and the flow analysis model, and achieving accurate flow calculation through the full-condition flow analysis model, includes: analyzing the velocity distribution compensation factor and the effective signal set to obtain a Reynolds number-related compensation factor; and fitting the influence parameter fitting coefficients based on the ultrasonic frequency, fluid composition parameters, and the attenuation influence coefficient.

[0019] This invention obtains the fitting coefficient of the influence parameter by fitting the ultrasonic frequency, fluid composition parameters and attenuation influence coefficient, which can more accurately quantify the attenuation of ultrasonic waves when they propagate in the fluid, and is beneficial to improving the accuracy of flow calculation results.

[0020] Optionally, the step of establishing a full-condition flow analysis model by combining the flow prediction model and the flow analysis model, and achieving accurate flow calculation through the full-condition flow analysis model, includes: establishing a full-condition flow analysis model by combining the flow prediction model, the flow analysis model, the Reynolds number-related compensation factor, and the fitting coefficient of the influencing parameters; and calculating the flow based on the full-condition flow analysis model and the effective signal set to achieve accurate analysis and effective monitoring of the ultrasonic water meter flow results.

[0021] The Reynolds number-related compensation factor of this invention can dynamically adjust the velocity distribution according to different Reynolds numbers, enabling the full-condition flow analysis model to adapt to various flow states and ensuring that the flow analysis model can perform flow measurement under different operating conditions.

[0022] Secondly, to efficiently execute the ultrasonic water meter flow measurement method provided by this invention, this invention also provides an ultrasonic water meter flow measurement system, including a processor, an input device, an output device, and a memory. The processor, input device, output device, and memory are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to call the program instructions to execute the ultrasonic water meter flow measurement method as described in the first aspect of this invention. The ultrasonic water meter flow measurement system of this invention has a compact structure and stable performance, and can stably execute the ultrasonic water meter flow measurement method provided by this invention, thus improving the overall applicability and practical application capability of this invention. Attached Figure Description

[0023] Figure 1 This is a flowchart of the flow measurement method of the ultrasonic water meter of the present invention;

[0024] Figure 2 This is a schematic diagram of the laminar and turbulent fluid states in the flow measurement method of the ultrasonic water meter of the present invention.

[0025] Figure 3 This is a structural diagram of the flow metering system of the ultrasonic water meter of the present invention. Detailed Implementation

[0026] See Figure 1 To comprehensively consider the combined influence of factors such as fluid characteristics, pipeline conditions, fluid velocity distribution, and temperature changes on the flow rate calculation results, and to further achieve accurate pipeline flow rate calculation and effectively analyze the actual flow conditions within the pipeline, this invention provides a flow rate measurement method for an ultrasonic water meter. The flow rate measurement method for the ultrasonic water meter includes the following steps:

[0027] S1. Analyze the actual and simulated signals of the ultrasonic water meter using an excitation transducer and a signal simulation module to obtain the effective time difference of the signal. Based on the effective time difference of the signal, obtain the effective signal set of the ultrasonic water meter. The specific implementation steps and contents are as follows.

[0028] First, the actual and simulated signals of the ultrasonic water meter are analyzed using an excitation transducer and a signal simulation module to obtain the effective time difference of the signal.

[0029] Ultrasonic water meters have advantages such as high precision, no pressure loss, and strong stability, and are widely used in various fluid flow measurement. Among them, signal generation and acquisition are the key links for accurate measurement by ultrasonic water meters, which directly affect the accuracy of subsequent signal processing and flow calculation, and at the same time provide information for flow measurement and metering.

[0030] In this embodiment, the ultrasonic water meter's transmitting transducer employs a segmented pulse excitation method, consisting of 20 positive-phase pulses and 6 negative-phase pulses, which can generate ultrasonic signals with specific frequencies and phases that meet metering requirements. Simultaneously, a simulation module generates corresponding simulated signals. To ensure the comparability of the simulated signals with the actual signals, the sampling rate is set to 8MHz and the signal length to 240 points, ensuring that the actual and simulated signals have the same scale in time and amplitude, facilitating subsequent comparative analysis and processing.

[0031] The first step is to generate the actual signal and the simulated signal.

[0032] The actual ultrasonic signal of the ultrasonic water meter is generated by exciting the transducer.

[0033] While the excitation transducer generates the actual signal, the simulation module is triggered to generate the corresponding simulation signal.

[0034] The sampling parameters of the generated actual signal and the simulated signal are consistent with those of the actual signal, that is, the sampling rate is 8MHz and the signal length is 240 points.

[0035] After transmitting an ultrasonic signal, a preset waiting time is required. The purpose of setting the waiting time is to ensure that the ultrasonic wave propagates fully in the fluid, while avoiding direct interference with the transmitted signal. The length of the waiting time needs to take into account factors such as the propagation distance of the ultrasonic wave in the fluid, the flow velocity range, and the performance of the transducer.

[0036] After the preset waiting time is completed, the receiver transducer begins to collect the actual ultrasonic signal that is propagated back. During the collection process, an 8MHz sampling rate and a signal length of 240 points are used to ensure the integrity and accuracy of the collected signal. In this embodiment, the actual signal collected mainly includes various information such as flow velocity, temperature, and fluid properties encountered by the ultrasonic wave during its propagation in the fluid.

[0037] The transmitter transducer employs a segmented pulse excitation method, consisting of a specific number of positive and negative phase pulses, capable of generating ultrasonic signals with specific frequencies and phases that meet metrological requirements. Simultaneously, a simulation module generates corresponding simulated signals, standardizing the sampling rate and signal length to ensure that the actual and simulated signals have the same scale in time and amplitude, laying the foundation for subsequent comparative analysis.

[0038] The second step is to extract and analyze the signal.

[0039] To facilitate subsequent signal processing and analysis, the envelope of the acquired actual signal is extracted. The envelope curve reflects the amplitude variation characteristics of the ultrasonic signal, removes high-frequency oscillation components from the signal, and highlights the main signal features. In this embodiment, the Hilbert transform method is used to extract the signal envelope curve. As a linear time-invariant filter, the Hilbert transform can convert the real signal into an analytic signal, and the magnitude of the analytic signal is the envelope of the original signal.

[0040] For the synchronously generated simulation signal, the Hilbert transform is also used to extract its envelope curve so that it can be compared and analyzed with the envelope of the actual signal. By extracting and analyzing the actual signal and the simulation signal, the extraction results of the actual signal and the simulation signal can be obtained.

[0041] Step 3: Randomly select three adjacent information sampling points and set the offset based on the three adjacent information sampling points.

[0042] In this embodiment, the simulation signal is set as The actual signal is , Let be the signal length, where Next, three adjacent sampling points are randomly selected as the calculation window, with a window size of 3, and an offset is set based on the above three adjacent information sampling points. .

[0043] Step 4: Analyze the cross-correlation values ​​of the simulation signal window and the actual signal window under the offset based on the offset, the actual signal extraction results and the simulation signal extraction results.

[0044] For offset Its value range can be adjusted and determined according to the signal length and actual needs. Further calculation of the cross-correlation value between the simulated signal window and the actual signal window is performed, and the following relationship is satisfied:

[0045]

[0046] in, This indicates that the simulated signal window and the actual signal window are offset by an amount of... Cross-correlation value at time, Indicates the number of sampling points. The first one in the simulation signal window The value of each sampling point, Indicates the first signal in the actual signal window The value of each sampling point.

[0047] Among them, when When the signal length exceeds the specified range, zero padding or other boundary handling methods can be used.

[0048] Step 5: Obtain the preliminary time difference based on the above cross-correlation values.

[0049] Traverse offset Find the maximum value among the cross-correlation values. corresponding offset The above preliminary estimates of the time difference satisfy the following relationship:

[0050]

[0051] in, Indicates the initial time difference. This represents the maximum value among the cross-correlation values. This indicates the sampling rate.

[0052] Step 6: Introduce interpolation method, and adjust the initial time difference by combining interpolation method and cross-correlation value to obtain the effective time difference of the ultrasonic water meter signal.

[0053] To improve the accuracy of time difference measurement, the embodiment uses an interpolation method to determine the precise location of the maximum value of the cross-correlation function and sets the cross-correlation value. , , The cross-correlation function at the sampling points are respectively , , The value at that location, and It is the maximum of the three values.

[0054] And the cross-correlation values ​​of the above sampling points , , The following relationship must be satisfied:

[0055]

[0056] in and The parameters of the interpolation function satisfy the following relationships:

[0057]

[0058] Furthermore, based on the aforementioned cross-correlation values, parameter information, and correlation expressions, we derive the quadratic function expression of the interpolation function, which satisfies the following relationship:

[0059]

[0060] in, This represents the calculation result of the cross-correlation interpolation function. This represents the first parameter of the interpolation function. Indicates the independent variable. This indicates the offset between the simulated signal window and the actual signal window. This represents the second parameter of the interpolation function. express The cross-correlation value at the location.

[0061] Based on the above cross-correlation interpolation function, the maximum value position of the interpolation function is determined. The embodiment describes the cross-correlation interpolation function... Take the derivative and set it to 0:

[0062]

[0063] Based on this, the position of the maximum value after interpolation can be obtained. To further compare with the original offset In combination, let the offset corresponding to the position of the maximum value after interpolation be... .

[0064] A more precise time difference, or effective time difference, satisfies the following relationship:

[0065]

[0066] in, Indicates the effective time difference. This indicates the offset between the simulated signal window and the actual signal window. This represents the first parameter of the interpolation function. This represents the second parameter of the interpolation function. This indicates the sampling rate.

[0067] By using the optimized steps and expressions described above, the effective time difference in ultrasonic water meter signal processing can be calculated more accurately, providing a reliable basis for subsequent flow measurement and calculation.

[0068] Then, the effective signal set of the ultrasonic water meter is obtained based on the effective time difference of the signal. After calculating the effective time difference in ultrasonic water meter signal processing according to the above optimized steps and formulas, the effective signal set of the ultrasonic water meter can be obtained based on the effective time difference, providing a technical support information foundation for the flow measurement and metering of ultrasonic water meters.

[0069] In this embodiment, the actual and simulated signals are first extracted to highlight the main characteristics of the signals; then, an offset is set to calculate the cross-correlation value; next, the preliminary time difference corresponding to the maximum value of the cross-correlation value is found; finally, an interpolation method is introduced to adjust the preliminary time difference to obtain a more accurate effective time difference. An accurate effective time difference provides precise time parameters for flow measurement, which helps to improve the accuracy of subsequent flow measurement results.

[0070] Furthermore, by obtaining the effective signal set of the ultrasonic water meter based on the effective time difference of the signal, an information basis is provided for the flow measurement and metering of the ultrasonic water meter, which helps to improve the accuracy and reliability of flow measurement. Through signal processing and calculation, it can adapt to different measurement environments and provide reliable data information under different operating conditions.

[0071] S2. Based on the ultrasonic propagation expression and the effective signal set, the corrected ultrasonic propagation speed is obtained. The attenuation influence coefficient is analyzed based on the corrected ultrasonic propagation speed. A flow prediction model is then constructed based on the attenuation influence coefficient. The specific implementation steps and content are as follows:

[0072] In the flow measurement of ultrasonic water meters, in order to improve the measurement accuracy, it is necessary to correct the ultrasonic propagation speed based on the ultrasonic propagation characteristics, ultrasonic propagation expression and effective signal set, so as to obtain the corrected ultrasonic propagation speed.

[0073] The first step is to acquire and fit static water temperature characteristic data based on the effective signal set.

[0074] During data acquisition, the water temperature was adjusted from a high temperature (50°C) to a low temperature (5°C) in uniform steps (1°C). After reaching a stable state at each temperature point, the propagation speed of ultrasonic waves in the fluid was measured using a sound velocity measuring instrument, and the corresponding temperature value was accurately recorded. In this embodiment, temperature (T) is used as the abscissa, and sound velocity (T) is used as the ordinate. Using the vertical axis as the ordinate, the recorded temperature and sound speed values ​​are plotted as a scatter plot of still water temperature characteristics, visually presenting the relationship between temperature and sound speed.

[0075] The second step involves fitting and analyzing the still water temperature characteristic data to obtain the temperature-sound speed mapping expression.

[0076] The scatter plot above was fitted using the least squares method to establish a mathematical mapping expression between temperature and sound speed:

[0077]

[0078] in, It is a polynomial function, and therefore the relational expression also satisfies the following relationship:

[0079]

[0080] in, This represents the speed of sound at different temperatures. They represent the fitting coefficients, This represents temperature. The coefficients can be determined through fitting calculations. The specific values ​​are calculated, and a temperature-velocity of sound mapping table is generated. The mapping table must compensate for the velocity of sound error within 0.1%, that is, when the temperature measurement error is ±0.1℃, the velocity of sound error calculated by the mapping table should be controlled within ±0.1%.

[0081] Step 3: Analyze the ultrasonic propagation expression, the temperature-velocity mapping expression, and the effective signal set to obtain the ultrasonic propagation speed at different water temperatures.

[0082] During the measurement process, the ultrasonic water meter calculates the flow rate by measuring the time of flight (ToF) of the ultrasonic waves upstream and downstream. In this embodiment, the propagation speed of the ultrasonic waves in the fluid is set to be... The upstream and downstream transmission distances are both The upstream flight time is Downstream flight time is .

[0083] Based on the fundamental formula for ultrasonic wave propagation, namely the ultrasonic wave propagation expression, the relationship between propagation speed, time, and distance can be analyzed, and the following relationship is satisfied:

[0084]

[0085] The upstream propagation speed can then be obtained separately:

[0086] Upstream propagation speed Downstream propagation speed .

[0087] In this embodiment, it is assumed that the water temperature is uniformly distributed, and the average of the upstream and downstream propagation velocities is taken as the ultrasonic propagation velocity at the current water temperature.

[0088]

[0089] Based on this, the ultrasonic propagation speed at different water temperatures can be obtained from the ultrasonic propagation expression and the temperature-velocity mapping expression.

[0090] The fourth step involves using interpolation to correct for different water temperatures and obtaining the corrected water temperatures.

[0091] Based on the temperature-velocity of sound mapping table above, water temperature is corrected using interpolation. If two adjacent temperature points in the mapping table... and The corresponding speeds of sound are respectively and and Then the corrected water temperature can be calculated using linear interpolation. The relationships are analyzed as follows:

[0092]

[0093] in, This indicates the corrected water temperature. Represents a temperature point, This indicates the speed at which ultrasound propagates at the current water temperature. express The speed of ultrasonic wave propagation at water temperature express The speed of ultrasonic wave propagation at water temperature This indicates another temperature point.

[0094] Based on the corrected water temperature Find the corresponding sound velocity value in the temperature-sound velocity mapping table, or use interpolation again to obtain the corrected ultrasonic wave propagation speed. .

[0095] The fifth step involves adjusting the ultrasonic wave propagation speed at different water temperatures based on the corrected speed, thus obtaining the corrected ultrasonic wave propagation speed. (Corrected ultrasonic wave propagation speed) It helps to achieve dynamic calibration of flow rate, reduce measurement errors caused by factors such as water temperature changes, and improve the accuracy and reliability of flow measurement results of ultrasonic water meters.

[0096] In this embodiment, based on the ultrasonic propagation expression and the effective signal set, through data analysis, fitting, calculation and correction, the corrected ultrasonic propagation speed is finally obtained, which provides strong support for the accurate flow measurement of ultrasonic water meters in the future.

[0097] Then, the attenuation influence coefficient is analyzed based on the corrected ultrasonic wave propagation speed.

[0098] The first step is to introduce characteristic parameters of fluid dynamic viscosity, fluid density, and thermal conductivity based on the effective signal set.

[0099] Fluid dynamic viscosity This indicates that the dynamic viscosity of a fluid reflects its ability to resist shear deformation and has a significant impact on the propagation and attenuation of ultrasound waves in the fluid.

[0100] fluid density with This indicates that fluid density is the mass per unit volume of a fluid, and it is closely related to the energy transfer and attenuation during the propagation of ultrasound.

[0101] Thermal conductivity characteristic parameters include thermal conductivity Specific heat capacity at constant volume and specific heat capacity at constant pressure Thermal conductivity reflects the fluid's ability to conduct heat, while specific heat capacity at constant volume and specific heat capacity at constant pressure are related to the energy changes of the fluid during heat exchange.

[0102] The above parameters collectively affect the attenuation of ultrasound waves in fluids due to thermal effects. By introducing key fluid parameters that affect ultrasound attenuation based on the effective signal set, a foundation of information is provided for subsequent analysis of the ultrasound attenuation coefficient.

[0103] The second step combines the corrected ultrasonic propagation velocity, fluid dynamic viscosity, fluid density, and thermal conductivity characteristics to obtain the ultrasonic attenuation coefficient, thereby quantifying the degree of attenuation of ultrasonic waves propagating in the fluid.

[0104] When using ultrasound for flow measurement, sound wave attenuation is a significant issue. As ultrasound propagates through liquids or gases, the viscosity and thermal conductivity of the fluid have a substantial impact. If the sound wave attenuation is too severe, the voltage value converted by the transducer will be insufficient to trigger the microcontroller unit for time acquisition, leading to errors in information acquisition and calculation.

[0105] The ultrasonic attenuation coefficient is obtained by combining the corrected ultrasonic propagation velocity, fluid dynamic viscosity, fluid density, and thermal conductivity characteristics. The ultrasonic attenuation coefficient is expressed as follows:

[0106]

[0107] in, Indicates the ultrasonic attenuation coefficient. Represents pi (π). Indicates fluid density, This indicates the corrected speed of ultrasonic wave propagation. Indicates the dynamic viscosity of a fluid. Indicates thermal conductivity, Indicates specific heat capacity at constant volume. This indicates the specific heat capacity at constant pressure.

[0108] The attenuation coefficient of ultrasound is directly proportional to the square of the vibration frequency; that is, the higher the frequency, the greater the attenuation coefficient, the faster the sound wave attenuates, and the shorter the propagation distance. Therefore, in high-frequency applications, such as small-diameter pipes, the attenuation coefficient of ultrasound needs to be calibrated experimentally to accurately quantify the impact of frequency on attenuation. For long-distance measurements, low-frequency ultrasound, such as… This effectively reduces signal loss caused by attenuation.

[0109] The third step is to further analyze the relationship between flow rate and attenuation based on the ultrasonic attenuation coefficient, determine the attenuation influence coefficient, and provide key parameters for building a flow prediction model.

[0110] ultrasonic attenuation coefficient It primarily affects signal strength and does not directly change the speed of sound or time of flight. To establish a clear relationship between flow rate and attenuation, an attenuation influence coefficient needs to be introduced. Based on the ultrasonic attenuation coefficient... The attenuation effect coefficient between matching flow rate and attenuation. Due to the ultrasonic attenuation coefficient With frequency It is proportional to the square of the value, therefore the ultrasonic attenuation coefficient can be further optimized and expressed as:

[0111]

[0112] in, This represents the attenuation effect coefficient between flow rate and attenuation. Indicates the ultrasonic attenuation coefficient. Indicates frequency.

[0113] Finally, based on the basic flow analysis formula and attenuation influence coefficient of time-of-flight difference, a flow prediction model is constructed, which helps to achieve accurate prediction of ultrasonic water meter flow.

[0114] The first step is to introduce the basic flow analysis formula based on flight time difference:

[0115]

[0116] in, This indicates the results of the basic traffic analysis. Indicates the upstream and downstream transmission distance. Indicates the upstream flight time. Indicates downstream flight time. This represents a constant related to the cross-sectional area of ​​the pipe and the properties of the fluid.

[0117] The aforementioned constant is related to the pipe cross-sectional area and fluid properties. Dynamically calibrating the sound velocity helps improve the accuracy of basic flow analysis results.

[0118] The second step is to obtain the basic flow analysis results based on the flight time difference using the basic flow analysis formula.

[0119] Based on actual measurements of upstream and downstream flight times and and the known upstream and downstream propagation distances and constant The above basic flow analysis formula can be used to calculate the flow rate. .

[0120] The third step is to construct a flow prediction model by combining the basic flow analysis results and the attenuation influence coefficient.

[0121] Based on the results of basic flow analysis and attenuation influence coefficient A flow prediction model is established. Since the attenuation effect coefficient can reduce the amplitude of the transducer's received signal, causing time measurement errors, the flow needs to be corrected using the signal-to-noise ratio or threshold trigger probability. The flow prediction model satisfies the following relationship:

[0122]

[0123] in, This represents the output of the traffic prediction model. This represents the results of basic flow analysis based on time-of-flight differences. This represents a constant related to the transducer sensitivity. Indicates the actual transmission distance. This represents the attenuation effect coefficient between flow rate and attenuation.

[0124] Separating the physical processes of flow calculation and attenuation correction avoids directly introducing the ultrasonic attenuation coefficient into the flow formula. The fuzzy effect; constants were calibrated experimentally. This makes the correction terms practically operable, thereby improving the engineering applicability of the flow prediction model and facilitating the subsequent practical application of ultrasonic water meters.

[0125] By sequentially completing the steps above—introducing key fluid parameters, calculating the ultrasonic attenuation coefficient, determining the attenuation influence coefficient, and constructing the flow prediction model—the accuracy of ultrasonic water meter flow measurement can be effectively improved.

[0126] In this embodiment, temperature correction and attenuation quantization can effectively eliminate environmental interference and reduce measurement errors. The establishment of the flow prediction model helps to realize dynamic flow analysis and comparative calibration based on time-of-flight difference, further improving the practicality and feasibility of the flow prediction model and providing technical support for subsequent flow calculation and prediction analysis.

[0127] S3. Based on the velocity distribution compensation factor and the effective signal set, a velocity distribution compensation analysis model is obtained. The velocity distribution compensation analysis model is then derived to obtain a flow analysis model based on velocity distribution. The specific implementation steps and contents are as follows:

[0128] In ultrasonic flow rate calculation, under ideal conditions, the flow velocity calculated based on flight time and pipe parameters is the average flow velocity of the fluid within the pipe. However, in practical applications, the fluid in the pipe does not flow uniformly forward. The calculated flow velocity is only the linear velocity in the direction of ultrasonic wave propagation. Directly using this as the average flow velocity will cause significant measurement errors. To address these issues, it is necessary to optimize the flow analysis model based on a velocity compensation factor to obtain a flow analysis model based on velocity distribution.

[0129] The first step is to establish the velocity compensation factor distribution function based on the distribution of the fluid Reynolds coefficient.

[0130] The state of a fluid is directly related to the Reynolds number. The calculation formula satisfies the following relationship:

[0131]

[0132] in, Represents the Reynolds coefficient of a fluid. Indicates fluid density, Indicates fluid velocity. Indicates the inner diameter of the pipe used to transport fluid. This indicates the dynamic viscosity of the fluid.

[0133] When the fluid density, viscosity coefficient, and pipe diameter remain constant, the Reynolds number depends only on the flow velocity. Fluids with different Reynolds numbers exhibit different motion states, and the corresponding velocity distributions also differ. Therefore, it is necessary to match different velocity distribution compensation factors and construct a velocity distribution compensation analysis model.

[0134] Furthermore, the embodiments include schematic diagrams of laminar and turbulent fluid states; please refer to the details below. Figure 2 , where a represents laminar flow and b represents turbulent flow.

[0135] Combination Figure 2 The information indicates that the laminar flow state is... At this point, the fluid in the pipe is in a laminar flow state, with the fluid flowing in layers that do not interfere with each other. The velocity distribution is parabolic, with the velocity being the highest at the center of the pipe and zero at the pipe wall. Let the velocity at the center of the pipe be... To obtain the average flow velocity of the fluid inside the pipe A compensation factor corresponding to the flow rate needs to be introduced. It satisfies the following conditions:

[0136]

[0137] Combination Figure 2 The information indicates that the turbulent state At this time, the fluid in the pipeline is in a state of turbulent motion, the fluid flow is chaotic, with a large number of vortices and pulsations, and the velocity distribution is relatively uniform. The compensation factor will change with... The compensation factor is obtained by increasing the value to approximately 1 and then fitting it experimentally. The calculation formula is as follows:

[0138]

[0139] in, express The compensation factor at that time.

[0140] Compensation factor The value of Reynolds Relatedly, the compensation factor values ​​at different Reynolds numbers can be determined experimentally, and a Reynolds number-compensation factor mapping table can be obtained. In the actual measurement process, the corresponding compensation factor can be obtained by looking up the table based on the calculated Reynolds number, which helps in the subsequent analysis of the average flow velocity of the fluid in the pipeline.

[0141] Furthermore, the distribution function of the compensation factor corresponding to the flow velocity, i.e., the flow velocity compensation factor distribution function, satisfies the following relationship:

[0142]

[0143] The second step is to obtain the velocity distribution compensation factor using the velocity compensation factor distribution function. Based on the velocity compensation factor distribution function, the Reynolds number is known. When considering the range of values, the velocity distribution compensation factor can be obtained according to the distribution function.

[0144] like , .

[0145] like , .

[0146] The third step is to construct a velocity distribution compensation analysis model based on the velocity distribution compensation factor and the effective signal set.

[0147] A velocity distribution compensation analysis model is constructed based on the above-mentioned velocity distribution compensation factors to calculate the average velocity of the fluid in the pipe. The calculation formula of the velocity distribution compensation analysis model is as follows:

[0148]

[0149] in, This indicates the average flow velocity of the fluid inside the pipe. and They represent The corresponding compensation factor at that time, The corresponding compensation factor at that time, Indicates fluid velocity.

[0150] The fourth step is to introduce a flow analysis model based on average flow velocity.

[0151] Obtain the average flow velocity of the fluid inside the pipe. A flow analysis model can then be constructed based on the average flow velocity. Flow rate The product of average flow velocity and pipe cross-sectional area is given. ,in, Indicates the cross-sectional area of ​​the pipe. Let be the inner diameter of the pipe transporting the fluid. Then, the flow analysis model satisfies the following relationship:

[0152]

[0153] The fifth step combines the flow analysis model based on average flow velocity and the flow velocity distribution compensation analysis model to derive and obtain the flow analysis model based on flow velocity distribution.

[0154] Substituting the velocity distribution compensation analysis model obtained in step three into the flow rate analysis model in step four for derivation and integration, we obtain a flow rate analysis model based on velocity distribution, which satisfies the following relationship:

[0155]

[0156] in, This represents a flow analysis model based on the average flow velocity of the fluid within the pipe. and They represent The corresponding compensation factor at that time, The corresponding compensation factor at that time, Indicates fluid velocity. Indicates the inner diameter of the pipe used to transport fluid. This represents the Reynolds coefficient of the fluid.

[0157] The above steps determine the velocity distribution compensation factor, construct and derive the flow analysis model of the velocity distribution, and provide a theoretical basis and calculation method for accurately measuring the fluid flow rate in the pipeline.

[0158] In the process of ultrasonic flow calculation, the flow velocity calculated based on flight time and pipe parameters is the average flow velocity of the fluid in the pipe. The calculated flow velocity is only the linear velocity of the fluid in the direction of ultrasonic wave propagation. In this embodiment, a flow velocity distribution compensation factor is introduced to take into account the influence of the fluid's motion state (laminar or turbulent) on the flow velocity distribution under different Reynolds numbers, making the measurement results closer to the true value.

[0159] The flow analysis model based on velocity distribution described above determines the corresponding velocity compensation factor distribution function for both laminar and turbulent flow states. It can accurately obtain the compensation factor based on the Reynolds number of the actual fluid, and thus accurately calculate the average velocity and flow rate. It can adapt to various complex fluid flow conditions and further ensure the accuracy of the calculation results.

[0160] S4. Combine the flow prediction model and the flow analysis model to establish a full-condition flow analysis model. Accurate flow calculation is achieved through the above full-condition flow analysis model. The specific implementation steps and contents are as follows:

[0161] In constructing a full-condition flow analysis model, factors such as temperature, attenuation, and velocity distribution compensation need to be comprehensively considered. To accurately describe the impact of these factors on flow, parameter information for establishing the full-condition flow analysis model is introduced based on a set of effective signals.

[0162] Temperature compensation function Since water temperature significantly affects the physical properties of fluids, and thus the flow rate measurement results, a temperature compensation function is defined. This function is determined based on the specific effect of water temperature on the physical properties of the fluid, and can correct for flow measurement errors caused by temperature changes.

[0163] Attenuation influence coefficient function Ultrasonic waves attenuate when propagating in fluids. The attenuation characteristics are closely related to the ultrasonic wave frequency and fluid composition. This study investigates the attenuation characteristics under different fluid compositions and ultrasonic wave frequencies, and establishes an attenuation influence coefficient. A mathematical model of relevant factors. Further definition of the function. ,in Indicates the frequency of the ultrasonic wave. The parameters representing fluid composition are obtained by fitting experimental data. The specific expression for this function is used to quantify the impact of attenuation on flow.

[0164] First, velocity distribution compensation factor analysis is required. Based on the velocity distribution compensation factor and the effective signal set, the velocity distribution of the fluid, the fluid motion state, and the Reynolds number can be analyzed. Directly related, fluids exhibit different motion states at different Reynolds numbers, and the corresponding velocity distributions also differ.

[0165] Based on the definition of Reynolds number-related compensation factors And satisfy the following relationship:

[0166]

[0167] in, This represents the compensation factor related to the Reynolds number. and They represent and Time-related compensation factors, which are based on laminar flow and turbulence The characteristics of velocity distribution under different conditions are determined. In laminar flow, the fluid flows in layers, and the layers do not interfere with each other, resulting in a parabolic velocity distribution. In turbulent flow, the fluid flow is chaotic, with numerous vortices and pulsations, and the velocity distribution is relatively uniform.

[0168] Then, a full-condition flow analysis model is established by combining the flow prediction model, the flow analysis model, the Reynolds number-related compensation factor, and the fitting coefficient of the influencing parameters.

[0169] Based on the above implementation details, the traffic prediction model satisfies the following relationship: ;

[0170] The flow analysis model based on velocity distribution satisfies the following relationship: ;

[0171] Based on the above parameters and prediction model, a full-condition flow analysis model was further constructed, which satisfies the following relationship:

[0172]

[0173] in, This indicates the flow forecast results based on all operating conditions. This represents the compensation factor related to the Reynolds number. Indicates the upstream and downstream transmission distance. Indicates the upstream flight time. Indicates downstream flight time. Indicates the temperature compensation coefficient. This represents a constant related to the transducer sensitivity. Indicates the actual transmission distance. Indicates the coefficients of the influencing parameters. This indicates the cross-sectional area of ​​the pipe.

[0174] The flow analysis model based on velocity distribution is mainly used to calculate the flow rate corresponding to the average velocity of fluid in a pipe. Furthermore, it performs a successive analysis of the computational terms of the full-condition flow analysis model.

[0175] Velocity distribution compensation section It is mainly used to correct flow measurement errors caused by uneven flow velocity distribution. By introducing a compensation factor related to the Reynolds number, the measurement results can be adjusted according to different flow regimes (laminar or turbulent) to ensure that relatively accurate flow calculation values ​​can be obtained under different flow velocity distributions.

[0176] Temperature compensation section This function is primarily used to adjust for the impact of changes in fluid physical properties caused by variations in water temperature on flow rate measurement. Changes in water temperature alter the fluid's density, viscosity, and other physical properties, thus affecting the flow rate measurement results. The temperature compensation function can be set according to the specific influence of water temperature on the fluid's physical properties, effectively eliminating measurement errors caused by temperature factors.

[0177] Attenuation compensation section This can improve flow measurement errors caused by ultrasonic wave attenuation. Ultrasonic waves attenuate as they propagate through fluids, and the degree of attenuation is closely related to factors such as the ultrasonic wave frequency, fluid composition, and propagation distance. By establishing an attenuation influence coefficient... By incorporating mathematical models of relevant factors into the full-condition flow analysis model, the impact of attenuation on flow can be accurately quantified, thereby allowing for reasonable correction of measurement results and reducing flow measurement errors caused by ultrasonic attenuation.

[0178] The full-condition flow analysis model effectively balances computational complexity while ensuring calculation accuracy through a phased compensation approach. In practical applications, this model enables ultrasonic water meters to operate under varying temperature, flow regimes, and signal quality conditions. With a flow measurement error within a certain range, it fully meets the needs of practical applications, providing a reliable theoretical basis and technical support for the accurate measurement of ultrasonic water meters.

[0179] Finally, the flow rate is calculated based on the full-condition flow analysis model and the effective signal set to achieve accurate analysis and effective monitoring of the flow rate results of the ultrasonic water meter.

[0180] Flow rate is calculated based on a full-condition flow analysis model and a set of valid signals. In practice, the upstream and downstream flight times are first obtained through the ultrasonic water meter's sensors, along with measurements of water temperature, ultrasonic frequency, fluid composition, and other relevant parameters. These parameters are then substituted into the full-condition flow analysis model, and the measurement results are corrected using various compensation components within the model. The set of valid signals is used to screen and verify the reliability of the measurement data, eliminating abnormal signals and ensuring the accuracy of the data used in the calculation. This method and analysis model enable accurate analysis and effective monitoring of ultrasonic water meter flow rates, providing precise and reliable data support for flow measurement in industrial and civilian sectors, and ensuring the stable operation and efficient management of related systems.

[0181] In this embodiment, a full-condition flow analysis model is established by combining a flow prediction model and a flow analysis model, taking into account factors such as temperature, attenuation, and velocity distribution compensation. This analysis model can adapt to different measurement conditions and environmental conditions, achieving accurate flow calculation. Through a staged compensation method, it effectively balances computational complexity while ensuring calculation accuracy, thus improving the practicality and operability of the analysis model.

[0182] Each parameter and compensation component of the aforementioned full-condition flow analysis model has a specific calculation method and practical significance. In practical applications, only relevant measurement parameters, such as upstream and downstream flight time, water temperature, ultrasonic frequency, and fluid composition, need to be obtained and substituted into the model to calculate the flow rate. The analysis model has clear logic, making the flow measurement method of ultrasonic water meters simple to operate, easy to implement, and convenient for promotion and application in industrial production and civilian fields.

[0183] The flow measurement method of the ultrasonic water meter in this embodiment comprehensively considers the influence of multiple factors on flow measurement and adopts effective correction and compensation measures, which improves the accuracy and reliability of flow measurement results, reduces malfunctions and erroneous operations caused by measurement errors, and improves the stability and reliability of the entire ultrasonic water meter flow measurement method.

[0184] Please see Figure 3 In an optional embodiment, to efficiently execute the ultrasonic water meter flow measurement method provided by the present invention, the present invention also provides an ultrasonic water meter flow measurement system. In this system, input devices, a processor, an output device, and a memory are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to call the program instructions and execute the specific steps of the relevant embodiments of the ultrasonic water meter flow measurement method provided by the present invention. The ultrasonic water meter flow measurement system of the present invention has a complete and stable structure, and can efficiently execute the ultrasonic water meter flow measurement method of the present invention, improving the overall applicability and practical application capability of the present invention.

[0185] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A flow measurement method for an ultrasonic water meter, characterized in that, Includes the following steps: The actual and simulated signals of the ultrasonic water meter are analyzed using an excitation transducer and a signal simulation module to obtain the effective time difference of the signal, and the effective signal set of the ultrasonic water meter is obtained based on the effective time difference of the signal. The corrected ultrasonic propagation speed is obtained based on the ultrasonic propagation expression and the effective signal set. The attenuation influence coefficient is analyzed based on the corrected ultrasonic propagation speed, and a flow prediction model is constructed based on the attenuation influence coefficient. Based on the velocity distribution compensation factor and the effective signal set, a velocity distribution compensation analysis model is obtained. The velocity distribution compensation analysis model is then derived to obtain a flow rate analysis model based on velocity distribution. A full-condition flow analysis model is established by combining the flow prediction model and the flow analysis model, and the flow is accurately calculated through the full-condition flow analysis model. The process of obtaining the corrected ultrasonic propagation velocity based on the ultrasonic propagation expression and the effective signal set, analyzing the attenuation influence coefficient based on the corrected ultrasonic propagation velocity, and constructing a flow prediction model based on the attenuation influence coefficient includes: Introduce a basic flow analysis formula based on flight time difference; The basic flow analysis results based on flight time difference are obtained through the aforementioned basic flow analysis formula; A flow prediction model is constructed by combining the basic flow analysis results and the attenuation influence coefficient; The process of obtaining a velocity distribution compensation analysis model based on the velocity distribution compensation factor and the effective signal set, and deriving the velocity distribution compensation analysis model to obtain a flow rate analysis model based on velocity distribution includes: The velocity compensation factor distribution function is established based on the distribution of the fluid Reynolds coefficients. The velocity distribution compensation factor is obtained using the velocity compensation factor distribution function. A flow velocity distribution compensation analysis model is constructed based on the flow velocity distribution compensation factor and the effective signal set. A flow analysis model based on average flow velocity is introduced; The flow analysis model based on average flow velocity and the flow velocity distribution compensation analysis model are combined to derive and obtain the flow analysis model based on flow velocity distribution. The step of establishing a full-condition flow analysis model by combining the flow prediction model and the flow analysis model, and achieving accurate flow calculation through the full-condition flow analysis model, includes: Based on the flow velocity distribution compensation factor and the effective signal set, an analysis is performed to obtain a Reynolds number-related compensation factor; The fitting coefficients of the influence parameters are obtained by fitting the ultrasonic frequency, fluid composition parameters, and the attenuation influence coefficient. A full-condition flow analysis model is established by combining the flow prediction model, the flow analysis model, the Reynolds number-related compensation factor, and the fitting coefficient of the influencing parameters. The flow rate is calculated based on the full-condition flow analysis model and the set of effective signals to achieve accurate analysis and effective monitoring of the flow rate results of the ultrasonic water meter.

2. The flow measurement method of the ultrasonic water meter according to claim 1, characterized in that, The method of analyzing the actual and simulated signals of the ultrasonic water meter using an excitation transducer and a signal simulation module to obtain the effective time difference of the signal includes: The actual signal of the ultrasonic water meter is generated through the excitation transducer. The signal simulation module is used to generate a simulation signal for the ultrasonic water meter. The actual signal and the simulated signal are extracted and analyzed to obtain the actual signal extraction result and the simulated signal extraction result.

3. The flow measurement method for an ultrasonic water meter according to claim 2, characterized in that, The step of analyzing the actual and simulated signals of the ultrasonic water meter using an excitation transducer and a signal simulation module to obtain the effective time difference of the signal, and obtaining the effective signal set of the ultrasonic water meter based on the effective time difference, includes: Three adjacent information sampling points are randomly selected, and an offset is set based on the three adjacent information sampling points; Based on the offset, the actual signal extraction result, and the simulation signal extraction result, analyze the cross-correlation value of the simulation signal window and the actual signal window under the offset; The preliminary time difference is obtained based on the cross-correlation value; An interpolation method is introduced, and the initial time difference is adjusted by combining the interpolation method and the cross-correlation value to obtain the effective time difference of the ultrasonic water meter signal; The effective signal set of the ultrasonic water meter is obtained based on the effective time difference of the signal.

4. The flow measurement method of the ultrasonic water meter according to claim 1, characterized in that, The corrected ultrasonic propagation speed, obtained based on the ultrasonic propagation expression and the effective signal set, includes: The static water temperature characteristic data are obtained based on the set of effective signals. By performing fitting analysis on the static water temperature characteristic data, a temperature-sound velocity mapping relationship expression is obtained; Based on the ultrasonic propagation expression, the temperature-velocity mapping expression, and the effective signal set, the ultrasonic propagation speed at different water temperatures is obtained through analysis. The different water temperatures were corrected by combining interpolation methods, and the corrected water temperatures were obtained. The ultrasonic propagation speed at different water temperatures is adjusted according to the corrected ultrasonic propagation speed to obtain the corrected ultrasonic propagation speed.

5. The flow measurement method for an ultrasonic water meter according to claim 1, characterized in that, The analysis of the attenuation influence coefficient based on the corrected ultrasonic propagation velocity includes: Introducing fluid dynamic viscosity, fluid density, and thermal conductivity characteristic parameters; The ultrasonic attenuation coefficient is obtained by combining the corrected ultrasonic propagation velocity, the fluid dynamic viscosity, the fluid density, and the thermal conductivity characteristic parameter. The attenuation influence coefficient between flow rate and attenuation is obtained based on the ultrasonic attenuation coefficient.

6. A flow metering system for an ultrasonic water meter, characterized in that, The system includes a processor, an input device, an output device, and a memory, which are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to invoke the program instructions to execute the flow measurement method of the ultrasonic water meter as described in any one of claims 1-5.

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