Turbine flowmeter precision control method and device

Abstract

The invention provides a turbine flowmeter precision control method and device which are applied to the technical field of flow measurement, temperature data acquisition is triggered by sensing the temperature change rate of an agricultural irrigation environment, and correction parameters are acquired from corresponding relation data between pre-stored temperature and correction parameters based on the temperature data. And then the original flow data are corrected, and finally the corrected data are used for water metering and valve control. Therefore, a complete temperature self-adaptive precision control process is formed, and the problem that the measurement precision of the turbine flowmeter is reduced due to temperature change is solved. The method has the advantages that errors caused by temperature changes to the turbine flowmeter are compensated through calculation of correction parameters, so that the flow metering precision is improved, and the water consumption management accuracy is improved.

Description

Technical Field

[0001] The present application relates to the field of flow measurement technology, and in particular to a method and device for controlling the accuracy of a turbine flowmeter. Background Art

[0002] Agricultural irrigation is a critical component in ensuring food security and improving agricultural production efficiency. In modern agricultural irrigation systems, turbine flowmeters with integrated IC card valve control are widely used in irrigation branch pipe networks to achieve refined water management and conserve water resources. They accurately measure irrigation water usage and enable automated water management and control through IC card prepayment. This integrated flowmeter device combines flow measurement, data processing, IC card interface, and valve control functions, providing convenient agricultural irrigation solutions.

[0003] However, agricultural irrigation environments present unique characteristics that differ from industrial or urban environments. Agricultural irrigation facilities are typically deployed in vast fields, exposed to the harsh outdoor environment for extended periods. These environmental characteristics include, but are not limited to, strong sunlight, rain, wind, dust, silt, weeds, and possible impurities and corrosive substances in the irrigation water. These factors pose significant challenges to flowmeters operating outdoors for extended periods.

[0004] In summer, strong direct sunlight and persistent high temperatures are common. Because agricultural irrigation facilities often lack effective shielding, turbine flowmeters with integrated IC card valve control can significantly heat up their housings and internal electronic components when exposed to sunlight for extended periods. Turbine flowmeters calculate flow by measuring the speed of the fluid-driven turbine. The acquisition and processing of turbine speed signals is highly sensitive to temperature fluctuations. High temperatures can cause physical changes in the flowmeter's internal mechanical components (such as bearings and turbine blades) and the integrated IC card valve control module, affecting the turbine's moment of inertia, friction, and accurate acquisition of speed signals. This can ultimately lead to significant deviations in flow measurement results. This measurement deviation not only impacts the normal operation of the irrigation system but also directly affects the accurate recording and billing of water consumption, resulting in overpayment for users or inaccurate water consumption. Therefore, there is a need for a technical solution that can autonomously perform temperature compensation within the flowmeter without external intervention and that can utilize a predetermined relationship between temperature and measurement deviation for correction.

[0005] In view of the above problems, the existing technology is in urgent need of improvement. Summary of the Invention

[0006] In view of the above-mentioned deficiencies in the prior art, the present application provides a method and device for controlling the accuracy of a turbine flowmeter, which has the beneficial effect of compensating for the errors caused by temperature changes on the turbine flowmeter by calculating correction parameters, thereby improving the flow measurement accuracy and improving the accuracy of water use management.

[0007] In a first aspect, a method for controlling the accuracy of a turbine flowmeter is provided, which is used in an agricultural irrigation environment and has a built-in IC card valve control turbine flowmeter. The method comprises the following steps: S1: monitoring the temperature change rate of the agricultural irrigation environment, and when the temperature change rate exceeds a preset change threshold, obtaining temperature data of the turbine flowmeter; S2: Acquire correction parameters corresponding to the temperature data from a storage unit, wherein the storage unit pre-stores corresponding relationship data between temperature and correction parameters determined through calibration experiments; S3: Using the correction parameters, performing correction calculation on the original flow data output by the turbine flowmeter to obtain corrected flow data; S4: Provide the corrected flow data to the IC card valve control module for water metering and valve control.

[0008] This application proposes a turbine flowmeter precision control method that triggers temperature data acquisition by sensing the temperature change rate of the agricultural irrigation environment. Based on this temperature data, correction parameters are obtained from pre-stored data on the correspondence between temperature and correction parameters. The original flow data is then corrected, and the corrected data is ultimately used for water metering and valve control. This constitutes a complete temperature-adaptive precision control process, resolving the issue of reduced turbine flowmeter accuracy due to temperature changes. This method has the beneficial effect of improving flow metering accuracy and water management accuracy by calculating correction parameters to compensate for the errors caused by temperature changes in the turbine flowmeter.

[0009] Furthermore, step S1 includes: S11: When the temperature change rate of the monitored agricultural irrigation environment exceeds a preset change threshold, the outer surface temperature of the turbine flowmeter housing, the turbine impeller bearing seat temperature, and the IC card valve control module temperature are obtained; S12: calculating a first temperature gradient, a second temperature gradient, and a third temperature gradient according to the outer surface temperature of the housing, the temperature of the turbine impeller bearing seat, and the temperature of the IC card valve control module respectively; S13: When the first temperature gradient, the second temperature gradient, and the third temperature gradient are all less than the preset temperature gradient threshold, the average values of the outer surface temperature of the casing, the turbine impeller bearing seat temperature, and the IC card valve control module temperature are calculated to obtain the temperature data; otherwise, resampling is performed until the first temperature gradient, the second temperature gradient, and the third temperature gradient are all less than the preset temperature gradient threshold.

[0010] A turbine flowmeter accuracy control method proposed in this application measures the temperature of multiple key points of the equipment and checks the temperature difference to ensure that the acquired temperature data reflects the temperature status of the equipment when the temperature changes, providing temperature data for correction calculations in subsequent steps.

[0011] Furthermore, step S2 includes: S21: According to the temperature data, query the corresponding relationship data between the temperature and the correction parameter pre-stored in the storage unit to obtain the initial correction parameter; S22: Calculate the correction parameter according to the temperature change rate and the initial correction parameter using the formula: correction parameter = initial correction parameter + (temperature change rate * adjustment coefficient).

[0012] This application proposes a turbine flowmeter accuracy control method that uses a specific formula to calculate the final correction parameter using the monitored temperature change rate and initial correction parameters. This formula uses a dynamic compensation algorithm to improve the metering accuracy of the turbine flowmeter in temperature-varying environments.

[0013] Furthermore, in step S21, the corresponding relationship data between the temperature and the correction parameter is pre-stored in the storage unit, and the pre-storage includes the steps of: S211: In an experimental environment, placing the turbine flowmeter in a temperature-controllable constant temperature bath, so that the temperature of the turbine flowmeter is consistent with the temperature of the constant temperature bath; S212: Record the output flow rate values of the turbine flowmeter at different temperature points, and obtain the actual flow rate values of the water flow in the constant temperature bath at different temperature points; S213: Calculating the ratio of the output flow value corresponding to each temperature point to the actual flow value to obtain a plurality of correction parameters; S214: fitting a "temperature-correction parameter" curve using a second-order polynomial according to each temperature point and its corresponding correction parameter, and pre-storing the "temperature-correction parameter" curve in the storage unit as data on the corresponding relationship between temperature and correction parameter.

[0014] This application proposes a turbine flowmeter precision control method, which converts discrete calibration data into a continuous functional relationship by establishing a "temperature-correction parameter" curve in an experimental environment, so that the system can provide correction parameters for any temperature within the operating temperature range.

[0015] Furthermore, step S3 includes: S31: Establishing a piecewise function relationship model between the original flow data and temperature, where different temperature ranges correspond to different function expressions, and the piecewise function relationship model is obtained through experimental calibration; S32: selecting a corresponding function expression from the piecewise function relationship model according to the temperature range in which the temperature data is located; S33: Substitute the temperature data into the selected function expression to calculate and obtain the corrected flow data.

[0016] Furthermore, step S31 includes: S311: In an experimental environment, collect multiple sets of raw flow data from turbine flowmeters at different temperatures; S312: For each set of the original flow data, using temperature as the independent variable and the original flow data as the dependent variable, a least squares fitting method is used to obtain a plurality of flow and temperature fitting curves; S313: Dividing the temperature intervals based on the slope change of the fitting curve to ensure that the functional relationship between the flow rate and the temperature in each temperature interval is approximately linear; S314: For each temperature interval, a linear functional relationship expression between the original flow data and the temperature is established to obtain the piecewise functional relationship model.

[0017] Furthermore, step S312 includes: S3121: Preset the fitting curve to a linear fitting curve; S3122: Calculating the slope and intercept of the linear fitting curve according to the original flow data and the temperature; S3123: According to the slope and the intercept, with temperature as the independent variable and the original flow data as the dependent variable, a plurality of fitting curves of flow and temperature are obtained.

[0018] Furthermore, step S313 includes: S3131: Calculate the second-order derivative of the slope of each fitting curve; S3132: superimposing the second-order derivatives of all the slopes to obtain a comprehensive slope change curve; S3133: In the comprehensive slope change curve, select a point where the absolute value of the second-order derivative is greater than a preset threshold as a candidate temperature segmentation point; S3134: Divide the temperature intervals according to the candidate temperature segmentation points to ensure that the functional relationship between the flow rate and the temperature in each temperature interval is approximately linear.

[0019] Furthermore, step S314 includes: S3141: For each temperature range, the least squares method is used to establish a linear functional relationship expression between the original flow data and temperature, and a linear regression equation for each temperature range is obtained; S3142: Combine the linear regression equations of each temperature range to construct a piecewise functional relationship model.

[0020] In a second aspect, a turbine flowmeter precision control device is provided, characterized in that, when applied to the steps of any of the above-mentioned turbine flowmeter precision control methods, the device comprises the steps of: Acquisition module: monitors the temperature change rate of the agricultural irrigation environment, and when the temperature change rate exceeds a preset change threshold, acquires the temperature data of the turbine flowmeter; Query module: obtains correction parameters corresponding to the temperature data from a storage unit, wherein the storage unit pre-stores corresponding relationship data between temperature and correction parameters determined through calibration experiments; Correction module: using the correction parameters to perform correction calculation on the original flow data output by the turbine flowmeter to obtain corrected flow data; Control module: Provides the corrected flow data to the IC card valve control module for water metering and valve control.

[0021] Beneficial Effects: This application proposes a method and device for controlling the precision of a turbine flowmeter. This method triggers the acquisition of temperature data by sensing the temperature change rate of the agricultural irrigation environment, and obtains correction parameters based on the temperature data from pre-stored data on the correspondence between temperature and correction parameters. The original flow data is then corrected, and the corrected data is ultimately used for water metering and valve control. This constitutes a complete temperature-adaptive precision control process, solving the problem of reduced metering accuracy of turbine flowmeters due to temperature changes. It has the beneficial effect of improving flow metering accuracy and water management accuracy by calculating correction parameters to compensate for the errors caused by temperature changes on the turbine flowmeter. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of a turbine flowmeter accuracy control method proposed in this application.

[0023] Figure 2 This is a structural diagram of a turbine flowmeter precision control device proposed in this application.

[0024] Description of reference numerals: 201, acquisition module; 202, query module; 203, correction module; 204, control module. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and marked in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work fall within the scope of protection of the present application.

[0026] It should be noted that similar reference numerals and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined or explained in subsequent figures. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0027] Please refer to Figure 1 A turbine flowmeter precision control method is provided for a turbine flowmeter with IC card valve control in an agricultural irrigation environment. The method comprises the following steps: S1: Monitor the temperature change rate of the agricultural irrigation environment. When the temperature change rate exceeds a preset change threshold, obtain the temperature data of the turbine flowmeter. S2: Acquire correction parameters corresponding to the temperature data from a storage unit, where the storage unit pre-stores data on the corresponding relationship between temperature and correction parameters determined through calibration experiments; S3: Using the correction parameters, the original flow data output by the turbine flowmeter is corrected and calculated to obtain the corrected flow data; S4: Provide the corrected flow data to the IC card valve control module for water metering and valve control.

[0028] In step S1, the need for accuracy correction is determined by monitoring the ambient temperature change rate. When the temperature change rate reaches a certain level, it indicates that the ambient temperature is rapidly changing, potentially affecting the metering performance of the turbine flowmeter. This triggers the acquisition of temperature data, which is used for subsequent correction calculations.

[0029] In step S2, a corresponding relationship between temperature and correction parameters is pre-stored in a storage unit, the relationship being established through experimental calibration. According to the acquired temperature data, the corresponding correction parameters are searched from the storage unit.

[0030] In step S3, the original flow data output by the turbine flowmeter is calculated and processed using the acquired correction parameters to obtain corrected flow data.

[0031] In step S4, the corrected flow data is used to accurately measure water consumption and control valves. Through this series of steps, the method can cope with the impact of temperature changes on the measurement accuracy of the turbine flowmeter and improve measurement accuracy.

[0032] Specifically, this method is applied to turbine flowmeters with integrated IC card valve control in agricultural irrigation environments, aiming to address the issue of decreased metering accuracy caused by temperature fluctuations. The method first continuously monitors the temperature change rate of the agricultural irrigation environment. When the temperature change rate exceeds a preset threshold, the system determines that the current ambient temperature is changing rapidly, potentially affecting the flowmeter's accuracy, and triggers the acquisition of temperature data.

[0033] The acquired temperature data represents the flowmeter's current operating temperature. The system then accesses an internal storage unit based on the acquired temperature data. This storage unit contains pre-stored data on the correspondence between temperature and correction parameters, established through extensive experimental calibration. Based on the current temperature data, the system searches this stored correspondence and retrieves the corresponding correction parameters.

[0034] After obtaining the correction parameters, the system uses them to perform a correction calculation on the raw flow data directly output by the turbine flowmeter. This correction calculation applies the correction parameters to the raw data to compensate for measurement errors caused by temperature variations, resulting in corrected flow data that is closer to the actual value. Finally, this temperature-corrected flow data is provided to the IC card valve control module integrated into the flowmeter.

[0035] The IC card valve control module uses this corrected, high-precision flow data to accurately measure water usage and, based on this data, executes corresponding valve control logic, such as controlling the total water supply or instantaneous flow rate based on the prepaid amount. This ensures that the turbine flowmeter can provide accurate water metering data in temperature-variable agricultural irrigation environments, ensuring fair water management and reliable valve control.

[0036] Furthermore, step S1 includes: S11: When the temperature change rate of the monitored agricultural irrigation environment exceeds a preset change threshold, the outer surface temperature of the turbine flowmeter housing, the turbine impeller bearing seat temperature, and the IC card valve control module temperature are obtained; S12: calculating a first temperature gradient, a second temperature gradient, and a third temperature gradient according to the outer surface temperature of the casing, the temperature of the turbine impeller bearing seat, and the temperature of the IC card valve control module respectively; S13: When the first temperature gradient, the second temperature gradient, and the third temperature gradient are all less than the preset temperature gradient threshold, the average values of the outer surface temperature of the casing, the turbine impeller bearing seat temperature, and the IC card valve control module temperature are calculated to obtain temperature data; otherwise, resampling is performed until the first temperature gradient, the second temperature gradient, and the third temperature gradient are all less than the preset temperature gradient threshold.

[0037] In step S11, temperature acquisition includes setting temperature sensors on the outer surface of the turbine flowmeter housing, the turbine impeller bearing seat, and the IC card valve control module position to measure the temperature at each position.

[0038] In step S12, the temperature gradient calculation includes determining the difference between the temperatures at these locations. For example, the turbine flowmeter may have at least three array temperature sensors integrated within it, located on the outer surface of the casing, the turbine impeller bearing seat, and near the IC card valve control module, to detect temperature data at these three locations. The process for calculating the first, second, and third temperature gradients based on the temperature data is as follows: Four corner points and one center point are randomly selected at each part as the temperature detection points of the array temperature sensor, and the temperature difference and distance between the center point and any adjacent corner point are calculated. The ratio of the temperature difference to the distance is the temperature gradient of each part.

[0039] In step S13, temperature gradient determination involves comparing the three calculated temperature gradients with a preset temperature gradient threshold. When all three temperature gradients are less than the preset temperature gradient threshold, average calculation is performed. Average calculation involves adding the temperatures at the three locations and dividing by three to obtain an average temperature value. Resampling involves re-executing the temperature acquisition and temperature gradient calculation process after a delay if the temperature gradients do not meet the preset temperature gradient threshold.

[0040] Furthermore, step S2 includes: S21: According to the temperature data, query the corresponding relationship data between the temperature and the correction parameter pre-stored in the storage unit to obtain the initial correction parameter; S22: According to the temperature change rate and the initial correction parameter, the correction parameter is calculated using the formula: correction parameter = initial correction parameter + (temperature change rate * adjustment coefficient).

[0041] In step S21, based on the temperature data, the corresponding relationship data between temperature and correction parameters pre-stored in the storage unit is searched to obtain the initial correction parameters. The storage unit pre-stores the corresponding relationship data between temperature and correction parameters determined through calibration experiments. This corresponding relationship data may be stored in the form of a function expression of a fitting curve. Based on the current temperature data, an initial correction parameter corresponding to the temperature is obtained by searching or calculating in the stored corresponding relationship data.

[0042] In step S22, a correction parameter is calculated using a formula based on the temperature change rate and the initial correction parameter. This formula adds the product of the initial correction parameter and the temperature change rate, where the temperature change rate is a quantified value that indicates how quickly the monitored ambient temperature changes. The adjustment coefficient is a preset parameter used to adjust the degree to which the temperature change rate affects the final correction parameter. This results in a final correction parameter that takes into account not only the static influence of the current temperature but also the influence of dynamic temperature changes.

[0043] In this way, the technical solution can more comprehensively consider the impact of temperature on the flowmeter accuracy, improve the accuracy of the correction parameters, and thus improve the measurement accuracy of the turbine flowmeter in a temperature-changing environment.

[0044] Furthermore, in step S21, the corresponding relationship data between the temperature and the correction parameter is pre-stored in a storage unit, and the pre-storage includes the steps of: S211: In the experimental environment, the turbine flowmeter is placed in a temperature-controlled constant temperature bath so that the temperature of the turbine flowmeter is consistent with the temperature of the constant temperature bath; S212: Record the output flow rate values of the turbine flowmeter at different temperature points, and obtain the actual flow rate values of the water flow in the constant temperature bath at different temperature points; S213: Calculate the ratio of the output flow value corresponding to each temperature point to the actual flow value to obtain multiple correction parameters; S214: fitting a “temperature-correction parameter” curve using a second-order polynomial according to each temperature point and its corresponding correction parameter, and pre-storing the “temperature-correction parameter” curve in a storage unit as data on the corresponding relationship between temperature and correction parameter.

[0045] Specifically, in order to solve the problem that the accuracy of the pre-stored correspondence data between temperature and correction parameters affects the calculation results of the correction parameters, this solution provides a method for obtaining and storing accurate correspondence data through experimental calibration.

[0046] First, in step S211, the turbine flowmeter to be calibrated is completely immersed or placed in a precisely controlled temperature bath in a specialized experimental environment. This is maintained for a period of time until the temperature of the flowmeter housing, internal mechanical components, and electronic components reaches and stabilizes with the water temperature in the bath. For example, the temperature can be set at multiple discrete points, such as 5°C, 15°C, 25°C, 35°C, and 45°C.

[0047] In step S212, after each temperature point stabilizes, the water circulation system within the thermostatic bath is activated to ensure a known and stable water flow through the turbine flowmeter. For example, a high-precision electromagnetic flowmeter can be used as a reference to measure the actual water flow through the thermostatic bath, or a predetermined known flow rate can be used to flow through the bath. Simultaneously, the turbine flowmeter output reading at the current temperature and actual flow rate is recorded.

[0048] In step S213, for each temperature point, the ratio of the turbine flowmeter's output flow rate to the actual flow rate is calculated. This ratio serves as the correction parameter for that temperature point. For example, if the actual flow rate at 25°C is 100 L and the flowmeter reading is 101 L, the correction parameter is 100 / 101 ≈ 0.9901. If the actual flow rate at 45°C is 100 L and the flowmeter reading is 98 L, the correction parameter is 100 / 98 ≈ 1.0204.

[0049] In step S214, a series of discrete (temperature, correction parameter) data points are obtained by measuring and calculating at multiple temperature points. For example, data points such as (5°C, 1.02), (15°C, 1.01), (25°C, 1.00), (35°C, 1.01), and (45°C, 1.02) are obtained. Using these discrete data points, a second-order polynomial fitting method is used to obtain a smooth "temperature-correction parameter" curve. Its mathematical expression is: Correction parameter = a * temperature² + b * temperature + c, where a, b, and c are fitting coefficients. This fitted second-order polynomial function (i.e., coefficients a, b, and c) or a sufficiently dense temperature-correction parameter data table generated by this function is stored in a non-volatile storage unit within the turbine flowmeter.

[0050] In this way, in an actual agricultural irrigation environment, when the flow meter monitors its own temperature changes and obtains temperature data, it can directly use the stored corresponding relationship data to quickly and accurately obtain the correction parameters corresponding to the current temperature by looking up the table or calculating the function value, thereby correcting the original flow data and improving the measurement accuracy of the flow meter at different temperatures.

[0051] Furthermore, step S3 includes: S31: Establishing a piecewise function relationship model between the original flow data and temperature, where different temperature ranges correspond to different function expressions, and the piecewise function relationship model is obtained through experimental calibration; S32: Selecting a corresponding function expression from the piecewise function relationship model according to the temperature range in which the temperature data is located; S33: Substitute the temperature data into the selected function expression to calculate and obtain the corrected flow data.

[0052] In step S31, the piecewise function relationship model between the original flow rate data and the temperature is established through experiments. In the experiments, the original flow rate data output by the turbine flow meter is collected at different temperature points.

[0053] In step S32, based on the collected data, the operating temperature range of the turbine flowmeter is divided into multiple temperature intervals. Within each temperature interval, a functional expression is established to describe the relationship between the raw flow data and the temperature within that interval. This piecewise functional relationship model is stored in a storage unit.

[0054] In step S33, during actual operation, the system obtains current temperature data. Based on the temperature data, the system searches for the temperature range to which it belongs. The system retrieves the function expression corresponding to the temperature range from the storage unit. The system inputs the temperature data into the obtained function expression to calculate the corrected flow rate data.

[0055] Furthermore, step S31 includes: S311: In an experimental environment, collect multiple sets of raw flow data from turbine flowmeters at different temperatures; S312: For each set of original flow data, using temperature as the independent variable and the original flow data as the dependent variable, a least squares fitting method is used to obtain multiple fitting curves of flow and temperature; S313: Dividing the temperature intervals based on the slope change of the fitting curve to ensure that the functional relationship between the flow rate and the temperature in each temperature interval is approximately linear; S314: For each temperature range, a linear function relationship expression between the original flow data and the temperature is established to obtain a piecewise function relationship model.

[0056] The method involves collecting multiple sets of raw flow data from a turbine flowmeter at different temperatures in an experimental environment. For each set of raw flow data, a least-squares fit is used, with temperature as the independent variable and the raw flow data as the dependent variable, to obtain multiple flow-temperature fitting curves. Temperature intervals are then divided based on the slope of the fitting curves to ensure that the functional relationship between flow and temperature within each temperature interval is approximately linear. For each temperature interval, a linear functional relationship expression between the raw flow data and temperature is established, resulting in a piecewise functional relationship model.

[0057] Through these steps, a piecewise function model for flow correction was systematically constructed, which solved the problem of how to accurately describe the complex relationship between the flow meter's original flow data and temperature at different temperatures, laying the foundation for improving the measurement accuracy of turbine flowmeters in different temperature environments.

[0058] Furthermore, step S312 includes: S3121: The preset fitting curve is a linear fitting curve; S3122: Calculating the slope and intercept of the linear fitting curve according to the original flow data and temperature; S3123: According to the slope and the intercept, with temperature as the independent variable and the original flow data as the dependent variable, a plurality of fitting curves of flow and temperature are obtained.

[0059] Among them, the technical solution provides a specific mathematical form of the flow rate and temperature fitting curve obtained in step S312. This form is a linear equation: .

[0060] By constraining the fitted curve to this linear form, this protocol provides standardized, easily extractable parameters (slope and intercept ). In particular, the slope , which directly reflects the degree of linear response of flow to temperature under different data sets or conditions. These quantitative slope values can be used to analyze the nonlinear characteristics of the relationship between flow and temperature.

[0061] Specifically, the slope is calculated and intercept The process is: Assume that the fitting curve is: , then the error function is: , is the actual flow value of the ith time, is the error function, which is expressed as the sum of squares of the difference between the actual flow rate and the fitted flow rate, Indicates the total number of temperature and flow data pairs.

[0062] The least squares method is used to solve the partial derivative equations of the linear regression model parameters, where the partial derivative equations are: ; .

[0063] Solve the partial derivative equations to get the slope and intercept Value: , .

[0064] Finally, the fitting curve is obtained: .

[0065] Furthermore, step S313 includes: S3131: Calculate the second-order derivative of the slope of each fitting curve; S3132: superimpose the second-order derivatives of all slopes to obtain a comprehensive slope change curve; S3133: In the comprehensive slope change curve, select a point where the absolute value of the second-order derivative is greater than a preset threshold as a candidate temperature segmentation point; S3134: Divide the temperature intervals according to the candidate temperature cut-off points to ensure that the functional relationship between the flow rate and the temperature in each temperature interval is approximately linear.

[0066] Specifically, to systematically determine the temperature interval division points, this method first calculates the second-order derivative of the slope of each flow rate vs. temperature fitting curve. The second-order derivative reflects the rate of change of the slope, and its value indicates the degree to which the flow rate-temperature relationship deviates from linearity. The second-order derivatives of all fitting curves are then superimposed to form a composite slope change curve, which represents the overall trend of slope change across the entire temperature range.

[0067] Then, within the integrated slope change curve, points where the absolute value of the second-order derivative exceeds a preset threshold are identified and selected. These points are locations where the slope changes at a high rate, indicating that the relationship between flow and temperature deviates significantly from linearity near these temperatures. These points are identified as candidate temperature cutoff points.

[0068] Finally, these candidate temperature split points are used to divide the entire temperature working range.

[0069] By segmenting the data at locations where the slope changes significantly, we can ensure that the functional relationship between flow and temperature is closer to linear within each temperature range. This provides a basis for subsequently establishing a linear function expression within each range, and improves the accuracy of the piecewise function model in fitting the actual flow and temperature relationship.

[0070] Furthermore, step S314 includes: S3141: For each temperature range, the least squares method is used to establish a linear functional relationship expression between the original flow data and temperature, and a linear regression equation for each temperature range is obtained; S3142: Combine the linear regression equations of each temperature range to construct a piecewise functional relationship model.

[0071] Specifically, the piecewise function relationship model is: ,in, 、 、 、 、 Indicates the temperature cutoff point, is the lower limit of the turbine flowmeter operating temperature, The upper limit of the working temperature of the turbine flowmeter is 、 ... represents the slope of each temperature interval, 、 ... represents the intercept of each temperature interval, Indicates traffic flow.

[0072] The piecewise functional relationship model divides the turbine flowmeter's operating temperature range into multiple temperature intervals. These temperature intervals are determined by preset temperature cutoff points and the turbine flowmeter's lower and upper operating temperature limits. Within each temperature interval, the relationship between the raw flow rate and temperature is modeled as a linear function. This linear function is defined by the slope and intercept corresponding to that temperature interval. In this way, the model can approximate the nonlinear relationship between the raw flow rate and temperature.

[0073] Please refer to Figure 2 A turbine flowmeter precision control device is characterized in that, in the steps of any of the above-mentioned turbine flowmeter precision control methods, the device includes the steps of: Acquisition module 201: monitors the temperature change rate of the agricultural irrigation environment, and when the temperature change rate exceeds a preset change threshold, acquires temperature data of the turbine flowmeter; Query module 202: obtains correction parameters corresponding to temperature data from a storage unit, where the storage unit pre-stores corresponding relationship data between temperature and correction parameters determined through calibration experiments; Correction module 203: uses correction parameters to perform correction calculation on the original flow data output by the turbine flow meter to obtain corrected flow data; Control module 204: provides the corrected flow data to the IC card valve control module for water metering and valve control.

[0074] The acquisition module 201 monitors the temperature change rate of the agricultural irrigation environment and acquires temperature data from the turbine flowmeter when the temperature change rate exceeds a preset threshold. This triggers data acquisition only when temperature changes may affect metering, improving system efficiency.

[0075] The query module 202 obtains the correction parameters corresponding to the temperature data from the storage unit. The storage unit pre-stores the corresponding relationship data between the temperature and the correction parameters determined through calibration experiments.

[0076] The correction module 203 uses the correction parameters to perform correction calculations on the original flow data output by the turbine flow meter to obtain corrected flow data, thereby eliminating the influence of temperature on the original flow data.

[0077] The control module 204 provides the corrected flow data to the IC card valve control module for water metering and valve control, thereby ensuring water management and control based on accurate flow data.

[0078] Specifically, the device realizes the whole process of autonomously completing temperature monitoring, parameter acquisition, flow correction and data output inside the turbine flowmeter by integrating the acquisition module 201, the query module 202, the correction module 203 and the control module 204.

[0079] The acquisition module 201 continuously monitors the rate of change of the ambient temperature, and triggers the collection of temperature data when the rate of change reaches a preset threshold, providing input for subsequent processing. The query module 202 searches the storage unit for pre-stored temperature and correction parameter correspondence data based on the acquired temperature data, and obtains the corresponding correction parameters. The correction module 203 receives the original flow data output by the turbine flowmeter and the correction parameters provided by the query module, and uses the correction parameters to calculate the original flow data to obtain the corrected flow data. The control module 204 passes the corrected flow data to the IC card valve control module, and the IC card valve control module uses the data to measure the water consumption, deduct fees and control the valve. The device does not require external intervention, adapts to the requirements of low maintenance and autonomous operation of the device in the agricultural irrigation environment, effectively solves the problem of inaccurate measurement caused by temperature changes, and ensures the accuracy and reliability of water metering and valve control.

[0080] In some specific embodiments, the acquisition module 201 may include a temperature sensor and a processing unit. The temperature sensor collects temperature signals, and the processing unit calculates the temperature change rate and reads the temperature data when the rate exceeds a threshold.

[0081] The query module 202 may include a memory and a search logic. The memory stores a correspondence table or fitting curve data between temperature and correction parameters, and the search logic searches or calculates the corresponding correction parameters in the memory according to the input temperature data.

[0082] The correction module 203 may include a calculation unit that receives the original flow data and the correction parameters and performs correction calculations, such as multiplication or function-based calculations.

[0083] The control module 204 may include a communication interface through which the corrected flow rate data is transmitted to the microcontroller of the IC card valve control module. For example, a temperature sensor may be mounted on the flow meter housing to collect ambient temperature. The processing unit may be a microcontroller within the flow meter, performing temperature change rate determination and data acquisition. The memory may be internal flash memory within the microcontroller or an external EEPROM to store calibration data. The search logic and calculation unit are implemented by the microcontroller executing corresponding software algorithms. The communication interface may be a UART or SPI interface for communicating with the IC card valve control module.

[0084] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any actual relationship or order between these entities or operations.

[0085] The foregoing is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. Persons skilled in the art will readily appreciate that the present application may be modified and altered in various ways. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A turbine flowmeter precision control method, characterized in that: A turbine flowmeter with IC card valve control for use in agricultural irrigation environments, the method comprising the steps of: S1: monitoring the temperature change rate of the agricultural irrigation environment, and when the temperature change rate exceeds a preset change threshold, obtaining temperature data of the turbine flowmeter; S2: Acquire correction parameters corresponding to the temperature data from a storage unit, wherein the storage unit pre-stores corresponding relationship data between temperature and correction parameters determined through calibration experiments; S3: Using the correction parameters, performing correction calculation on the original flow data output by the turbine flowmeter to obtain corrected flow data; S4: Provide the corrected flow data to the IC card valve control module for water metering and valve control.

2. A turbine flowmeter precision control method according to claim 1, characterized in that: Step S1 includes: S11: When the temperature change rate of the monitored agricultural irrigation environment exceeds a preset change threshold, the outer surface temperature of the turbine flowmeter housing, the turbine impeller bearing seat temperature, and the IC card valve control module temperature are obtained; S12: calculating a first temperature gradient, a second temperature gradient, and a third temperature gradient according to the outer surface temperature of the housing, the temperature of the turbine impeller bearing seat, and the temperature of the IC card valve control module respectively; S13: When the first temperature gradient, the second temperature gradient, and the third temperature gradient are all less than the preset temperature gradient threshold, the average values of the outer surface temperature of the casing, the turbine impeller bearing seat temperature, and the IC card valve control module temperature are calculated to obtain the temperature data; otherwise, resampling is performed until the first temperature gradient, the second temperature gradient, and the third temperature gradient are all less than the preset temperature gradient threshold.

3. A turbine flowmeter precision control method according to claim 1, characterized in that: Step S2 includes: S21: According to the temperature data, query the corresponding relationship data between the temperature and the correction parameter pre-stored in the storage unit to obtain the initial correction parameter; S22: Calculate the correction parameter according to the temperature change rate and the initial correction parameter using the formula: correction parameter = initial correction parameter + (temperature change rate * adjustment coefficient).

4. A turbine flowmeter precision control method according to claim 3, characterized in that: In step S21, the corresponding relationship data between the temperature and the correction parameter is pre-stored in the storage unit, and the pre-storage includes the steps of: S211: In an experimental environment, placing the turbine flowmeter in a temperature-controllable constant temperature bath, so that the temperature of the turbine flowmeter is consistent with the temperature of the constant temperature bath; S212: Record the output flow rate values of the turbine flowmeter at different temperature points, and obtain the actual flow rate values of the water flow in the constant temperature bath at different temperature points; S213: Calculating the ratio of the output flow value corresponding to each temperature point to the actual flow value to obtain a plurality of correction parameters; S214: fitting a "temperature-correction parameter" curve using a second-order polynomial according to each temperature point and its corresponding correction parameter, and pre-storing the "temperature-correction parameter" curve in the storage unit as data on the corresponding relationship between temperature and correction parameter.

5. The method for controlling the precision of a turbine flowmeter according to claim 1, characterized in that: Step S3 includes: S31: Establishing a piecewise function relationship model between the original flow data and temperature, where different temperature ranges correspond to different function expressions, and the piecewise function relationship model is obtained through experimental calibration; S32: selecting a corresponding function expression from the piecewise function relationship model according to the temperature range in which the temperature data is located; S33: Substitute the temperature data into the selected function expression to calculate and obtain the corrected flow data.

6. A turbine flowmeter precision control method according to claim 5, characterized in that: Step S31 includes: S311: In an experimental environment, collect multiple sets of raw flow data from turbine flowmeters at different temperatures; S312: For each set of the original flow data, using temperature as the independent variable and the original flow data as the dependent variable, a least squares fitting method is used to obtain a plurality of flow and temperature fitting curves; S313: Dividing the temperature intervals based on the slope change of the fitting curve to ensure that the functional relationship between the flow rate and the temperature in each temperature interval is approximately linear; S314: For each temperature interval, a linear functional relationship expression between the original flow data and the temperature is established to obtain the piecewise functional relationship model.

7. A turbine flowmeter precision control method according to claim 6, characterized in that: Step S312 includes: S3121: Preset the fitting curve to a linear fitting curve; S3122: Calculating the slope and intercept of the linear fitting curve according to the original flow data and the temperature; S3123: According to the slope and the intercept, with temperature as the independent variable and the original flow data as the dependent variable, a plurality of fitting curves of flow and temperature are obtained.

8. A turbine flowmeter precision control method according to claim 7, characterized in that: Step S313 includes: S3131: Calculate the second-order derivative of the slope of each fitting curve; S3132: superimposing the second-order derivatives of all the slopes to obtain a comprehensive slope change curve; S3133: In the comprehensive slope change curve, select a point where the absolute value of the second-order derivative is greater than a preset threshold as a candidate temperature segmentation point; S3134: Divide the temperature intervals according to the candidate temperature segmentation points to ensure that the functional relationship between the flow rate and the temperature in each temperature interval is approximately linear.

9. A turbine flowmeter precision control method according to claim 8, characterized in that: Step S314 includes: S3141: For each temperature range, the least squares method is used to establish a linear functional relationship expression between the original flow data and temperature, and a linear regression equation for each temperature range is obtained; S3142: Combine the linear regression equations of each temperature range to construct a piecewise functional relationship model.

10. A turbine flowmeter precision control device, characterized in that: In the steps of the turbine flowmeter precision control method according to any one of claims 1 to 9, the device comprises the steps of: Acquisition module: monitors the temperature change rate of the agricultural irrigation environment, and when the temperature change rate exceeds a preset change threshold, acquires the temperature data of the turbine flowmeter; Query module: obtains correction parameters corresponding to the temperature data from a storage unit, wherein the storage unit pre-stores corresponding relationship data between temperature and correction parameters determined through calibration experiments; Correction module: using the correction parameters to perform correction calculation on the original flow data output by the turbine flowmeter to obtain corrected flow data; Control module: Provides the corrected flow data to the IC card valve control module for water metering and valve control.

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